GA4 and Universal Analytics: what changed

Universal Analytics and GA4 are, essentially, two generations of Google Analytics. Universal Analytics was the model that dominated for many years, and GA4 is the new generation that replaced it. The transition wasn't just a cosmetic update: it represented a profound change in how data is structured, collected, and analyzed. Therefore, those who migrated from one to the other had to relearn several concepts, as the underlying logic changed significantly.

The most fundamental difference lies in the data model. Universal Analytics was primarily organized around sessions and page views. GA4 adopts an event-based model, where almost every interaction is registered as an event. This change makes data collection more flexible and aligned with how people actually use websites and apps today, which goes far beyond simply loading pages. It's a different and more modern way of thinking about data.

The transition responded to changes in digital behavior and current analytical needs. The old model, centered on pages and sessions, reflected a simpler web. Today, people move between sites and apps, interact in various ways, and privacy concerns have grown. GA4 was built to better handle this scenario: more diverse interactions, cross-platform journeys, and a context of greater attention to data privacy. The change sought to modernize the tool for today's reality.

For users, the transition brought several practical changes: different metrics and concepts, a reorganized interface, new ways to configure events and conversions, and reports structured differently. Some metrics from the old model changed their definition or ceased to exist, requiring caution when comparing historical data. In practice, many people had to relearn how to use the tool and interpret the numbers, as not everything has a direct equivalent between the two generations.

An important point of caution is that directly comparing Universal Analytics data with GA4 data can be misleading. Since the measurement method changed, the same metric may have different meanings or values between the two tools. Therefore, care must be taken when looking at historical series that span the transition, to avoid drawing incorrect conclusions from comparisons that are, in fact, not equivalent. Understanding that these are different models prevents misinterpretations of the numbers.

Ultimately, the most important thing is not to dwell on what has changed, but to use the current tool effectively. GA4 is the standard Google Analytics today, and the effort should be directed towards configuring it correctly and extracting value from it, rather than lamenting the old model. As tools continue to evolve, the most useful approach is to understand the principles (what the tool measures and how) and focus on transforming that data into decisions, regardless of the tool's generation.