Google Analytics (Universal Analytics) VS. Google Analytics 4

Google Analytics Page Vues KPI.

Google Analytics (Universal Analytics)  VS. Google Analytics 4 

Back in the fall of 2020, Google introduced Google Analytics 4 (GA4), previously Google (App+Web). GA4 will replace Universal Analytics (UA) as the default for digital analytics measurement in GA. GA4 is not a new version or an iteration of Universal Analytics, rather anan entire overhaul of Google Analytics, including a new interface, new features, reports, and settings, and a complete shift in GA’s philosophy of data collection. Google Analytics 4 serves as a leap forward in Web Analytics, but one that is not at all surprising in light of the direction web analytics has been trending in years past.

What is Google Analytics 4

Google introduced Classic Analytics in 2008, after purchasing Urchin Analytics. In 2013, Universal Analytics became the standard method of tracking website traffic across multiple devices using user ID and introducing enhanced ecommerce. GA4 takes the platform into the future of web tracking, allowing users to track app and website traffic within the same property. Along with a ton of new features and settings (including Big Query connections, improved ML, automatic event tracking, and controls for data governance/user consent),GA4 also forces users to rethink the collection and analysis of their data.

Fundamental Difference: GA4 vs UA 

The integration of Web and App Analytics (which was previously the App+Web Property Beta) meant that Google needed to retool the basic methodology behind how data is collected and reported within GA. While web tracking was pageview driven (hit type) and rooted in session based tracking, app analytics is fundamentally different. The difference between the two meant that analysis of each was not always an apples to apples comparison. In order for GA4 to combine both data sets into one platform effectively, GA4 has shifted away from session based tracking, towards amore user-based form of analytics. Where UA was focused on pageview-driven dimensions and metrics (landing page, session duration, pages per session, etc.), GA4 uses an event driven model. This means that users must change the way they think about their GA data. Instead of thinking of GA data in terms of aggregated session information broken down by pageviews, GA data will now be organized with a focus on users and their web and/or app journey and engagement.

Enhancements and Features

User Measurement

Moving from a session to user-based methodology, Google has made it a priority to focus on user identification and unification, mostly leveraging their single-sign on technology to stitch users together across multiple devices. 

In the previous version of Google Analytics, data was collected through cookie-based tracking. A website with UA places a 1st party cookie onto the user’s browser, and that allows the platform to monitor and record web activity on the site in question during that session.

Whereas now,  GA4 uses multiple forms of identification, including marketer-provided User IDs and unique Google signals from users opted into ads personalization. GA4 also continues to place the GA 1st party cookie wherever available, which allows GA4 to establish a much clearer and fuller picture of users. 

With this new method of measuring users, Google will be able to provide a more user-centric and more complete view of how users interact with digital properties. For example, tracking app downloads back to a desktop paid search ad will be possible directly within GA4. Alsoin a world where privacy is becoming of paramount importance to users, it’s a fair assumption that cookie-based tracking will become less reliable. Additional methods of user identification will continue to provide for means of sufficient data collection.

Enhanced Machine Learning

Google Analytics 4 will leverage Machine Learning much more than UA. The ability to close the gap on data loss due to privacy concerns, cookie reliability issues, and general tracking limitations is immensely important in today’s landscape and will only continue to grow.

GA4’s Machine Learning will provide additional insights that analysts may miss or not have the tools to identify today. The “Predictive Metrics and Audiences” feature provides the ability to alert users of significant trends/anomalies in their data, as well as empowering the everyday  analyst to find and target User Audiences that have a high propensity to convert

Additional Changes and Features

  • No more View filtering – the only data filtering possible is for internal/development traffic
  • Standard codeless event tracking automatically captured (scrolling, video engagement, file download, user engagements, page or screen views, etc.)
  • Each GA4 property can be connected to BigQuery (previously only available with GA360)
  • Enhanced Controls for User Data – flexibility on separating consent status and simpler data deletion options
  • Data retention period limited to 14 months
  • Much more robust Real-Time tracking/reporting capabilities 

Final Thoughts

While GA4 is indeed the future of both Google Analytics/web tracking and analytics,, it’s not showtime ready. Google is continuing to roll out updates and bug fixes. There will be more settings updates, reporting capabilities, and enhancements released moving forward. Much of what GA4 is currently missing, results in the product being less  useful compared to a mature UA implementation.. Net Conversion’s recommendation is to gameplan a structure that makes sense for each users’ web ecosystem within the GA4 platformthen implement Google Analytics 4 alongside a current Universal Analytics set up. This will allow you to collect historical data in GA4, familiarize yourself with the new interface and data structure, and most importantly find and utilize the benefits already available within GA4, while continuing to rely on the stability of a reliable and mature Universal Analytics property.


Written By: Lead Implementation, Daniel Crayner + Tracking Specialist, Eric Chandler

Turning Strategies Into “Always On” Tactics.

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