GA4 (Google Analytics 4) is the access analytics tool provided by Google. Since Universal Analytics (UA) stopped processing data in July 2023, GA4 has become the de facto standard tool for analyzing websites and apps. This article provides a systematic overview of GA4's basic structure, key features, differences from UA, and the benefits of adopting it.
GA4 is Google's next-generation analytics platform. While the previous UA (Universal Analytics) used a session-based measurement model centered on page views, GA4 adopts an event-based data model that uniformly records all user interactions as "events."
This allows you to analyze website and mobile app data across a single property, making it possible to understand user behavior more accurately.
In GA4, all user interactions—page views, scrolls, clicks, video plays, file downloads, and more—are measured as events. Events are broadly categorized into four types: automatically collected events, enhanced measurement events, recommended events, and custom events. A major advantage is that many user behaviors can be captured without any additional coding.
In addition to standard reports, GA4 includes an "Explorations" feature. You can freely combine multiple templates—such as free form, funnel exploration, path exploration, and segment overlap—using drag and drop for more advanced analysis. This is the equivalent of UA's "Custom Reports," but with significantly improved flexibility and intuitiveness.
BigQuery export, which was only available in the paid version (GA 360) under UA, is now available for free in GA4. By sending raw data to BigQuery, you can perform advanced analysis using SQL and integrate with BI tools, greatly expanding your data utilization capabilities.
GA4 has Google's machine learning models built in, automatically calculating predictive metrics such as "purchase probability," "churn probability," and "predicted revenue." You can create predictive audiences based on these metrics and use them for targeting in Google Ads.
GA4 uses the concept of "data streams" to manage website and mobile app (iOS/Android) data within a single property. Even when users move between web and app, they are more easily recognized as a single user, enabling more accurate cross-platform analysis.
The main differences between GA4 and UA can be summarized in the following points.
Regarding the data model, UA used hit-based measurement centered on sessions and page views, whereas GA4 has shifted to an event-based model that records everything as events. In terms of platform support, UA was specialized for website analysis, while GA4 can analyze both web and app data across a single property.
Session definitions also differ. In UA, sessions would end at midnight, but GA4 has removed this behavior, resulting in more natural session measurement. As a result, session counts may not match between UA and GA4.
The report structure has also changed significantly. UA used a hierarchical menu with categories like "Acquisition," "Behavior," and "Conversions," whereas GA4 has been reorganized into a simpler structure of "Reports," "Explore," and "Advertising." The handling of bounce rate is also different—in GA4, it has been redefined as the percentage of sessions without engagement.
Adopting GA4 offers numerous benefits. First, it improves your ability to comply with privacy regulations. GA4 is designed to move away from cookie-dependent data collection and does not store IP addresses. It is built to accommodate privacy regulations such as GDPR and the ePrivacy Directive.
Second, conversion setup has become more flexible. While UA had limits on goal settings, in GA4 you simply mark an event as a conversion to complete the setup. Managing multiple conversion points is now effortless.
Third, integration with Google Ads has been strengthened. By leveraging predictive audiences and importing audience segments created in GA4 directly into Google Ads, you can increase the precision of your ad delivery.
When implementing GA4, it is important to complete several initial settings reliably. After creating a data stream, the standard approach is to deploy a GA4 configuration tag via GTM (Google Tag Manager). Next, turn on Enhanced Measurement to enable automatic events such as scroll tracking and outbound link clicks.
Additionally, the default data retention period is only 2 months, so if you want to use Exploration reports for long-term analysis, be sure to change it to 14 months. Enabling Google Signals and setting up a BigQuery link early on will also make future data utilization much smoother.
GA4 is a significantly evolved analytics tool compared to UA, featuring an event-based measurement model, unified web and app analysis, BigQuery integration, and machine learning-powered predictive metrics. While many people may feel uneasy about the transition from UA, understanding how GA4 works and correctly completing the initial setup will provide a powerful foundation for data-driven web marketing. If you haven't fully utilized GA4 yet, start by working through the basic features and setup points introduced in this article.
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