Google Data Studio is a leading software for rapid data visualization and dashboard development. While a data scientist might miss some in-depth data analysis or data cleaning features, this software has its strength elsewhere: It's free, has a simplified UI resulting in a great experience, a gentle learning curve and focus on quick results: Data visualization doesn't always need be rocket science.

As a designer and developer of custom visualizations for Data Studio, one of my priorities is to perfectly integrate custom charts with this same mindset: Keep it simple to enhance to the already outstanding user experience.

To keep this promise there are a series of design guidelines that I applied to all my customized charts.

First drop - right chart

As soon as a user places a chart on the page it should immediately reveal its purpose. Magic? Not really.

Each chart accepts a certain quantity of metrics and dimensions. When creating custom charts the developer decides how many metrics and how many dimensions are required. Data Studio then automatically adds required metrics and dimensions from the available dataset to the chart.

But of course Data Studio doesn't know your dataset, nor the intention of the chart.

The trick is to keep the majority of metrics and dimensions optional. The fewer guesses Data Studio has to make the more likely it becomes that the chart is revealing its purpose right after the user drops it on the page.

Watch the video to see two custom charts in action.

Default settings should return the "best" result

Once the data part is settled, a chart usually gives you the option to fine-tune the "look" of the chart. This is done within the style tab of Data Studio.

A developer can define default values for each parameter. These default values must be carefully chosen: they always represent my preferred chart design.

Theme integration

Within Data Studio there is the possibility to define report-wide styles. A custom chart should take advantage of these settings as much as possible.

If a user has worked out a theme that matches its corporate identity and a new chart is added to the report, it should adhere type face definitions and the basic colour scheme.

Plan for every edge case

A chart can't be tested against all possible datasets. But it is possible to test against edge cases and find acceptable visual solutions. And in case this is not possible, provide helpful error messages with clear instructions for the user.

Keep no secrets

Each chart should come with an example report that must explain each feature and illustrate different use cases. In many cases the user can then simply copy the style settings and paste it into their own chart.

The near future: Better form controls for custom visualizations

And then of course, there is also my wish-list of features that would help me to improve the UX of custom charts. On top of this list, you will find more input controls like conditional formatting, optional metrics or access to dimension coulours. I am sure the Data Studio Team is already working on it secretly...

Once this is the case there will be even more options to fine-tune custom charts. This venture just started.

If you have questions about Google Data Studio custom visualizations, simply reach out.