- March 18, 2022
Google Analytics 4: Waiting Is No Longer an Option
Let’s face it: change is always hard. It typically requires time, resources, and effort. It will also generally include a learning curve, as well as paying off technical debt – particularly when it comes to web technologies and software. In the web analytics space, Google Analytics 4 (GA4) represents a major change to the class-leading tool that so many of us are familiar with.
Originally released in October of 2020, GA4 has been promoted by Google as being the future of the product, and one that website owners and marketers should start thinking about.
Well, as of this week, making the move to GA4 is no longer going to be an option - it’s the only GA option thanks to Google’s announcement that Universal Analytics will be deprecated in 2023. After July 1, 2023, GA4 will be the only framework supported. In light of this, now is the time to start planning your upgrade to GA4!
It’s no surprise that privacy on the web has become a much bigger issue in recent years, with Facebook and Apple taking different stances on the matter. Universal Analytics (which is now 10 years old!) is still reliant on cookies – and we know that, at some point next year, Google Chrome will no longer support the use of third-party cookies in the interest of preserving user privacy. GA4 is very much built for the future of the cookieless web, with an entirely different data model and structure relative to Universal Analytics. Because of the fundamentally different structure of GA4, implementation isn’t as simple as flipping a switch or running a migration assistant. In most cases, significant tagging work is going to need to be done to maintain parity with Universal Analytics. Thus, the time to get moving on this is now, so that by the time Universal Analytics goes away, your GA4 instance has enough meaningful data to do year-over-year and period-over-period analysis.
Beyond the forced “need” to upgrade, given Google’s announcement, GA4 offers a number of advantages:
- The ability to understand your visitors across web + app touchpoints in one spot
- Data-driven attribution modeling that uses machine learning to help analyze the full impact of your marketing efforts across the user journey. This analysis can be exported into Google Ads to drive campaign optimizations to further improve performance
- Country-level privacy controls that helps ensure regulatory compliance, while still providing key measurement functionality
- Deeper integrations with Google Search Console, Google Ads, Google BiQuery, and other solutions to do more sophisticated analysis and data mining
- Event-based modeling that’s more accurate and privacy-compliant relative to Universal Analytics