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 produce clear and compelling reports? 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.

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 on how you’ll make 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).

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 Contentsquare

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 Contentsquare, an analytics platform for user behavior and experience analytics you can

• Gather qualitative data via tools like surveys, user tests, and interviews

• Plus visualize quantitative data via heatmaps and capture user behavior in real-time with session replays, 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.

With Contentsquare, you can click through from information on your qualitative data (such as the number of rage clicks) to see qualitative data (such as relevant session replays) 

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. 📈

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 Contentsquare.

Luckily for you, there's a faster way to stand back and spot patterns occurring in your metrics. Contentsquare’s AI CoPilot assistant lets you ask chat-style questions about your analytics data and get thorough answers and charts. There’ll even be an explanation of how it reached its conclusions. 

For example, ask which product package was most popular among new sign-ups last week, and it will create a chart that reveals how many of last week’s sign-ups chose each one of your packages.

It’s a brilliant hack for when you have a hunch about a key trend in your data but don’t have the time to crunch the numbers yourself.

AI CoPilot can make useful data visualizations from your metrics instantly, helping you understand the bigger picture behind the numbers

📋 Using Contentsquare? Try creating a custom dashboard 

Pulling together the data for your report can be a scavenger hunt. However, if Contentsquare is your main analytics tool, it’s easy to streamline the process. 

Contentsquare allows you to create a customized dashboard that monitors only the metrics essential to your report. Set it up using templates or build your dashboard from scratch. No matter what Contentsquare plan you’re on, you can make an unlimited number of these. 

Use one of the template dashboards as a starting point, or start from scratch

Best of all, you can subscribe to receive notifications from your dashboard at regular intervals. You could, for example, set up a dashboard that sends you notifications with all your crucial report metrics every month, two days before your monthly report is due. 

📖 Case study: Contentsquare’s dashboards proved invaluable for Motorpoint, the UK’s leading independent retailer of used cars. According to Martin Wood, their UX Analyst, putting together the company’s data points on website performance used to be time-consuming. 

So, he set up a custom dashboard with only crucial metrics, such as page views, bounce rates and session times. He also included line graphs to visualize KPIs' performance over time. 

The dashboard slashed his reporting time by 75%, and the whole team has visibility over the metrics that matter. 

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 Contentsquare’s dashboard to save time and effort. Showcase relevant heatmaps, session replays, survey responses, and interview feedback to drive your point home and get everyone on the same page.

With Contentsquare, you can easily share session replays. This can really bring the points in your report to life. 

6. Collect feedback from your audience

Just as surveys 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, 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.

Pro tip: the thought of launching a survey just for internal use can be off-putting, since building one used to take a good few hours’ work. However, if you use Contentsquare’s AI survey builder, all you need to do is write a few lines about your goals for the project and it’ll create a batch of questions in seconds.

The AI survey creator isn’t just faster at this task than a human—it’s also much less likely to accidentally write biased questions that influence the user into telling you what you want to hear. 

With a brief text prompt, you can generate survey questions that’ll help you get the customer insights you need 

Contentsquare also offers AI features to speed up processing your results: 


• Sentiment analysis automatically categorizes responses as ‘positive,’ ‘neutral,’ or ‘negative’ in tone. You can filter your results by vibe: dive into the negative ones for constructive criticism, or go through the positive ones to find quotes for your marketing materials. 

• The AI reporting feature synthesizes your open-text responses into a one-page report. It’ll summarize the main feedback, pull out some relevant quotes, and even point to actions you could take based on survey results. It’ll save you trawling through responses. 

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).

1. 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.

❗Pro tip: use Contentsquare’s Impact Qualification capability to analyze different zones in your heatmap by their impact—that is, how much difference they have, positive or negative, on your goals. If a zone is performing particularly well (or particularly badly) at converting customers, it’ll be flagged as ‘high impact’. 

When writing an executive report, connecting data to your conversion goals is powerful, as it speaks directly to the numbers senior leadership really cares about.  

Use Impact Qualification to single out a zone that’s performing poorly, and you’ll be able to suggest an evidence-based action item in your report, like changing the zone’s contents  

2. 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.

Contentsquare’s Organic Content & SEO Lead creates a quarterly SEO report summarized on Slack, along with a Loom walkthrough and presentation

Note that you can track these essential metrics in Contentsquare’s dashboards. Screenshot your customized dashboard or share it live with your audience as you discuss key insights. Pull up a session replay or two or highlight customer feedback to strengthen your case.

For example, if session replays 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.

3. 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.

4. Customer journey report

Customer journeys allow you to hone in on the few steps users take from first contact to final conversion. Here’s a basic customer journey if you’re marketing an ecommerce brand:

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

Of course, it’s unlikely that every customer takes the same path to conversion. In fact, there are so many branches to each possible path that it can be quite hard to get your head around customer journey data. 

Contentsquare’s Journey Analysis capability is invaluable here. It turns your conversion path data into an interactive sunburst-shaped chart, helping you understand not just how users navigate through your site to conversion goals, but also the points where they most commonly drop off. You can click on any step to learn more about your customer behavior data at that moment.

Contentsquare’s data visualizations make it easier to report on your customers’ paths to conversion in a way that your audience will intuitively understand

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. 

While it can feel like a chore to regularly create data analysis reports, needle-moving, user-centric insights are the lifeblood of every good marketing strategy. Report your metrics frequently and accurately, and your team will have all the information they need to chart a path to success.

FAQs about data analysis reports