Before GA4, a connection from Google Analytics to BigQuery was only available for those that paid for the Analytics 360 version. However, with GA4, a free connector was made available to all users, allowing Google to open BigQuery to all businesses. Undoubtedly, this is a business-savvy move for Google, since it allows them to attain revenue from the cost of querying and storing data on the platform. However, despite the cost, this gives businesses the ability to access a phenomenal tool that can help them scale up their data analysis on their GA4 data should they have the specialized expertise available. Here are a few reasons why you should use BigQuery with your GA4 data.
BigQuery’s primary purpose is to serve as a data warehouse. In broad strokes, a data warehouse is a type of database that is meant for centralizing all of your data for the purposes of analysis in a cost-efficient way. This means that you can use BigQuery to connect and analyze your web analytics data with other parts of your business. This includes your CRM data, data from your payroll platforms, data from transactional databases, or even public data.
Centralizing your data through a data warehouse can help lead to new opportunities for reporting. For example, by combining your CRM data with your GA4 data, you would be able to:
These types of reporting will allow you to capture the full scope of your business and also prevent certain areas of your business from having data siloes inaccessible to other areas of your business.
Another benefit of utilizing BigQuery for GA4 is that you have complete access to the raw GA4 data that you are collecting. This gives you the ability to create custom reports that are not available on GA4 currently such as:
Another key benefit of creating custom reports on BigQuery is that there is no sampling involved in the data and BigQuery isn’t subject to the 14-month maximum data retention limit of GA4. This will allow you to get a more accurate display of your data.
A little-known feature of BigQuery is the ability to create supervised and unsupervised machine learning models directly on the interface using the platform’s Structured Query Language (SQL). This simplifies the machine learning process often undergone with data and saves time and money in implementing models across organizations. A few ways that machine learning can be utilized on GA4 data could be to:
These are only a few of the possibilities that can be accomplished by applying machine learning methods to GA4 data.
Even though BigQuery can accomplish a lot, it can be difficult to implement and hard to estimate cost. If you need help in understanding and applying BigQuery to your data, reach out to us at firstname.lastname@example.org.