Google Analytics tool – Temporal anomaly checker
I’m happy to announce the launching of a new tool for Google Analytics data (Universal) – built with Google Data Studio – to help to check quickly all usual common denominators explaining a temporal change & get a first level of insights.
It is the first version of an experimental project, available for all, proving how Google Data Studio can address recurring advanced needs of digital analysts working with Google Analytics data.
Observations and reasons of this project
As Google Analytics users, we often need to understand the reason of temporal anomalies noticed manually or automatically. And following the maturity in analytics skills for each of us, we use the same investigation method…or the same no-method to understand the origin of a sudden discrepancy inside GA data.
We are a lot to use Google Analytics data but with very disparate means to treat this kind of issue, regarding how it is considered as important for our activity/business. Some advertisers and agencies get skills & premium tools to compute automatically data and raise the reason of temporal anomalies. On the other side, some Google Analytics users bounce randomly from one GA standard report to another, prying for a magic discovery. (yes…quite caricatural..but…)
And often, the resulting explanations can be understood at first, thanks to one common denominator, let’s say one or two, to get the right track.
On the other hand, Google Data Studio is a free amazing tool, offering more and more interactivity and controls for report readers…more and more options for data visualisation, with a strong affinity with Google Analytics, materialized as example with GA data control.
So, if the problem is simple for most of cases, why not trying to replace computing & skills for some, by visualisation for all? Let’s try.
Proof of concept
For this first version, I mixed the elements below:
- Control and navigation features to use build a tool
- Short list of 8 metrics and 19 dimensions, taking care of sampling (pre-aggregation) and data loading performance
- Choices of data visualisations with various chart types to try to cover graphically important cases of discrepancy
(explained in the help section)
Access to the tool
Now, I let you discover this tool, test it on your Google Analytics view, maybe with an example of old anomaly to see if the features are relevant and what can be improved regarding real use cases.