Transition periods in the digital world can often feel overwhelming, particularly when dealing with critical data. However, they also offer new opportunities and potential for greater insights. This is the case with Google's shift from Universal Analytics (UA) to Google Analytics 4 (GA4).
In this article, we'll guide you on how to navigate this shift by signing up for the Google Marketing Platform, linking your Google Analytics account to it, transitioning to GA4, and importantly, preserving your historical data in Google's BigQuery for future reference.
The Transition Process
Firstly, it's important to know that the migration from UA to GA4 is not an automatic process. Each migration will be a mostly manual operation, largely dependent on the complexity of the data and your specific requirements.
The process involves transferring your historical UA data to BigQuery, a powerful, SQL-like database provided by Google. This way, all your data stays within the Google ecosystem. The data will need to be prepared in a way that's easily understandable and accessible for a non-tech audience.
A crucial part of this transition is defining which fields to move. The data manager will need to closely collaborate with the technical team during this phase to decide which data is most significant. Keep in mind that exporting all available data might lead to confusion and incur unnecessary expenses.
Upgrading to GA4
While preserving your historical UA data, it's also time to embrace the future with GA4. This platform provides more advanced features and is built with a focus on user privacy. Unfortunately, the UA data won't be directly available in GA4 due to differences in data formatting.
This is where BigQuery steps in as a guardian of your historical data. By storing your UA data in BigQuery, you have the ability to access it whenever needed, despite the shift to GA4.
Navigating Costs
Transitioning to GA4 and using BigQuery will require subscription to additional Google services. The pricing model is based on the computational resources required to process and analyze the data. This consideration is particularly important when handling your data in BigQuery.
When running queries in BigQuery, remember that costs are directly tied to the compute resources used. Hence, running large or complex queries can quickly increase costs. To manage this, set limits in the Billing section to keep expenses under control.
However, it's worth noting that Google offers the first 1 TB per month for free. This makes BigQuery a cost-effective solution for smaller companies, as costs are likely to be minimal or even FREE in many cases.
FAQs
Is it possible to import historical UA data into GA4?
- No. Unfortunately, due to data formatting differences, direct import is not possible. However, storing your historical UA data in BigQuery and your GA4 data in separate tables provides a workaround.
When is Google retiring UA data?
- As of the latest updates, the end of 2023 is the set date. Regardless of potential deadline changes, it's wise to prepare for this transition as soon as possible.
Why is Google making this change?
- While it might seem like a hassle, the shift to GA4 is driven by changes in privacy and data handling standards, making UA less viable in the long-term. GA4 is designed to be more in line with modern requirements, such as GDPR.
In conclusion
While the transition to GA4 might seem challenging, it's an opportunity to leverage Google's powerful tools for enhanced data analysis. With careful planning and execution, you can ensure that no precious data is lost, and you are set up for future success.
