GA4 x BigQuery: 4 Relevant Use Cases

👋🏻 In 2023, Google Analytics 4 (GA4) marked a turning point for Digital Analysts. GA4, powered by a new way of working, offers extended possibilities compared to its predecessor Universal Analytics.

Since Universal Analytics stopped collecting data on July 1, 2023, GA4 has become the standard. Google plans to remove data from Universal Analytics properties, making it inaccessible. This move to GA4, although forced, is in response to the need to comply with privacy laws.

GA4 stands out for its innovative interface, reports and features, some of which are still under development. One of the key benefits of GA4 is its new data model, which opens the way to in-depth analysis and serves as the starting point for your Marketing Data Hub.

Unlike Universal Analytics' website-centric data model, GA4's is more mature and suited to a world where consumers interact with companies via various touchpoints (events), such as apps, connected devices (IoT), stores, etc.

ℹ️ GA4 also offers a direct connection to Google BigQuery for exporting raw data, even in its free version, enabling daily and intraday exports of raw data.

With BigQuery, a world of possibilities opens up for you, as you can combine, transform, analyze and activate data at your leisure via Google Cloud Platform. Don't forget :

1. Build your own Marketing Data Hub

2. Data activation/sharing with Meta, Programmatics, CRM, website personalization, etc. (Composable CDP)

3. Get started with Machine Learning by leveraging Vertex AI within the Google Cloud Platform infrastructure.

4 cases of powerful GA4 activation

Retroactive Performance Tracking

It may be interesting to export Universal Analytics data and merge it with new GA4 data for long-term comparison. It is recommended to export UA data via the API to a BigQuery environment, enabling data to be combined, analyzed and visualized for retrospective analysis.

Creating Your Own Marketing Data Hub in BigQuery

GA4 offers the ability to function as a Marketing Data Hub, combining data from GA4 with that from traditional data warehouses and marketing channels. This makes it possible to build a centralized customer view by combining all data points.

Advanced analysis with Machine Learning via Vertex AI :

BigQuery opens the door to the use of Machine Learning via the Google Cloud Platform. Templates are available to easily discover trends and anomalies in the data, enabling automatic monitoring of all your marketing activities.

Using real-time GA4 exports for marketing activation :

GA4 makes it easy to activate your data in your marketing/marketingautomation channels. For example, you can segment and reactivate the most valuable customers who have been inactive on your website for a long time. Or you can anticipate the purchases of your recurring customers, or just those with abnormal behavior if the usual purchase dates seem to be overdue, to trigger marketing or customer support actions.

In conclusion

Migration to GA4 offers new possibilities and applications, from in-depth analysis to the construction of a complete Marketing Data Hub. Although GA4 still has some way to go in terms of functionality, it represents an opportunity for companies to improve their data management and analysis.