Quick & Essential Tips for Google Data Studio Beginners
The number of tools out there for marketers is pretty amazing, and sometimes the choices can feel overwhelming.
Apart from Google tools I use regularly and my two main SEO performance tools (SEMrush and Agency Analytics) — I also have clusters of extensions bookmarked, as well as extra links from project management apps and visualisation creators to keyword research resources.
To stay away from potential overload, I’m always wary of adding new things into the mix, but I have witnessed how Google Data Studio, Google’s completely free reporting tool, is powerful, customisable and automatable in the past, I just hadn’t taken the leap into using it myself.
As I’m aiming to streamline my workload and reporting better, it was a fortunate moment to get that opportunity to learn and test Google Data Studio out, and this course, lead by analytics expert Michelle Kiss, is a strong foundation.
For this week (my 8th one in the CXL Digital Analytics Minidegree), I reviewed the Google Data Studio (from here known as GDS) course for beginners, and I’ve compiled 5 essential tips that first-timers might find useful. Let’s go!
Tip #1 — Know Your Charts
As SEOs, we work with client reports on a daily basis, but often we rely on the standard report visualisations our chosen tools provide us. Here are some guidelines for when you’re spinning up your own charts that will point you in the right direction.
Line charts
Line charts emphasise trends: a view over time, or spikes in performance
- Remember when using line charts that if you’re adding multiple data points, for example users along with sessions per use, make sure the data points chart a relationship, and tell a story
- Don’t put multiple metrics on a chart unless they have a relationship, put them side-by-side in separate line charts!
Bar/Column charts
Bar/column charts are excellent for emphasising differences
- If the specific data is important on each day, choose time series data as columns
- If all you are about is the values (and not the date) then a bar or column chart is more important. Names are easier to read on a bar chart (left to right)
Area charts
Area charts show differences over time
With an area chart, you can show multiple acquisition sources, or device types, denoted by colour — line line charts they show trends well over time
Pie charts
Pie charts are good for comparison breakdowns
The course instructor was quite strict on using bar and donut charts — it was pretty clear they were here least favourite of all the options available. Here are some rules to using them well:
- Only use when you have minimal items: ideally 3, max. 5
- They must be parts of a whole!
Sparklines and Scorecards
Paired together, sparklines and scorecards are a handy snapshot for stakeholders on performance
Unsure what kind of chart to use? Try this chart selector.
Tip #2 — Be Conscious of Colours and Space
When budgeting for space, remember that less is more. Don’t be afraid to remove unnecessary pixels, or to use a white box to cover up something you can’t get rid of (use “Shape” in the top toolbar)!
Always ask what’s adding value, and get rid of what you don’t need. Cleaner visualisations are great.
Audience Awareness
Data visualization principles are important — almost 10% of the population is colourblind. So are greyscale printers. Don’t rely solely on colour.
It doesn’t mean no red/green, but make sure colour has purpose, and think about cultural implications, too.
Using Legends
One example is only adding a legend to your data if you need it. For a line charts that shows different trendlines on desktop, mobile and tablet it’s helpful — but if you only have one line like for ‘sessions’ you don’t need it.
Use Colour as a Point of Emphasis
If there’s a step in a funnel everyone should care most about, colour is an excellent way to call it out. Also make sure to keep colours consistent across visualizations. Your users will draw different conclusions than intended.
Tip #3 — Customise Your Reports with Filters
Report-Level Filters vs. Widget-Level Filters
Filters will help you customise reports for your users, for example, you can filter to only mobile, if you just wanted a full report on that. See screenshot below on creating a report-level filter.
You can also, as an admin/editor, add a specific filter to specific widgets if you just want to keep them at chart-level, and not affecting the whole report. Just remember, then you will need to add them every time.
Filters Make Reports More Interactive
If you’d like to make filters available to your users, you can do that by adding them to a report. This will bring reports alive, as users can allows users to engage and explore the data, filtering by date, source, or any other information you make available. You can even add a search box if you have a lot of data to show!
If you enable the search box, make sure you have all of the options available for users to search instead of just a top 10.
Remember:
- when you create a filter, you create it once in the report
- if you copy a report, you will have it available
- if you edit a filter, that change will happen in all charts you’re using it in
- to save time, try not to build a whole bunch of 1 time filters — apply the filters separately and stack them!
- filter controls are set to the page-level, you can flip to make it at the report level, too!
Tip #4 — Make Life Easier With Alerts
A super-handy tip for keeping up to date with client performance is that you can schedule aggregate reports to run at X time per day and send to you, or a number of users.This allows you to keep an eye on the data for your clients so you can keep an eye on their KPIs. Simply go to the ‘Share’ option at the top of the report, and select “Schedule Email Delivery”.
Tip #5 — Use Alternatives to GA Funnel Visualisations
This one is a bit of a level-up, but worth it for visualising success for clients’ KPIs and goals.
In GDS you can’t show goal funnels like in Google Analytics, but you can use side-by-side bar charts to visualise these funnels for clients. In the example below, you can see 3 bar charts showing checkout behaviour funnels for an ecommerce website.
The first one is a chart will all the steps, starting with all users to the site, then add-to-basket, and so on until purchase is complete. It shows the number of users who completed these steps.
In the second (middle) chart, you see the same steps, except with percentages.
In the third (right) chart, there is another set of metrics that shows the % of users who completed the next step of the funnel, based on the number of users in the step just before. This allows you to see not only the overall drop off, but also if there is a specific step that has higher or lower drop off in comparison to those beside it.
Here are two ways to set that up — the first is from Michelle Kiss herself and the second is a handy one I found.
Phew! It was a lot of data processing(!) for my brain, and hopefully you’ll find the above useful, too.
Until next week!