Data visualization for marketers: How to build actionable dashboards (Even if you’re not a data analyst or designer)

If you’ve ever felt like marketing data visualization is a beast of a task that you can’t seem to figure out, you’re not alone. I, too, used to struggling with building dashboards when I transitioned from a sales rep to a data analyst. So in this article, I’ll share all the tried-and-true tips and my process to make it easier for you to see and act on your marketing data.

This guide covers dashboard planning, KPI selection, tool comparison, data pipeline automation, and best practices in visual storytelling for marketers.

Key takeaways

• Start with business questions. Focus on the decisions you need to make, and only include KPIs that drive action.
• Sketch before building: Plan your dashboard layout, for example, top KPIs → trends → breakdowns, to avoid clutter.
• Choose simple, clear visuals: Use bar charts for comparisons, line charts for trends, scorecards for overviews. Avoid overloaded pie charts.
• Keep your dashboards clean and actionable: Limit to ~6 key marketing metrics per page, use clear titles, and group related charts together.
• Automate when possible: Use a marketing intelligence platform like Supermetrics, or a simple marketing data pipeline tool to streamline data flow and keep dashboards up to date.

My 3-step process to build marketing dashboards that drive action

1. Start with the problems

I’ve seen so many marketing dashboards that are overwhelming and don’t help anyone drive meaningful actions. Typically, it’s because the dashboard:

• Has too many metrics and dimensions available to you (in fact, our recent research showed that marketers are dealing with 230% more data compared to 2020)
• Tries to answer too many things with your dashboard
• Has the wrong visualization, for example, using a pie chart with 10 values. It’s very hard for the human eye to see the proportion

Even people who are great with data often struggle with choosing what to show. I’ve worked with many marketers who know their KPIs and still get stuck trying to tell the right story. The trick here is to start with the business problems and questions.

Let’s say your job is to increase brand awareness. You may ask: Are we reaching more people with this campaign? Now you’ll try to identify metrics that could help you answer that question. From there, use secondary questions to get more clarity, for example:

• What does success look like (maybe reach, impressions, frequency)?
• How does this tie to your business goals?
• What decisions can you make using this data?

Tip: Always think about the actions you’ll be able to make with certain KPIs. This helps you avoid putting unnecessary data in your dashboard and allows you to drive results.

Additional reading:

8 data principles you should apply for marketing

2. Plan your dashboard layout: Sketch before you build

This step reinforces intentional information design and helps align visual output with business objectives. Similar to how writers do outlines, I like to plan my dashboard in Miro (you may use Canva or even paper). It’s literally boxes and labels, but it helps me build a map of where I’m trying to go, for example:

• What question will each page answer?
• What types of visualizations will I need?
• Where does each element go?
  • For the dashboard:
    • Start with a high-level overview
    • Add individual pages for specific areas—spend, campaigns, channels, etc.
  • For each page:
    • Scorecards at the top of the page to show key KPIs
    • Lines and donut charts to show trends and breakdowns in the middle
    • Tables to show more details

The more you prep, the easier it’ll be for you to build your dashboard later on. Here’s what I typically include in my Miro:

• Clear page structure: Top KPIs first, trends next, then breakdowns
• Descriptive titles: Especially important if stakeholders don’t know the acronyms
• Limit the number of scorecards: I usually go with no more than six per page

3. Visualize and automate your marketing data

Get data into your dashboard

Now that you’ve mapped your dashboard strategy, let’s explore which marketing data visualization tools best align with your reporting needs. Since a dashboard is something you’ll want to come back to and use to make decisions about your performance frequently, I recommend automating your data transfer. If it’s a one-off dashboard and you only need data from one single channel, it’s fine to use native connectors to export your data to your visualization tool, whether it’s Looker Studio or Power BI, or some other marketers prefer spreadsheets. Other than that, use a marketing intelligence platform like Supermetrics to automate and transform your data.

Choose the right visuals

The effectiveness of your dashboard depends on the relevance and clarity of its visual elements. Most marketing questions can be answered using basic charts:

• Bar charts are great for comparisons, for example, month over month.
• Line charts are great for long-term trend analysis
• Scorecards are for a quick look at the most important KPIs
• Pie charts for distribution, but if there are a few categories (maximum 5). Additionally, use pie charts when you’re showing a clear whole—like 100% of budget or traffic split across all channels. They work best when each slice represents a meaningful part of the total. But if you're visualizing an arbitrary subset—like the impression distribution of the top 5 campaigns—it’s better to use a bar chart.
• Filters to switch between views, for example, different date ranges or channels
• Area charts are great for seeing distributions over time

Some tips for visualizing data:

1. Avoid using acronyms like CPC, CPM, etc, especially when presenting to stakeholders who might not understand what those mean.
2. Add charts with the same metrics or story together, next to each other, and on the same line. For example, spend overtime on the left, and spend by channel on the right.
3. Limit the number of scorecards or visuals so your audience doesn’t get overwhelmed.

Best tools for marketing data visualization

Typically, the data visualization tools you’re choosing to use will depend on your existing tech stack. For example, teams that are using Microsoft will probably go with Power BI. Similarly, if you’re using a Google product, then Looker Studio is a no-brainer, which is a very popular tool among the marketing community. I’ll discuss three popular options for marketing data visualization tools.

1. Looker Studio

It’s a perfect tool for those who:

• Love an intuitive and easy-to-use interface and want to get things done quickly
• Deal with simple marketing reporting needs, add data sources, create charts, and build reports
• Want to share and collaborate on dashboards

However, Looker Studio runs into some limitations when you:

• Connect more than five data sources, which leads to slow Looker Studio dashboards
• Use UNION to combine your data. For example, you want to combine data from Facebook Ads, Google Ads, and LinkedIn Ads and then stitch it with Google Analytics 4 to see conversions. That wouldn't be possible to do in Looker Studio. You can’t do both types of data blending—JOIN and UNION.
• Blend data from more than five data sources. You can’t do that in Looker Studio; it’s a hard limit.

That’s why I recommend using Looker Studio on top of a data warehouse like BigQuery or Snowflake to handle complex data blending. You can do all the transformations there before visualizing your data. This way, you'll have more control over your marketing data and also speed up your dashboard loading time. Alternatively, using Supermetrics' Marketing Intelligence Platform’s data management features could also help you with some data transformations.

Further reading:

• Data blending in Looker Studio and how to overcome its limitations

2. Power BI

Power BI is for you if you:

• Already work with Microsoft products and don’t want to add a new tool to your stack
• Have some data analysis skills
• Want more advanced and powerful data transformation features—data analysis expressions (DAX), star schemas, data modeling, etc.

Many love Power BI because it has many advanced features for data visualization, but for those with basic data skills, it can be a bit overwhelming to use Power BI. Compared to Looker Studio, Power BI can come across as more rigid and unnecessarily complicated to navigate. Scrolling through all the design panels can easily become overwhelming, especially for beginners.

Further reading:

• Looker Studio vs. Power BI for data visualization
• Power BI for marketing: How to set up your dashboards
• A guide to data transformation in Power BI for marketers
• Power BI custom visuals: 5 charts to elevate your data storytelling

3. Google Sheets

Google Sheets is a versatile tool for marketing reporting, and you can use it to visualize data. It’s a great tool when you:

• Want to do a quick, one-off analysis. For example, you notice a drop in some key metric, and you want to understand why this happened. You can build some charts in Google Sheets that include more clues, other data sources, different marketing metrics, time ranges, time breakdowns, and find the answer
• Need to crunch and manipulate your data, group data with pivot tables, join data with LOOKUP functions, or play around with IF statements
• Have more control over how your data is being transformed
• Want faster access to data. Google Sheets can be more forgiving with larger datasets and preloaded results. Once your automatic refresh is set up, the data is ready when you open the sheet, unlike Looker Studio dashboards that may take time to load.

On the other hand, Google Sheets isn’t the best option when it comes to:

• Filtering reports with different date ranges, campaigns, and product categories. It’s technically doable, but then you’ll end up with a very complicated spreadsheet that’s hard to maintain
• Analyzing high volumes of data, for example, Google Sheets has a 10 million cell limit

Further reading:

• How to create a Google Sheets marketing dashboard
• Data blending in Google Sheets: 2 ways to combine data from multiple sources for deeper marketing reports
• Automate ad spend tracking and budget pacing with Google Sheets and Supermetrics [Free cheat sheet and template included]

8 data visualization best practices for better storytelling

1. Start with the right question: Framing your dashboard with strategic questions grounds the data in real-world marketing decisions. This will focus your dashboard and prevent data overload. It will also tie data to business outcomes.
2. Always tie data to actions: Data alone isn't going to do anything. It really needs to drive decisions.
3. Apply basic design principles: Using the right layout, spacing, and color could improve the user experience and make it easy for them to understand your dashboards. You could ask for a designer’s help to figure out the layout of your first dashboard, and then apply it to the rest. In case you’re on your own, use our Looker Studio design guide.
4. Use descriptive titles: Avoid jargon like CPM, CPC, especially when presenting to stakeholders who are outside of marketing.
5. Use interactive filters: customize reporting views by campaign, date range, or audience segment. This helps different audiences get relevant data and insight.
6. Always cite sources: If I see a big number with no source, I immediately go, ‘Can I trust this?’ So always include citations or the data sources to build trust.
7. Use marketing reporting templates: These are good starting points, and a good template gets 75% of the job done. You can always customize a template to fit your needs.
8. Design for accessibility: Make sure your charts and dashboards are readable for everyone. Avoid relying solely on red and green to show good or bad performance—many people have color vision deficiencies. Use colorblind-friendly palettes, clear labels, and icons (like arrows) to support your visuals.

By applying these principles, you can transform static reports into dynamic, decision-enabling dashboards.

Final thoughts: A checklist for your dashboard

Now, if you've made it here and followed all the steps above, you should end up with a good marketing dashboard. Here’s a checklist:

• Each page answers one clear question
• The data supports a specific business goal or action
• The most important KPIs are visible
• Use descriptive titles instead of acronyms
• Charts are grouped logically by theme or metric
• There’s enough white space
• There are filters for different views—channels, campaigns, date, etc.
• There are sources for the data
• The dashboard has a consistent theme or design system
• The colors are accessible
• The dashboard is automated

Frequently asked questions about marketing data visualization

What should a good marketing dashboard include?

A good rule of thumb is that your stakeholders should be able to understand each chart in less than 3 seconds. For this, you need to include descriptive titles, clear legends, and make sure not to overload the user with too much information, and make sure it serves your stakeholders’ goals.

How can I make my dashboard easier for non-marketing stakeholders to understand?

For non-marketing stakeholders, avoid using acronyms and opt for full descriptive titles instead. Even the names such as ‘impressions’ might not be as obvious to others, so a descriptive title in this case would be “Count of ad impressions” or “Number of times the ad was seen”.

How can I automate my marketing reporting workflows?

You can use a marketing intelligence platform like Supermetrics to automate, manage, and transform your data in Looker Studio or any reporting destinations.

How do I decide which KPIs to include in a marketing dashboard?

Ask yourself: What are our goals, how will we get there, and how will we know we’re making progress?

How do I know if my marketing dashboard is actually helping decision-making?

Ask yourself: What decisions are you or your stakeholders trying to make? Then, evaluate whether your dashboard effectively supports those decisions.