Ok the title is click baity – Google Data Studio is an awesome tool and many of you are probably already using it on some level. For those of you that don’t know Google Data Studio, it’s time to get on board. After all, it’s free and allows you to simplify the visualisation and accessibility of your data.
There are a multitude of systems it can connect to by default – don’t forget it is a Google product, so it’s connections are biased towards the Google ecosystem.
Being able to visualise the data from multiple systems in one place simplifies and streamlines reporting. For example, surfacing organic Analytics data alongside Google Search console clicks and impressions or connecting it with Google sheets to help pull in aggregated search data that’s updated live.
There are some gripes I have it with though, and it’s a good idea to be mindful of the shortcomings with the platform before you dive straight in.
So let’s start with seven pitfalls you need to be mindful of when using Google Data Studio.
- Aggregating metrics from different sources
This is probably my number one gripe. You want to add metrics for AdWords, Bing, Facebook etc. to create a total aggregated metrics to calculate ROAS, but there is currently no direct way to aggregate metrics from multiple data sources in Google Data Studio. The messy solution to aggregate the metrics, as in the example below is to use Google Sheets to aggregate the sources, and then connect it back up to Google Data Studio to display the results. This isn’t ideal (in fact, it’s awful). For agencies and in-house analysts who need aggregated metrics, this is probably the number one reason you’ll be looking at other providers.
- Limited data connectors
It’s a Google product so connections to systems are limited. There are third party connectors available to download and use but beware not all are maintained. We use the Supermetrics suite of connectors extensively and the support that these guys offer deserves a special mention.
- Metrics labelling
Let’s say for example you display the Site CTR metric from Google Search Console. If you were to relabel the heading to CTR, for example, it also relabels the metric – this is not cool. Debugging this involves going into the metric and removing the name to see what actual metric is being used to pull in the data. They really should include a display name field.
- Calculated metrics
One of the cool features of Data Studio is the ability to use calculated metrics.
For example, you have 3 goals that you need to sum up in analytics to give you an aggregated view of engagement, you can do something like this in Data Studio. Don’t forget though, you can’t aggregate this over different sources.
You create a calculated metric by hitting the ADD A FIELD when editing the source connection.
Calculated metrics appear in the source mapping appended with ‘fx’. Below is an example of an ROI calculated metric.
The problem is, custom metrics definitions are not saved when you change to a different source e.g. if you change the source from Joe Blogs AdWords to Mr Smiths Adwords, you have to create every single custom metric again for each source – there is no way to save this into a template.
The only way to export a Data Studio dashboard in the interface is to export to PDF.
This can mean trying to work it into another deck is a bit problematic – I’d really like to see some form of integration with Google Slides in future.
- Comparison arrows in tables
For actionable data, you’ll need comparison metrics. The problem is, you can’t select how you want to display the up and down arrows per table column in Data Studio – changing down to be green would change the whole table. In the below example, an increasing Avg. CPC is probably not a reason to celebrate.
- Comparison metrics precision
Similiar to the above, you can’t change the precision of the comparison metrics in tables. They are always to a single decimal point.
I’m sure there are other gripes you have with Data Studio – feel free to tweet me @_AlanNg and share your frustrations!
On the flip side, it’s not all doom and gloom. Keep your eyes out for a new post on all the reasons we do like Data Studio.