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Analyze Report: How to Write the Best Analytical Report (+ 6 Examples!)

By Varun Saharawat | March 1, 2024

Organizations analyze reports to improve performance by identifying areas of strength and weakness, understanding customer needs and preferences, optimizing business processes, and making data-driven decisions!

analyze report

Analyze Report: Picture a heap of bricks scattered on the ground. Individually, they lack purpose until meticulously assembled into a cohesive structure—a house, perhaps?

In the realm of business intelligence , data serves as the fundamental building material, with a well-crafted data analysis report serving as the ultimate desired outcome.

However, if you’ve ever attempted to harness collected data and transform it into an insightful report, you understand the inherent challenges. Bridging the gap between raw, unprocessed data and a coherent narrative capable of informing actionable strategies is no simple feat.

Table of Contents

What is an Analyze Report?

An analytical report serves as a crucial tool for stakeholders to make informed decisions and determine the most effective course of action. For instance, a Chief Marketing Officer (CMO) might refer to a business executive analytical report to identify specific issues caused by the pandemic before adapting an existing marketing strategy.

Marketers often utilize business intelligence tools to generate these informative reports. They vary in layout, ranging from text-heavy documents (such as those created in Google Docs with screenshots or Excel spreadsheets) to visually engaging presentations.

A quick search on Google reveals that many marketers opt for text-heavy documents with a formal writing style, often featuring a table of contents on the first page. In some instances, such as the analytical report example provided below, these reports may consist of spreadsheets filled with numbers and screenshots, providing a comprehensive overview of the data.

Also Read: The Best Business Intelligence Software in 2024

How to Write an Analyze Report?

Writing an Analyze Report requires careful planning, data analysis , and clear communication of findings. Here’s a step-by-step guide to help you write an effective analytical report:

Step 1: Define the Purpose:

  • Clearly define the objective and purpose of the report. Determine what problem or question the report aims to address.
  • Consider the audience for the report and what information they need to make informed decisions.

Step 2: Gather Data:

  • Identify relevant sources of data that can provide insights into the topic.
  • Collect data from primary sources (e.g., surveys, interviews) and secondary sources (e.g., research studies, industry reports).
  • Ensure that the data collected is accurate, reliable, and up-to-date.

Step 3: Analyze the Data:

  • Use analytical tools and techniques to analyze the data effectively. This may include statistical analysis, qualitative coding, or data visualization.
  • Look for patterns, trends, correlations, and outliers in the data that may provide insights into the topic.
  • Consider the context in which the data was collected and any limitations that may affect the analysis.

Step 4: Organize the Information:

  • Structure the report in a logical and coherent manner. Divide the report into sections, such as an introduction, methodology, findings, analysis, and conclusion.
  • Ensure that each section flows logically into the next and that there is a clear progression of ideas throughout the report.

Step 5: Write the Introduction:

  • Start with an introduction that provides background information on the topic and outlines the scope of the report.
  • Clearly state the purpose and objectives of the analysis.
  • Provide context for the analysis and explain why it is relevant and important.

Step 6: Present the Methodology:

  • Describe the methods and techniques used to gather and analyze the data.
  • Explain any assumptions made and the rationale behind your approach.
  • Provide sufficient detail so that the reader can understand how the analysis was conducted.

Step 7: Present the Findings:

  • Present the findings of your analysis in a clear and concise manner.
  • Use charts, graphs, tables, and other visual aids to illustrate key points and make the data easier to understand.
  • Provide context for the findings and explain their significance.

Step 8: Analyze the Data:

  • Interpret the findings and analyze their implications.
  • Discuss any patterns, trends, or insights uncovered by the analysis and explain their significance.
  • Consider alternative explanations or interpretations of the data.

Step 9: Draw Conclusions:

  • Draw conclusions based on the analysis and findings.
  • Summarize the main points and insights of the report.
  • Reiterate the key takeaways and their implications for decision-making.

Step 10: Make Recommendations:

  • Finally, make recommendations based on your conclusions.
  • Suggest actionable steps that can be taken to address any issues identified or capitalize on any opportunities uncovered by the analysis.
  • Provide specific, practical recommendations that are feasible and aligned with the objectives of the report.

Step 11: Proofread and Revise:

  • Review the report for accuracy, clarity, and coherence.
  • Ensure that the writing is clear, concise, and free of errors.
  • Make any necessary revisions before finalizing the report.

Step 12: Write the Executive Summary:

  • Write a brief executive summary that provides an overview of the report’s key findings, conclusions, and recommendations.
  • This summary should be concise and easy to understand for busy stakeholders who may not have time to read the entire report.
  • Include only the most important information and avoid unnecessary details.

By following these steps, you can write an analytical report that effectively communicates your findings and insights to your audience.

Also Read: Analytics For BI: What is Business Intelligence and Analytics?

Analyze Report Examples

Analyze Report play a crucial role in providing valuable insights to businesses, enabling informed decision-making and strategic planning. Here are some examples of analytical reports along with detailed descriptions:

1) Executive Report Template:

An executive report serves as a comprehensive overview of a company’s performance, specifically tailored for C-suite executives. This report typically includes key metrics and KPIs that provide insights into the organization’s financial health and operational efficiency. For example, the Highlights tab may showcase total revenue for a specific period, along with the breakdown of transactions and associated costs. 

Additionally, the report may feature visualizations such as cost vs. revenue comparison charts, allowing executives to quickly identify trends and make data-driven decisions. With easy-to-understand graphs and charts, executives can expedite decision-making processes and adapt business strategies for effective cost containment and revenue growth.

2) Digital Marketing Report Template:

In today’s digital age, businesses rely heavily on digital marketing channels to reach their target audience and drive engagement. A digital marketing report provides insights into the performance of various marketing channels and campaigns, helping businesses optimize their marketing strategies for maximum impact. 

This report typically includes key metrics such as website traffic, conversion rates, and ROI for each marketing channel. By analyzing these KPIs, businesses can identify their best-performing channels and allocate resources accordingly. For example, the report may reveal that certain channels, such as social media or email marketing, yield higher response rates than others. Armed with this information, businesses can refine their digital marketing efforts to enhance the user experience, attract more customers, and ultimately drive growth.

3) Sales Performance Report:

A sales performance report provides a detailed analysis of sales activities, including revenue generated, sales volume, customer acquisition, and sales team performance. This report typically includes visualizations such as sales trend charts, pipeline analysis, and territory-wise sales comparisons. By analyzing these metrics, sales managers can identify top-performing products or services, track sales targets, and identify areas for improvement.

4) Customer Satisfaction Report:

A customer satisfaction report evaluates customer feedback and sentiment to measure overall satisfaction levels with products or services. This report may include metrics such as Net Promoter Score (NPS), customer survey results, and customer support ticket data. By analyzing these metrics, businesses can identify areas where they excel and areas where they need to improve to enhance the overall customer experience.

5) Financial Performance Report:

A financial performance report provides an in-depth analysis of an organization’s financial health, including revenue, expenses, profitability, and cash flow. This report may include financial ratios, trend analysis, and variance reports to assess performance against budgeted targets or industry benchmarks. By analyzing these metrics, financial managers can identify areas of strength and weakness and make strategic decisions to improve financial performance .

6) Inventory Management Report:

An inventory management report tracks inventory levels, turnover rates, stockouts, and inventory costs to optimize inventory management processes. This report may include metrics such as inventory turnover ratio, carrying costs, and stock-to-sales ratios. By analyzing these metrics, inventory managers can ensure optimal inventory levels, minimize stockouts, and reduce carrying costs to improve overall operational efficiency.

7) Employee Performance Report:

An employee performance report evaluates individual and team performance based on key performance indicators (KPIs) such as sales targets, customer satisfaction scores, productivity metrics, and attendance records. This report may include visualizations such as performance scorecards, heatmaps, and trend analysis charts to identify top performers, areas for improvement, and training needs.

Also Check: Analytics & Insights: The Difference Between Data, Analytics, and Insights

Why are Analyze Report Important?

Analyze Report are important for several reasons:

  • Informed Decision Making: Analytical reports provide valuable insights and data-driven analysis that enable businesses to make informed decisions. By presenting relevant information in a structured format, these reports help stakeholders understand trends, identify patterns, and evaluate potential courses of action.
  • Problem Solving: Analytical reports help organizations identify and address challenges or issues within their operations. Whether it’s identifying inefficiencies in processes, addressing customer complaints, or mitigating risks, these reports provide a framework for problem-solving and decision-making.
  • Business Opportunities: Analytical reports can uncover new business opportunities by analyzing market trends, customer behavior, and competitor activities. By identifying emerging trends or unmet customer needs, businesses can capitalize on opportunities for growth and innovation.
  • Performance Evaluation: Analytical reports are instrumental in evaluating the performance of various aspects of a business, such as sales, marketing campaigns, and financial metrics. By tracking key performance indicators (KPIs) and metrics, organizations can assess their progress towards goals and objectives.
  • Accountability and Transparency: Analytical reports promote accountability and transparency within an organization by providing objective data and analysis. By sharing insights and findings with stakeholders, businesses can foster trust and confidence in their decision-making processes.

Overall, analytical reports serve as valuable tools for businesses to gain insights, solve problems, identify opportunities, evaluate performance, and enhance decision-making processes.

Types of Analyze Report

  • Financial Analyze Report: These reports analyze the financial performance of an organization, including revenue, expenses, profitability, and cash flow. They help stakeholders understand the financial health of the business and make informed decisions about investments, budgeting, and strategic planning.
  • Market Research Reports: Market research reports analyze market trends, consumer behavior, competitive landscape, and other factors affecting a particular industry or market segment. They provide valuable insights for businesses looking to launch new products, enter new markets, or refine their marketing strategies .
  • Performance Analysis Reports: These reports evaluate the performance of various aspects of an organization, such as sales performance, operational efficiency, employee productivity, and customer satisfaction. They help identify areas of improvement and inform decision-making to enhance overall performance.
  • Risk Assessment Reports: Risk assessment reports analyze potential risks and vulnerabilities within an organization, such as financial risks, operational risks, cybersecurity risks, and regulatory compliance risks. They help stakeholders understand and mitigate risks to protect the organization’s assets and reputation.
  • SWOT Analysis Reports: SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis reports assess the internal strengths and weaknesses of an organization, as well as external opportunities and threats in the business environment. They provide a comprehensive overview of the organization’s strategic position and guide decision-making.
  • Customer Analysis Reports: Customer analysis reports examine customer demographics, purchasing behavior, satisfaction levels, and preferences. They help businesses understand their target audience better, tailor products and services to meet customer needs, and improve customer retention and loyalty.
  • Operational Efficiency Reports: These reports evaluate the efficiency and effectiveness of operational processes within an organization, such as production, logistics, and supply chain management. They identify bottlenecks, inefficiencies, and areas for improvement to optimize operations and reduce costs.
  • Compliance and Regulatory Reports: Compliance and regulatory reports assess an organization’s adherence to industry regulations, legal requirements, and internal policies. They ensure that the organization operates ethically and legally, mitigating the risk of fines, penalties, and reputational damage.

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Analyze Report FAQs

What is an analytical report.

An analytical report is a document that presents data, analysis, and insights on a specific topic or problem. It provides a detailed examination of information to support decision-making and problem-solving within an organization.

Why are analytical reports important?

Analytical reports are important because they help organizations make informed decisions, solve problems, and identify opportunities for improvement. By analyzing data and providing insights, these reports enable stakeholders to understand trends, patterns, and relationships within their business operations.

What types of data are typically included in analytical reports?

Analytical reports may include various types of data, such as financial data, sales data, customer feedback, market research, and operational metrics. The specific data included depends on the purpose of the report and the information needed to address the topic or problem being analyzed.

How are analytical reports different from other types of reports?

Analytical reports differ from other types of reports, such as descriptive reports or summary reports, in that they go beyond presenting raw data or summarizing information. Instead, analytical reports analyze data in-depth, draw conclusions, and provide recommendations based on the analysis.

What are the key components of an analytical report?

Key components of an analytical report typically include an introduction, methodology, findings, analysis, conclusions, and recommendations. The introduction provides background information on the topic, the methodology outlines the approach used to analyze the data, the findings present the results of the analysis, the analysis interprets the findings, and the conclusions and recommendations offer insights and actionable steps.

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Writing a Good Data Analysis Report: 7 Steps

As a data analyst, you feel most comfortable when you’re alone with all the numbers and data. You’re able to analyze them with confidence and reach the results you were asked to find. But, this is not the end of the road for you. You still need to write a data analysis report explaining your findings to the laymen - your clients or coworkers.

That means you need to think about your target audience, that is the people who’ll be reading your report.

They don’t have nearly as much knowledge about data analysis as you do. So, your report needs to be straightforward and informative. The article below will help you learn how to do it. Let’s take a look at some practical tips you can apply to your data analysis report writing and the benefits of doing so.

Writing a Good Data Analysis Report: 7 Steps

source: Pexels  

Data Analysis Report Writing: 7 Steps

The process of writing a data analysis report is far from simple, but you can master it quickly, with the right guidance and examples of similar reports .

This is why we've prepared a step-by-step guide that will cover everything you need to know about this process, as simply as possible. Let’s get to it.

Consider Your Audience

You are writing your report for a certain target audience, and you need to keep them in mind while writing. Depending on their level of expertise, you’ll need to adjust your report and ensure it speaks to them. So, before you go any further, ask yourself:

Who will be reading this report? How well do they understand the subject?

Let’s say you’re explaining the methodology you used to reach your conclusions and find the data in question. If the reader isn’t familiar with these tools and software, you’ll have to simplify it for them and provide additional explanations.

So, you won't be writing the same type of report for a coworker who's been on your team for years or a client who's seeing data analysis for the first time. Based on this determining factor, you'll think about:

the language and vocabulary you’re using

abbreviations and level of technicality

the depth you’ll go into to explain something

the type of visuals you’ll add

Your readers’ expertise dictates the tone of your report and you need to consider it before writing even a single word.

Draft Out the Sections

The next thing you need to do is create a draft of your data analysis report. This is just a skeleton of what your report will be once you finish. But, you need a starting point.

So, think about the sections you'll include and what each section is going to cover. Typically, your report should be divided into the following sections:


Body (Data, Methods, Analysis, Results)

For each section, write down several short bullet points regarding the content to cover. Below, we'll discuss each section more elaborately.

Develop The Body

The body of your report is the most important section. You need to organize it into subsections and present all the information your readers will be interested in.

We suggest the following subsections.

Explain what data you used to conduct your analysis. Be specific and explain how you gathered the data, what your sample was, what tools and resources you’ve used, and how you’ve organized your data. This will give the reader a deeper understanding of your data sample and make your report more solid.

Also, explain why you choose the specific data for your sample. For instance, you may say “ The sample only includes data of the customers acquired during 2021, in the peak of the pandemic.”

Next, you need to explain what methods you’ve used to analyze the data. This simply means you need to explain why and how you choose specific methods. You also need to explain why these methods are the best fit for the goals you’ve set and the results you’re trying to reach.

Back up your methodology section with background information on each method or tool used. Explain how these resources are typically used in data analysis.

After you've explained the data and methods you've used, this next section brings those two together. The analysis section shows how you've analyzed the specific data using the specific methods. 

This means you’ll show your calculations, charts, and analyses, step by step. Add descriptions and explain each of the steps. Try making it as simple as possible so that even the most inexperienced of your readers understand every word.

This final section of the body can be considered the most important section of your report. Most of your clients will skim the rest of the report to reach this section. 

Because it’ll answer the questions you’ve all raised. It shares the results that were reached and gives the reader new findings, facts, and evidence. 

So, explain and describe the results using numbers. Then, add a written description of what each of the numbers stands for and what it means for the entire analysis. Summarize your results and finalize the report on a strong note. 

Write the Introduction

Yes, it may seem strange to write the introduction section at the end, but it’s the smartest way to do it. This section briefly explains what the report will cover. That’s why you should write it after you’ve finished writing the Body.

In your introduction, explain:

the question you’ve raised and answered with the analysis

context of the analysis and background information

short outline of the report

Simply put, you’re telling your audience what to expect.

Add a Short Conclusion

Finally, the last section of your paper is a brief conclusion. It only repeats what you described in the Body, but only points out the most important details.

It should be less than a page long and use straightforward language to deliver the most important findings. It should also include a paragraph about the implications and importance of those findings for the client, customer, business, or company that hired you.

Include Data Visualization Elements

You have all the data and numbers in your mind and find it easy to understand what the data is saying. But, to a layman or someone less experienced than yourself, it can be quite a puzzle. All the information that your data analysis has found can create a mess in the head of your reader.

So, you should simplify it by using data visualization elements.

Firstly, let’s define what are the most common and useful data visualization elements you can use in your report:

There are subcategories to each of the elements and you should explore them all to decide what will do the best job for your specific case. For instance, you'll find different types of charts including, pie charts, bar charts, area charts, or spider charts.

For each data visualization element, add a brief description to tell the readers what information it contains. You can also add a title to each element and create a table of contents for visual elements only.

Proofread & Edit Before Submission

All the hard work you’ve invested in writing a good data analysis report might go to waste if you don’t edit and proofread. Proofreading and editing will help you eliminate potential mistakes, but also take another objective look at your report.

First, do the editing part. It includes:

reading the whole report objectively, like you’re seeing it for the first time

leaving an open mind for changes

adding or removing information

rearranging sections

finding better words to say something

You should repeat the editing phase a couple of times until you're completely happy with the result. Once you're certain the content is all tidied up, you can move on to the proofreading stage. It includes:

finding and removing grammar and spelling mistakes

rethinking vocabulary choices

improving clarity 

improving readability

You can use an online proofreading tool to make things faster. If you really want professional help, Grab My Essay is a great choice. Their professional writers can edit and rewrite your entire report, to make sure it’s impeccable before submission.

Whatever you choose to do, proofread yourself or get some help with it, make sure your report is well-organized and completely error-free.

Benefits of Writing Well-Structured Data Analysis Reports

Yes, writing a good data analysis report is a lot of hard work. But, if you understand the benefits of writing it, you’ll be more motivated and willing to invest the time and effort. After knowing how it can help you in different segments of your professional journey, you’ll be more willing to learn how to do it.

Below are the main benefits a data analysis report brings to the table.

Improved Collaboration

When you’re writing a data analysis report, you need to be aware more than one end user is going to use it. Whether it’s your employer, customer, or coworker - you need to make sure they’re all on the same page. And when you write a data analysis report that is easy to understand and learn from, you’re creating a bridge between all these people.

Simply, all of them are given accurate data they can rely on and you’re thus removing the potential misunderstandings that can happen in communication. This improves the overall collaboration level and makes everyone more open and helpful.

Increased Efficiency

People who are reading your data analysis report need the information it contains for some reason. They might use it to do their part of the job, to make decisions, or report further to someone else. Either way, the better your report, the more efficient it'll be. And, if you rely on those people as well, you'll benefit from this increased productivity as well.

Data tells a story about a business, project, or venture. It's able to show how well you've performed, what turned out to be a great move, and what needs to be reimagined. This means that a data analysis report provides valuable insight and measurable KPIs (key performance indicators) that you’re able to use to grow and develop. 

Clear Communication

Information is key regardless of the industry you're in or the type of business you're doing. Data analysis finds that information and proves its accuracy and importance. But, if those findings and the information itself aren't communicated clearly, it's like you haven't even found them.

This is why a data analysis report is crucial. It will present the information less technically and bring it closer to the readers.

Final Thoughts

As you can see, it takes some skill and a bit more practice to write a good data analysis report. But, all the effort you invest in writing it will be worth it once the results kick in. You’ll improve the communication between you and your clients, employers, or coworkers. People will be able to understand, rely on, and use the analysis you’ve conducted.

So, don’t be afraid and start writing your first data analysis report. Just follow the 7 steps we’ve listed and use a tool such as ProWebScraper to help you with website data analysis. You’ll be surprised when you see the result of your hard work.

Jessica Fender

Jessica Fender is a business analyst and a blogger. She writes about business and data analysis, networking in this sector, and acquiring new skills. Her goal is to provide fresh and accurate information that readers can apply instantly.

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How to build a marketing data analysis report (template and examples)

Creating a data analysis report is an underrated yet critical skill for marketers. A marketing report can impact team, stakeholder, and company decisions, so highlighting (and omitting) the right information is crucial.

But how do you consistently churn out clear and compelling reports? This guide will help you tie your reports up in a neat little bow, ensuring alignment with and buy-in from your audience—and beneficial decisions for your end-users. 

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how to write an analysis report of data

Data analysis reporting is a process that combines quantitative and qualitative data to evaluate performance, share findings, and inform future decisions. One common example is reporting on the results of a marketing campaign, but there are plenty more reasons marketers might create a data analysis report.

More examples—plus the reporting steps, tools, and template—await below, so keep reading.

Get started fast with our  free monthly data analysis report template , and follow these six key steps to creating a persuasive report:

Nail down the elements : provide a title, timeframe, and summary. Present data visually and close with action points.

Determine your purpose : figure out why you're making this report so you can focus on the right information

Identify your audience and their needs : define your readers and tailor your report to their requirements

Put your key insights first : maximize Hotjar, a multi-product data analytics platform, to track metrics and gather meaningful insights 

Visualize your data : incorporate charts, heatmaps, and other visuals to convey facts and insights effectively

Ask your audience for feedback : collect your audience's feedback to continuously improve your reporting approach

How to write a data analysis report in 6 easy steps

Knowing how to write a data analysis report is vital—especially in a data-informed field like marketing. Organizing and visualizing your data helps you

Evaluate strategies and performance

Inform future decisions and actions

Share findings and recommendations to serve users better

However, even marketers dealing with data regularly may find the task time-consuming. But we can promise you one thing: it won’t feel that way once you have a repeatable process and fewer data analysis and visualization tools to work with.  

1. Nail down the elements

This chapter of our data analysis guide focuses on creating an executive report. But regardless of the type of report (we'll touch on a few more of them later), most share the same building blocks:

Title: use a straightforward title to convey your report's intent. Call it as it is, whether it's your overall marketing performance or a multi-channel marketing campaign.

Timeframe: reporting intervals include daily, weekly, monthly, quarterly, and annually. Monthly data analysis reports work best for marketing teams, clients, and executives.

TL;DR: summarize your key objectives and findings, such as insights, issues, and recommendations, in an executive summary. This sets your audience's expectations and helps busy team members focus on what matters to them. 

Body: your bar charts, graphs, tables, and heatmaps go here. Add visual evidence from your analysis that supports your conclusion to win buy-in from decision-makers.

Conclusion: backed by the data in the body, state your plan for making progress with your goals. For instance, say you need additional dollars to spend on social media advertising since it's shown a consistent return on investment (ROI).

Discover actionable data, enhance business decisions

Craft compelling marketing reports fast. Collect, analyze, and report on crucial insights using Hotjar’s multi-product platform to get stakeholder buy-in and team alignment.

2. Determine your purpose

What data should you incorporate in your report? The answer lies in the purpose of your data analysis report.

Consider this: what do you hope to achieve when you share the results of your analysis? Is it to show stakeholders how customers use your products so you can improve them? Or is it to enlighten your team about what customers like so you can tailor campaigns to each segment?

Pulling the relevant data becomes a breeze once you’ve locked in your report’s primary purpose.

Collect meaningful data in real time with Hotjar

Marketers conduct quantitative data analysis to answer questions like, “How many?” or “How often?” In other words: this type of analysis involves numerical data, such as traffic and conversions. 

But numbers alone don't provide the whole picture—you need to uncover the why behind them. Why did traffic from France increase yesterday? Why do certain customers rage-click on a call-to-action (CTA) button on your Demo page?

It's qualitative data that reveals the reasons customers behave a certain way. This non-numerical data includes behavioral observations, interview clips, and survey responses. 

In Hotjar, an analytics platform for user behavior and digital experience insights, you can gather qualitative data via Surveys , Feedback, and Interviews , plus visualize quantitative data via Heatmaps and capture user behavior in real-time with Recordings, all from a single platform.

Here, it's easier than ever to collect and analyze quantitative and qualitative data, and build a user-centric marketing report based on your analysis.

Complement quantitative data with qualitative insights

3. Identify your audience

Always determine two audience types for your report: primary and secondary.

Company executives, clients (for marketing agencies), team members, and cross-functional collaborators, such as product managers, can fit into either category, depending on your report. Once you've categorized your primary and secondary audiences, it's easier to customize the report to their needs. Here are a few tips on how to do it:

Speak their language: in any business setting, this means striking a balance between not too formal and not too casual—think business in the front, party in the back 

Discuss results, not methodologies: immediately dive into the insights gleaned from your quantitative and qualitative data analysis  

Present key takeaways in the summary: as we said earlier, highlight your main points at the top of your report so the reader can instantly note what they think is interesting

Place eye-catching visuals in the body: your audience may skim through and search only for additional details in the body, so ensure your data visualization is easy to interpret

📋 Need a hand? Try using a template 

If you’re unsure how to design your report or prefer not to build from scratch each time you run it, use a data analysis report template. Ensure it’s a well-crafted one aimed at showing—instead of telling—your audience what works and what doesn’t.

Aside from making you look good (😎), an excellent template saves you time, and gives your readers something to rely on during each reporting period.

So, what would an extremely occupied marketer do? Streamline the creation process, of course! Plug, play, and present your insights with our free monthly data analysis report template to get started 📈.

how to write an analysis report of data

Click the link above to make a copy of our handy template

4. Prioritize key insights

Here comes the exciting part: assembling the data to draw a clear picture for your audience. Before you discovered this guide, you might have gathered data manually from various sources, such as Google Analytics, your preferred A/B testing platform, and even Hotjar.

Luckily for you, there's a faster way to track and spot patterns occurring in your custom metrics. Hotjar Trends enables you to find the behavioral data you need, such as visitors who viewed any of the two landing page variations you were A/B testing, or users who rage clicked (a sign of frustration) before exiting your checkout page. 

Compare your A/B test participants or new and returning users to see if one segment encountered any issues. Or view your rage clicks over time to understand what makes users frustrated. Then, click the ‘play’ icon to dive straight into your session recordings and discover the reason behind their actions.

how to write an analysis report of data

Go from quantitative to qualitative data in a single click with Hotjar Trends

Finally, screencap the charts in Trends and link to some relevant recordings in your trend report .

A sample trend report showing rage clicks over time, created via Hotjar Trends

What else can you do within Hotjar? Use Highlights and Collections to group snippets of recordings and heatmaps to support your conclusion. Add these meaningful insights to your monthly report or share them with teammates on an ordinary day, without having to switch between multiple analytics tools. 

Trends, Highlights, Recordings…will my audience remember all these names?  

They may even start looking for them in every report from now on. Our tools and features are self-explanatory, so everyone, from the marketing and sales teams to clients and C-suite execs, can quickly understand them.

Personally I love using Highlights and Collections together. I see each highlight as a self-contained explanation for the case I’m making to the product team. I’ve got the video. I’ve got the tags if I need them. I’ll add comments and a thread for a response. 

There’s no risk of distraction and minimal lift to get my stakeholders directly to the central issue. 

And then the Collections view basically creates a visual report of all the evidence I have for a given case. Here's how much this hurts (one Highlight); click on the rest of these if you can stomach it (a Collection of Highlights).

5. Incorporate visual data

Whether you're comparing past and present conversion rates or sharing multiple data sets, it's crucial to get your point across quickly. After all, you're not the only team or department vying for your audience's attention. This is where data visualization plays a considerable role: maps and charts allow you to effectively convey your message by making your data interactive, digestible, and enjoyable. 

To visualize data, use your spreadsheet of choice (for example, Excel or Google Sheets) or a dedicated platform like Tableau . You can also screenshot your data in the Hotjar Dashboard to save time and effort. Showcase relevant heatmaps, recordings, survey responses, interview snapshots, and direct feedback to drive your point home and get everyone on the same page.

6. Collect feedback from your audience

Just as Surveys and Feedback let you connect with actual customers, they also prove valuable in asking your audience’s thoughts once you’ve sent out your reports. By building a custom survey—for free—in Hotjar, you can include and analyze open-ended questions like, “How did this data analysis report help you?” and “What would you want to see in the next report?”

This enables stakeholders to give you proper feedback, especially if they didn't get the chance to speak after your presentation.

4 examples of data analysis reports 

Now, we’re tackling four popular types of data analysis reports. Practice makes permanent, so let’s go over the ones you’ll likely produce regularly (you'll ace them in no time).

Executive report or digital marketing report

This comprehensive report combines vital insights into your marketing efforts across various channels. It tracks metrics like advertising ​​cost, conversion rate, customer acquisition cost, and online revenue. 

Remember: you'll send this document out to company executives who want to see how marketing directly contributes to the bottom line. Be sure to connect your efforts to revenue. And what better way to demonstrate your impact than showing heatmaps or recordings of people responding positively to your campaigns?

Search engine optimization (SEO) report

While an executive report may contain an SEO performance overview, this specialized report breaks down organic traffic in detail. Show your keyword rankings, conversion rates, and top traffic channels to explain your strategy to executives and stakeholders.

#Hotjar’s senior SEO and content strategist creates a quarterly SEO report summarized on Slack, along with a Loom walkthrough and presentation

Note that you can track these essential metrics in Hotjar's Dashboard. Screenshot your customized dashboard or share it live with your audience as you discuss key insights. Pull up a recording or two or highlight customer feedback to strengthen your case.

For example, if session recordings reveal an unclear CTA has caused conversions for several landing pages to decline, you might recommend changing the CTA by running an A/B test and going with the winning variation.

Social media marketing report

This data analysis report example unpacks multiple channels. Which ones are helping you spread brand awareness and enhance customer loyalty? As such, you should track social key performance indicators (KPIs) like new followers, total reach, share of voice (SOV), engagement, and website referrals.

You can access relevant data and insights in your social media pages’ in-app analytics or analytics tools like Buffer and Hootsuite .

Marketing funnel report

Conversion funnels allow you to home in on the few steps users take from first contact to final conversion. Here’s a basic conversion path if you’re marketing an ecommerce brand:

Homepage > category page > product page > cart > checkout > thank you page

Initially, you’ll look at how many people visit your main pages and who they are. Take your data analysis further with Hotjar Funnels , where you can measure conversion and drop-off rates. Add filters like traffic channels and user attributes to compare performance. To deepen your insights, jump into relevant recordings and see what causes users to leave before they convert. 

The best part? You can gradually collect data, conduct funnel analysis , and integrate your findings into your report with in Hotjar and with out manually handling data: no hassle, no fuss.

#A conversion flow with four steps, visualized in Funnels

Create data analysis reports that drive action

Ensure your team, stakeholders, and executives make data-informed decisions regarding your marketing campaigns and strategies with compelling data analysis reports.

Needle-moving, user-centric insights deserve the spotlight. Start with our free template and populate it with numerical and non-numerical data from Hotjar and other sources. Go ahead and tell a visual story that inspires action today. 

FAQs about data analysis reports

What is a data analysis report.

A data analysis report is a document containing key insights derived from quantitative and qualitative data analysis. Marketers, for instance, use it to share findings and recommendations with teammates, stakeholders, clients, and company executives. This is to ensure everyone is on the same page before deciding on any improvements to marketing strategies and campaigns.

What is an example of a data analysis report?

One example of a data analysis report is the executive report on a company’s digital marketing efforts. It presents evidence backed by data on how different channels create opportunities for a business to serve its customers better and, in return, achieve sustainable growth.

How do you write a data analysis report?

Here’s how to develop your marketing report in seven simple steps:

Nail down the elements

Determine your purpose

Identify your audience and their needs

Enhance your reports using templates

Put your key insights first

Visualize your data

Ask your audience for feedback

Data analysis tools

Previous chapter

Guide index

How To Create Data Reports That Will Skyrocket Your Business Performance

How to create data reports by datapine.

Table of Contents

1) What Is a Data Report?

2) Data Reporting Importance

3) Data Reporting Basics

4) Data Reporting Best Practices

5) Data Reporting Mistakes To Avoid

6) Data Reports Examples and Templates

While they have always played a pivotal role in business success, the terms ‘data report’ or ‘business report’ haven’t exactly been synonymous with creativity or innovation. Data reporting and analysis are often seen as necessary evils created by analysts and consultants to offer functional operational insights. 

As such, the term usually conjures up images of static PDFs, old-school PowerPoint slides, and big tables. Usually created with past data without any room for generating real-time or predictive insights, static reports were deemed obsolete, consisting of numerous external and internal files, without proper information management processes at hand.

But it doesn’t have to be this way in the digital age. In fact, the business intelligence industry has evolved enormously over the past decade, and data analytics reports are riding the crest of this incredible technological wave.

The rise of innovative report tools means you can create report insights that people are compelled to read and that offer a wealth of business-boosting value. If you utilize business intelligence correctly, not only will you be able to connect your informational dots, but you will also be able to take control of your data across the company and improve your bottom line.

Here, we will consider the question, ‘what is a data report?’, explore how to generate one, and provide the best possible data reports examples, all created with modern software. Without further ado, let's get started!

What Is a Data Report?

A data report is an analytical tool used to extract past, present, and future performance insights to accelerate a company’s growth. It combines various sources of information and is usually used for operational and strategic decision-making.

As mentioned, these reports originally had features of static presentation of data, manually written or calculated, but with the introduction of modern processes such as dashboard reporting , they have developed into an invaluable resource to successfully manage your sales processes, marketing data, and even robust manufacturing analytics and numerous other organizational processes needed to stay on top of the pack.

Let’s explore the basics in more detail, and then we will look at data reporting examples that you can use for your own internal processes and more.

The Importance Of Data Reporting

In our current data-driven world, the importance of data reporting cannot be overstated. Organizations rely heavily on data to gain insights into their operations, understand market trends, and make informed decisions. In the reporting phase, you give meaning to your data by presenting it in a structured format so users can understand and use it to its potential.

At its core, data reporting serves as a bridge between raw data and actionable insights. It transforms vast amounts of information into digestible formats so stakeholders can assess performance, allocate resources, and drive decision-making. Without reporting, companies would struggle to navigate business challenges and complexities, relying instead on guesswork and intuition to guide their actions.

When done correctly, data reporting can offer the following benefits:

  • Better decision-making : Effective reporting provides insights into trends, patterns, and performance metrics, enabling stakeholders to make informed decisions based on evidence. With a well-designed report and access to data at any time, decision-making power improves significantly.
  • Objective performance evaluation : By analyzing data reports, organizations can evaluate the performance of individuals, teams, departments, or entire systems. This helps leaders find areas for improvement and recognize their strengths without letting personal feelings skew their judgment.
  • Better resource allocation : Data analysis reports can help decision-makers proactively decide where resources are most needed and where they can be optimized for better outcomes. They can also identify potential waste areas, allowing them to curb losses and reduce budget strain.
  • Improved risk management : Every organization faces risks, and reporting can help call attention to risks that might otherwise go unnoticed. Data helps uncover potential issues so leaders can take immediate action and reduce the likelihood of negative outcomes.
  • Accountability and transparency : Data (and access to data) helps foster a culture of transparency and allows users to be more accountable for their performance and decisions. Empowering employees with data gives them clear metrics against which they can measure their performance and activities.
  • Customer insights : Analyzing customer behaviors helps organizations understand customer behavior, preferences, and needs. These insights can lead to a better marketing approach and customer experience.
  • Continuous improvement : Ongoing reporting creates a culture of continuous improvement, with data guiding your decisions rather than a set-in-stone strategy. Metrics and KPIs provide feedback on strategies, processes, and initiatives, allowing you to see what’s working and what needs to be changed to achieve better outcomes.
  • New trends and opportunities : Data can reveal many things about your company and services that might otherwise go unnoticed, such as emerging trends and patterns. Spotting these trends early gives you the best advantage to get ahead of competitors.

Data Reporting Basics

We’ve explored the data report definition and its benefits. Now, we’re going to look at the fundamentals of data and effective reports, the building blocks of business intelligence success.

  • Purpose: Data analytics is the art of curating and analyzing raw insights to transform metrics into actionable insights. Data analytics reports present metrics, analyses, conclusions, and recommendations in an accessible, digestible visual format so everyone can make informed, data-driven decisions.
  • Data types: Business data reports cover a variety of topics and functions. As such, all types vary greatly in length, content, and format. It’s possible to present reporting data as an annual overview, monthly sales, accounting report , data requested by management exploring a specific issue, information requested by the government showing a company’s compliance with regulations, progress reports, feasibility studies, and more. The all-encompassing nature of data-centric reports means working with a mix of historical, predictive, and in-the-moment insights to paint a panoramic picture of your organization's functions, processes, and overall progress is possible.
  • Accessibility: Historically, creating data-driven reports was time- and resource-intensive. Data pull requests were the exclusive duties of the IT department, with a significant amount of effort spent analyzing, formatting, and then presenting the data. Because this task was so resource-heavy, data analysis was an occasional luxury. Also, by the time the data was presented, it was generally out of date. The emergence of real-time cloud-based BI reporting tools has changed the game. Now a wider range of users can act as analysts, even performing advanced analytics. The right BI platform can blend multiple data sources into one analysis, enhancing insights and better-informed decision-making. These cloud-based tools allow organizations to collaborate on data, bringing various subject matter experts (SMEs) to the same table. Modern business dashboard tools allow a wider audience to comprehend and disseminate the findings. Users can also easily export these dashboards and data visualizations into visually stunning writeups that can be shared via multiple options, such as automating emails or providing a secure viewer area, even embedding data into your own application, for example.
  • Flexibility: In addition to the fact that software offers a wealth of visually accessible KPI-driven insight , business intelligence dashboards are also completely customizable to suit individual goals or needs. Moreover, data dashboards are optimized for mobile devices, meaning users can access a wealth of business-boosting information from a central display, 24/7, without restrictions or limits. You can leverage business intelligence day or night from anywhere in the world.

Now that you understand the superior analytical capabilities of modern business data reporting, we’ll examine a mix of tips and ideas designed to help you build and create online data reports that will save time and costs while driving innovation across the company.

Your Chance: Want to test a modern data reporting software for free? We offer a 14-day free trial. Benefit from great data reports today!

Top 14 Data Reporting Best Practices & Tips

Top 14 data reporting best practices and tricks on how to build efficient reports

We’ve covered the basics, so now we’ll examine how to create these reports from a practical perspective. Our tips for documenting data will help you do so.

Depending on the type of report, each has its own set of rules and best practices. Below, we will mention the most popular ones, but our main focus is on best practices that will make your reporting more productive. Let’s get started.

1. Define The Type Of Data Report

What types of data reporting do you need to present? Having this definition in advance will help set parameters you can easily stick to. Here are the most common types of data reports:

1) Informational vs. analytical: First, determine if this report provides factual information. Informational reports are usually smaller in size, the writing structure is not strict, and the sole purpose is to inform about facts without adding any analysis. On the other hand, if it includes any analysis, demonstrates relationships, or provides recommendations, it is an analytical report .

2) Recommendation/justification report: This report presents an idea and makes suggestions to management or other decision-makers. As the name suggests, it provides recommendations for changes in internal procedures and justifies courses of action that aim to improve organizational success.

3) Investigative report: This type helps determine the risks involved with a specific course of action. It is based on documenting specific information objectively to present enough information to stakeholders, who will ultimately decide if further actions are needed. An example would be a report created for legal purposes.

4) Compliance report: Shows accountability by providing compliance information, for example, to a governing body. This is particularly important as accurate, well-presented compliance metrics will avoid costly mistakes or red tape issues.

5) Feasibility report: An exploratory report to determine whether an idea will work. Data-driven insights could save significant time and money by helping organizations avoid redundant processes or developments.

6) Research studies report: This presents in-depth research and insights on a specific issue or problem. Research is pivotal to growth and evolution, and having the visual insights to back up your decisions will set you apart from the pack.

7) Periodic report: Improves policies, products, or processes via consistent monitoring at fixed intervals, such as weekly, monthly, quarterly, etc. These types of reports help foster incremental growth and consistency across the board.

8) KPI report : Monitors and measures key performance indicators ( KPIs ) to assess if your operations deliver the expected results. The best dashboards for benchmarking progress in many internal and external areas.

9) Yardstick report: Weigh several potential solutions for a given situation, an invaluable tool to adapt to your specific goals, aims, needs, and situations. This is a solution-centric tool that every modern organization should embrace.

2. Know Your Target Audience

Knowing your audience will help determine which insights you present, the recommendations you make, and how you present the data. Your audience may be upper, middle, or line management, other departments, coworkers, clients, potential clients, the government, or another company in the same market.

Knowing your audience helps determine what information to include in the report. If a report is internally facing, branding, such as colors, font, and logo, isn’t as crucial. If it is a one-time live presentation, formatting for printing isn’t key. Determine in advance if your audience needs persuasion or education. If your audience is at the C-suite or board levels, you may want to present mostly high-level insights with specific call-outs and action items.

If the report is more exploratory in nature, you may want to include more granular information and options to interact with the data. Ramon Ray, tech evangelist and founder of Smart Hustle Magazine, wrote about presenting your data to a wide audience. He focused on keeping text simple, using visualizations whenever possible, including video and animation when appropriate, and making your presentations interactive. Knowing your audience before you start your analysis – and even more importantly before you put together the report – will keep everything data-focused and impactful.

3. Use Data From Various Sources  

Once you understand the questions you want to answer with your reports and your audience, you must determine the data sources you need. As data has become a regular part of organizations’ daily activities, the number of internal and external sources from which companies are extracting data has grown. When building your reports, it can get overwhelming to decide which information to use and how to ensure everything is clean and optimized. This can be done with the help of data connectors . 

Among some of the many BI features in the market today, datapine offers professional data connectors that allow you to connect flat files, social media data, APIs, CRM data, and several other sources with just a few clicks. And not just that, once your sources are connected, the tool automatically updates them for you. That way, you can always have up-to-date data ready to be analyzed. 

4. Have A Detailed Plan And Select Your KPIs

We will sound like a broken record here, but have a plan before you start your analysis. What information does the management need for its effective decision-making? What data and insights do your shareholders require? Understand the required data scope and think about how you will use that data.

Utilize as many data sources as possible, but don’t go data crazy and get bogged down in unnecessary information. Of course, you have to remain agile and may have to adapt the plan, but a robust plan is crucial. Remaining purpose-driven will focus your work, save you in the long run and improve your business outcomes.

When creating your plan, it is essential to select the right key performance indicators. You don’t need dozens of metrics that will answer all your organizational questions at once , but pick a few that will tell a comprehensive data story (more on that later), and enable you to take proper action (more on that later, too).

Depending on your department or industry, reports will vary as key success indicators also vary, but choose the ones that will help you put your data into proper context and always keep in mind the audience you’re addressing. Understanding your audience deeply and setting clear-cut strategic objectives will make the KPI selection process easier and more valuable.

Choose KPIs that align directly with your specific aims, and you will benefit from a cohesive mix of visual benchmarks that will help you track your progress accurately while spotting trends that will help you streamline your company for success. Remember to avoid vanity metrics that can mislead your visual efforts and choose only the indicators that will bring value to your strategic decisions. If you want to learn more about this, check out our insightful guide on KPIs vs. metrics .

5. Be Objective, When Possible

Business reporting describes the past, present, or possible future situation objectively and neutrally. Objective means the information states facts, not an opinion. Keep the opinions minimal. It helps to combine them in one section, possibly titled “Suggested Actions.” Also, using a passive voice in a report will help keep it formal and inoffensive. For example:

Active : The managers need to make changes in their management style.

Passive : Changes in management style need to be made.

If you’re too subjective or biased, you’re essentially moving away from your goal of uncovering factual information that will give you a competitive edge. Collect data from reliable sources, record your discoveries with pinpoint accuracy, and you will connect with objective information that will push your organization to the next level.

6. Be Visually Stunning

Numerous types of graphs and charts prove to be extremely powerful. Presenting analytics visually makes it easier for decision-makers to grasp difficult concepts or identify new patterns. Data presented visually are easier for humans to perceive and digest. Reports should include data visualizations over text whenever possible. Just make sure you are choosing the most appropriate data visualization to tell your data story and that you are following BI dashboard best practices. With the right data reporting tool, anyone can create meaningful visuals and share them with their team, customers, and other shareholders. All this can be accomplished without involving a data scientist.

Also, ensure your report remains visually stunning , no matter how it is shared and disseminated. Your platform should look good on a computer, tablet, PDF, or mobile screen. That’s why utilizing an analytics platform can be the most cost-effective solution, providing you with stunning visuals and interactivity. More on this in the next point.

7. Don’t Neglect the Design 

Once you’ve chosen the type of report you will use as well as the data visualizations that will be on it, you want to consider the design. How your data is organized will tell a lot about how it is perceived. For instance, you need to include metrics that will provide context to the data; this way, you will tell a story that is easy to understand. You also need to avoid overcrowding the report. If you want to add a lot of data to it, you can use tabs to split the information by theme or subject, making it easier for users to find information. 

When discussing design, you also need to consider colors. For starters, you can follow the company's color palette. Choose up to three colors and play with different gradients to draw people’s attention to specific areas of the report while avoiding colors that can distract the audience from what really matters: the data. 

Lastly, you need to consider the format in which the report will be shared and visualized. For example, for annual reports that will be printed and widely shared, extra focus should be spent on dashboard design principles .

8. Have Content Sharply Written

While the focus should be on visuals, some data report types also need text. In this case, use persuasive and even-toned business writing, including concise, active, and engaging language. Use bullet points versus long paragraphs. Use headers and provide legends and supplementary text for your visualizations. Also, you should always proofread!

To optimize your data analytics presentation and content, our guide to digital dashboard creation and best practices offers practical insights that will help you format your reports for success.

9. Make Sure the Report Is Actionable

Prescriptive, descriptive, and predictive analytics have become increasingly popular in recent years. Each brings new insights needed to make better business decisions and increase ROI – information from the past and future, as well as prescribing possible outcomes. That being said, make sure your analytical efforts have a conclusion. When necessary, provide recommendations.

Reports should be objective, but the best ones should also be actionable. Intended audiences should walk away with the next steps or greater insights. Doing so will enable a data-driven environment and foster more efficient collaboration.

To help make your data-centric reporting more actionable, you must ensure that your KPIs and insights work together to paint a comprehensive picture of a particular process, strategy, or function.

For instance, if you’re looking to analyze your customer service success, adding metrics relating to staff performance and consumer satisfaction will give you a balanced mix of information to help you take decisive action. Naturally, all of your metrics will offer invaluable standalone information, but if they all complement one another, you will accelerate your organization’s success in a number of key areas.

10. Keep It Simple And Don’t Be Misleading

While data should be objective, formatting, filtering, and manipulation can lead to misleading statistics . Make sure your presentation is consistent and reliable. Also, keep it simple. The boom of data visualization and reporting tools has led to the creation of visualizations that don’t tell a relevant data story.

You shouldn’t need 3-D glasses to read a report. Sometimes, a simple chart is all you need. You also don’t need to go nuts with colors and formats. You can easily overwhelm your audience this way. Choose a couple of colors that are easy on the eyes. Keep to one font that’s large and legible. Don’t go crazy with highlighted, bold, or italicized text. You don’t have to create a “piece of art” for your report to be visually stunning and impactful.

The key takeaway here is: Keep your eyes on the prize and always remember the goal or primary objective when developing your reports. Remembering your objectives while prioritizing making your dashboards universally accessible will ensure you keep your efforts simple, transparent, and accurate.

11. Don’t Forget to Tell a Complete Story

To successfully deliver data, you must consider your story's logic. The presentation should provide a clear narrative that will not confuse the recipient but enable him/her to derive the most important findings.

Consider creating an analytical presentation. That way, you will have your data on a single screen, and you can interact with numerous charts and graphs while your story stays focused and effective. By utilizing interactive visualizations, you have a strong backbone on how to write a data report and ensure that your audience is well-informed and digests data easily and quickly.

Human beings absorb and engage with narratives better than other formats. Telling a tale with your data will skyrocket your organization’s success, improve your chances of executive buy-in, and foster innovation.

Our definitive guide to dashboard presentation and storytelling will tell you all you need to know to get started.

12. Regularly Measure The Progress Of Specific Goals

When it comes to data reporting, creating a persuasive narrative is important. For maximum effectiveness, it’s also essential to check whether data report arrangements and designs are helping you work toward your specific organizational goals.

The best way to do this is to set time aside to drill down into specific pockets of information frequently. If you’ve set watertight benchmarks (taking your company’s current capabilities and industry standards into consideration), you will gain an actionable view of how you are progressing goal-wise.

For example, if you’re trying to improve customer loyalty through your email marketing efforts, you can drill down into specific metrics to check your performance. If progress is slow - or you’re underachieving - you can tweak your storytelling design to help provide extra clarity and, ultimately, give everyone the tools to meet or even exceed expectations.

The main point here: As a best practice, make checking in with every one of your goals individually a priority. Doing so will ensure that your designs and visuals provide the clarity and information you need to succeed.

13. Use Professional Data Report Software

Utilizing modern visual analytics software will ensure you design your reports based on the decisions you need to make, filtering the ever-present noise in reporting processes and making sure you don’t get lost in the details. Oftentimes, reports are piled with large volumes of spreadsheets and presentation slides that can create an obscure view of the presented data and increase the possibility of (unintentional) errors. The software can eliminate hideous manual tasks of searching through rows and columns and provide the necessary real-time view, alongside the possibility of looking into the past and the future of how the data will behave.

No matter if you’re an analyst working with databases and need a strong MySQL reporting tool or a marketing professional looking to consolidate all your channels under the same umbrella, the software will enable you to clear the clutter and automate your reports based on your specific intervals. It will update the data automatically, and you will not need more than small refinements to ensure the data you present is what your audience needs.

14. Empower Everyone In The Organization

Another valuable data reporting and analysis tip is ensuring full buy-in across the organization. Providing education and training will ensure everyone in the company pulls in the same direction.

Hosting talks as well as workshops will not only help everyone in the organization understand the practical importance of data analysis reporting, but it will empower everyone with the skills to use your new data tools to their advantage.

If everyone has the right level of access to your data reporting systems and the skills to interact with those tools confidently, your organization will more often exceed its goals.

Now that we’ve covered essential best practices let’s explore common challenges and mistakes to avoid.

Data Reporting Challenges & Mistakes To Avoid

Regardless of which types of data reports you’re talking about, there are certain universal mistakes you should avoid. Knowing these common pitfalls inside and out will ensure you stay on the right path and earn the best possible return on investment (ROI) from your analytical efforts. Let’s look at them:

Working with uncleaned information

One of the biggest mistakes we see is companies working with unvetted or unclean data. While it’s best to work with information from various relevant sources, it’s also crucial to omit any analytical information that is incorrect, misleading, or not absolutely essential to your organizational goals or progress.

To avoid such a pitfall, select sources you know will offer genuine value to your organization, then set about cleaning each pocket of information so that a clean funnel of metrics remains. Doing so will ensure your reports are true and accurate and won’t lead you down the wrong path.

Using one type of metric

What we mean here is that you shouldn’t narrow your analytical scope when creating a report. That said, you ideally want to work with visuals that offer historical, predictive, and in-the-moment intelligence.

By working with all of these ‘metric types,’ you will become more responsive while gaining the tools to examine past successes or failures and make accurate strategic projections for the future.


While adding as much information as humanly possible is tempting, doing so will only result in overload. If your users are presented with too many metrics at one time, they will become distracted and overwhelmed.

You should only include visuals vital to your storytelling efforts while avoiding on-page clutter at all costs. Keep your designs neat, functional, and logical—doing so will help your users discover the information they need swiftly and confidently.

Being set in stone

Another significant pitfall of reporting is thinking that the battle is won once you’ve set everything up and you’re earning results.

Niche or sector aside, the business world is in a state of continual change. What works today might not work tomorrow, so it's paramount to regularly check in with your creations and make visual or informational tweaks where required.

The best analysis tools are fully customizable, making it easy to switch informational sources or update designs or metrics at any point. Consider whether your reporting formats are still offering the best ROI for your efforts, and if you believe they are falling short, evolve your designs and your efforts for success.

Data Reports Examples and Templates

Let's move on to data reporting examples to put everything we’ve discussed so far into perspective. Apply these examples during your report generation process to create reports that drive action and add value to your company’s efforts. 

These powerful data report examples have been developed with the help of a professional dashboard designer , who empowers everyone in the business to build their own reports. Let’s start with the finance department.

1. Financial KPI Dashboard

Finance is the beating heart of any organization, and creating a financial report is the basis for sustainable development. Companies need to monitor their monetary operations closely and ensure that their financial data is 100% accurate.

Our example focuses on metrics meticulously chosen to depict a company's general financial health. The information is presented logically, connecting various financial indicators that make a complete data story without overcrowding the screen or complicating the report.

Data report example from the financial department

**click to enlarge**

Primary KPIs:

  • Working Capital
  • Quick Ratio / Acid Test
  • Cash Conversion Cycle
  • Vendor Payment Error Rate
  • Budget Variance

Data reporting is quite simple in this case: Presenting the most important information in a clear financial narrative that will drive action. This financial dashboard shows that the company managed to decrease the cash cycle, but the vendor payment rate spiked in September last year. It might make sense to take action and see in more detail what happened so that the processes can be adjusted accordingly.

2. Marketing KPI Dashboard 

Our next example is an intuitive marketing report composed of critical metrics related to costs and revenue. Marketers need to keep close track of this data as it helps them understand the success of their marketing efforts as well as find improvement opportunities to ensure a healthy marketing ROI.

Marketing data report for management, with main KPIs about costs and revenue

Primary KPIs: 

  • Cost per Acquisition (CPA)
  • Customer Lifetime Value (CLTV)
  • Return on Investment (ROI)

With valuable coverage on revenue per acquisition, profit per acquisition, cost per acquisition, and more, this data report format provides a useful overview of the most impactful marketing indicators for making strategic decisions. For instance, by looking at the CPA by channel and campaign, you can understand which of them are acquiring the most customers at the lowest price. In this case, we see that social media is the channel that brings the lowest cost per acquisition and the highest profit; therefore, it makes sense to invest more time and resources into it. 

Aside from being a great tool to support efficient decision-making, the report's visual nature makes it the perfect overview for your CEO or investors to prove the success of different marketing activities.  

3. Retail KPI Dashboard

Retailers must be extra careful in picking the right metrics and presenting their data in a clear order. They must avoid cluttering the report or confusing the people who need to read it and act accordingly.

Data reporting examples from the retail industry

  • Back Order Rate
  • Rate of Return
  • Customer Retention
  • Total Volume of Sales

A retail dashboard such as the one presented above focuses on the perspective of orders, which is one of the crucial points in this cutthroat business.

Gaining access to these touchpoints will equip you with the best possible ingredients to stay competitive in the market. Utilizing KPIs such as the rate of return (also by category), customer retention rate, and the number of new and returning customers will enable you to access in-depth information on your order processes and ensure your actions stay focused on developing your company sustainably. For example, you can monitor the return rate and ensure it stays as low as possible. That way, your costs will be significantly lower and, ultimately, customers more satisfied.

Your retail analytics processes don’t need to foster complex reports, but with an example, such as we presented above, you can see that reporting with dynamic visualizations empowers you to make better business decisions.

4. Customer Support Dashboard 

Our next data report template is a customer service dashboard that offers a mix of metrics related to costs, revenue, and customer satisfaction. With this information, the support team can optimize their performance by finding improvement opportunities based on data.

Customer service data report presented with the revenue value, costs per support, average time to solve an issue and overall satisfaction

**click to enlarge** 

  • Service Level
  • Support Costs vs Revenue
  • Customer Satisfaction

Although it might not seem the most obvious area to invest in, your customer service experience can make or break your company. If clients are unhappy with your problem-solving capabilities, they will likely not return to make another purchase. For this purpose, this report offers insights into revenue and costs, which helps you monitor that everything is running smoothly. For example, if your revenue is going down and your costs are up, you need to think of solutions to make the service department more profitable. 

This insightful report also offers insights into customer satisfaction and the average time your support agents spend solving issues. This can also give you insights into your team's general productivity. If you see that the average time to solve an issue is rising, then you can dig deeper into the reasons and find solutions to decrease it. 

5. Talent Management Dashboard

The next example is our HR dashboard , which is focused on talent management. Talent retention and development are ongoing challenges for HR managers. This data-centric reporting tool is designed to consistently keep your top-performing staff engaged and motivated.

A visual data reporting example showing the talent management metrics of a company: the hiring stats, NPS, talent turnover rate, etc.

  • Talent Satisfaction
  • Talent Rating
  • Talent Turnover Rate
  • Dismissal Rate

With a wealth of at-a-glance insights essential to successful talent management strategies and HR KPIs focused on rising talent as well as dismissal and turnover rates, this invaluable tool will prove vital to the health and growth of your organization. Moreover, your HR analytics efforts will prove to enhance hiring processes, enabling you to attract the best possible talent, automate tasks, and create a satisfying workforce environment.

6. Sales Opportunity Dashboard

Sales are integral to most companies' success. Our sales dashboard will help you easily identify revenue-boosting sources and prioritize them in order of prospective value.

A monthly sales report focused on sales opportunities and showing details on latest opportunities, number of opportunities and average purchase value by package, and churn reasons, among other metrics

  • Number of Sales Opportunities
  • Sales Opportunity Score
  • Average Purchase Value

These KPIs will allow you to streamline your sales strategy for maximum income, efficiency, and sustainability. This visually-balanced performance dashboard is easy to understand and will help you take direct action when it matters most – a priceless business intelligence tool for any forward-thinking organization.

7. IT Issue Management Dashboard 

IT analytics is another relevant area in which reporting data is useful. The IT department deals with a lot of information daily, and this report helps them keep track of everything related to technical issue management.

IT data report tracking the occurrence of technical issues to improve system operational performance

  • Server Downtime
  • Meantime To Repair
  • Unsolved Tickets Per Employee
  • IT Support Employees per End Users

This insightful IT dashboard overviews the most important metrics needed to ensure technical issues are resolved efficiently. First, we get an overview of the real-time status of three main servers alongside information on the last time they were down. This lets you see at a glance if everything is going smoothly or if something needs immediate attention. 

This data report sample also offers information on the most common downtime issues, which lets you find the root causes of recurring issues and prevent them from happening again. Paired with this, you get data about the performance of the different IT employees. As seen in the chart, three employees have a low ratio of solved tickets compared to unsolved, meaning their amount of unsolved issues is much higher than the number of tickets they have solved. This can mean they lack training or a specific issue is very hard to solve. The data allows you to dig deeper into the reasons and improve efficiency. 

8. Procurement Quality Dashboard

Our procurement dashboard is designed to streamline and fortify the relationship between you, your vendors, and your suppliers.

The procurement quality dashboard is a data report that shows KPIs such as the number of suppliers, quality rating, project analysis, etc.

  • Supplier Quality Rating
  • Vendor Rejection Rate & Costs
  • Emergency Purchase Ratio
  • Purchases In Time & Budget
  • Spend Under Management

Cohesive procurement is vital to any modern organization's financial and operational success, regardless of industry or sector. This interactive procurement report will help you quality-check your suppliers while digging deeper into metrics surrounding emergency purchases, rejection rates, costs, budgetary constraints, and more. These insights help procurement managers to be more proactive, efficient, and sustainable in their every move.

9. Hospital Performance Dashboard 

From patient care to staff management, this insightful data report template for hospital performance is the perfect visual tool to ensure efficient facility management. More than any other industry, healthcare institutions can benefit from real-time data as it allows them to act immediately as soon as an issue arises – especially considering that any problems can affect the well-being of patients.

Hospital data report displayed on a dashboard to monitor the performance of the facility

  • Average Hospital Stay
  • Hospital Readmission Rates
  • Costs By Payer

Armed with powerful healthcare KPIs , this data analysis report covers every relevant area to ensure the efficient functioning of the hospital. By using targets and desired outcomes to achieve, managers can find improvement opportunities on a clinical, operational, and financial level. For example, readmission rates are a metric that can directly affect your reputation as it is a token of the quality of care provided in your facilities and should remain as low as possible. 

This tool can also provide relevant information about patients and staff. The nurse-to-patient ratio indicates how many nurses are available per patient. For example, if you see the ratio increasing during night shifts, you must ensure you have the right staff working at those times.

10. Facebook Page Dashboard 

Next up, we have a social media report example for Facebook. With insights into page views, behaviors, interactions, follower demographics, likes, engagements, and more, this report provides all the needed information to optimize your Facebook page's growth and ensure your strategies' success.

A Facebook page data report that provides insights into all the important metrics on this social network

  • Number of Fans
  • Follower Demographics
  • Page Views by Sources
  • Actions on Page

Understanding the behaviors of your target audience is crucial for success when creating social media campaigns. Generating targeted experiences for your audience will not only make them more loyal to your brand but also save you money and time on targeting the wrong people. For that purpose, this insightful Facebook dashboard is an invaluable tool. 

Like other social channels, Facebook has its best practices and techniques to follow to ensure the best results from your organic, paid, and viral campaigns. While some of the metrics might seem purely informational, like the fans by country or gender, when mixed together, they can provide deeper conclusions that will help generate interesting content and gain loyal followers in the process.

11. Supply Chain Management Dashboard

Your supply chain is one of the most crucial aspects of any modern organization. Optimizing every element of your supply chain will make your company more efficient while boosting your bottom line. Having an effective supply chain will also help you deliver on your customer-facing promises, which in turn, will build trust and accelerate your commercial growth.

One of our data reporting examples for the supply chain management

Primary metrics

  • Inventory Accuracy
  • Inventory Turnover
  • Inventory to Sales Ratio

As one of our most visually grabbing data report examples, our supply chain logistics dashboard offers all the metrics required to explore, examine, and improve every key aspect of your processes.

Here, you can establish a firm grip on your inventory level of out-of-stock items while gaining a deeper understanding of overall inventory accuracy. You can also uncover key trends in your sales-to-inventory ratio and inventory turnover.

By gaining access to this melting pot of visual information in one cohesive space, you can decide exactly where you need to rethink your inventory choices, stocking, supply, and communication processes.

Regularly working with this data analysis report template will empower you to take charge of your supply chain while remaining adaptable to consistent change. In turn, you will gain an edge over the competition.

12. Manufacturing Production Dashboard

For organizations that deal in manufacturing, having the tools to track various processes, respond to issues, and make informed development decisions is essential. Without a clear-cut vision, things can quickly spiral out of control, putting a significant dent in budget and brand reputation.

Manufacturing data report displaying main manufacturing KPIs to keep the pulse of your factory

  • Production Volume
  • Production Downtime
  • Production Cost

This eye-catching data report example serves up critical manufacturing metrics , offering a panoramic snapshot of every cog in the machine as a result.

Here, you can drill down into your key production volumes over a specific timeframe while gaining a detailed glimpse into production costs and downtimes. Combined, these metrics will show you how efficiently your machines work while finding a correlation between productivity and revenue.

This dynamic tool will also tell you which machines are the most efficient, which will help you better distribute your production output or volumes to make your strategy as efficient as possible across the board.

Working with this tool frequently will reduce unnecessary costs and long-winded processes while helping you nip any emerging issue in the bid before it gets out of control–the perfect manufacturing manager’s companion.

13. Content Quality Control Dashboard

In an age where the consumer is well and truly in control, content is the cornerstone of building trust, establishing brand authority, and standing out from the crowd. Without publishing consistently high-quality content that meets your audience’s needs across channels, you will get left in the commercial dust.

Data report example tracking content marketing performance metrics

  • Flesch Reading Ease
  • Average Comments per Article
  • Story Turnaround Time

A data report sample designed to keep your content marketing efforts consistently on track, this powerful reporting tool is packed with visuals that will elevate your brand to new heights.

Here you can use the Flesch reading test metric to gauge the accessibility of your content while pinpointing exactly which pieces of content are performing best across channels. This most dynamic of data analysis report examples will also show how many digital subscribers you’ve gained over a certain timeframe while exploring article engagement.

If you know what your consumers want or need in terms of informational value, you will skyrocket your company’s success—and you can do that with this content report .

This perfect combination of visual information will ultimately ensure you’re producing the content that resonates most with specific audience segments while earning a consistently high return on investment (ROI) from your efforts.

14. Cyber Security Dashboard

Next is our cyber security dashboard, which helps businesses maintain a firm grasp of their systems. This IT report is mission-critical, as today’s organizations handle no shortage of sensitive information that needs to be protected. With the potential for cyber crimes at an all-time high, it’s crucial for companies to monitor for threats and implement long-term prevention measures. 

Data report example tracking cybersecurity metrics

  • Total intrusion attempts
  • Phishing test success rate
  • Intrusion attempts by malware type

To deploy proactive cyber defense, we compile essential insights into a single view. This cyber security dashboard shows you an overall security rating, along with key elements like intrusion attempts, phishing test success rates, and mean detect and resolution times.

Metrics like intrusion attempts by week and phishing test success rate show you historical values so you can see how you’re improving your cyber security efforts week by week. You can also dig deeper into specific weeks to gain more context about your efforts and events for that week. These insights can help you identify major risks and understand your employees' daily challenges, allowing you to implement the right measures to protect them (and your organization).

15. Pick and Pack Scorecard

The pick and pack scorecard focuses on warehouse operations, specifically order processing. Pick and pack refers to the procedure employees follow, starting from receiving an order to preparing an order for shipment. It entails locating the item(s) on the order, placing them in the packaging, logging them out of inventory, printing shipping labels, packaging them together, and scheduling the shipment. With so many moving parts, a detailed scorecard can provide the comprehensive view you need to identify inefficiencies.

Data report template tracking pick and pack metrics

  • Pick and pack costs
  • Pick and pack cycle times
  • Cost of packaging materials
  • Picking accuracy

This pick and pack dashboard offers insights into four key areas: Financial, Effectiveness, Utilization, and Quality. Starting with the financial section, users can track the average cost of pick and pack processes by line and the cost of returns per order. These metrics are displayed on a monthly basis, and you can view the current month and previous month on the same screen.

Next, we see productivity and effectiveness data to show how efficiently employees work. Big fluctuations in these metrics could indicate a lack of training and/or a need for new processes or quality controls, for example. Utilization also relates to the financial aspect, as you don’t want to spend more on materials and equipment than necessary. 

16. Energy Operational Dashboard

Our energy dashboard is designed for operations managers who need a bird' s-eye view of their operations and facilities. Here, we combine production distribution, availability, energy savings, and other metrics in a single view. Large plants have complex energy needs, so this dashboard helps simplify understanding energy consumption.

Energy operational dashboard as an example of a data report

  • Production distribution
  • Energy savings
  • Availability factor
  • Performance ratio

The availability section refers to the amount of time your plant can operate. This metric is especially helpful when you manage multiple plants, as it helps identify potential equipment problems so you can plan for downtime. 

Production distribution helps you better understand your customers. Knowing how much of each type of energy you’re producing allows you to anticipate consumer demand and adapt your supply accordingly.

Last but not least, we have each plant's performance ratio. You can compare actual production to projected production, gauging each facility's efficiency. The difference between these two metrics can arise from a number of factors, including energy losses from solar input or water systems, for example. This indicator allows you to spot issues and take action before losses mount significantly.

17. HR Executive Dashboard

Next on our list is the HR executive dashboard, a critical helper for maintaining growth goals, employee satisfaction, and salary costs. Talent shortages and an unpredictable labor market directly impact a company’s ability to grow, so it’s essential for HR to stay ahead of the curve and make key hiring decisions at critical moments.

Data report template tracking HR metrics for executives

  • Employee satisfaction
  • Vacancy rate
  • Salary costs to gross revenue

Maintaining a healthy workforce focuses on three key areas: high employee satisfaction, adequate staffing so employees are not overworked, and fair salary costs compared to the company’s financial health. This dashboard encompasses each of these areas in a single view.

This first section shows a growth headcount chart with insights into current vacancies, new hires, and turnover. We can see how these counts fluctuate and prepare salary budgets, recruiting efforts, and retention initiatives accordingly. 

In the employee satisfaction section, we gain insight into employees' happiness, which may indicate their likelihood of remaining with the company. This chart also includes manager feedback scores, which directly impact how confident employees feel in their roles. We can observe how these values change over time and influence other areas like hiring, retention, and turnover.

18. Operating Expenses Dashboard

Last on our list is the operating expenses dashboard. This financial dashboard is a daily helper to CFOs, as it allows them to view operating expenses, fixed and variable expenses, and operating ratios in one view.

Operating expenses analysis as an example of data reporting

  • Operating expense ratio
  • Fixed expenses
  • Variable expenses
  • Net profit margin

Operating expenses refer to all of the costs an organization incurs as a result of operations. These expenses may include marketing costs, production costs, employee salaries, rent or mortgage, inventory costs, and insurance, for example. 

Here we have a breakdown of fixed and variable costs, which are paid over a defined period. We can look at fluctuations in these expenses as they relate to output to see which ones we can influence. To better understand these costs, we can look to other metrics like production to see why certain costs may increase or decrease.

One of the most valuable KPIs in this chart is the operating ratio, which adds context to the overall financial picture. This metric represents operational expenses as a percentage of revenue and can indicate the success of your expense optimization efforts. Ideally, you’ll keep this ratio as low as possible without impacting efficiency or output.

Start Building Your Data Reports Now!

We’ve answered the question, ‘What is data reporting?’ and explored a host of powerful data reporting templates. During our journey, one thing has become clear: investing in the right analytical tools and processes will propel your organization ahead of the pack.

Now that you know how to create efficient data analysis reports, it’s time to embrace the power of modern BI solutions and data analytics.

Reporting, analytics, and smart informational processing can have a transformational impact if approached correctly.

Fortunately, the mind-numbing task of manually creating daily or weekly reports is a thing of the past. With the right plan and proper business reporting software , you can easily analyze your data and also create eye-catching and remarkable reports.

We live in the age of information, a time when anything is possible. By embracing data-centric reports and forming the right foundations, you will accelerate your organization's success in ways you never thought possible, pushing you ahead of the pack in the process.

All you need to do is follow these essential steps and recommendations, and you will be on your way to a brighter, more prosperous commercial future. If you want to start creating your own powerful and modern reports and testing all of these practices, you can try datapine for a 14-day trial , which is completely free. The time to strike is now.

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How to Create a Data Analysis Report: A Comprehensive Guide

Pravinan Sankar

Table of Contents

Imagine you're a skilled chef tasked with creating an exquisite dish for a prestigious culinary competition. 

You know that the quality of your dish depends on the ingredients you choose, the techniques you employ, and the way you present that impress the food critics.

In marketing operations, creating a data analysis report is a lot like preparing that exquisite dish: every step matters, from selecting the right metrics "ingredients" to presenting the final insights with clarity and accuracy.

As marketing operations become increasingly data-driven, the significance of data analysis reports cannot be overstated. These reports empower marketing professionals to make informed decisions, optimize campaigns, and lead to improving return on investment (ROI). 

A research study from McKinsey Global Institute reveals that organizations that leverage data-driven approaches are 23 times more likely to acquire new customers, six times more likely to retain existing customers, and 19 times more likely to be profitable. 

The stakes are high, and it's essential for marketers to master the art of creating comprehensive and actionable data analysis reports.

Just as a chef must balance flavors and textures, marketers must balance their data analysis with the right mix of tools, techniques, and presentation. 

Carly Fiorina , Hewlett-Packard (HP) Company's former CEO, famously stated, "The goal is to turn data into information and information into insight." 

To achieve this, one must understand the nuances of crafting data analysis reports that provide valuable insights and are easily digestible for high-level business stakeholders.

In this blog post, let’s explore how to create a data analysis report for marketing operations that can help you leverage your data effectively and convert it into actionable insights that drive marketing success.

What is a Data Analysis Report?

A data analysis report is a structured business report that presents insights, findings, and actionable recommendations derived from the analysis of raw data. Think of it as a treasure map, guiding you through vast oceans of data to unearth valuable insights and make informed decisions.

This comprehensive report consolidates, interprets, and presents data, enabling you to transform raw information into actionable knowledge. 

For a SaaS business, a data analysis report is crucial in helping you understand your customers better, enabling you to tailor your offerings and marketing campaigns to meet their needs and preferences better.

For instance, product marketers may analyze customer churn rates alongside user engagement metrics, discovering that customers who engage with specific features are less likely to churn. This insight could prompt the marketing team to create targeted campaigns that promote those features to customers at risk of churning.

Also, a data analysis report allows you to track the performance of your various marketing initiatives, such as cost-per-click (CPC) of campaigns, content marketing, and email marketing.

By analyzing key performance indicators (KPIs) like click-through rates, conversion rates , and customer acquisition costs , you can identify the most effective marketing channels and allocate your resources accordingly.

Suppose your data analysis report reveals that your email campaigns are generating a higher ROI than your social media advertising. In that case, you can focus more resources on email marketing to maximize results.

In a nutshell, a data analysis report acts as a roadmap for decision-makers, providing them with the necessary information to make informed choices that drive growth and success.

Are you struggling with scattered sales data across multiple channels?

Dataflo Sales Dashboard offers a unified view for sales funnel performance tracking, KPI monitoring, automated reporting, and seamless collaboration, all tailored to simplify your analytics process.

how to write an analysis report of data

Importance of Data Analysis Report

Data analysis reports play a critical role in modern businesses, especially in the fast-paced and competitive landscape of SaaS. Let's discuss the key reasons why data analysis reports are vital for your marketing operations and overall business success.

Data-Driven Decision-Making

Data analysis reports provide a solid foundation for making strategic decisions. They transform raw data into meaningful insights, allowing decision-makers to understand trends, patterns, and opportunities. With a data-driven approach, you can ensure that your marketing strategies are based on evidence rather than relying solely on intuition.

Performance Evaluation

The effectiveness of marketing campaigns, ranging from content marketing to PPC ads, can be measured using a well-designed data analysis report. Tracking KPIs and other metrics enables businesses to evaluate which tactics are successful and which require improvement, allowing them to optimize their marketing strategies and achieve better results.

Enhanced Customer Understanding

Understanding your customers is at the heart of any successful marketing campaign. Data analysis reports help you gain a deeper understanding of your target audience's preferences, behavior, and needs. This information enables you to tailor your marketing messages, product offerings, and user experience to better resonate with your customers and attract new users.

Improved Marketing Strategies

Armed with insights from data analysis reports, you can optimize your marketing strategies to ensure maximum impact. Identify the most effective channels, create targeted campaigns, and allocate your resources wisely to drive engagement, conversions, and better ROI.

Better Resource Allocation

Efficient use of resources is vital for any business, especially in the SaaS industry. Data analysis reports can help you determine which aspects of your marketing operations require more attention or investment. This way, you can allocate your resources effectively and ensure that every dollar spent contributes to growth and success.

Improve Cost-effectiveness:  

Focusing on strategies that deliver the best results, businesses can optimize their marketing budget and achieve a higher return on investment. Data analysis reports enable businesses to identify the most effective marketing channels and tactics, leading to cost-effectiveness while optimizing their marketing spend.

Improved collaboration and communication:  

A clear, concise data analysis report can facilitate better communication and collaboration across your organization. When stakeholders can easily understand the insights and recommendations derived from data analysis, aligning teams and working towards common goals becomes more effortless.

How to Create a Data Analysis Report

Now that we've grasped the significance of data analysis reports, let's delve into the step-by-step process of crafting one that caters to the diverse needs of your business and enhances decision-making across various departments.

How to Create a Data Analysis Report

Define the Purpose of the Report

Start by identifying the specific objectives you want to achieve with your data analysis report. Are you looking to optimize your marketing campaigns, improve customer retention, or identify new growth opportunities? 

Defining the questions you want to answer or problems you aim to solve is crucial to guide your data collection and analysis process and keeping your report focused on addressing the most relevant scopes.

Identify Your Audience

Understanding your audience is crucial for creating an effective report. Think about who will read the report and what information they need. 

Evaluate the needs and preferences of your stakeholders, whether they are executives, marketing team members, or product managers, and tailor your report accordingly.

Tailor your presentation style, language, and level of detail to meet the needs and expectations of your target audience, ensuring the report is accessible and engaging for them.

Gather and Organize Your Data

Collect the data required to address the report's purpose. This may involve pulling data from various sources, such as CRM systems, Google Analytics, and marketing automation tools. Organize the data in a logical and structured manner, making it easier to analyze and interpret.

Analyze and Interpret Your Data

Use appropriate statistical techniques and data visualization tools to analyze the data and uncover insights. Interpret the findings in the context of your business objectives, highlighting the key takeaways and potential implications for your marketing operations.

Determine the Structure of Your Report

Organize your report in a clear and logical manner, and make it easy for the reader to follow. A typical structure may include an executive summary, introduction, methodology, results, discussion, recommendations, and conclusion. Use headings, subheadings, and bullet points to break up the text and enhance readability. This approach will help ensure your content is well-organized and easy to follow.

Write an Executive Summary

Create a concise and informative executive summary that provides an overview of the report's purpose, key findings, and recommendations. This will allow busy stakeholders to grasp the main points quickly and decide whether they need to delve deeper into the report.

Write the Body of the Report

Craft the main sections of your report, presenting your data analysis findings, insights, and conclusions. Be clear, concise, and focused on addressing the report's purpose. Use visuals like charts, graphs, and tables to illustrate key points and make the information more easily digestible.

Reporting and Visualization

Use appropriate data visualization tools to present your findings in a visually appealing and easy-to-understand format. Choose the most appropriate visualizations for your data, such as bar charts, pie charts, or line graphs, and ensure they are well-designed, clear, and accurately represent the data.

Review and Revise Your Report

Carefully review your report, and check for accuracy, clarity, and consistency. Ensure the information presented is relevant to your purpose and audience. 

Edit and revise as necessary, making sure your report is polished, professional, and ready for presentation.

Following these steps will help you create a comprehensive data analysis report that effectively communicates your findings, provides valuable insights, and empowers your marketing operations to make data-driven decisions for your SaaS business's success.

As the renowned data scientist W. Edwards Deming once said, "In God we trust; all others must bring data." 

Your data analysis report serves as a testament to the power of data, helping your organization navigate the complexities of the business landscape and achieve greater heights.

How can Dataflo help in Dashboard Analysis Reports?

Dataflo is a powerful platform that simplifies the way your team visualizes and analyzes marketing metrics from various business applications. With Dataflo, you can spend less time creating reports and more time acting on valuable insights.

Here's how Dataflo can help you create effective dashboard analysis reports:

Scale Performance Across All Marketing Channels:

Dataflo allows you to gather data from different marketing channels to compare and understand their performance. Measure campaign performance, derive insights from channels that generate more revenue, and optimize for higher ROI. Also, you can leverage insights from the funnel dashboard to comprehend the customer journey better.

Pre-built Dashboard for Every Marketing Activity:

With Dataflo, you don't have to waste time creating reports from scratch. Your metrics are auto-populated into the dashboard after the initial setup, allowing you to easily measure ad spend, social media performance, blog traffic, and email open rates and adjust your marketing strategy accordingly.

Save Hours Preparing Marketing Reports:

Dataflo eliminates the need for spreadsheets and juggling countless tools to prepare marketing reports. Simply sync data sources, select the metrics you want to track, and you're ready to go. 

Stay informed of spikes or dips in key metrics with instant Slack notifications. Improve efficiency by automating performance alerts and ensuring everyone is notified about changes in KPIs, metric performance, goals, and more. 

Track Progress and Measure Marketing Goals in Real-Time:

Your dashboard is always up-to-date with real-time data once you connect the data source. Dataflo's KPI dashboard platform enables you to set goals against your KPIs, allowing you to measure and track marketing success against both short-term and long-term objectives planned for your business.

Collaborate with Context:

Dataflo facilitates seamless communication and collaboration among team members. Easily comment on and tag key metrics that need attention, and share the progress of your marketing initiatives with department heads via Slack or email. 

Dataflo seamlessly integrates with your marketing tech stack, providing a comprehensive solution for managing and analyzing your marketing data.

Data analysis reports are a critical aspect of marketing operations, providing invaluable insights and actionable recommendations to drive your SaaS business's success. Leveraging a data analytics tool like Dataflo , you can simplify the process of creating visually appealing dashboards that can automate report generation and foster a data-driven culture within your team.

Remember, much like a skilled chef preparing a dish, select the right metrics "ingredients," use effective analysis techniques, and present your insights in a clear and engaging manner. 

With the right approach and tools, you can turn raw data into valuable insights that empower your marketing team to optimize campaigns, improve ROI—and grow your business!

Get a 360 degree view of your business performance with GA4 Dashboard today

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Wouldn't it be nice to have a single dashboard that summarizes all your marketing efforts in one place? Check out Dataflo’s pre-built customizable dashboard for monitoring and evaluating the success of your paid marketing efforts across all your ad campaigns.

What if you get common values for Impressions, Clicks, CTR, CPC etc. for your multiple ad campaigns all under one roof?

Dataflo simplifies your paid advertising reporting with this feature. You don’t have to depend on often messy, time-consuming spreadsheets to track the most important KPIs/ metrics. No more logging into multiple accounts or hopping between different tools in the tech stack to check how your accounts on different channels are performing, or compiling a comprehensive report that seems to take eternity.

Now you can view your Facebook, Twitter and other social media performance metrics in one place.

Get started by following these 3 simple steps:

Step 1: Get our pre-built template

Step 2: Connect and integrate your PPC accounts with Dataflo

Step 3: In seconds, your dashboard will be ready to use

All your metrics inside your slack

Using Slash command in Slack, track your key metrics for a given period in just 3 clicks.

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Pravinan Sankar

Pravinan is a physicist turned writer who's currently wearing the marketer's hat. A tech enthusiast by nature and an avid non-fiction books reader, he loves to explore the world around him and always keep learning new things. When he's not working on his latest project, he likes to spend his time writing Tamil poetry or finding out more about organic farming.

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How to write a Data Analysis Report like a Pro

How to write a Data Analysis Report

In the last article, I discussed the great use of new software to build interactive dashboards to show the most important indicators in a company while retaining interactivity. But, beyond the dashboards, you would want to know that how to write a data analysis report like a pro.

Why? Because there are times when you don’t want only to show information to your audience – you want to make a point.

Probably it’s because you found something while investigating those huge datasets that really caught you off guard, and you want everyone to know about it.

Perhaps you found a faulty process and you want to analyse many courses of corrective action.

Or you may want to implement new ideas to improve sales.

In these cases when your analysis leads to a story that you can tell your audience to make them arrive at the same conclusions you made, reports come in. That’s why it really important for you to know how to write a data analysis report like a pro so that you can make a rock-solid impact!

I’ve worked in many companies where dashboards weren’t implemented and the main way to communicate indicators to the executive with periodical measurements of certain indicators was to mail them a report.

Sometimes these reports included some analysts’ explanation of the changes of the numbers from point A to B in time, but, mostly, these reports were some static version of a dashboard. With technology nowadays on our side, this isn’t the idea of reports that I’m trying to tell you about.

  So, what is a report?

A report tells your audience a story and backs it up with indicators and stats. However, they aren’t scientific papers.

While reports can include methodologies, be rigorous and have a thread like paper. Most of the times your readers won’t care about how you conducted your investigation while replicating your findings, not even to assess whether your methods are correct. This is your job and probably your boss’.

What they want to hear is a compelling story. They are waiting to be convinced of your conclusions.

Great, where do I get started?

Here I answer and suggest some of the most crucial things to suggest how to write a data analysis report.

First of all, whatever your report is about, you start with a problem or a question you want to solve. You’ll write about this in your introduction , where you’ll also write, albeit briefly, about the tools and methods you used for the data analysis.

Most of the times you can omit these things and leave your problem statement only, so as not to lose your reader’s attention from the very beginning, especially when reports go to high executives.

Once the problem is introduced, you’ll have a body where you further describe and analyse the problem with the available data. Here you’ll measure and plot all the necessary indicators to support the conclusions you’ll make at the end of the report.

In this point, I suppose you’ve arrived to correct conclusions and that you’ve tested them in order to gather evidence of the correctness of them. Testing them could be done by either using statistical tests or by searching for hard evidence against your hypothesis.

If you do not find conclusive and strong proofs against your hypothesis, it stays. If you do find then go back and do the work again, please do not lie to yourself and your bosses.

The report tries to make a point arriving at a certain conclusion, therefore, gather all the evidence in the body of the report. Isolate the most convincing arguments and, if possible, show opposing views that can’t be supported with the available data. This kind of intellectual honesty will gather strong support for the opposing view and add more credibility to the conclusions

You can also have a descriptive report , where you want to find why certain indicators changed the way they did. Or you would also want to know whether this is positive or negative and if there are any correlations among variables that affect these indicators.

You should avoid making a conclusion in a descriptive report. Sometimes, executives want to be the ones making conclusions or suggestions from the report and want to have an accurate description of the changes in indicators and highlight the most important ones with the biggest changes.

This is in contrast with dashboards, where they are left to figure it out for themselves.

Warning! When graphs become your enemy

I’ve talked lots about reports being stories, but they’re kind of boring stories. Or, in fact, they’re like trying to explain the story to someone who hasn’t heard of it and does not have much time to listen to you anyway.

So, with this in mind, your main goal is coming as clear as it’s possible to what you’re trying to convey with the minimal amount of wording possible. And seriously, that’s the best advice for how to write a data analysis report like a pro.

Anything else it’s just a distraction. This is especially true for plotting data sets in your reports.

Many like including lots of plots in their reports. This can lead to cluttering the reader’s vision and diverting his attention to unimportant things.

Avoid it at all costs.

Memorize this for your entire career: any graph that doesn’t back any of your points and that you don’t refer to in the main body of your argumentation, it’s best to eliminate it .

When you’re talking to someone and this person strays from the thing they’re trying to tell you and you’re becoming increasingly upset by this, you say: ‘Okay, but, go to the point!’. Keep this attitude with your reports. If possible, get someone else to do proofreading for you – only then you can receive criticism from someone who can abstract from the problem you’ve faced and for which you’re writing your report.

Choosing the right graphs

Even if many graphs are backing the main point, you should consider whether your arguments are evident in this visualizations. If not, better try to aggregate your data or change the visualization completely.

There are many considerations that can be had with graphs. There are entire courses and lots of scientific research that’s done on the topic of visualization of information.

You should be faithful to these points when graphing:

  • Be minimalist: don’t make things more complex than they need to be, they obscure the intent of the graph.
  • Beware of distortions in the visualization with respect to the data being mapped to a visualization. Many graphs vary more than one visual element for each variation on a single variable in data (see the graph below). Never EVER do something like that. This is plain lying, do not compromise your credibility by designing something of this sort.
  • Give context to the data. Don’t distort your conclusions by avoiding comparisons of the same indicator at different points in time, for example. Give spatial and temporal context for the reader to compare.
  • Avoid cluttering a charts area with many things happening at once in your graph. Keep it as simple as you can while the data can still be understandable.

How to write a data analysis report

Just look at this graph, for example.

This is an abomination from the same depths Cthulhu came.

It’s beyond repair. It’s better to not plot anything than plotting something so misleading.

You can also calculate a “lie factor” by calculating the ratio of variation in data with the variation of the visual metaphor, in this case, the coin. In this example, it goes through the roof. Any number apart from approximately 1 is heavily distorting the data, giving the reader the impression of a variation in data that doesn’t exist.

For those of you who want to delve deeper into this fascinating world, check the following books:

  • “ Readings in Information Visualization. Using Vision to Think.” Card, S., Mackinlay, J., and Shneiderman, B. Morgan Kaufmann Pub., 1999.
  • “ Beautiful Evidence” , Edward R. Tufte, Graphics Press, 2006

Tools you can use

Basic tools.

In this case, there aren’t many specific tools for reporting. You can use any standard text processor like LibreOffice, Abiword, Google Docs, MS Word, etc. for standard writing. Then you can include plots coming from other tools, like those we’ve seen for dashboards, and also spreadsheet software like LibreOffice, Google Sheets and MS Excel.

More advanced tools

For those of yearning for something deeper, there are tools that help integrating code for data analysis, graphing and text for reports, compiling later to reports in various formats, like Rmarkdown (R code) and Jupyter Notebooks.  There’s also LaTeX, which is a way of formatting documents with code, it’s outcome looks super professional and it’s a standard in scientific publishing.

I’ll add two great open source code libraries for those who want to draw with them. You’ll find lots of templates of graphs and give you more freedom to do complex, innovative visualizations.

  • D3.js (JavaScript)
  • Processing (Java, JavaScript)

D3 How to write a data analysis report

Whew! Lots of info for you to go through. We’ve explored lots of things about how to write a data analysis report like a pro in this article! I’ve illustrated some key points for you to consider for your reports and for you to explore for yourself from now on. Look at other reports made in your sector and that other person made to learn both from the good and the bad. Read and write reports with a critic mind. Get started right now!

See you in the next article!

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A Step-by-Step Guide to the Data Analysis Process

Like any scientific discipline, data analysis follows a rigorous step-by-step process. Each stage requires different skills and know-how. To get meaningful insights, though, it’s important to understand the process as a whole. An underlying framework is invaluable for producing results that stand up to scrutiny.

In this post, we’ll explore the main steps in the data analysis process. This will cover how to define your goal, collect data, and carry out an analysis. Where applicable, we’ll also use examples and highlight a few tools to make the journey easier. When you’re done, you’ll have a much better understanding of the basics. This will help you tweak the process to fit your own needs.

Here are the steps we’ll take you through:

  • Defining the question
  • Collecting the data
  • Cleaning the data
  • Analyzing the data
  • Sharing your results
  • Embracing failure

On popular request, we’ve also developed a video based on this article. Scroll further along this article to watch that.

Ready? Let’s get started with step one.

1. Step one: Defining the question

The first step in any data analysis process is to define your objective. In data analytics jargon, this is sometimes called the ‘problem statement’.

Defining your objective means coming up with a hypothesis and figuring how to test it. Start by asking: What business problem am I trying to solve? While this might sound straightforward, it can be trickier than it seems. For instance, your organization’s senior management might pose an issue, such as: “Why are we losing customers?” It’s possible, though, that this doesn’t get to the core of the problem. A data analyst’s job is to understand the business and its goals in enough depth that they can frame the problem the right way.

Let’s say you work for a fictional company called TopNotch Learning. TopNotch creates custom training software for its clients. While it is excellent at securing new clients, it has much lower repeat business. As such, your question might not be, “Why are we losing customers?” but, “Which factors are negatively impacting the customer experience?” or better yet: “How can we boost customer retention while minimizing costs?”

Now you’ve defined a problem, you need to determine which sources of data will best help you solve it. This is where your business acumen comes in again. For instance, perhaps you’ve noticed that the sales process for new clients is very slick, but that the production team is inefficient. Knowing this, you could hypothesize that the sales process wins lots of new clients, but the subsequent customer experience is lacking. Could this be why customers don’t come back? Which sources of data will help you answer this question?

Tools to help define your objective

Defining your objective is mostly about soft skills, business knowledge, and lateral thinking. But you’ll also need to keep track of business metrics and key performance indicators (KPIs). Monthly reports can allow you to track problem points in the business. Some KPI dashboards come with a fee, like Databox and DashThis . However, you’ll also find open-source software like Grafana , Freeboard , and Dashbuilder . These are great for producing simple dashboards, both at the beginning and the end of the data analysis process.

2. Step two: Collecting the data

Once you’ve established your objective, you’ll need to create a strategy for collecting and aggregating the appropriate data. A key part of this is determining which data you need. This might be quantitative (numeric) data, e.g. sales figures, or qualitative (descriptive) data, such as customer reviews. All data fit into one of three categories: first-party, second-party, and third-party data. Let’s explore each one.

What is first-party data?

First-party data are data that you, or your company, have directly collected from customers. It might come in the form of transactional tracking data or information from your company’s customer relationship management (CRM) system. Whatever its source, first-party data is usually structured and organized in a clear, defined way. Other sources of first-party data might include customer satisfaction surveys, focus groups, interviews, or direct observation.

What is second-party data?

To enrich your analysis, you might want to secure a secondary data source. Second-party data is the first-party data of other organizations. This might be available directly from the company or through a private marketplace. The main benefit of second-party data is that they are usually structured, and although they will be less relevant than first-party data, they also tend to be quite reliable. Examples of second-party data include website, app or social media activity, like online purchase histories, or shipping data.

What is third-party data?

Third-party data is data that has been collected and aggregated from numerous sources by a third-party organization. Often (though not always) third-party data contains a vast amount of unstructured data points (big data). Many organizations collect big data to create industry reports or to conduct market research. The research and advisory firm Gartner is a good real-world example of an organization that collects big data and sells it on to other companies. Open data repositories and government portals are also sources of third-party data .

Tools to help you collect data

Once you’ve devised a data strategy (i.e. you’ve identified which data you need, and how best to go about collecting them) there are many tools you can use to help you. One thing you’ll need, regardless of industry or area of expertise, is a data management platform (DMP). A DMP is a piece of software that allows you to identify and aggregate data from numerous sources, before manipulating them, segmenting them, and so on. There are many DMPs available. Some well-known enterprise DMPs include Salesforce DMP , SAS , and the data integration platform, Xplenty . If you want to play around, you can also try some open-source platforms like Pimcore or D:Swarm .

Want to learn more about what data analytics is and the process a data analyst follows? We cover this topic (and more) in our free introductory short course for beginners. Check out tutorial one: An introduction to data analytics .

3. Step three: Cleaning the data

Once you’ve collected your data, the next step is to get it ready for analysis. This means cleaning, or ‘scrubbing’ it, and is crucial in making sure that you’re working with high-quality data . Key data cleaning tasks include:

  • Removing major errors, duplicates, and outliers —all of which are inevitable problems when aggregating data from numerous sources.
  • Removing unwanted data points —extracting irrelevant observations that have no bearing on your intended analysis.
  • Bringing structure to your data —general ‘housekeeping’, i.e. fixing typos or layout issues, which will help you map and manipulate your data more easily.
  • Filling in major gaps —as you’re tidying up, you might notice that important data are missing. Once you’ve identified gaps, you can go about filling them.

A good data analyst will spend around 70-90% of their time cleaning their data. This might sound excessive. But focusing on the wrong data points (or analyzing erroneous data) will severely impact your results. It might even send you back to square one…so don’t rush it! You’ll find a step-by-step guide to data cleaning here . You may be interested in this introductory tutorial to data cleaning, hosted by Dr. Humera Noor Minhas.

Carrying out an exploratory analysis

Another thing many data analysts do (alongside cleaning data) is to carry out an exploratory analysis. This helps identify initial trends and characteristics, and can even refine your hypothesis. Let’s use our fictional learning company as an example again. Carrying out an exploratory analysis, perhaps you notice a correlation between how much TopNotch Learning’s clients pay and how quickly they move on to new suppliers. This might suggest that a low-quality customer experience (the assumption in your initial hypothesis) is actually less of an issue than cost. You might, therefore, take this into account.

Tools to help you clean your data

Cleaning datasets manually—especially large ones—can be daunting. Luckily, there are many tools available to streamline the process. Open-source tools, such as OpenRefine , are excellent for basic data cleaning, as well as high-level exploration. However, free tools offer limited functionality for very large datasets. Python libraries (e.g. Pandas) and some R packages are better suited for heavy data scrubbing. You will, of course, need to be familiar with the languages. Alternatively, enterprise tools are also available. For example, Data Ladder , which is one of the highest-rated data-matching tools in the industry. There are many more. Why not see which free data cleaning tools you can find to play around with?

4. Step four: Analyzing the data

Finally, you’ve cleaned your data. Now comes the fun bit—analyzing it! The type of data analysis you carry out largely depends on what your goal is. But there are many techniques available. Univariate or bivariate analysis, time-series analysis, and regression analysis are just a few you might have heard of. More important than the different types, though, is how you apply them. This depends on what insights you’re hoping to gain. Broadly speaking, all types of data analysis fit into one of the following four categories.

Descriptive analysis

Descriptive analysis identifies what has already happened . It is a common first step that companies carry out before proceeding with deeper explorations. As an example, let’s refer back to our fictional learning provider once more. TopNotch Learning might use descriptive analytics to analyze course completion rates for their customers. Or they might identify how many users access their products during a particular period. Perhaps they’ll use it to measure sales figures over the last five years. While the company might not draw firm conclusions from any of these insights, summarizing and describing the data will help them to determine how to proceed.

Learn more: What is descriptive analytics?

Diagnostic analysis

Diagnostic analytics focuses on understanding why something has happened . It is literally the diagnosis of a problem, just as a doctor uses a patient’s symptoms to diagnose a disease. Remember TopNotch Learning’s business problem? ‘Which factors are negatively impacting the customer experience?’ A diagnostic analysis would help answer this. For instance, it could help the company draw correlations between the issue (struggling to gain repeat business) and factors that might be causing it (e.g. project costs, speed of delivery, customer sector, etc.) Let’s imagine that, using diagnostic analytics, TopNotch realizes its clients in the retail sector are departing at a faster rate than other clients. This might suggest that they’re losing customers because they lack expertise in this sector. And that’s a useful insight!

Predictive analysis

Predictive analysis allows you to identify future trends based on historical data . In business, predictive analysis is commonly used to forecast future growth, for example. But it doesn’t stop there. Predictive analysis has grown increasingly sophisticated in recent years. The speedy evolution of machine learning allows organizations to make surprisingly accurate forecasts. Take the insurance industry. Insurance providers commonly use past data to predict which customer groups are more likely to get into accidents. As a result, they’ll hike up customer insurance premiums for those groups. Likewise, the retail industry often uses transaction data to predict where future trends lie, or to determine seasonal buying habits to inform their strategies. These are just a few simple examples, but the untapped potential of predictive analysis is pretty compelling.

Prescriptive analysis

Prescriptive analysis allows you to make recommendations for the future. This is the final step in the analytics part of the process. It’s also the most complex. This is because it incorporates aspects of all the other analyses we’ve described. A great example of prescriptive analytics is the algorithms that guide Google’s self-driving cars. Every second, these algorithms make countless decisions based on past and present data, ensuring a smooth, safe ride. Prescriptive analytics also helps companies decide on new products or areas of business to invest in.

Learn more:  What are the different types of data analysis?

5. Step five: Sharing your results

You’ve finished carrying out your analyses. You have your insights. The final step of the data analytics process is to share these insights with the wider world (or at least with your organization’s stakeholders!) This is more complex than simply sharing the raw results of your work—it involves interpreting the outcomes, and presenting them in a manner that’s digestible for all types of audiences. Since you’ll often present information to decision-makers, it’s very important that the insights you present are 100% clear and unambiguous. For this reason, data analysts commonly use reports, dashboards, and interactive visualizations to support their findings.

How you interpret and present results will often influence the direction of a business. Depending on what you share, your organization might decide to restructure, to launch a high-risk product, or even to close an entire division. That’s why it’s very important to provide all the evidence that you’ve gathered, and not to cherry-pick data. Ensuring that you cover everything in a clear, concise way will prove that your conclusions are scientifically sound and based on the facts. On the flip side, it’s important to highlight any gaps in the data or to flag any insights that might be open to interpretation. Honest communication is the most important part of the process. It will help the business, while also helping you to excel at your job!

Tools for interpreting and sharing your findings

There are tons of data visualization tools available, suited to different experience levels. Popular tools requiring little or no coding skills include Google Charts , Tableau , Datawrapper , and Infogram . If you’re familiar with Python and R, there are also many data visualization libraries and packages available. For instance, check out the Python libraries Plotly , Seaborn , and Matplotlib . Whichever data visualization tools you use, make sure you polish up your presentation skills, too. Remember: Visualization is great, but communication is key!

You can learn more about storytelling with data in this free, hands-on tutorial .  We show you how to craft a compelling narrative for a real dataset, resulting in a presentation to share with key stakeholders. This is an excellent insight into what it’s really like to work as a data analyst!

6. Step six: Embrace your failures

The last ‘step’ in the data analytics process is to embrace your failures. The path we’ve described above is more of an iterative process than a one-way street. Data analytics is inherently messy, and the process you follow will be different for every project. For instance, while cleaning data, you might spot patterns that spark a whole new set of questions. This could send you back to step one (to redefine your objective). Equally, an exploratory analysis might highlight a set of data points you’d never considered using before. Or maybe you find that the results of your core analyses are misleading or erroneous. This might be caused by mistakes in the data, or human error earlier in the process.

While these pitfalls can feel like failures, don’t be disheartened if they happen. Data analysis is inherently chaotic, and mistakes occur. What’s important is to hone your ability to spot and rectify errors. If data analytics was straightforward, it might be easier, but it certainly wouldn’t be as interesting. Use the steps we’ve outlined as a framework, stay open-minded, and be creative. If you lose your way, you can refer back to the process to keep yourself on track.

In this post, we’ve covered the main steps of the data analytics process. These core steps can be amended, re-ordered and re-used as you deem fit, but they underpin every data analyst’s work:

  • Define the question —What business problem are you trying to solve? Frame it as a question to help you focus on finding a clear answer.
  • Collect data —Create a strategy for collecting data. Which data sources are most likely to help you solve your business problem?
  • Clean the data —Explore, scrub, tidy, de-dupe, and structure your data as needed. Do whatever you have to! But don’t rush…take your time!
  • Analyze the data —Carry out various analyses to obtain insights. Focus on the four types of data analysis: descriptive, diagnostic, predictive, and prescriptive.
  • Share your results —How best can you share your insights and recommendations? A combination of visualization tools and communication is key.
  • Embrace your mistakes —Mistakes happen. Learn from them. This is what transforms a good data analyst into a great one.

What next? From here, we strongly encourage you to explore the topic on your own. Get creative with the steps in the data analysis process, and see what tools you can find. As long as you stick to the core principles we’ve described, you can create a tailored technique that works for you.

To learn more, check out our free, 5-day data analytics short course . You might also be interested in the following:

  • These are the top 9 data analytics tools
  • 10 great places to find free datasets for your next project
  • How to build a data analytics portfolio

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8.5 Writing Process: Creating an Analytical Report

Learning outcomes.

By the end of this section, you will be able to:

  • Identify the elements of the rhetorical situation for your report.
  • Find and focus a topic to write about.
  • Gather and analyze information from appropriate sources.
  • Distinguish among different kinds of evidence.
  • Draft a thesis and create an organizational plan.
  • Compose a report that develops ideas and integrates evidence from sources.
  • Give and act on productive feedback to works in progress.

You might think that writing comes easily to experienced writers—that they draft stories and college papers all at once, sitting down at the computer and having sentences flow from their fingers like water from a faucet. In reality, most writers engage in a recursive process, pushing forward, stepping back, and repeating steps multiple times as their ideas develop and change. In broad strokes, the steps most writers go through are these:

  • Planning and Organization . You will have an easier time drafting if you devote time at the beginning to consider the rhetorical situation for your report, understand your assignment, gather ideas and information, draft a thesis statement, and create an organizational plan.
  • Drafting . When you have an idea of what you want to say and the order in which you want to say it, you’re ready to draft. As much as possible, keep going until you have a complete first draft of your report, resisting the urge to go back and rewrite. Save that for after you have completed a first draft.
  • Review . Now is the time to get feedback from others, whether from your instructor, your classmates, a tutor in the writing center, your roommate, someone in your family, or someone else you trust to read your writing critically and give you honest feedback.
  • Revising . With feedback on your draft, you are ready to revise. You may need to return to an earlier step and make large-scale revisions that involve planning, organizing, and rewriting, or you may need to work mostly on ensuring that your sentences are clear and correct.

Considering the Rhetorical Situation

Like other kinds of writing projects, a report starts with assessing the rhetorical situation —the circumstance in which a writer communicates with an audience of readers about a subject. As the writer of a report, you make choices based on the purpose of your writing, the audience who will read it, the genre of the report, and the expectations of the community and culture in which you are working. A graphic organizer like Table 8.1 can help you begin.

Summary of Assignment

Write an analytical report on a topic that interests you and that you want to know more about. The topic can be contemporary or historical, but it must be one that you can analyze and support with evidence from sources.

The following questions can help you think about a topic suitable for analysis:

  • Why or how did ________ happen?
  • What are the results or effects of ________?
  • Is ________ a problem? If so, why?
  • What are examples of ________ or reasons for ________?
  • How does ________ compare to or contrast with other issues, concerns, or things?

Consult and cite three to five reliable sources. The sources do not have to be scholarly for this assignment, but they must be credible, trustworthy, and unbiased. Possible sources include academic journals, newspapers, magazines, reputable websites, government publications or agency websites, and visual sources such as TED Talks. You may also use the results of an experiment or survey, and you may want to conduct interviews.

Consider whether visuals and media will enhance your report. Can you present data you collect visually? Would a map, photograph, chart, or other graphic provide interesting and relevant support? Would video or audio allow you to present evidence that you would otherwise need to describe in words?

Another Lens. To gain another analytic view on the topic of your report, consider different people affected by it. Say, for example, that you have decided to report on recent high school graduates and the effect of the COVID-19 pandemic on the final months of their senior year. If you are a recent high school graduate, you might naturally gravitate toward writing about yourself and your peers. But you might also consider the adults in the lives of recent high school graduates—for example, teachers, parents, or grandparents—and how they view the same period. Or you might consider the same topic from the perspective of a college admissions department looking at their incoming freshman class.

Quick Launch: Finding and Focusing a Topic

Coming up with a topic for a report can be daunting because you can report on nearly anything. The topic can easily get too broad, trapping you in the realm of generalizations. The trick is to find a topic that interests you and focus on an angle you can analyze in order to say something significant about it. You can use a graphic organizer to generate ideas, or you can use a concept map similar to the one featured in Writing Process: Thinking Critically About a “Text.”

Asking the Journalist’s Questions

One way to generate ideas about a topic is to ask the five W (and one H) questions, also called the journalist’s questions : Who? What? When? Where? Why? How? Try answering the following questions to explore a topic:

Who was or is involved in ________?

What happened/is happening with ________? What were/are the results of ________?

When did ________ happen? Is ________ happening now?

Where did ________ happen, or where is ________ happening?

Why did ________ happen, or why is ________ happening now?

How did ________ happen?

For example, imagine that you have decided to write your analytical report on the effect of the COVID-19 shutdown on high-school students by interviewing students on your college campus. Your questions and answers might look something like those in Table 8.2 :

Asking Focused Questions

Another way to find a topic is to ask focused questions about it. For example, you might ask the following questions about the effect of the 2020 pandemic shutdown on recent high school graduates:

  • How did the shutdown change students’ feelings about their senior year?
  • How did the shutdown affect their decisions about post-graduation plans, such as work or going to college?
  • How did the shutdown affect their academic performance in high school or in college?
  • How did/do they feel about continuing their education?
  • How did the shutdown affect their social relationships?

Any of these questions might be developed into a thesis for an analytical report. Table 8.3 shows more examples of broad topics and focusing questions.

Gathering Information

Because they are based on information and evidence, most analytical reports require you to do at least some research. Depending on your assignment, you may be able to find reliable information online, or you may need to do primary research by conducting an experiment, a survey, or interviews. For example, if you live among students in their late teens and early twenties, consider what they can tell you about their lives that you might be able to analyze. Returning to or graduating from high school, starting college, or returning to college in the midst of a global pandemic has provided them, for better or worse, with educational and social experiences that are shared widely by people their age and very different from the experiences older adults had at the same age.

Some report assignments will require you to do formal research, an activity that involves finding sources and evaluating them for reliability, reading them carefully, taking notes, and citing all words you quote and ideas you borrow. See Research Process: Accessing and Recording Information and Annotated Bibliography: Gathering, Evaluating, and Documenting Sources for detailed instruction on conducting research.

Whether you conduct in-depth research or not, keep track of the ideas that come to you and the information you learn. You can write or dictate notes using an app on your phone or computer, or you can jot notes in a journal if you prefer pen and paper. Then, when you are ready to begin organizing your report, you will have a record of your thoughts and information. Always track the sources of information you gather, whether from printed or digital material or from a person you interviewed, so that you can return to the sources if you need more information. And always credit the sources in your report.

Kinds of Evidence

Depending on your assignment and the topic of your report, certain kinds of evidence may be more effective than others. Other kinds of evidence may even be required. As a general rule, choose evidence that is rooted in verifiable facts and experience. In addition, select the evidence that best supports the topic and your approach to the topic, be sure the evidence meets your instructor’s requirements, and cite any evidence you use that comes from a source. The following list contains different kinds of frequently used evidence and an example of each.

Definition : An explanation of a key word, idea, or concept.

The U.S. Census Bureau refers to a “young adult” as a person between 18 and 34 years old.

Example : An illustration of an idea or concept.

The college experience in the fall of 2020 was starkly different from that of previous years. Students who lived in residence halls were assigned to small pods. On-campus dining services were limited. Classes were small and physically distanced or conducted online. Parties were banned.

Expert opinion : A statement by a professional in the field whose opinion is respected.

According to Louise Aronson, MD, geriatrician and author of Elderhood , people over the age of 65 are the happiest of any age group, reporting “less stress, depression, worry, and anger, and more enjoyment, happiness, and satisfaction” (255).

Fact : Information that can be proven correct or accurate.

According to data collected by the NCAA, the academic success of Division I college athletes between 2015 and 2019 was consistently high (Hosick).

Interview : An in-person, phone, or remote conversation that involves an interviewer posing questions to another person or people.

During our interview, I asked Betty about living without a cell phone during the pandemic. She said that before the pandemic, she hadn’t needed a cell phone in her daily activities, but she soon realized that she, and people like her, were increasingly at a disadvantage.

Quotation : The exact words of an author or a speaker.

In response to whether she thought she needed a cell phone, Betty said, “I got along just fine without a cell phone when I could go everywhere in person. The shift to needing a phone came suddenly, and I don’t have extra money in my budget to get one.”

Statistics : A numerical fact or item of data.

The Pew Research Center reported that approximately 25 percent of Hispanic Americans and 17 percent of Black Americans relied on smartphones for online access, compared with 12 percent of White people.

Survey : A structured interview in which respondents (the people who answer the survey questions) are all asked the same questions, either in person or through print or electronic means, and their answers tabulated and interpreted. Surveys discover attitudes, beliefs, or habits of the general public or segments of the population.

A survey of 3,000 mobile phone users in October 2020 showed that 54 percent of respondents used their phones for messaging, while 40 percent used their phones for calls (Steele).

  • Visuals : Graphs, figures, tables, photographs and other images, diagrams, charts, maps, videos, and audio recordings, among others.

Thesis and Organization

Drafting a thesis.

When you have a grasp of your topic, move on to the next phase: drafting a thesis. The thesis is the central idea that you will explore and support in your report; all paragraphs in your report should relate to it. In an essay-style analytical report, you will likely express this main idea in a thesis statement of one or two sentences toward the end of the introduction.

For example, if you found that the academic performance of student athletes was higher than that of non-athletes, you might write the following thesis statement:

student sample text Although a common stereotype is that college athletes barely pass their classes, an analysis of athletes’ academic performance indicates that athletes drop fewer classes, earn higher grades, and are more likely to be on track to graduate in four years when compared with their non-athlete peers. end student sample text

The thesis statement often previews the organization of your writing. For example, in his report on the U.S. response to the COVID-19 pandemic in 2020, Trevor Garcia wrote the following thesis statement, which detailed the central idea of his report:

student sample text An examination of the U.S. response shows that a reduction of experts in key positions and programs, inaction that led to equipment shortages, and inconsistent policies were three major causes of the spread of the virus and the resulting deaths. end student sample text

After you draft a thesis statement, ask these questions, and examine your thesis as you answer them. Revise your draft as needed.

  • Is it interesting? A thesis for a report should answer a question that is worth asking and piques curiosity.
  • Is it precise and specific? If you are interested in reducing pollution in a nearby lake, explain how to stop the zebra mussel infestation or reduce the frequent algae blooms.
  • Is it manageable? Try to split the difference between having too much information and not having enough.

Organizing Your Ideas

As a next step, organize the points you want to make in your report and the evidence to support them. Use an outline, a diagram, or another organizational tool, such as Table 8.4 .

Drafting an Analytical Report

With a tentative thesis, an organization plan, and evidence, you are ready to begin drafting. For this assignment, you will report information, analyze it, and draw conclusions about the cause of something, the effect of something, or the similarities and differences between two different things.


Some students write the introduction first; others save it for last. Whenever you choose to write the introduction, use it to draw readers into your report. Make the topic of your report clear, and be concise and sincere. End the introduction with your thesis statement. Depending on your topic and the type of report, you can write an effective introduction in several ways. Opening a report with an overview is a tried-and-true strategy, as shown in the following example on the U.S. response to COVID-19 by Trevor Garcia. Notice how he opens the introduction with statistics and a comparison and follows it with a question that leads to the thesis statement (underlined).

student sample text With more than 83 million cases and 1.8 million deaths at the end of 2020, COVID-19 has turned the world upside down. By the end of 2020, the United States led the world in the number of cases, at more than 20 million infections and nearly 350,000 deaths. In comparison, the second-highest number of cases was in India, which at the end of 2020 had less than half the number of COVID-19 cases despite having a population four times greater than the U.S. (“COVID-19 Coronavirus Pandemic,” 2021). How did the United States come to have the world’s worst record in this pandemic? underline An examination of the U.S. response shows that a reduction of experts in key positions and programs, inaction that led to equipment shortages, and inconsistent policies were three major causes of the spread of the virus and the resulting deaths end underline . end student sample text

For a less formal report, you might want to open with a question, quotation, or brief story. The following example opens with an anecdote that leads to the thesis statement (underlined).

student sample text Betty stood outside the salon, wondering how to get in. It was June of 2020, and the door was locked. A sign posted on the door provided a phone number for her to call to be let in, but at 81, Betty had lived her life without a cell phone. Betty’s day-to-day life had been hard during the pandemic, but she had planned for this haircut and was looking forward to it; she had a mask on and hand sanitizer in her car. Now she couldn’t get in the door, and she was discouraged. In that moment, Betty realized how much Americans’ dependence on cell phones had grown in the months since the pandemic began. underline Betty and thousands of other senior citizens who could not afford cell phones or did not have the technological skills and support they needed were being left behind in a society that was increasingly reliant on technology end underline . end student sample text

Body Paragraphs: Point, Evidence, Analysis

Use the body paragraphs of your report to present evidence that supports your thesis. A reliable pattern to keep in mind for developing the body paragraphs of a report is point , evidence , and analysis :

  • The point is the central idea of the paragraph, usually given in a topic sentence stated in your own words at or toward the beginning of the paragraph. Each topic sentence should relate to the thesis.
  • The evidence you provide develops the paragraph and supports the point made in the topic sentence. Include details, examples, quotations, paraphrases, and summaries from sources if you conducted formal research. Synthesize the evidence you include by showing in your sentences the connections between sources.
  • The analysis comes at the end of the paragraph. In your own words, draw a conclusion about the evidence you have provided and how it relates to the topic sentence.

The paragraph below illustrates the point, evidence, and analysis pattern. Drawn from a report about concussions among football players, the paragraph opens with a topic sentence about the NCAA and NFL and their responses to studies about concussions. The paragraph is developed with evidence from three sources. It concludes with a statement about helmets and players’ safety.

student sample text The NCAA and NFL have taken steps forward and backward to respond to studies about the danger of concussions among players. Responding to the deaths of athletes, documented brain damage, lawsuits, and public outcry (Buckley et al., 2017), the NCAA instituted protocols to reduce potentially dangerous hits during football games and to diagnose traumatic head injuries more quickly and effectively. Still, it has allowed players to wear more than one style of helmet during a season, raising the risk of injury because of imperfect fit. At the professional level, the NFL developed a helmet-rating system in 2011 in an effort to reduce concussions, but it continued to allow players to wear helmets with a wide range of safety ratings. The NFL’s decision created an opportunity for researchers to look at the relationship between helmet safety ratings and concussions. Cocello et al. (2016) reported that players who wore helmets with a lower safety rating had more concussions than players who wore helmets with a higher safety rating, and they concluded that safer helmets are a key factor in reducing concussions. end student sample text

Developing Paragraph Content

In the body paragraphs of your report, you will likely use examples, draw comparisons, show contrasts, or analyze causes and effects to develop your topic.

Paragraphs developed with Example are common in reports. The paragraph below, adapted from a report by student John Zwick on the mental health of soldiers deployed during wartime, draws examples from three sources.

student sample text Throughout the Vietnam War, military leaders claimed that the mental health of soldiers was stable and that men who suffered from combat fatigue, now known as PTSD, were getting the help they needed. For example, the New York Times (1966) quoted military leaders who claimed that mental fatigue among enlisted men had “virtually ceased to be a problem,” occurring at a rate far below that of World War II. Ayres (1969) reported that Brigadier General Spurgeon Neel, chief American medical officer in Vietnam, explained that soldiers experiencing combat fatigue were admitted to the psychiatric ward, sedated for up to 36 hours, and given a counseling session with a doctor who reassured them that the rest was well deserved and that they were ready to return to their units. Although experts outside the military saw profound damage to soldiers’ psyches when they returned home (Halloran, 1970), the military stayed the course, treating acute cases expediently and showing little concern for the cumulative effect of combat stress on individual soldiers. end student sample text

When you analyze causes and effects , you explain the reasons that certain things happened and/or their results. The report by Trevor Garcia on the U.S. response to the COVID-19 pandemic in 2020 is an example: his report examines the reasons the United States failed to control the coronavirus. The paragraph below, adapted from another student’s report written for an environmental policy course, explains the effect of white settlers’ views of forest management on New England.

student sample text The early colonists’ European ideas about forest management dramatically changed the New England landscape. White settlers saw the New World as virgin, unused land, even though indigenous people had been drawing on its resources for generations by using fire subtly to improve hunting, employing construction techniques that left ancient trees intact, and farming small, efficient fields that left the surrounding landscape largely unaltered. White settlers’ desire to develop wood-built and wood-burning homesteads surrounded by large farm fields led to forestry practices and techniques that resulted in the removal of old-growth trees. These practices defined the way the forests look today. end student sample text

Compare and contrast paragraphs are useful when you wish to examine similarities and differences. You can use both comparison and contrast in a single paragraph, or you can use one or the other. The paragraph below, adapted from a student report on the rise of populist politicians, compares the rhetorical styles of populist politicians Huey Long and Donald Trump.

student sample text A key similarity among populist politicians is their rejection of carefully crafted sound bites and erudite vocabulary typically associated with candidates for high office. Huey Long and Donald Trump are two examples. When he ran for president, Long captured attention through his wild gesticulations on almost every word, dramatically varying volume, and heavily accented, folksy expressions, such as “The only way to be able to feed the balance of the people is to make that man come back and bring back some of that grub that he ain’t got no business with!” In addition, Long’s down-home persona made him a credible voice to represent the common people against the country’s rich, and his buffoonish style allowed him to express his radical ideas without sounding anti-communist alarm bells. Similarly, Donald Trump chose to speak informally in his campaign appearances, but the persona he projected was that of a fast-talking, domineering salesman. His frequent use of personal anecdotes, rhetorical questions, brief asides, jokes, personal attacks, and false claims made his speeches disjointed, but they gave the feeling of a running conversation between him and his audience. For example, in a 2015 speech, Trump said, “They just built a hotel in Syria. Can you believe this? They built a hotel. When I have to build a hotel, I pay interest. They don’t have to pay interest, because they took the oil that, when we left Iraq, I said we should’ve taken” (“Our Country Needs” 2020). While very different in substance, Long and Trump adopted similar styles that positioned them as the antithesis of typical politicians and their worldviews. end student sample text

The conclusion should draw the threads of your report together and make its significance clear to readers. You may wish to review the introduction, restate the thesis, recommend a course of action, point to the future, or use some combination of these. Whichever way you approach it, the conclusion should not head in a new direction. The following example is the conclusion from a student’s report on the effect of a book about environmental movements in the United States.

student sample text Since its publication in 1949, environmental activists of various movements have found wisdom and inspiration in Aldo Leopold’s A Sand County Almanac . These audiences included Leopold’s conservationist contemporaries, environmentalists of the 1960s and 1970s, and the environmental justice activists who rose in the 1980s and continue to make their voices heard today. These audiences have read the work differently: conservationists looked to the author as a leader, environmentalists applied his wisdom to their movement, and environmental justice advocates have pointed out the flaws in Leopold’s thinking. Even so, like those before them, environmental justice activists recognize the book’s value as a testament to taking the long view and eliminating biases that may cloud an objective assessment of humanity’s interdependent relationship with the environment. end student sample text

Citing Sources

You must cite the sources of information and data included in your report. Citations must appear in both the text and a bibliography at the end of the report.

The sample paragraphs in the previous section include examples of in-text citation using APA documentation style. Trevor Garcia’s report on the U.S. response to COVID-19 in 2020 also uses APA documentation style for citations in the text of the report and the list of references at the end. Your instructor may require another documentation style, such as MLA or Chicago.

Peer Review: Getting Feedback from Readers

You will likely engage in peer review with other students in your class by sharing drafts and providing feedback to help spot strengths and weaknesses in your reports. For peer review within a class, your instructor may provide assignment-specific questions or a form for you to complete as you work together.

If you have a writing center on your campus, it is well worth your time to make an online or in-person appointment with a tutor. You’ll receive valuable feedback and improve your ability to review not only your report but your overall writing.

Another way to receive feedback on your report is to ask a friend or family member to read your draft. Provide a list of questions or a form such as the one in Table 8.5 for them to complete as they read.

Revising: Using Reviewers’ Responses to Revise your Work

When you receive comments from readers, including your instructor, read each comment carefully to understand what is being asked. Try not to get defensive, even though this response is completely natural. Remember that readers are like coaches who want you to succeed. They are looking at your writing from outside your own head, and they can identify strengths and weaknesses that you may not have noticed. Keep track of the strengths and weaknesses your readers point out. Pay special attention to those that more than one reader identifies, and use this information to improve your report and later assignments.

As you analyze each response, be open to suggestions for improvement, and be willing to make significant revisions to improve your writing. Perhaps you need to revise your thesis statement to better reflect the content of your draft. Maybe you need to return to your sources to better understand a point you’re trying to make in order to develop a paragraph more fully. Perhaps you need to rethink the organization, move paragraphs around, and add transition sentences.

Below is an early draft of part of Trevor Garcia’s report with comments from a peer reviewer:

student sample text To truly understand what happened, it’s important first to look back to the years leading up to the pandemic. Epidemiologists and public health officials had long known that a global pandemic was possible. In 2016, the U.S. National Security Council (NSC) published a 69-page document with the intimidating title Playbook for Early Response to High-Consequence Emerging Infectious Disease Threats and Biological Incidents . The document’s two sections address responses to “emerging disease threats that start or are circulating in another country but not yet confirmed within U.S. territorial borders” and to “emerging disease threats within our nation’s borders.” On 13 January 2017, the joint Obama-Trump transition teams performed a pandemic preparedness exercise; however, the playbook was never adopted by the incoming administration. end student sample text

annotated text Peer Review Comment: Do the words in quotation marks need to be a direct quotation? It seems like a paraphrase would work here. end annotated text

annotated text Peer Review Comment: I’m getting lost in the details about the playbook. What’s the Obama-Trump transition team? end annotated text

student sample text In February 2018, the administration began to cut funding for the Prevention and Public Health Fund at the Centers for Disease Control and Prevention; cuts to other health agencies continued throughout 2018, with funds diverted to unrelated projects such as housing for detained immigrant children. end student sample text

annotated text Peer Review Comment: This paragraph has only one sentence, and it’s more like an example. It needs a topic sentence and more development. end annotated text

student sample text Three months later, Luciana Borio, director of medical and biodefense preparedness at the NSC, spoke at a symposium marking the centennial of the 1918 influenza pandemic. “The threat of pandemic flu is the number one health security concern,” she said. “Are we ready to respond? I fear the answer is no.” end student sample text

annotated text Peer Review Comment: This paragraph is very short and a lot like the previous paragraph in that it’s a single example. It needs a topic sentence. Maybe you can combine them? end annotated text

annotated text Peer Review Comment: Be sure to cite the quotation. end annotated text

Reading these comments and those of others, Trevor decided to combine the three short paragraphs into one paragraph focusing on the fact that the United States knew a pandemic was possible but was unprepared for it. He developed the paragraph, using the short paragraphs as evidence and connecting the sentences and evidence with transitional words and phrases. Finally, he added in-text citations in APA documentation style to credit his sources. The revised paragraph is below:

student sample text Epidemiologists and public health officials in the United States had long known that a global pandemic was possible. In 2016, the National Security Council (NSC) published Playbook for Early Response to High-Consequence Emerging Infectious Disease Threats and Biological Incidents , a 69-page document on responding to diseases spreading within and outside of the United States. On January 13, 2017, the joint transition teams of outgoing president Barack Obama and then president-elect Donald Trump performed a pandemic preparedness exercise based on the playbook; however, it was never adopted by the incoming administration (Goodman & Schulkin, 2020). A year later, in February 2018, the Trump administration began to cut funding for the Prevention and Public Health Fund at the Centers for Disease Control and Prevention, leaving key positions unfilled. Other individuals who were fired or resigned in 2018 were the homeland security adviser, whose portfolio included global pandemics; the director for medical and biodefense preparedness; and the top official in charge of a pandemic response. None of them were replaced, leaving the White House with no senior person who had experience in public health (Goodman & Schulkin, 2020). Experts voiced concerns, among them Luciana Borio, director of medical and biodefense preparedness at the NSC, who spoke at a symposium marking the centennial of the 1918 influenza pandemic in May 2018: “The threat of pandemic flu is the number one health security concern,” she said. “Are we ready to respond? I fear the answer is no” (Sun, 2018, final para.). end student sample text

A final word on working with reviewers’ comments: as you consider your readers’ suggestions, remember, too, that you remain the author. You are free to disregard suggestions that you think will not improve your writing. If you choose to disregard comments from your instructor, consider submitting a note explaining your reasons with the final draft of your report.

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How to Write a Business Analysis Report [Examples and Templates]

how to write an analysis report of data

Table of contents

Business analysis reports are a lot like preparing a delicious meal.

Sometimes, the recipe is simple enough that you only need to use the basic ingredients. Other times, you will have to follow specific instructions to ensure those tasty delicacies turn out just right.

Want to make sure your business report never turns out like a chewy piece of meat? You’ve come to the right place.

Stay tuned until the end of this blog post, and we promise you won’t be hungry… for business knowledge!

What Is a Business Analysis Report?

Why is analytical reporting important, what should be included in a business analysis report, how do you write a business analysis report, business data analysis report examples and templates.

  • Improve Business Reporting with Databox


A business analysis report provides information about the current situation of your company. This report is usually created by the management to help in the decision-making process and is usually used by other departments within a company.

Business analysis reports can either focus your research on the effectiveness of an existing business process or a proposed new process. Besides, an effective business analysis report should also assess the results to determine if the process changes had a positive or negative effect on the company’s goals. In fact, according to Databox’s State of business reporting , an overwhelming majority of companies said that reporting improved their performance.

Analytical reports are the bridge that connects your company to an effective, data-driven business intelligence strategy . By leveraging analytical reports , you can make informed decisions about your organization’s most critical issues. You will no longer need to rely on gut instinct or anecdotal evidence when assessing risks, threats, and opportunities. Instead, you will have access to a wealth of reliable data to inform your decisions.

Here are some essential benefits of analytical reporting:

  • Improve communication and foster collaboration – The most obvious benefit of business analysis report writing is an improvement in communication between all stakeholders involved in the project. Also, analytical business reports can help you to generate more trust and foster better collaboration among your employees and colleagues. By using data analytics reporting tools , you will be able to monitor your employees’ performance on a day-to-day basis. This will allow you to hold them accountable for their actions and give them greater freedom within the business as they know that their superiors have faith in their decision-making capabilities.
  • Increase productivity – Without this level of shared insight, businesses struggle to stay on top of their most important tasks and can become less efficient. An effective analytical business report provides the information needed for more efficient internal processes and helps you find more time for strategic activities such as improving your business strategy or working on long-term goals .
  • Innovation – In today’s digital age, the pressure to innovate was never greater. When consumers basically have everything they want at their fingertips, stepping up to the plate with a new and improved product or service has never been more important. With an accessible dashboard in place, you will be able to create data-driven narratives for each of your business’ critical functions. For example, if you are a software company, you can use the insights gained from report analysis done with your dashboard software to tailor your product development efforts to the actual needs of your customers. By doing so, you will be able to develop products that are better tailored to specific customer groups. You can also use the same information for developing new marketing strategies and campaigns.
  • Continuous business evolution – When it comes to digital businesses, data is everything. No model lasts forever, so having access to a business dashboard software that allows you to constantly keep tabs on your business’ performance will help you refine it as time goes on. If there are any glitches in your business model, or if something isn’t panning out as expected, the insight offered by a business analysis report can help you improve upon what works while scrapping what doesn’t.

A business analysis report has several components that need to be included to give a thorough description of the topic at hand. The structure and length of business analysis reports can vary depending on the needs of the project or task.

They can be broken down into different sections that include an:

  • Executive summary
  • Study introduction
  • Methodology
  • Review of statistics

Reports of this nature may also include case studies or examples in their discussion section.

A report can be written in a formal or informal tone, depending on the audience and purpose of the document. While a formal tone is best for executives , an informal tone is more appropriate for technical audiences . It is also a good idea to use something like an executive summary template to report on the results repeatedly with ease.

A good business analysis report is detailed and provides recommendations in the form of actionable steps. Here we have listed some simple steps that you need to follow to write a good business analysis report. Report writing is a major part of the business analysis process. In this section, you will learn how to write a report for your company:



Obtain an overview of what you want to analyze in the business report . For example, if you are writing a business analysis report on how to improve customer service at an insurance company, you will want to look through all the customer service processes to determine where the problems lie. The more prepared you are when starting a project, the easier it will be to get results. Here is what your preparation should look like:

Set your goals

The first step in writing this document is to set your goals . What do you hope to accomplish with this paper? Do you need to assess the company’s finances? Are you looking for ways to make improvements? Or do you have outside investors who want to know if they should buy into the company? Once you know what your goal is, then you can begin setting up your project.

PRO TIP: How Well Are Your Marketing KPIs Performing?

Like most marketers and marketing managers, you want to know how well your efforts are translating into results each month. How much traffic and new contact conversions do you get? How many new contacts do you get from organic sessions? How are your email campaigns performing? How well are your landing pages converting? You might have to scramble to put all of this together in a single report, but now you can have it all at your fingertips in a single Databox dashboard.

Our Marketing Overview Dashboard includes data from Google Analytics 4 and HubSpot Marketing with key performance metrics like:

  • Sessions . The number of sessions can tell you how many times people are returning to your website. Obviously, the higher the better.
  • New Contacts from Sessions . How well is your campaign driving new contacts and customers?
  • Marketing Performance KPIs . Tracking the number of MQLs, SQLs, New Contacts and similar will help you identify how your marketing efforts contribute to sales.
  • Email Performance . Measure the success of your email campaigns from HubSpot. Keep an eye on your most important email marketing metrics such as number of sent emails, number of opened emails, open rate, email click-through rate, and more.
  • Blog Posts and Landing Pages . How many people have viewed your blog recently? How well are your landing pages performing?

Now you can benefit from the experience of our Google Analytics and HubSpot Marketing experts, who have put together a plug-and-play Databox template that contains all the essential metrics for monitoring your leads. It’s simple to implement and start using as a standalone dashboard or in marketing reports, and best of all, it’s free!


You can easily set it up in just a few clicks – no coding required.

To set up the dashboard, follow these 3 simple steps:

Step 1: Get the template 

Step 2: Connect your HubSpot and Google Analytics 4 accounts with Databox. 

Step 3: Watch your dashboard populate in seconds.

Assess the Company’s Mission

It’s almost impossible to write a business analysis report without access to the company’s mission statement. Even if you don’t plan on using the mission statement as part of your business analysis summary, it can help you understand the company’s culture and goals. Mission statements are typically short and easy to read, but they may not include every area of focus that you want to include in your report.

Thus, it is important to use other sources when possible. For example, if you are writing a business analysis report for a small start-up company that is just beginning to market its product or service, review the company website or talk directly with management to learn what they believe will be most crucial in growing the company from the ground up.

Stakeholder Analysis

Who is your audience? Create the reader’s persona and tailor all information to their perspective. Create a stakeholder map that identifies all the groups, departments, functions, and individuals involved in this project (and any other projects related to this one). Your stakeholder map should include a description of each group’s role.

Review Financial Performance

Review the financing of the business and determine whether there are any potential threats to the company’s ability to meet its future financial obligations. This includes reviewing debt payments and ownership equity compared with other types of financing such as accounts receivable, cash reserves, and working capital. Determine whether there have been any changes in the funding over time, such as an increase in long-term debt or a decrease in owners’ equity.

Apart from reviewing your debt payments and ownership equity with other types of financing, wouldn’t it be great if you could compare your financial performance to companies that are exactly like yours? With Databox, this can be done in less than 3 minutes.

For example, by  joining this benchmark group , you can better understand your gross profit margin performance and see how metrics like income, gross profit, net income, net operating increase, etc compare against businesses like yours.

One piece of data that you would be able to discover is the average gross profit a month for B2B, B2C, SaaS and eCommerce. Knowing that you perform better than the median may help you evaluate your current business strategy and identify the neccessary steps towards improving it.

Instantly and Anonymously Benchmark Your Company’s Performance Against Others Just Like You

If you ever asked yourself:

  • How does our marketing stack up against our competitors?
  • Are our salespeople as productive as reps from similar companies?
  • Are our profit margins as high as our peers?

Databox Benchmark Groups can finally help you answer these questions and discover how your company measures up against similar companies based on your KPIs.

When you join Benchmark Groups, you will:

  • Get instant, up-to-date data on how your company stacks up against similar companies based on the metrics most important to you. Explore benchmarks for dozens of metrics, built on anonymized data from thousands of companies and get a full 360° view of your company’s KPIs across sales, marketing, finance, and more.
  • Understand where your business excels and where you may be falling behind so you can shift to what will make the biggest impact. Leverage industry insights to set more effective, competitive business strategies. Explore where exactly you have room for growth within your business based on objective market data.
  • Keep your clients happy by using data to back up your expertise. Show your clients where you’re helping them overperform against similar companies. Use the data to show prospects where they really are… and the potential of where they could be.
  • Get a valuable asset for improving yearly and quarterly planning . Get valuable insights into areas that need more work. Gain more context for strategic planning.

The best part?

  • Benchmark Groups are free to access.
  • The data is 100% anonymized. No other company will be able to see your performance, and you won’t be able to see the performance of individual companies either.

When it comes to showing you how your performance compares to others, here is what it might look like for the metric Average Session Duration:

how to write an analysis report of data

And here is an example of an open group you could join:

how to write an analysis report of data

And this is just a fraction of what you’ll get. With Databox Benchmarks, you will need only one spot to see how all of your teams stack up — marketing, sales, customer service, product development, finance, and more. 

  • Choose criteria so that the Benchmark is calculated using only companies like yours
  • Narrow the benchmark sample using criteria that describe your company
  • Display benchmarks right on your Databox dashboards

Sounds like something you want to try out? Join a Databox Benchmark Group today!

Examine the “Four P’s”

“Four P’s” — product , price , place, and promotion . Here’s how they work:

  • Product — What is the product? How does it compare with those of competitors? Is it in a position to gain market share?
  • Price — What is the price of the product? Is it what customers perceive as a good value?
  • Place — Where will the product be sold? Will existing distribution channels suffice or should new channels be considered?
  • Promotion — Are there marketing communications efforts already in place or needed to support the product launch or existing products?

Evaluate the Company Structure

A business analysis report examines the structure of a company, including its management, staff, departments, divisions, and supply chain. It also evaluates how well-managed the company is and how efficient its supply chain is. In order to develop a strong strategy, you need to be able to analyze your business structure.

When writing a business analysis report, it’s important to make sure you structure your work properly. You want to impress your readers with a clear and logical layout, so they will be able to see the strengths of your recommendations for improving certain areas of the business. A badly written report can completely ruin an impression, so follow these steps to ensure you get it right the first time.

A typical business analysis report is formatted as a cover page , an executive summary , information sections, and a summary .

  • A cover page contains the title and author of the report, the date, a contact person, and reference numbers.
  • The information section is backed up by data from the work you’ve done to support your findings, including charts and tables. Also, includes all the information that will help you make decisions about your project. Experience has shown that the use of reputable study materials, such as  StuDocu  and others, might serve you as a great assistant in your findings and project tasks.
  • A summary is a short overview of the main points that you’ve made in the report. It should be written so someone who hasn’t read your entire document can understand exactly what you’re saying. Use it to highlight your main recommendations for how to change your project or organization in order to achieve its goals.
  • The last section of a business analysis report is a short list of references that include any websites or documents that you used in your research. Be sure to note if you created or modified any of these documents — it’s important to give credit where credit is due.

The Process of Investigation

Explain the problem – Clearly identify the issue and determine who is affected by it. You should include a detailed description of the problem you are analyzing, as well as an in-depth analysis of its components and effects. If you’re analyzing a small issue on a local scale, make sure that your report reflects this scale. That way, if someone else reads your work who had no idea about its context or scope, they would still be able to understand it.

Explain research methods – There are two ways to do this. Firstly, you can list the methods you’ve used in the report to determine your actions’ success and failure. Secondly, you should add one or two new methods to try instead. Always tell readers how you came up with your answer or what data you used for your report. If you simply tell them that the company needs to improve customer service training then they won’t know what kind of data led you to that conclusion. Also, if there were several ways of addressing a problem, discuss each one and why it might not work or why it may not be appropriate for the company at this time.

Analyze data – Analyzing data is an integral part of any business decision, whether it’s related to the costs of manufacturing a product or predicting consumer behavior. Business analysis reports typically focus on one aspect of an organization and break down that aspect into several parts — all of which must be analyzed in order to come to a conclusion about the original topic.

The Outcome of Each Investigation Stage

The recommendations and actions will usually follow from the business objectives not being met. For example, if one of your goals was to decrease costs then your recommendations would include optimization strategies for cost reduction . If you have more than one suggestion you should make a list of the pros and cons of each one. You can make several recommendations in one report if they are related. In addition, make sure that every recommendation has supporting arguments to back them up.

Report Summary

Every business analysis report should start with a summary. It’s the first thing people see and it needs to capture their attention and interest. The report summary can be created in two ways, depending on the nature of the report:

  • If the report is a brief one, that simply gives a summary of the findings, then it can be created as part of the executive summary.
  • But if it’s a long report, it could be too wordy to summarise. In this case, you can create a more detailed overview that covers all the main aspects of the project from both an internal and external point of view.

Everything comes down to this section. A presentation is designed to inform, persuade and influence decision-makers to take the next action steps.

Sometimes a slide or two can make them change their mind or open new horizons. These days, digital dashboards are becoming increasingly popular when it comes to presenting data in business reports. Dashboards combine different visualizations into one place, allowing users to get an overview of the information they need at a glance rather than searching through a bunch of documents or spreadsheets trying.

Databox offers dynamic and accessible digital dashboards that will help you to convert raw data into a meaningful story. And the best part is that you can do it with a ‘blink of an eye’ even if you don’t have any coding or designs skills. There is also an option of individual report customization so that you can tailor any dashboard to your own needs.

Pre-made dashboard templates can be extremely useful when creating your own business analysis report. While examples serve as inspiration, templates allow you to create reports quickly and easily without having to spend time (and money) developing the underlying data models.

Databox dashboard templates come with some of the most common pre-built metrics and KPIs different types of businesses track across different departments. In order to create powerful business insights within minutes, all you need to do is download any of our free templates and connect your data source — the metrics will populate automatically.

Business Report Examples and Templates

Databox business dashboard examples are simple and powerful tools for tracking your business KPIs and performance. These dashboards can be used by executive teams and managers as well as by senior management, marketing, sales, customer support, IT, accounting, and other departments. If you are new to this kind of reporting, you may not know how to set up a dashboard or what metrics should be displayed on it. This is where a premade template for business dashboards comes in handy.

For example, this Google Ads Report Template is designed to give you a simple way to keep track of your campaigns’ performance over time, and it’s a great resource for anyone who uses Google’s advertising platform, regardless of whether they’re an SMB, an SME or an enterprise.

Google ads dashboard

KPI Report Examples and Templates

KPIs are the foundation of any business analysis, and they can come in a multitude of forms. While we’ve defined KPIs as metrics or measurements that allow you to assess the effectiveness of a given process, department, or team, there are a number of ways to evaluate your KPIs. Through the use of color-coding, user-friendly graphs and charts, and an intuitive layout, your KPIs should be easy for anyone to understand. A good way to do this is by having a dedicated business analyst on your team who can take on the task of gathering data, analyzing it, and presenting it in a way that will drive actionable insights. However, if you don’t have a dedicated analyst or don’t want to spend money on one, you can still create KPI reporting dashboards using free KPI Databox templates and examples .

For example, this Sales Overview template is a great resource for managers who want to get an overview of their sales team’s performance and KPIs. It’s perfect for getting started with business analysis, as it is relatively easy to understand and put together.

sales overview dashboard

Performance Report Examples and Templates

All businesses, regardless of size or industry, need to know how well they are performing in order to make the best decisions for their company and improve overall ROI. A performance dashboard is a strategic tool used to track key metrics across different departments and provide insight into the health of a business. Databox has a collection of 50+ Performance Dashboard Examples and Templates which are available for free download.

For example, if your business is investing a lot into customer support, we recommend tracking your customer service performance with this Helpscout Mailbox Dashboard which will give you insights into conversations, your team’s productivity, customer happiness score, and more.

Helpscout dashboard example

Executive Report Examples and Templates

An executive dashboard is a visual representation of the current state of a business. The main purpose of an executive dashboard is to enable business leaders to quickly identify opportunities, identify areas for improvement, pinpoint issues, and make data-informed decisions for driving sales growth, new product launches, and overall business growth. When an executive dashboard is fully developed, as one of these 50+ Databox Free Executive Examples and Templates , it offers a single view of the most important metrics for a business at a glance.

For example, you probably have more than one set of financial data tracked using an executive dashboard software : invoices, revenue reports (for accounting), income statements, to mention a few. If you want to view all this data in one convenient place, or even create a custom report that gives you a better picture of your business’s financial health, this Stripe Dashboard Template is a perfect solution for you.

Stripe dashboard

Metrics Report Examples and Templates

Choosing the right metrics for your business dashboard can be crucial to helping you meet your business objectives, evaluate your performance, and get insights into how your business is operating. Metrics dashboards are used by senior management to measure the performance of their company on a day-to-day basis. They are also used by mid-level managers to determine how their teams are performing against individual goals and objectives. Databox provides 50+ Free Metrics Dashboard Examples and Templates that you can use to create your company’s own dashboards. Each is unique and will depend on your business needs.

For example, if you are looking for ways to track the performance of your DevOps team, and get the latest updates on projects quickly – from commits, and repository status, to top contributors to your software development projects, this GitHub Overview Dashboard is for you.

GitHub overview dashboard

Small Business Report Examples and Templates

A lot of small business owners don’t realize how important it is to have a proper dashboard in place until they actually use one. A dashboard can help you track and compare different metrics, benchmark your performance against industry averages, evaluate the effectiveness of your marketing and sales strategies, track financials, and much more. So if you’re looking for a tool to help you measure and manage your small business’ performance, try some of these 50+ Free Small Business Dashboard Examples and Templates .

For example, this Quickbooks Dashboard template can help you get a clear understanding of your business’s financial performance, ultimately allowing you to make better-informed decisions that will drive growth and profitability.

Quickbooks dashboard

Agency Report Examples and Templates

Agency dashboards are not a new concept. They have been around for years and are used by companies all over the world. Agency dashboards can be powerful tools for improving your marketing performance, increasing client loyalty, and landing new clients. There is no single correct way to create an agency dashboard. Everyone has their own goals and objectives, which will ultimately determine which data points you choose to include or track using a client dashboard software , but with these Databox 100+ Free Agency Dashboard Examples and Templates you have plenty of options to start with.

For example, you can use this Harvest Clients Time Report to easily see how much time your employees spend working on projects for a particular client, including billable hours and billable amount split by projects.

Harvest Clients Time Report dashboard

Better Business Reporting with Databox

Business analysis is all about finding smart ways to evaluate your organization’s performance and future potential. And that’s where Databox comes in.

Databox can be a helpful tool for business leaders who are required to analyze data, hold frequent meetings, and generate change in their organizations. From improving the quality and accessibility of your reporting to tracking critical performance metrics in one place, and sharing performance metrics with your peers and team members in a cohesive, presentable way, allow Databox to be your personal assistant in these processes, minimize the burdens of reporting and ensure you always stay on top of your metrics game.

Sign up today for free to start streamlining your business reporting process.

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How to write analytic reports that showcase growth: Expert tips + a free template

How to write analytic reports that showcase growth: Expert tips + a free template

If you’re running a small business, you don’t have hours to devote to analytical reporting. The good news is that gathering insights and creating reports with the right tools and templates is a walk in the park. 

In this article, we’ll break down everything you need to know about crafting the perfect analytical report, showing you how to craft reports that present data accurately and captivate your audience. Whether it's clients, stakeholders, or your internal team, we'll help you write a compelling report — in no time. 

What is an analytical report?

An analytical report is a written document that businesses use to strategize and make decisions. It examines a specific issue, scenario, or data set, and through analysis, it identifies trends, patterns, and relationships. 

In a business context, this report is your roadmap for navigating the ever-evolving landscape of your market. This type of report can cover anything from financial performance and customer behavior to market trends and operational efficiency. 

By methodically breaking down data, an analytical report empowers you to make informed decisions backed by concrete evidence rather than just intuition.

How to write an analytical report in 5 steps

By breaking it down into manageable steps, you can transform a complex process into a structured and straightforward one. 

Whether you're analyzing sales data, customer feedback, or financial trends, the approach stays the same — and if you still need a hand getting started, you can download our free analytic report template. 

Let’s jump in! 

1. Define your objective and gather relevant data

The first step is clearly defining your objectives and gathering the data you need to back it up. 

What specific questions are you aiming to answer? Are you looking to understand customer behavior, evaluate financial performance, or identify operational inefficiencies? Having a clear objective will guide you in gathering the correct data.

Tools that offer features that collect and automate financial data, like integrated accounting software , can be a game-changer during this step. Doing everything manually opens the doors to pesky errors and inefficiencies — plus, when all your data is automated, you get real-time insights that make reporting quick and easy. 

2. Analyze the data to identify patterns and trends

Once you have your data in hand, the next step is to dive into analysis. In this stage, you sift through the data to identify patterns, trends, and anomalies. Whether it's scanning over a financial statement or evaluating operational efficiencies, your analysis will form the basis of your report's conclusions. 

To kickstart your analysis effectively, consider these tips:

Identify key variables: Start by pinpointing the critical variables in your data most relevant to your objectives.

Look for trends: Examine your data over time to identify any trends. Are there patterns or shifts in customer behavior, sales, or expenses?

Compare and contrast: To spot any significant deviations, compare your data against different benchmarks, such as industry standards or previous periods.

Use data visualization: Employ graphs and charts to represent your data visually. This can help in spotting trends and outliers more easily.

Segment your data: Break down your data into segments (e.g., by region, product line, or customer demographics) to uncover more specific insights.

Remember, the depth of your analysis will determine the effectiveness of your recommendations. Take the time to thoroughly examine the data from multiple angles, and don't hesitate to use available digital resources to your advantage. 

3. Structure your report for clarity and impact

Now that you’ve analyzed your data and gathered your insights, the next step is to structure your report. A well-structured report presents information logically and makes it easy for your audience to follow and understand your findings. 

Start with an introduction outlining your objectives and methodology, then a section presenting your data analysis, and conclude with your findings and recommendations. When structuring your report, consider these tips to enhance clarity and impact:

Highlight critical data early: Present the most significant data or insights. This captures your attention and sets the tone for the rest of your report.

Use clear headings and subheadings: Organize your content with clear, descriptive headings and subheadings. This helps readers navigate through the report easily.

Prioritize data presentation: Focus on the data that directly supports your objectives. Avoid cluttering your report with irrelevant information.

Incorporate visuals: Utilize charts, graphs, and infographics to present complex data visually. This makes it easier to digest and prevents overwhelming the reader.

Use bullet points for clarity: Bullet points can make complex information more manageable and reader-friendly.

Balance text with white space: Avoid dense blocks of text. Use white space effectively to give your report a clean, uncluttered look.

Use a logical flow: Ensure your report flows logically from one section to the next. Each part should build upon the previous one, leading smoothly to your conclusions.

The structure of your report should guide the reader through your thought process, leading them to your conclusions coherently and persuasively. Remember, the easier it is to understand your report, the more impactful your insights will be.

4. Draft and refine your content

With your report's structure in place, the next step is to draft your content! This involves transforming your data and analysis into a compelling narrative. 

Your draft should clearly articulate the insights and conclusions drawn from your data, ensuring they are directly tied to your objectives. For instance, if your report is about customer spending habits, you might highlight an insight like, "Our analysis shows a 20% increase in spending on eco-friendly products this year." Link this directly to a conclusion, such as, "This trend suggests a growing market interest in sustainability, recommending a focus on eco-friendly product lines." 

Remember, a well-crafted report communicates the findings and a story that resonates with the audience. Use clear, concise, and jargon-free language to make your report accessible to all readers, regardless of their expertise in the subject matter. It's about making complex data understandable and engaging. As you refine your content, keep your audience in mind and tailor your narrative to meet their needs and expectations.

5. Present your findings and make recommendations

The final step is to present your findings and recommendations. This step is what it has all been about! 

Your presentation should focus on the key insights and recommendations from your analysis. Use visual aids like graphs, charts, and infographics to make complex data more digestible and engaging.

Ending your report with solid and actionable recommendations based on your analysis is essential. These should be practical and aligned with your report's objectives. The goal is to provide value by offering solutions or strategies to help drive growth and efficiency in your or your client's business. Remember, an excellent analytical report doesn't just inform; it inspires action.

Why is analytical reporting so important?

Analytical reporting is important because it provides the necessary tools to make informed decisions. By highlighting trends and patterns in data, these reports allow businesses to understand their performance and plan strategically. 

Analytical reports also make it easier to communicate complex information to stakeholders in a simple, understandable way. This guarantees that everyone, from team members to investors, can make sense of the data and the decisions based on it. 

In short, analytical reporting connects the dots between data and action, helping businesses grow and succeed.

What are the benefits of analytical reporting?

Analytical reporting offers several key benefits that can transform how your business operates and makes decisions. From better money management to streamlined bookkeeping , these reports make every aspect of running a business more efficient and effective. 

Here’s a look at some of the significant advantages:

Improved decision-making: With precise data analysis, businesses can make more informed decisions, reducing guesswork and increasing effectiveness.

A deeper understanding of performance: These reports provide deep insights into every aspect of business performance, from sales and marketing to finance and operations.

Identification of trends and patterns: Analytical reports help spot trends and patterns that might go unnoticed, aiding in strategic planning.

Increased efficiency: Businesses can allocate resources more effectively by identifying areas of strength and weakness.

Better communication: A well-structured analytical report communicates complex data, making it easier for stakeholders to understand critical insights.

Strategic planning: Conclusions drawn from these reports make a huge difference in shaping short-term and long-term strategies.

Risk management: Analytical reports can highlight potential risks and challenges, allowing businesses to address them before they become significant problems.

Facilitating growth: By providing insights into market trends, customer preferences, and operational efficiencies, analytical reports can be a driving force behind business growth, helping companies identify and capitalize on new opportunities.

Tips to simplify analytical reporting

Analytical reporting can be streamlined with a few innovative strategies. Here are some tips to make the process more efficient and less overwhelming:

Utilize digital tools: Use tools like Expensify to automate data collection and organization, reducing manual effort and potential errors.

Collaborate and get feedback: Work with team members or stakeholders to review and provide feedback on your report. Different perspectives can offer new insights and improve the overall quality.

Focus on storytelling: Elevate your report by weaving data into a compelling narrative. Show how the data tells a story about your business, market trends, or customer behaviors.

Conduct situational analysis: Compare your findings with industry benchmarks or competitors through a situational analysis . This context adds depth to your analysis and can uncover unique insights.

Emphasize actionable insights: Ensure each section of your report provides actionable insights. Clearly state how these insights can be implemented in business strategies.

Optimize for different mediums: Consider how your report will be consumed (e.g., presentation, PDF, online). Tailor the format and design to suit the medium for maximum impact.

Leverage templates: Use pre-designed templates, like ours included above, to save time and ensure a consistent format.

Analytical reporting has always been challenging — but Expensify makes it easier

When creating an analysis report, we recommend choosing the path of least resistance. With automated reporting tools, Expensify can help streamline the entire process, making it more efficient and accessible for businesses of any size to analyze data and communicate their findings. 

So, are you ready to make analytical reporting a walk in the park? Get started with Expensify today. 

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Data and Technology Insights

How to Write a Data Analysis Report

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how to write an analysis report of data

Lets face it, data analysis reports, whether youre writing them for universities or for big data , are intimidating. Theyre also not a great deal of fun to write. I asked some people where theyd rank writing one and it came in just above going to the dentist. Thats not a good place to find yourself (and here Im talking both about the list and the chair).

You know what the crazy thing is? Theyre actually not that hard to write! Like so many things in life you just need to know where to start. For that reason, I thought Id write you up a quick article so that the next time you at least know how to get it over with as quickly as possible. And then, maybe youll start to enjoy it more and it will become only as unpleasant as being woken by your neighbor drilling holes in the wall. We can only hope, right?

There is no one right way

The first thing youve got to realize is that there is not yet one way to present your data. Admittedly, thats unfortunate. It would probably be helpful for everybody if there was some standard way to do these things. Thats not the case, however. Nor will it happen soon, as different companies , sectors and data presenters want to do entirely different things.

What that means is that there is no official wrong way. These are of course the unofficial one, which is where you hand over your 10,000-word report, people stare at it for a while, point to the first sentence and ask what does that mean?

Follow by example

The best thing to do is to find data analyses reports that you yourself find clear and easy to understand and to not just read them, but keep them on file . Then, when youre writing up a report, pull out one that is close to what youre trying to do and follow their example as closely as possible. This works surprisingly well, particularly if youre not that confident what youre doing is the right way to do things.

Whats more, if you do this a number of times without doing anything else, youll still start noticing underlying patterns and ideas that you can use .

Dont be afraid to ask

There are tons of very smart people online at such places as Quora and Linkedin Groups who are willing to answer even the most complicated questions , provided youve demonstrated youve at least tried to understand the concepts.

So no asking how do I write a data report? as then people will call you lazy. If on the other hand, you want to know if you should use a regression or a Linear Model for a specific analysis, then theyll gladly answer that for you.

Pay attention to the right criticism

Note that quite often youre going to get criticized. Thats just the name of the game. There are always people out there with opinions and the desire to share them. Make sure you pay attention to the right ones.

If the person delivering the criticism has no understanding of data or how to present it (and lets face it, there are a lot of those) then you can generally simply say thank you for them being so kind as to give their opinions and move on. Of course, if the person that is doing the criticizing is paying for the report, thats a different story. Unfortunately, then youre going to have to accommodate their criticism.

Know your content

When youre going to write a data report, make sure that you know the content . With that, I mean that youve actually been the one to do the analysis. It should always be the person who has done the analyses that write the content. Only in that way can you be sure that the data presentation isnt distorted.

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Start out by describing the data. Who was the population you analyzed? How did you collect the data? What were the conditions, if any, for you excluding samples from your data set? Did excluding them make a substantial difference to your results?

At the same time, you dont want to go into too much detail here. Include whats relevant (how results changed as a result of different treatments) and ruthlessly cut down on whats not (what program you used).

Know what matters

A data report, just like any other report, has a message. It is trying to convey an idea. Of course, this is often more difficult when youre writing a data-driven report as data rarely cares about what you want to say and can therefore not fit your story exactly.

Nonetheless, you should focus on telling your stories (while not deleting the data-driven caveats). The natural structure of abstract, introduction, method, results, conclusion, thats generally used for these kinds of texts will help in that regard as it will steer your story.

The abstract is vital

A lot of students will write the abstract right at the end, when everything else is done and when theyre thinking about their friends down at the pub. Dont be like those students. The abstract is probably the most important part of your entire paper. Its certainly the part that is going to get read most.

The abstract is not a wow, pazaaz! piece. Youre not trying to impress your audience with it. Instead, youre trying to summarize the main findings of your data and the conclusions you draw from there. A well-written abstract will make the rest of the paper much easier to digest.

Remember to cater your abstract to your audience. If theyre looking to find out about a specific result, then include that! This way, what they want is right there at the beginning. Yes, that does make it less likely that theyll read the whole report, but then if you only have to explain the abstract, that makes life so much easier.

Numbers and words

Remember that not everybody understands data and what it means. For that reason, when you write out a result, dont just write it out in numbers, also write out the results in words. In fact, if you really want to do it correctly, you want to write it out twice the first time to translate the results into words pretty much one on one, the second time to explain what that actually means.

In this way, both the numerate and the number-illiterate will find it easy to understand what youre trying to say.

The most important thing to remember is that you can ask for help. If youre struggling with an analysis or how to write it out, go online and ask people! Youll be surprised how quickly people will get back to you if your question is specific enough.

Then, you can move forward confident in the knowledge that your report is as understandable as it can be. And thats a great feeling. And who knows, maybe once you stop being so intimidated by presenting the numbers, you can finally get that position as chief data officer !

About Pat Fredshaw

Pat Fredshaw is a passionate freelance writer and content editor at . She writes about digital marketing marketing, SEO, and blogging.

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  • How to Write a Results Section | Tips & Examples

How to Write a Results Section | Tips & Examples

Published on August 30, 2022 by Tegan George . Revised on July 18, 2023.

A results section is where you report the main findings of the data collection and analysis you conducted for your thesis or dissertation . You should report all relevant results concisely and objectively, in a logical order. Don’t include subjective interpretations of why you found these results or what they mean—any evaluation should be saved for the discussion section .

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Table of contents

How to write a results section, reporting quantitative research results, reporting qualitative research results, results vs. discussion vs. conclusion, checklist: research results, other interesting articles, frequently asked questions about results sections.

When conducting research, it’s important to report the results of your study prior to discussing your interpretations of it. This gives your reader a clear idea of exactly what you found and keeps the data itself separate from your subjective analysis.

Here are a few best practices:

  • Your results should always be written in the past tense.
  • While the length of this section depends on how much data you collected and analyzed, it should be written as concisely as possible.
  • Only include results that are directly relevant to answering your research questions . Avoid speculative or interpretative words like “appears” or “implies.”
  • If you have other results you’d like to include, consider adding them to an appendix or footnotes.
  • Always start out with your broadest results first, and then flow into your more granular (but still relevant) ones. Think of it like a shoe store: first discuss the shoes as a whole, then the sneakers, boots, sandals, etc.

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If you conducted quantitative research , you’ll likely be working with the results of some sort of statistical analysis .

Your results section should report the results of any statistical tests you used to compare groups or assess relationships between variables . It should also state whether or not each hypothesis was supported.

The most logical way to structure quantitative results is to frame them around your research questions or hypotheses. For each question or hypothesis, share:

  • A reminder of the type of analysis you used (e.g., a two-sample t test or simple linear regression ). A more detailed description of your analysis should go in your methodology section.
  • A concise summary of each relevant result, both positive and negative. This can include any relevant descriptive statistics (e.g., means and standard deviations ) as well as inferential statistics (e.g., t scores, degrees of freedom , and p values ). Remember, these numbers are often placed in parentheses.
  • A brief statement of how each result relates to the question, or whether the hypothesis was supported. You can briefly mention any results that didn’t fit with your expectations and assumptions, but save any speculation on their meaning or consequences for your discussion  and conclusion.

A note on tables and figures

In quantitative research, it’s often helpful to include visual elements such as graphs, charts, and tables , but only if they are directly relevant to your results. Give these elements clear, descriptive titles and labels so that your reader can easily understand what is being shown. If you want to include any other visual elements that are more tangential in nature, consider adding a figure and table list .

As a rule of thumb:

  • Tables are used to communicate exact values, giving a concise overview of various results
  • Graphs and charts are used to visualize trends and relationships, giving an at-a-glance illustration of key findings

Don’t forget to also mention any tables and figures you used within the text of your results section. Summarize or elaborate on specific aspects you think your reader should know about rather than merely restating the same numbers already shown.

A two-sample t test was used to test the hypothesis that higher social distance from environmental problems would reduce the intent to donate to environmental organizations, with donation intention (recorded as a score from 1 to 10) as the outcome variable and social distance (categorized as either a low or high level of social distance) as the predictor variable.Social distance was found to be positively correlated with donation intention, t (98) = 12.19, p < .001, with the donation intention of the high social distance group 0.28 points higher, on average, than the low social distance group (see figure 1). This contradicts the initial hypothesis that social distance would decrease donation intention, and in fact suggests a small effect in the opposite direction.

Example of using figures in the results section

Figure 1: Intention to donate to environmental organizations based on social distance from impact of environmental damage.

In qualitative research , your results might not all be directly related to specific hypotheses. In this case, you can structure your results section around key themes or topics that emerged from your analysis of the data.

For each theme, start with general observations about what the data showed. You can mention:

  • Recurring points of agreement or disagreement
  • Patterns and trends
  • Particularly significant snippets from individual responses

Next, clarify and support these points with direct quotations. Be sure to report any relevant demographic information about participants. Further information (such as full transcripts , if appropriate) can be included in an appendix .

When asked about video games as a form of art, the respondents tended to believe that video games themselves are not an art form, but agreed that creativity is involved in their production. The criteria used to identify artistic video games included design, story, music, and creative teams.One respondent (male, 24) noted a difference in creativity between popular video game genres:

“I think that in role-playing games, there’s more attention to character design, to world design, because the whole story is important and more attention is paid to certain game elements […] so that perhaps you do need bigger teams of creative experts than in an average shooter or something.”

Responses suggest that video game consumers consider some types of games to have more artistic potential than others.

Your results section should objectively report your findings, presenting only brief observations in relation to each question, hypothesis, or theme.

It should not  speculate about the meaning of the results or attempt to answer your main research question . Detailed interpretation of your results is more suitable for your discussion section , while synthesis of your results into an overall answer to your main research question is best left for your conclusion .

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I have completed my data collection and analyzed the results.

I have included all results that are relevant to my research questions.

I have concisely and objectively reported each result, including relevant descriptive statistics and inferential statistics .

I have stated whether each hypothesis was supported or refuted.

I have used tables and figures to illustrate my results where appropriate.

All tables and figures are correctly labelled and referred to in the text.

There is no subjective interpretation or speculation on the meaning of the results.

You've finished writing up your results! Use the other checklists to further improve your thesis.

If you want to know more about AI for academic writing, AI tools, or research bias, make sure to check out some of our other articles with explanations and examples or go directly to our tools!

Research bias

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The results chapter of a thesis or dissertation presents your research results concisely and objectively.

In quantitative research , for each question or hypothesis , state:

  • The type of analysis used
  • Relevant results in the form of descriptive and inferential statistics
  • Whether or not the alternative hypothesis was supported

In qualitative research , for each question or theme, describe:

  • Recurring patterns
  • Significant or representative individual responses
  • Relevant quotations from the data

Don’t interpret or speculate in the results chapter.

Results are usually written in the past tense , because they are describing the outcome of completed actions.

The results chapter or section simply and objectively reports what you found, without speculating on why you found these results. The discussion interprets the meaning of the results, puts them in context, and explains why they matter.

In qualitative research , results and discussion are sometimes combined. But in quantitative research , it’s considered important to separate the objective results from your interpretation of them.

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10 Best Reporting Tools and Software of 2024

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  • Best for comprehensive data integration: Zoho Analytics
  • Best for task-based reporting: Asana
  • Best for high-level project reporting: Hive
  • Best for data-driven decision-making: Google Looker
  • Best for customizable project reporting: Wrike
  • Best for visual project tracking:
  • Best for all-in-one project management: ClickUp
  • Best for agile project management: Jira Software
  • Best for data visualization: Tableau
  • Best for Microsoft ecosystem integration: Power BI

Reporting tools and software are crucial to teams, especially in terms of project management as they provide a structured way to track progress, identify risks and make informed decisions. They offer a sweeping view of project health that helps managers to not only pinpoint areas of concern but also identify successes. With effective reporting, an organization gets transparency and ensures its stakeholders are aligned, which plays a part in making projects successful since everyone involved has access to the same information and insights. We’ve analyzed 10 top reporting tools and software worth your consideration.

Top reporting software: Comparison table

Zoho analytics: best for comprehensive data integration.

Zoho Analytics logo.

Zoho Analytics is a reporting tool that excels at aggregating data from a wide array of sources as it connects with over 250 data sources, including files, feeds, databases and cloud services. Its comprehensive suite of reporting options includes charts, pivot tables, summary views, tabular views and more. Zoho Analytics also offers an intuitive drag-and-drop interface to further simplify the report creation process and make it accessible for users of varying skill levels.

Zoho Analytics offers plans starting at $22 per month for the Basic plan, while the Standard, Premium and Enterprise plans cost $45, $112 and $445 per month, respectively, when billed annually. There’s also a Custom plan for prospective users to share their requirements.

  • Extensive data integration from over 250 sources.
  • Data preparation and management tools for accurate analysis.
  • A wide array of visualization options for insightful reporting ( Figure A ).
  • AI and ML-powered augmented analytics for guided insights.

A dashboard showing a few visualization options in Zoho Analytics.


Zoho Analytics’s integrations include Zoho CRM, Salesforce CRM, Microsoft Dynamics CRM, HubSpot CRM and Zoho Bigin.

  • Comprehensive data integration capabilities.
  • Wide range of visualization tools.
  • Advanced augmented analytics features.
  • May be complex for beginners.
  • Customization can require a learning curve.

Why we chose Zoho Analytics

We selected Zoho Analytics for its broad range of reporting capabilities and user-friendly design. Its ability to present data in various visual formats makes analysis flexible and insightful and caters to diverse reporting needs as well as a wide variety of users.

Learn more about other Zoho products, like Zoho Projects and Zoho Vault .

Asana: Best for task-based reporting

Asana logo.

Asana simplifies project management with its Universal Reporting feature, which provides teams with a clear overview of task progress and project health. Its visual reporting format is designed for easy interpretation, meaning that users at all levels within an organization can easily access and use Asana.

Asana’s paid plans include the Premium plan at $10.99 per user per month, billed annually, and the Business plan at $24.99 per user per month. Its Enterprise plan’s pricing hasn’t been listed publicly.

  • Visual and intuitive reporting tools for task and project tracking ( Figure B ).
  • Goal tracking to align daily tasks with strategic objectives.
  • Real-time updates to keep teams informed on project progress.
  • A variety of highly customizable charts.

Getting started with the reporting feature in Asana.

Asana’s top integrations include Microsoft Teams, Slack, the Asana for Gmail add-on, Asana for Adobe Creative Cloud and Google Calendar.

  • User-friendly reporting and task management.
  • Effective goal alignment features.
  • Wide range of integrations.
  • Limited depth in analytical features.
  • Real-time analytics are somewhat restricted.

Why we chose Asana

We simply selected Asana for its user-friendly approach to task-based reporting. Asana is also highly effective when it comes to aligning tasks with organizational goals.

For more information, check out our full Asana review .

Hive: Best for high-level project reporting

Hive logo.

Hive is recognized for its high-level reporting capabilities, offering a suite of options for a variety of project management use cases. With features like goals, analytics dashboards and timesheet reporting, Hive provides a comprehensive tool for gaining visibility and gathering insights into projects.

Hive has two premium plans atop a free plan. Teams at $12 per user per month when billed annually and $18 when billed monthly, and Enterprise, whose prices aren’t publicly listed.

  • Goals for setting, tracking and monitoring goals across teams.
  • Analytics dashboards to showcase project status, project breakdowns and more.
  • Timesheets reporting to analyze data across timesheets.
  • Multiple views like Portfolio, Summary, Table, Kanban and more ( Figure C ).

A Kanban dashboard in Hive.

Hive’s top integrations include Google Calendar, Gmail, Google Sheets, Google Drive and Slack.

  • Customizable high-level reporting options.
  • Variety of views for different reporting needs.
  • Efficient project and action management features.
  • May require initial setup time to customize views.
  • Some advanced features might be available only on higher-tier plans.

Why we chose Hive

We selected Hive for its versatile high-level reporting options and customizable views. They bring a flexible and comprehensive overview to projects.

For more information, check out our full Hive review .

Google Looker: Best for data-driven decision-making

Google Looker logo.

A rather different entry from most tools on this list, Google Looker stands as a unified business intelligence platform that excels at turning data into actionable insights. It offers self-service BI that allows users to access, analyze and act on up-to-date, trusted data. As a reporting tool, Looker offers reliable data experiences at scale and empowers users with real-time insights.

Looker has a 30-day free trial, and its Standard plan costs $5,000 per month. For an annual quote, as well as quotes for the Enterprise and Embed plans, contact Google sales.

  • Embedded analytics and applications for enhanced data experiences.
  • Data modeling to unify business metrics across teams and applications.
  • Real-time insights to empower users with up-to-date information.
  • An extensive template gallery for templates on many of Google’s applications ( Figure D ).

Looker’s template gallery.

Looker offers extensive integration capabilities, including BigQuery, Spanner, Cloud SQL and Cloud Storage.

  • Unified platform for all BI needs.
  • Real-time insights for up-to-date decision-making.
  • Extensive integration capabilities with data sources.
  • Pricing transparency could be improved.
  • May require a learning curve to fully utilize advanced features.

Why we chose Google Looker

Google Looker’s reporting capabilities can be seen particularly through its embedded analytics and real-time insights. It easily unifies business metrics across teams and applications. It’s also a great tool for users predominantly using applications in the Google ecosystem.

Wrike: Best for customizable project reporting

Wrike logo.

Wrike stands out for its highly customizable reporting features. This flexibility, combined with Wrike’s thorough resource management and advanced analytics, makes Wrike competent enough to provide detailed insights into project performance and resource allocation and flexible enough to adapt to various workflows.

Wrike has five plans: the ones with prices listed are the Free plan, Team plan at $9.80 per user per month and Business plan at $24.80 per user per month. The Enterprise and Pinnacle plans’ pricing plans aren’t publicly listed.

  • Customizable reports for tailored project insights ( Figure E ).
  • Resource management to monitor progress and identify risks.
  • Advanced analytics for deep visibility into project performance.

A reporting dashboard in Wrike.

Wrike’s top integrations include Jira, GitHub, Google Sheets, Azure DevOps and HubSpot.

  • Highly customizable reporting options.
  • Comprehensive project and resource monitoring.
  • Advanced analytics capabilities.
  • Customization options may require time to master.
  • Extensive features can be overwhelming for newcomers.

Why we chose Wrike

Wrike has robust reporting capabilities and customizable features, which give users the flexibility and depth needed to gain extensive insights into their projects and resources.

For more information, check out our full Wrike review . Best for visual project tracking logo. is a favorite among teams that love visual task management and prioritize ease of use as it offers a visually intuitive platform for project tracking. Its advanced reporting features, such as stacked charts and workload views, provide a thorough overview of project progress and team capacity.’s dashboard customization is very flexible; this enables teams to mold their reporting to meet their project needs.

monday has a free plan and a handful of premium plans, namely, Basic at $9 per seat per month, billed annually, or $12 per seat billed monthly; Standard at $12 per seat per month, billed annually, or $14 per seat billed monthly; Pro at $19 per seat per month, billed annually, or $24 per seat billed monthly; and Enterprise, which offers customized pricing.

  • Stacked charts for multi-dimensional data analysis.
  • Workload views for balanced resource allocation.
  • Pivot tables for detailed data breakdowns.
  • Customizable dashboards for tailored project insights ( Figure F ).

A customizable dashboard in monday.

Some of the best integrations include GitLab, OneDrive, Todoist, Slack and Microsoft Teams.

  • Highly visual and intuitive interface.
  • Advanced reporting for comprehensive project insights.
  • Flexible dashboard customization.
  • Can be overwhelming for new users due to numerous features.
  • Some advanced features require higher-tier plans.

Why we chose is a visually intuitive platform and has advanced reporting capabilities. It delivers a balance between visual project tracking and in-depth reporting.

For more information, check out our full review .

ClickUp: Best for all-in-one project management

ClickUp logo.

ClickUp is recognized for its all-in-one approach to project management, offering a wide range of features from task management to time tracking and goal setting. Its reporting features are designed to provide teams with insights into productivity and project progress, supporting data-driven decision-making. ClickUp’s customizable dashboards and reporting tools allow teams to monitor key metrics and track performance effectively.

ClickUp offers a generous free forever plan alongside three premium tiers: Unlimited at $7 per user per month when billed annually, or $10 per user per month when billed monthly; Business at $12 per user per month when billed annually, or $19 per user per month when billed monthly; and Enterprise that needs prospective users to contact ClickUp for a custom quote.

  • Comprehensive dashboards for project overview ( Figure G ).
  • Customizable reporting for tailored insights.
  • Goal tracking to align efforts with objectives.
  • Time tracking to monitor task durations and productivity.

A dashboard showing some of the many views ClickUp offers.

Some of ClickUp’s top integrations include Gmail, Zoom, HubSpot, Make and Google Calendar.

  • Versatile all-in-one project management solution.
  • Extensive customization options for dashboards and reporting.
  • Generous free plan with substantial features.
  • Steep learning curve due to feature richness.
  • Customization can be time-consuming.

Why we chose ClickUp

We included ClickUp because of its comprehensive feature set and flexibility, offering teams an all-in-one solution for project management and reporting. It proves suitable for a wide range of project types and sizes.

For more information, check out our full ClickUp review .

Jira Software: Best for agile project management

Jira Software logo.

Jira Software is tailored for agile project management with specialized reporting features like sprint reports, burndown charts and velocity charts. These agile-centric reports give teams critical insights into their agile processes to help them optimize workflows and improve sprint planning. It’s worth considering for software development teams and those that follow scrum or kanban frameworks.

Jira offers a free plan for 10 users max. Its premium plans are the Standard plan at about $8.15 per user per month and the Premium plan at about $16 per user per month. It also offers an Enterprise plan that’s billed annually. However, you need to contact Jira for a quote.

  • Sprint reports for tracking sprint progress ( Figure H ).
  • Burndown charts for visualizing task completion.
  • Velocity charts for assessing team performance over sprints.
  • Cumulative flow diagrams for Kanban teams.

A sprint report in Jira Software.

Jira has extensive integrations with development tools like Bitbucket, Confluence, GitHub, Opsgenie, Jenkins and Dynatrace.

  • Tailored for agile project management.
  • Comprehensive reporting for scrum and kanban teams.
  • Wide range of integrations with development tools.
  • Primarily focused on software development teams.
  • Can be complex for non-technical users.

Why we chose Jira Software

Jira Software has robust agile reporting features and is capable of providing deep insights into agile project management processes, especially for teams practicing scrum or kanban methodologies.

For more information, check out our full Jira Software review .

Tableau: Best for data visualization

Tableau logo.

Tableau sets the standard for data visualization, offering a wide range of chart types and interactive dashboards that make complex data understandable at a glance. As reporting software, it offers a user-friendly interface and powerful data handling capabilities for users to create detailed and insightful visual reports.

Tableau’s pricing starts at $15 per user per month, with its highest tier costing $75 per user per month, both billed annually.

  • Wide range of visualization options.
  • User-friendly interface for non-technical users ( Figure I ).
  • Powerful data handling and processing capabilities.

Tableau’s user interface.

Tableau’s top integrations include Salesforce, Google Analytics, Microsoft Excel, Amazon Redshift and Snowflake.

  • Leading data visualization capabilities.
  • Intuitive interface for easy use.
  • Strong data connectivity options.
  • Higher price point compared to some competitors.
  • Can require significant resources for large datasets.

Why we chose Tableau

We considered Tableau because of its unparalleled data visualization capabilities and user-friendly interface. It should make it to your shortlist if your teams value both data accessibility and detailed reporting.

For more information, check out our full Tableau review .

Power BI: Best for Microsoft ecosystem integration

Microsoft Power BI logo.

Power BI is a key player in the reporting and analytics space, especially for those deeply embedded in the Microsoft ecosystem. Its seamless integration with other Microsoft products, like Excel and Azure, makes it a no-brainer for teams that want compatibility and ease of use with their reporting tools. What makes it a great reporting and analytics tool is its ability to handle large datasets and provide advanced analytics, including AI capabilities and custom visualizations.

Power BI offers a free version, with premium plans starting at $10 per user per month for the Pro plan and $20 per user per month for the Premium plan.

  • Seamless integration with Microsoft products.
  • Advanced analytics with AI capabilities.
  • Custom visualizations for personalized reporting ( Figure J ).

Visualization of an AI report in Power BI.

Aside from a variety of tools in the Microsoft ecosystem like Microsoft Office 365, Power BI’s top integrations include Asana, HubSpot, Google Sheets and Salesforce Pardot.

  • Strong Microsoft integration.
  • Comprehensive analytics and AI features.
  • Flexible pricing with a robust free version.
  • Can be complex for new users.
  • Limited integration outside the Microsoft ecosystem.

Why we chose Power BI

We chose Power BI due to its strong analytics capabilities combined with its seamless integration with tools in the Microsoft ecosystem. It’s a particularly fitting choice for teams that already use Microsoft products.

For more information, check out our full Power BI review .

Key features of reporting software

Real-time analytics.

Real-time analytics allows users to view, assess and analyze data as it flows into the business, which can be displayed on dashboards or reports. With this, users get to make decisions faster since they get instant, descriptive insights from the most current data.

Custom reports

Custom reports save time as they automate the data gathering and report generation processes. After the initial setup, reporting processes can be entirely streamlined, with live data feeds ensuring that any additional requests can be quickly addressed by making changes to existing reports.

Dashboard customization

Dashboard customization is crucial in reporting software as it allows users to set up their reporting environment based on their needs. Custom dashboards can provide in-depth data on various aspects of business operations, illustrating potential revenue and areas where improvements are needed. Businesses can mix and match data sources for a comprehensive view of their digital environment.

Automated reporting

This kind of reporting streamlines the process of generating regular reports and reduces the manual effort required while making sure that stakeholders receive timely updates. Users can schedule report generation and ensure that reports are always current and reflect the latest data.

Data visualization

Data visualization transforms complex datasets into graphical representations, making it easier to understand trends, patterns and outliers. This feature helps to make data more accessible and actionable, which enables users to quickly grasp the insights presented in the data.

How do I choose the best reporting software for my business?

First things first, when it comes to choosing the best reporting software for you, you must match a tool’s capabilities to your needs. For small to medium-sized businesses, tools like Zoho Analytics and ClickUp offer a vast feature set at a more accessible price point, which makes them great options when seeking value without compromising on functionality. Larger enterprises or those with more complex reporting and data analysis needs might lean towards Power BI or Tableau, known for their advanced analytics and integration within larger ecosystems.

Consider the types of reports you need, the data you’re working with and who will be using the tool. For teams that prioritize real-time data and collaboration, and Asana provide user-friendly interfaces and seamless integration with other productivity tools. On the other hand, if your focus is on in-depth data analysis and visualization, Tableau’s extensive customization options and Power BI’s deep Microsoft integration stand out.

In essence, the best reporting tool is one that not only fits your budget and technical requirements but also grows with your business, adapting to changing needs and helping you make informed decisions based on accurate, up-to-date data.


Our approach to identifying the top reporting tools for 2024 involved a detailed examination of each tool’s core features, ease of use, use cases and pricing. This allowed us to provide popular tools that cut across industries, use cases and team sizes. Additionally, we tested the tools where possible to understand how they approached reporting and compared our findings to verified reviews by real users. From this, we got to understand the pros and cons of each tool.

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AI Index Report

The AI Index Report tracks, collates, distills, and visualizes data related to artificial intelligence. Our mission is to provide unbiased, rigorously vetted, broadly sourced data in order for policymakers, researchers, executives, journalists, and the general public to develop a more thorough and nuanced understanding of the complex field of AI. The report aims to be the world’s most credible and authoritative source for data and insights about AI.

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Steering Committee Co-Directors

Jack Clark

Ray Perrault

Steering committee members.

Erik Brynjolfsson

Erik Brynjolfsson

John Etchemendy

John Etchemendy

Katrina light

Katrina Ligett

Terah Lyons

Terah Lyons

James Manyika

James Manyika

Juan Carlos Niebles

Juan Carlos Niebles

Vanessa Parli

Vanessa Parli

Yoav Shoham

Yoav Shoham

Russell Wald

Russell Wald

Staff members.

Loredana Fattorini

Loredana Fattorini

Nestor Maslej

Nestor Maslej

Letter from the co-directors.

AI has moved into its era of deployment; throughout 2022 and the beginning of 2023, new large-scale AI models have been released every month. These models, such as ChatGPT, Stable Diffusion, Whisper, and DALL-E 2, are capable of an increasingly broad range of tasks, from text manipulation and analysis, to image generation, to unprecedentedly good speech recognition. These systems demonstrate capabilities in question answering, and the generation of text, image, and code unimagined a decade ago, and they outperform the state of the art on many benchmarks, old and new. However, they are prone to hallucination, routinely biased, and can be tricked into serving nefarious aims, highlighting the complicated ethical challenges associated with their deployment.

Although 2022 was the first year in a decade where private AI investment decreased, AI is still a topic of great interest to policymakers, industry leaders, researchers, and the public. Policymakers are talking about AI more than ever before. Industry leaders that have integrated AI into their businesses are seeing tangible cost and revenue benefits. The number of AI publications and collaborations continues to increase. And the public is forming sharper opinions about AI and which elements they like or dislike.

AI will continue to improve and, as such, become a greater part of all our lives. Given the increased presence of this technology and its potential for massive disruption, we should all begin thinking more critically about how exactly we want AI to be developed and deployed. We should also ask questions about who is deploying it—as our analysis shows, AI is increasingly defined by the actions of a small set of private sector actors, rather than a broader range of societal actors. This year’s AI Index paints a picture of where we are so far with AI, in order to highlight what might await us in the future.

- Jack Clark and Ray Perrault

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The independent source for health policy research, polling, and news.

Americans’ Challenges with Health Care Costs

Lunna Lopes , Alex Montero , Marley Presiado , and Liz Hamel Published: Mar 01, 2024

This issue brief was updated on March 1, 2024 to include the latest KFF polling data. 

For many years, KFF polling has found that the high cost of health care is a burden on U.S. families, and that health care costs factor into decisions about insurance coverage and care seeking. These costs and the prospect of unexpected medical bills also rank as the top financial worries for adults and their families, and recent polling shows that lowering out-of-pocket health care costs is by and large the public’s top health care priority. Health care affordability is also one of the top issues that voters want to hear presidential candidates talk about during the 2024 election. This data note summarizes recent KFF polling on the public’s experiences with health care costs. Main takeaways include:

  • About half of U.S. adults say it is difficult to afford health care costs, and one in four say they or a family member in their household had problems paying for health care in the past 12 months. Younger adults, those with lower incomes, adults in fair or poor health, and the uninsured are particularly likely to report problems affording health care in the past year.
  • The cost of health care can lead some to put off needed care. One in four adults say that in the past 12 months they have skipped or postponed getting health care they needed because of the cost. Notably six in ten uninsured adults (61%) say they went without needed care because of the cost.
  • The cost of prescription drugs prevents some people from filling prescriptions. About one in five adults (21%) say they have not filled a prescription because of the cost while a similar share say they have instead opted for over-the-counter alternatives. About one in ten adults say they have cut pills in half or skipped doses of medicine in the last year because of the cost.
  • Those who are covered by health insurance are not immune to the burden of health care costs. About half (48%) of insured adults worry about affording their monthly health insurance premium and large shares of adults with employer-sponsored insurance (ESI) and those with Marketplace coverage rate their insurance as “fair” or “poor” when it comes to their monthly premium and to out-of-pocket costs to see a doctor.
  • Health care debt is a burden for a large share of Americans. About four in ten adults (41%) report having debt due to medical or dental bills including debts owed to credit cards, collections agencies, family and friends, banks, and other lenders to pay for their health care costs, with disproportionate shares of Black and Hispanic adults, women, parents, those with low incomes, and uninsured adults saying they have health care debt.
  • Notable shares of adults still say they are worried about affording medical costs such as unexpected bills, the cost of health care services (including out-of-pocket costs not covered by insurance, such as co-pays and deductibles), prescription drug costs, and long-term care services for themselves or a family member. About three in four adults say they are either “very” or “somewhat worried” about being able to afford unexpected medical bills (74%) or the cost of health care services (73%) for themselves and their families. Additionally, about half of adults would be unable to pay an unexpected medical bill of $500 in full without going into debt.

Difficulty Affording Medical Costs

Many U.S. adults have trouble affording health care costs. While lower income and uninsured adults are the most likely to report this, those with health insurance and those with higher incomes are not immune to the high cost of medical care. About half of U.S. adults say that it is very or somewhat difficult for them to afford their health care costs (47%). Among those under age 65, uninsured adults are much more likely to say affording health care costs is difficult (85%) compared to those with health insurance coverage (47%). Additionally, at least six in ten Black adults (60%) and Hispanic adults (65%) report difficulty affording health care costs compared to about four in ten White adults (39%). Adults in households with annual incomes under $40,000 are more than three times as likely as adults in households with incomes over $90,000 to say it is difficult to afford their health care costs (69% v. 21%). (Source: KFF Health Care Debt Survey: Feb.-Mar. 2022 )

When asked specifically about problems paying for health care in the past year, one in four adults say they or a family member in their household had problems paying for care, including three in ten adults under age 50 and those with lower household incomes (under $40,000). Affording health care is particularly a problem for those who may need it the most as one-third of adults who describe their physical health as “fair” or “poor” say they or a family member had problems paying for health care in the past 12 months. Among uninsured adults, half (49%) say they or a family member in their household had problems paying for health care, including 51% of uninsured adults who say they are in fair or poor health.

The cost of care can also lead some adults to skip or delay seeking services. One-quarter of adults say that in the past 12 months, they have skipped or postponed getting health care they needed because of the cost. The cost of care can also have disproportionate impacts among different groups of people; for instance, women are more likely than men to say they have skipped or postponed getting health care they needed because of the cost (28% vs. 21%). Adults ages 65 and older, most of whom are eligible for health care coverage through Medicare, are much less likely than younger age groups to say they have not gotten health care they needed because of cost.

One in four immigrant adults (22%) say they have skipped or postponed care in the past year, rising to about a third (36%) among those who are uninsured. Seven in ten (69%) of immigrant adults who skipped or postponed care (15% of all immigrant adults) said they did so due to cost or lack of health coverage. (Source: The 2023 KFF/LA Times Survey of Immigrants: Apr.-June 2023 )

Six in ten uninsured adults (61%) say they have skipped or postponed getting health care they needed due to cost. Health insurance, however, does not offer ironclad protection as one in five adults with insurance (21%) still report not getting health care they needed due to cost.

KFF health polling from March 2022 also looked at the specific types of care adults are most likely to report putting off and found that dental services are the most common type of medical care that people report delaying or skipping, with 35% of adults saying they have put it off in the past year due to cost. This is followed by vision services (25%), visits to a doctor’s offices (24%), mental health care (18%), hospital services (14%), and hearing services, including hearing aids (10%). (Source: KFF Health Tracking Poll: March 2022 )

A 2022 KFF report found that people who already have debt due to medical or dental care are disproportionately likely to put off or skip medical care. Half (51%) of adults currently experiencing debt due to medical or dental bills say in the past year, cost has been a probititor to getting the medical test or treatment that was recommended by a doctor. (Source: KFF Health Care Debt Survey: Feb.-Mar. 2022 )

Prescription Drug Costs

For many U.S. adults, prescription drugs are a component of their routine care. More than one in four (28%) adults say it is either “somewhat” or “very difficult” for them to afford to pay for prescription drugs. Affording prescription drugs is particularly difficult for adults who take four or more prescription medications (37%) and those in households with annual incomes under $40,000 (40%). Black and Hispanic adults are also more likely than White adults to say it is difficult for them to afford to pay for prescription drugs. (Source: KFF Health Tracking Poll: July 2023 )

The high cost of prescription drugs also leads some people to cut back on their medications in various ways. About one in five adults (21%) say in the past 12 months they have not filled a prescription because of the cost. A similar share (21%) say they have taken an over-the-counter drug instead of getting a prescription filled – rising to about one third of Hispanic adults (32%) and more than one in four adults (27%) with annual household incomes under $40,000. About one in ten adults say that in the past 12 months they have cut pills in half or skipped doses of medicine due to cost. (Source: KFF Health Tracking Poll: July 2023 )

Health Insurance Cost Ratings

Overall, most insured adults rate their health insurance as “excellent” or “good” when it comes to the amount they have to pay out-of-pocket for their prescriptions (61%), the amount they have to pay out-of-pocket to see a doctor (53%), and the amount they pay monthly for insurance (54%). However, at least three in ten rate their insurance as “fair” or “poor” on each of these metrics, and affordability ratings vary depending on the type of coverage people have.

Adults who have private insurance through employer-sponsored insurance or Marketplace coverage are more likely than those with Medicare or Medicaid to rate their insurance negatively when it comes to their monthly premium, the amount they have to pay out of pocket to see a doctor, and their prescription co-pays. About one in four adults with Medicare give negative ratings to the amount they have to pay each month for insurance and to their out-of-pocket prescription costs, while about one in five give their insurance a negative rating when it comes to their out-of-pocket costs to see a doctor.

Medicaid enrollees are less likely than those with other coverage types to give their insurance negative ratings on these affordability measures (Medicaid does not charge monthly premiums in most states, and copays for covered services, where applied, are required to be nominal.) (Source: KFF Survey of Consumer Experiences with Health Insurance )

Health Care Debt

In June 2022, KFF released an analysis of the KFF Health Care Debt Survey , a companion report to the investigative journalism project on health care debt conducted by KFF Health News and NPR, Diagnosis Debt . This project found that health care debt is a wide-reaching problem in the United States and that 41% of U.S. adults currently have some type of debt due to medical or dental bills from their own or someone else’s care, including about a quarter of adults (24%) who say they have medical or dental bills that are past due or that they are unable to pay, and one in five (21%) who have bills they are paying off over time directly to a provider. One in six (17%) report debt owed to a bank, collection agency, or other lender from loans taken out to pay for medical or dental bills, while similar shares say they have health care debt from bills they put on a credit card and are paying off over time (17%). One in ten report debt owed to a family member or friend from money they borrowed to pay off medical or dental bills.

While four in ten U.S. adults have some type of health care debt, disproportionate shares of lower income adults, the uninsured, Black and Hispanic adults, women, and parents report current debt due to medical or dental bills.

Vulnerabilities and Worries About Health Care and Long-Term Care Costs

A February 2024 KFF Health Tracking Poll shows unexpected medical bills and the cost of health care services are at the top of the list of people’s financial worries, with about three-quarters of the public – and similar shares of insured adults younger than 65 – saying they are at least somewhat worried about affording unexpected medical bills (74%) or the cost of health care services (73%) for themselves and their families. Just over half (55%) of the public say they are “very” or “somewhat worried” about being able to afford their prescription drug costs, while about half (48%) of insured adults say they are worried about affording their monthly health insurance premium.

Worries about health care costs pervade among a majority of adults regardless of their financial situation . Among adults who report difficulty affording their monthly bills, more than eight in ten say they are worried about the cost of health care services (86%) or unexpected medical bills (83%). Among those who report being just able to afford their bills, about eight in ten say they are worried about being able to afford unexpected medical bills (84%) or health care services (83%). And even among adults who say they can afford their bills with money left over, six in ten nonetheless say they are “very” or “somewhat worried” about being able to afford unexpected medical bills (62%) or the cost of health care services (60%) for themselves and their family. (Source: KFF Health Tracking Poll: February 2024 )

Many U.S. adults may be one unexpected medical bill from falling into debt. About half of U.S. adults say they would not be able to pay an unexpected medical bill that came to $500 out of pocket. This includes one in five (19%) who would not be able to pay it at all, 5% who would borrow the money from a bank, payday lender, friends or family to cover the cost, and one in five (21%) who would incur credit card debt in order to pay the bill. Women, those with lower household incomes, Black and Hispanic adults are more likely than their counterparts to say they would be unable to afford this type of bill. (Source: KFF Health Care Debt Survey: Feb.-Mar. 2022 )

Among older adults, the costs of long-term care and support services are also a concern. Almost six in ten (57%) adults 65 and older say they are at least “somewhat anxious” about affording the cost of a nursing home or assisted living facility if they needed it, and half say they feel anxious about being able to afford support services such as paid nurses or aides. These concerns also loom large among those between the ages of 50 and 64, with more than seven in ten saying they feel anxious about affording residential care (73%) and care from paid nurses or aides (72%) if they were to need these services. See The Affordability of Long-Term Care and Support Services: Findings from a KFF Survey for a deeper dive into concerns about the affordability of nursing homes and support services.

  • Health Costs
  • Racial Equity and Health Policy
  • Private Insurance
  • Affordability
  • High Deductible Plans
  • Tracking Poll

Also of Interest

  • Health Care Debt In The U.S.: The Broad Consequences Of Medical And Dental Bills
  • KFF Health Tracking Poll – March 2022: Economic Concerns and Health Policy, The ACA, and Views of Long-term Care Facilities
  • KFF’s Kaiser Health News and NPR Launch Diagnosis: Debt, a Yearlong Reporting Partnership Exploring the Scale, Impact, and Causes of the Health Care Debt Crisis in America
  • How Financially Vulnerable are People with Medical Debt?

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how to write an analysis report of data

  • Environment
  • Rural and countryside
  • Forests and woodland
  • Tree Supply Report 2024

Forestry Commission

Tree supply report, data analysis and appendix

Published 3 April 2024

how to write an analysis report of data

© Crown copyright 2024

This publication is licensed under the terms of the Open Government Licence v3.0 except where otherwise stated. To view this licence, visit or write to the Information Policy Team, The National Archives, Kew, London TW9 4DU, or email: [email protected] .

Where we have identified any third party copyright information you will need to obtain permission from the copyright holders concerned.

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Considerations and limitations

Production data was collected between August and November 2023 from some of the largest 15 private forest nurseries in England, Scotland, and Wales, as well as the 2 public nurseries in England and Scotland. These include the 13 nurseries surveyed in 2022-23, plus 4 additional nurseries, all newly established.

Due to the lack of some up-to-date figures, previous year’s data have been used for 2 of the private nurseries, using the assumption that these nurseries’ production hasn’t substantially changed in a single year. We estimate that these 17 nurseries grow more than 90% of the saplings used in forest and woodland planting in GB.

We have decided to leave the figures of Christmas trees and hedging species as given by the producers. It should be noted however that the report mainly targeted nurseries which produce forest and woodland trees, therefore this report does not aim to be representative of the production of Christmas trees and hedging species.

Nurseries have been asked to provide the species and number of trees produced at their site expected to be ready for sale in the 2023-24 season. Because data was supplied during the growing season, it relied on sample extrapolation and/or predicted figures rather than actual counts.

From conversations with stakeholders, imports and exports of forestry trees are considered marginal, and have been included in this report wherever declared by nurseries.

This report aims to illustrate the overall production of saplings for woodland and forestry planting in the 2023-24 season in Great Britain. Unless otherwise stated, ‘tree’ and ‘sapling’ are used interchangeably and refer to stock destined to woodland and forestry.

Amenity and urban planting are outside of the scope of this report, although we cannot exclude some overlap.

The given figures represent overall saleable tree production in Great Britain in 2023-24, but do not intend to represent availability for sale, nor market demand.

The complete species dataset used for analysis can be found in the Appendix .

Number of trees produced

Figure 1: Bar chart showing the number of saplings produced. 160.1 million were produced this season, compared to 151.8 million last season.

The total number of trees produced by the nurseries surveyed in 2023-24 is of 160 million, around 8 million higher than last year (Figure 1).

The majority of this increase is due to the added capacity of new entrant nurseries, although the 13 nurseries who participated last year have also seen a small production increase from 151.8 million to 152.9 million (data not shown).

Number of species produced

Figure 2: Bar chart showing the number of tree species produced by the nurseries. 129 species were produced in 2023-2024.

The nurseries surveyed have produced a total of 129 species, which is a similar figure to the previous season (Figure 2). A complete list of all the species can be found in the Appendix .

Broadleaved and conifers

Figure 3: Pie and ring chart representing the percentage of broadleaves (lighter shading) versus conifer (darker shading) trees produced. The inner and outer pie charts shows how many trees have been produced for each group. Broadleaves make up a third of the overall production, but around 2 thirds of the number of species produced.

The 2023-24 season has seen a definite increase of broadleaf saplings in both percentage (from 26% to 32%) and absolute numbers (from 40 million to 51 million). Conifers have seen a slight decrease from 112 million to 109 million, but still represent more than 2 thirds of the overall production. An overview of the annual change within species is provided in Figure 9 .

The increase in overall broadleaf production is largely due to new entrant nurseries specialising in broadleaves. Many existing nurseries have also communicated an increase in broadleaf production as well as alternative timber species in the past few years. They have however also expressed frustration with the volatility of the market and planting, which prevents them from making robust decisions about species production for the future.

Figure 4 shows broadleaves as a percentage of the total production in each nursery (mean 53%, median 58%). Again, the apparent shift towards broadleaves compared to the previous year (mean 40%, median 28%) is largely lead by the inclusion of new nurseries which specialise in broadleaf production. Specifically, we can now see three nurseries which exclusively produce broadleaves. However, the majority of nurseries still grow both coniferous and broadleaf trees.

Figure 4: Dot plot showing the percentage of broadleaves grown at each nursery. Each dot represents a nursery. Most of the dots are spread between 2 and 75%, with 3 dots around the 100% broadleaf mark.

Figure 5: Dot plot showing the number of species grown at each nursery. Each dot represents a nursery. The majority of the dots are clustered between 10 and 35 species, with some just below the 90 mark.

There is a great variety in the number of species grown at each nursery, ranging from only 5 sapling species to almost 90, as shown in Figure 5. Larger nurseries tend to stock more species.

Top species produced

At nearly 70 million, Sitka spruce dominates sapling production in GB. It is followed by Scots pine at 16 million. Hawthorn is the third most-produced species in 2023-24, closely followed by Norway spruce, Downy birch, and Douglas fir (Figure 6).

Refer to Figure 9 to see the change in production from 2022-23.

Figure 6: Bar chart of the top 20 species grown in GB. Sitka spruce tops the chart at 69.4 million trees, followed by Scots pine at 15.9 million and hawthorn at 8.9 million. The darker coloured bars represent conifer species, and the light coloured bars represent broadleaf. Note - the measurement bar for Picea sitchensis fades at the end for ease of interpretation.

Figure 7: Bar chart of the top species grown in GB from 21st to 40th. The unit of measurement has changed from M (million) to K (thousand). The darker coloured bars represent conifer species, and the light coloured bars represent broadleaf.

Figure 8: Bar chart of the top species grown in GB from 41st to 60th. The darker coloured bars represent conifer species, and the light coloured bars represent broadleaf.

Figure 9: Bar chart showing the change in production in percentage for each species compared to last year. The most produced species are at the top. Sitka spruce has decreased 6%, while Scots pine has increased 14%. Hawthorn, Blackthorn and Beech have increased respectively by 28, 37 and 61%.

Figure 9 broadly reflects the increased broadleaf production seen in other parts of this report. Hedging species (hawthorn, blackthorn, beech, hazel and hornbeam) show a marked increase in production, although this can be partly attributed to the addition of new hedging-specific nurseries, which were not included in last year’s data.

While conifers overall show a decrease in production, Scots, Lodgepole and radiata pine, Western hemlock, Japanese cedar, European larch, and Coastal redwood have all increased numbers from last year, potentially driven by an increased interest in alternative timber species.

It should be noted however that these figures are based solely on 2 years of data and as such do not necessarily represent a trend. Various external factors such as seed availability, weather conditions and market assumptions underpin nurseries’ production.

The data shown throughout this report are production and not sales figures, and therefore do not directly reflect tree demand in GB.

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Global Methane Tracker 2024

how to write an analysis report of data

About this report

Methane is responsible for around 30% of the rise in global temperatures since the Industrial Revolution, and rapid and sustained reductions in methane emissions are key to limiting near-term global warming and improving air quality. The energy sector – including oil, natural gas, coal and bioenergy – accounts for over a third of methane emissions from human activity. The IEA’s Global Methane Tracker is an indispensable tool in the fight to bring down emissions from across the energy sector.

This year’s update provides our latest estimates of emissions from across the sector – drawing on the more recent data and readings from satellites and ground-based measurements – and the costs and opportunities to reduce these emissions. It also tracks current pledges and policies to drive down methane emissions and progress towards these goals. For the first time the Tracker includes the investments needed to deliver emissions reductions and the potential revenue from these measures. 

Online table of contents

1.0 key findings.

Read online

2.0 Understanding methane emissions

3.0 what did cop28 mean for methane, 4.0 methane emissions in a 1.5 °c pathway, 5.0 tracking pledges, targets and action, 6.0 progress on data and lingering uncertainties, methane tracker database.

Database of country and regional estimates for methane emissions and abatement options and free datasets.

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  • Documentation Download "Documentation"
  • Acknowledgements Download "Acknowledgements"


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IEA (2024), Global Methane Tracker 2024 , IEA, Paris, Licence: CC BY 4.0

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Jobs Report Today: Hiring Blows Past Projections

Follow the latest news and analysis of the march nonfarm payrolls report..

Last Updated: 

A Deeper Look at the Numbers

Friday's jobs report surpassed projections.

The U.S. added 303,000 jobs in March according to Bureau of Labor Statistics data released Friday. Economists surveyed by FactSet expected the data to show a payroll gain of 205,000 last month. The BLS reported a revised 270,000 jobs added in February.

The bulk of March’s job gains occurred in healthcare, government, and construction .

The unemployment rate dipped slightly to 3.8% from 3.9% in February.

Wage growth , a closely watched metric, bounced higher last month to 0.3% from the 0.2% logged in February.

Follow our coverage of the report below.

Strong March Labor Report Raises the Stakes for Inflation Data

The picture on employment is getting clearer, more sectors are picking up the pace of hiring, wage growth picked up in march, unemployment dips in march, job growth was much stronger than expected in march, another jobs report is about to land. what the fed is watching., latest updates.

Megan Leonhardt

The March jobs report was a very good one for everyday Americans. Payroll gains were very strong, unemployment remained low, wages grew more quickly than inflation, and some of the previous mixed signals on the strength of the job market seemed to fade.

But with the labor market so strong, it brings up the question: What does this mean for interest-rate cuts by the Federal Reserve? Are three cuts of a quarter of a percentage point still feasible for this year?

Many economists and analysts say that Friday’s report likely doesn’t change what the Fed will do. Chair Jerome Powell himself said following the March policy meeting that strong job growth alone wouldn't be enough to keep the Federal Open Market Committee from starting to lower the fed funds rate.

“The monetary policy implications of the March employment report are minimal,” writes Dante DeAntonio, Moody’s Analytics labor economist.

While payroll gains came in much stronger than expected, the unemployment rate and average hourly earnings were in line with expectations, so there is some optimism that the Fed will look past the hiring numbers as it considers the bigger picture. And many economists and Fed watchers predict the Fed will start cutting in June—the odds of that remain at around 60%, writes Rob Swanke, senior equity strategist for Commonwealth Financial Network.

“The bar for starting an easing cycle has little to do with the labor market—it is the inflation picture that will be determinant,” writes Eric Winograd, AllianceBernstein’s director of developed- market economic research.

That means next week’s consumer price index inflation reading is more important to near-term monetary policy than Friday’s employment data. Fed officials will have two additional employment reports—for April and May—in hand by the time the committee meets in early June. Several additional reports on inflation will affect their thinking as well.

“If the Fed is confident that inflation is sliding, they will cut even if the labor market is strong,” Winograd says.

In recent months, there have been some mixed signals in the Bureau of Labor Statistics employment data around the true state of the U.S. job market. The bureau uses two surveys to compile its jobs report, and one had shown much more strength than the other.

Friday’s data, however, shows that the secondary household survey, which has been significantly weaker recently, is “finally converging with the stronger establishment survey,” writes ZipRecruiter Chief Economist Julia Pollak. Generally speaking, the household survey is used to track the unemployment rate, while a survey of establishments tracks payrolls.

The convergence of what the two surveys show is due, in part, to the fact that Friday’s household survey showed that the U.S civilian labor force grew by 469,000. The number of Americans employed grew by 498,000. Additionally, the labor-force participation rate hit 62.7%, a modest uptick from the 62.5% rate logged in February and January.

Another sign of strength is that the average workweek, tracked by the establishment survey, surprisingly went up. Last month, the average workweek for all employees on private nonfarm payrolls edged up to 34.4 hours from 34.3 hours logged in February.

“We have found plenty of reasons to poke holes in the payroll data of the last several months, but that is a much harder exercise to perform today,” writes Thomas Simons, senior economist at Jefferies.

“The data leaves us borderline speechless. We were optimistic about the payroll numbers coming into today based on recent trends in jobless claims and momentum from prior months, but we did not expect to see such strong data around the periphery and within the details,” Simons said.

Updated 3 days ago

Much of the recent hiring has been in areas that are less affected by higher interest rates, such as the public sector and education, but the latest data show that broadened slightly last month.

The bulk of March’s job gains occurred in healthcare, government, and construction, the Bureau of Labor Statistics reported Friday.

Healthcare added 72,000 jobs in March, which is a bit above the average monthly gain of 60,000 the sector has posted over the last year. In March, hiring within healthcare was strongest in ambulatory healthcare services, hospitals, and nursing and residential care facilities.

Government employment grew by 71,000 last month. That is markedly higher than the 54,000 jobs that the public sector has added on an average monthly basis over the past 12 months. Local governments continue to lead the way.

The construction sector significantly picked up the pace of hiring last month, adding 39,000 jobs in March. Over the past year, construction has only added an average of about 19,000 jobs a month.

Employment in leisure and hospitality returned to prepandemic levels after several years of slow job growth, adding 49,000 jobs in March. Over the past year, job growth in the sector had averaged 37,000 per month.

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Poor Nations Are Writing a New Handbook for Getting Rich

Economies focused on exports have lifted millions out of poverty, but epochal changes in trade, supply chains and technology are making it a lot harder.

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A group of men sitting together at a market stall.

By Patricia Cohen

Reporting from London

For more than half a century, the handbook for how developing countries can grow rich hasn’t changed much: Move subsistence farmers into manufacturing jobs, and then sell what they produce to the rest of the world.

The recipe — customized in varying ways by Hong Kong, Singapore, South Korea, Taiwan and China — has produced the most potent engine the world has ever known for generating economic growth. It has helped lift hundreds of millions of people out of poverty, create jobs and raise standards of living.

The Asian Tigers and China succeeded by combining vast pools of cheap labor with access to international know-how and financing, and buyers that reached from Kalamazoo to Kuala Lumpur. Governments provided the scaffolding: They built up roads and schools, offered business-friendly rules and incentives, developed capable administrative institutions and nurtured incipient industries.

But technology is advancing, supply chains are shifting, and political tensions are reshaping trade patterns. And with that, doubts are growing about whether industrialization can still deliver the miracle growth it once did. For developing countries, which contain 85 percent of the globe’s population — 6.8 billion people — the implications are profound.

Today, manufacturing accounts for a smaller share of the world’s output, and China already does more than a third of it . At the same time, more emerging countries are selling inexpensive goods abroad, increasing competition. There are not as many gains to be squeezed out: Not everyone can be a net exporter or offer the world’s lowest wages and overhead.

There are doubts that industrialization can create the game-changing benefits it did in the past. Factories today tend to rely more on automated technology and less on cheapworkers who have little training.

“You cannot generate enough jobs for the vast majority of workers who are not very educated,” said Dani Rodrik, a leading development economist at Harvard.

The process can be seen in Bangladesh, which the World Bank’s managing director called “one of the world’s greatest development stories” last year. The country built its success on turning farmers into textile workers.

Last year, though, Rubana Huq, chair of Mohammadi Group, a family-owned conglomerate, replaced 3,000 employees with automated jacquard machines to do complex weaving patterns.

The women found similar jobs elsewhere in the company. “But what follows when this happens on a large scale?” asked Ms. Huq, who is also president of the Bangladesh Garment Manufacturers and Exporters Association.

These workers don’t have training, she said. “They’re not going to turn into coders overnight.”

Recent global developments have accelerated the transition.

Supply chain meltdowns related to the Covid-19 pandemic and to sanctions prompted by Russia’s invasion of Ukraine drove up the price of essentials like food and fuel, biting into incomes. High interest rates, imposed by central banks to quell inflation, set off another series of crises: Developing nations’ debts ballooned , and investment capital dried up.

Last week, the International Monetary Fund warned of the noxious combination of lower growth and higher debt.

The supercharged globalization that had encouraged companies to buy and sell in every spot around the planet has also been shifting. Rising political tensions, especially between China and the United States, are affecting where businesses and governments invest and trade.

Companies want supply chains to be secure as well as cheap, and they are looking at neighbors or political allies to provide them.

In this new era, Mr. Rodrik said, “the industrialization model — which practically every country that has become rich has relied on — is no longer capable of generating rapid and sustained economic growth.”

Nor is it clear what might replace it.

There’s a future in service jobs.

One alternative might be found in Bengaluru, a high-tech center in the Indian state of Karnataka.

Multinationals like Goldman Sachs, Victoria’s Secret and the Economist magazine have flocked to the city and set up hundreds of operational hubs — known as global capability centers — to handle accounting, design products, develop cybersecurity systems and artificial intelligence, and more.

Such centers are expected to generate 500,000 jobs nationwide in the next two to three years, according to the consulting firm Deloitte .

They are joining hundreds of biotech, engineering and information technology companies including homegrown giants like Tata Consultancy Services, Wipro and Infosys Limited. Four months ago, the American chip company AMD unveiled its largest global design center there.

“We have to move away from the idea of classic development stages, that you go from the farm to the factory and then from the factory to offices,” said Richard Baldwin , an economist at the IMD in Lausanne. “That whole development model is wrong.”

Two-thirds of the world’s output now comes from the service sector — a mishmash that includes dog walkers, manicurists, food preparers, cleaners and drivers, as well as highly trained chip designers, graphic artists, nurses, engineers and accountants.

It is possible to leapfrog to the service sector and grow by selling to businesses around the world, Mr. Baldwin argued. That is what helped India become the world’s fifth-largest economy .

In Bengaluru, formerly known as Bangalore, a general rise in middle-class living attracted more people and more businesses that, in turn, attracted more people and businesses, continuing the cycle, Mr. Baldwin explained.

Covid sped this transition, by forcing people to work remotely — from a different part of town, a different city or a different country.

In the new model, countries can focus growth around cities rather than a particular industry. “That creates economic activities which are fairly diverse,” Mr. Baldwin said.

“Think Bangalore, not South China,” he said.

Free markets are not enough.

Many developing nations remain focused on building export-oriented industries as the path to prosperity. And that’s how it should be, said Justin Yifu Lin , dean of the Institute of New Structural Economics at Peking University.

Pessimism about the classic development formula, he said, has been fueled by a misguided belief that the growth process was automatic: Just clear the way for the free market and the rest will take care of itself.

Countries were often pressured by the United States and the international institutions to embrace open markets and hands-off governance.

Export-led growth in Africa and Latin America stumbled because governments failed to protect and subsidize infant industries, said Mr. Lin, a former chief economist at the World Bank.

“Industrial policy was taboo for a long time,” he said, and many of those who tried failed. But there were also success stories like China and South Korea.

“You need the state to help the private sector overcome market failures,” he said. “You cannot do it without industrial policy.”

It won’t work without education.

The overriding question is whether anything — services or manufacturing — can generate the type of growth that is desperately needed: broad based, large scale and sustainable.

Service jobs for businesses are multiplying, but many offering middle and high incomes are in areas like finance and tech, which tend to require advanced skills and education levels far above what most people in developing nations have.

In India, nearly half of college graduates don’t have the skills they need for these jobs, according to Wheebox , an educational testing service.

The mismatch is everywhere. The Future of Jobs report , published last year by the World Economic Forum, found that six in 10 workers will need retraining in the next three years, but the overwhelming majority won’t have access to it.

Other kinds of service jobs are proliferating, too, but many are neither well paid nor exportable. A barber in Bengaluru can’t cut your hair if you’re in Brooklyn.

That could mean smaller — and more uneven — growth.

Researchers at Yale University found that in India and several countries in sub-Saharan Africa, agricultural workers jumped into consumer service jobs and raised their productivity and incomes.

But there was a catch: The gains were “strikingly unequal” and disproportionately benefited the rich .

With a weakening global economy , developing countries will need to wring every bit of growth they can from every corner of their economies. Industrial policy is essential, Mr. Rodrik of Harvard said, but it should focus on smaller service firms and households because that is going to be the source of most future growth.

He and others caution that even so, gains are likely to be modest and hard won.

“The envelope has shrunk,” he said. “How much growth we can get is definitely less than in the past.”

An earlier version of this article misidentified the location of IMD. It is in Lausanne, not Geneva.

How we handle corrections

Patricia Cohen writes about global economics and is based in London. More about Patricia Cohen


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