How to Turn Your Google Data Studio Chart From Zero To Hero
Bring data from your major marketing platforms to Data Studio. Check out all the advanced tips and tricks for all marketers and analysts!
Creating a chart to visualise and explore data is accessible. In this article, you’ll dive into the different charts and learn how to use various visualisations to convey distinct messages.
Before you go ahead and consume the article, please ensure having the data sources connected, and if you haven’t done the step, please check out this guide. Once you complete the first step, click on “Add a chart” in the top navigation bar. A menu will open, showing you the available chart types.
And now, let’s start with the ones that are most heavily used.
Line charts are often a perfect way to emphasise a trend in the data. A great example could be when you want people to view trended data over time or the spikes at specific periods. Under the charts, you can find three different types of time series: time series, sparkling and smoothed time series. They’re all the same chart, but it’s just giving you an easier way to get there.
One small tip for using the line charts is turning off the dark grid lines ( remember we talked about the data pixel ratio and only devote our pixel to data display rather than ancillary information).
Bar/Column Charts are used when users want to show differences, whereby A line chart is used if the time aspect is essential for the visualisation. If all you care about is the total and wanted to compare different values, then Bar/Column Charts is a good choice. For example, we are using this chart to show the difference in magnitude across the traffic from different countries.
In most cases, placing your dimension to the X-axis can be a lot easier for people to read, but it depends on your space and what you have available. Moreover, you have an option to switch the chart you want by clicking the top right corner.
Now, building an Area chart to show differences over time. Note that over time is the key, Bar/Column charts allow you to compare different values, but it doesn’t necessarily let you show the data over time or how it all adds up to a whole.
If you have a lot of information to convey but with limited space, Sparklines can be a handy way to do this. It’s a kind of compressed time series line chart without the axes, and you would be able to give a quick gist of the trends without taking up much real space in the report.
Otherwise, the in-table bar is also an alternate option when trying to conserve the space to add additional insights.
Every selected data will represent in bar form, and you would always want to tie with the “Column number” rather than the “metric”. One thing to keep in mind is that colour could be distracting and unhelpful to help the user intuitively understand it. And hence, it is always suggested to standardise the colour and stick with the same colour. You may also want to pay attention to a couple of things, e.g. turn off the quote & unquote grid lines, header, page/row numbers and pagination.
You would want to follow these suggestions by circling back to what’s called the data pixel ratio — to remove ancillary info and give your data a succinct and cleaner visual look because the general DS default would violate the ratio. Here you’ll notice that the transformation of how your data table could look like when applying the principle.
Next, Scorecards. The most common use case for the Scorecard is when the user wants to highlight a single, important number, especially your KPI. But as a bonus, you can use it creatively to create a visualisation that might not be possible, .i.e. pull the scorecard data into a data table. One thing to note is that always compact the numbers where appropriate as it helps the reader quickly understand at a glance.
Secondly, you may want to be thoughtful about how you use decimals — remove unnecessary decimals but using them when the numbers are close. Below are some examples.
The pie chart is an acceptable choice when you have minimal items to showcase as a whole ( one dimension with no more than three values). Otherwise, you would not get the desired result as you expect. The reason why pie/donut charts fail is that the human brain can’t judge the size difference in the area very well, and people tend to use too many pieces to visualise the data.
So, always keep in mind that the level of effort to show something different is out of line with the value you’ll get from the chart. This means you would only use it when it is easy enough to understand and nothing to compare, for example below
That being said, if you really want to use a pie chart to compare the value instead of using the multiple pie charts, here is something you can do — adding the bar/column chart at the side to break down the view.
Map chart is a useful visualisation where it tells the story in a better way. As the image is shown, you can understand the geographic data and its performance at the first glance but it lacks additional info. On the other hand, a bar chart could be more informative than a map and it can be a good choice if you have more to tell.
Pivot table are the another option that you can use in DS, whereby it allows you to show two dimensions by each other. It has also had a cool hover-over columns to give you more flexibility. One thing to be aware of that is an option for expanding collapse within pivot tables. This allows the users to drill down into a certain level of information and be more interactive with the data.
Advanced tips for multiple visualisations
The value in DS comes from being able to combine multiple visualisations to make your entire case unique and paint the picture for your end user. And there’re two common uses of the combined viusalisation:
Scorecard + Time series
Scorecard basically tells you the magnitudeof the number and the time series show how things has been trending, i.e. the insane spike or the wild drop.
Scorecard + Sparkline
By using these charts together, it can also help to add context to data points without a large use of real estate.
Other chart settings
Changing the metrics display is possible in DS, especially showing the percent of total for each data. To do that, you can simply click on the pencil and hit the “comparison calculation” to select the percent of total and relative to corresponding data.
I hope you will find it useful. If you want to dive deep into more of GDS course, here is the CXL course you can look up to.
