While some may still be uncomfortable with the new data format and the few missing features, GA4 opens up some new areas with great business and insight potential:
First and foremost:
1. BigQuery integration
Universal Analytics required the premium tier licence to activate this integration, but with GA4 it is a standard feature. BigQuery itself comes with storage and usage fees – while these will be negligible for most organisations, calculate your costs before activating the integration.
For those new to BigQuery – in a nutshell, it is:
- It is a fully managed, scalable cloud data warehouse.
- It comes with an on-demand pricing model (i.e. you pay for the amount of data stored and accessed).
- BigQuery is a native data source for DataStudio, Power BI, Looker, Domo and other data visualisation tools.
- You can think of BigQuery integration as a first step in a Machine Learning project, with BigQuery ML available out of the box – for starters.
2. Cross-platform user identification
In Universal Analytics, User ID can be a basis for user-centred cross-platform analysis. It is available in User-ID enabled Views and gives insight into device overlap, device paths toward conversion etc.
GA4 takes user cross-platform user identification well beyond that by making user ID a default user identifier. Thus,
- User ID is a basis for the Users metric, which results in a more reliable user count.
- This way, User Properties are shared across devices. E.g. if you assign a (signed-in) user a user-scoped attribute, that attribute will apply if the user visits your site (or app) from a different device.
- It allows cross-device targeting of users in Google Ads, giving your campaigns greater reach within a qualified audience.
3. Machine learning
GA4 uses machine learning to deliver insights:
Fig. 4: ML in action: anomaly detection in reports using a line chart
It also uses predictions to build Google-Ad-ready audiences. This is so advanced! Combining the power of Machine Learning with the reach of Google Ads makes Google Analytics 4 a marketing powerhouse:
Fig. 5: Audiences built on predicted metric values!
I’m sure that GA4 will make use of ML more extensively. In their blog post, Google show a churn probability report. In the GA4 properties which I have access to, I unfortunately cannot see the metric. All the blog posts about GA4 also show the same screenshot, so I assume others can’t see it either 🙂 As we have often seen, however, Google release product features gradually, so let’s wait and see.
Initially we were overjoyed by the fact that GA4’s predecessor Firebase Analytics didn’t use sampled data in reports. With GA4 it is partly true:
- the out-of-the-box reports are not sampled,
- but the custom reports (in the Analysis section) do not have that privilege.I haven’t seen documentation regarding GA4’s sampling thresholds, but they could be similar to those of Universal Analytics.
If your reports are heavily sampled, data export to BigQuery can be a solution. In that scenario, you can access 100% of your data. You can also use your BigQuery dataset as an unsampled data source of your visualisations (in DataStudio, Power BI, etc.).