How I design dashboards in Data Studio — Part 2: Structuring and organizing your page

Josh Cottrell-Schloemer
7 min readMay 6, 2021

This is the first of several articles in my Data Studio design series. You can find links to the other articles here. Or get started with Part 1: Data hierarchy and telling your story.

CIPP (aka Complex Ideas Per Page)

The way you structure your dashboards is intrinsically tied to your users and how you plan on informing or improving their actions.

In our last exercise we thought about the persona of our users and the hierarchy of the data we’d be using. We’re going to take that information and use it to help us start structuring our pages.

If you found that you needed lots and lots of sections at the bottom of your narrative pyramid from Part 1, then there’s a good chance you need to break up your dashboard into multiple sections or pages.

That’s because a single dashboard can only communicate a limited number of complex ideas at one time. Add too much complexity and your user gets confused and overwhelmed.

So start by considering those complex ideas and how they should be separated. In my case it might have been a good idea to have one page with all my top-level KPIs (like total impressions, engagements and conversions) and a separate page with individual ads and campaigns. Because these both are very different ideas: ‘how is my ad performance overall’ versus ‘which of my ads are performing the best and why’

Once you have an idea of the complex ideas for each of your dashboard pages, you’ll start to consider laying out your information on each page.

Block out the sections for each of your main ideas and start to consider how many metrics or visualizations you’ll need to illustrate your idea.

Information Density

You can’t fit an unlimited amount of metrics and charts on a laptop or mobile sized screen. So you need to choose wisely.

I start by thinking about sections for each of the main ideas that I’m trying to illustrate and consider how much room is available for each of those sections.

In the example above we have Top Level KPIs, Deep Dive Metrics and Individual Campaigns. The complex ideas break down something like:

  • Top Level KPIs — How are we performing over this time period?
  • Deep Dive Metrics — How much are we spending? how many people are seeing our ads? Is it driving more purchases of our product? What does it cost for each of those purchases?
  • Individual Campaigns — What ads and campaigns are working best? Which are costing the most?

[NOTE: this is a dashboard for an analyst that actually understands paid media and ad spend. If this was for the c-suite, I would simplify things a lot more.]

You can use your categories to think about how many metrics/visualizations you need to properly communicate the idea behind each one. You can also think about how much information needs to be explained vs presented without explanation. Which brings us to our next section:

Infographic or data tool — to handhold or not to handhold

When thinking about laying out your metrics, visualizations and overall design you need to think about how much you trust your audience to interpret data on their own.

Sometimes it’s as simple as describing your data in plain english.

If your user is someone with zero experience interpreting data you may need to include clear instructions and provide your own interpretation of the results. I think of these types of dashboards as a live version of Infographics.

If your user is an analyst or highly skilled at interpreting data, you may want to provide them a tool for exploring the data on their own. I call these… you guessed it, Data Tools!

In this example we provide more metrics and the ability to more freely explore the data. No safety bumpers required!

So now you have a good idea of the level of detail, level of guidance, and the types of data you’ll be putting on the page. The next step is deciding how to structure the page to create clear and understandable insights.

Focus areas and layout

This is basically a fancy way of saying that you should wireframe your idea, starting with the complex ideas you thought of at the first step of this article and then consider how much explanation and guidance is needed using the infographic v. data table exercise.

There are a million other articles that can teach you the technical skills for wireframing. Instead of going into those technical skills, I’m going to just list some guidelines that apply to Data Studio projects.

My basic guidelines for laying out your wireframe:

  • Consider the device that your audience will be using to view your dashboard. Data Studio does not allow responsive web design so you need to choose a screen size and stick to it. If you use a mobile sized screen, it’s important to know that Data Studio does allow users to scroll, so your wireframe can be taller than a typical mobile screen.
  • In most western cultures people tend to read from left to right and top to bottom (but that’s not true everywhere, so consider your audience). Think about where your reader’s eyes will start on the page. That’s often a good place for you to put the data equivalent of your ‘intro’ — adding filters/date ranges/descriptive titles to this section is a good idea.
  • People also tend to focus on larger metrics first, followed by smaller metrics. Big font sizes and large charts draw your attention and imply importance.
  • Big bold visuals can also break up the flow of the page and direct our attention. If your dashboard feels too dense or is just a collection of boring tables, it’s worth considering a visualization to break up the page.
  • Don’t worry too much about choosing the perfect visualization. If a pie or donut chart fits and makes the page more visually engaging, then add it. Despite what they teach you in Data Visualization courses, there are many situations where a pie chart is appropriate. Your primary concern is to avoid creating misleading insights — e.g. adding a line chart with two completely unrelated data series and implying a correlation or causation where there is none.
  • Don’t just think about the metrics or visualizations for each section, also consider the text descriptions you are going to provide. How are you going to spell out what a particular section is showing your audience? Where do you need more or less explanation.

That’s it for today! In part 3 we’ll be exploring how to style a page. It’ll go a bit deeper into choosing an aspect ratio, background colors, scrolling, navigation and more.

You can also follow my Medium account to get notified or connect with me on Twitter where I’ll post these and can answer questions.

Series links:

Thanks for tuning in!
I hope this is valuable for you all. The Data Studio community is one of the most helpful and supportive groups you’ll find, so get engaged, ask questions, start conversations. We’re all here to help.

This is the The Data Studio Design Toolkit

If you’d like a helping hand on your Data Studio project, then check out the Data Studio Design Toolkit. This set of copy-pasteable dashboards and UI elements includes 6 dashboards (3 light and 3 dark themed) along with colors, guidelines/tips/tricks and UI elements in 7 different colors.



Josh Cottrell-Schloemer

Building data-focused products. Startups acquired=1. Hobby = making Google Data Studio & Excel beautiful.