With the official sunsetting of Google’s Universal Analytics (UA) as of July 1, 2023, legacy users have a limited window to continue accessing existing data before the platform is shut down for good. However, the new and improved Google analytics offering—now simply referred to as Google Analytics 4 (GA4)—offers a host of improvements over its predecessor and more powerful, comprehensive analytics capabilities worth getting to know sooner rather than later.
In this article, we’ll explore GA4 and discuss what you need to know to migrate to the new platform.
What is Google Analytics 4 (GA4)?
GA4 is the latest version of Google’s analytics offering, featuring myriad new tracking data types for advanced analysis of customer usage metrics and cross-channel data measurement. These tracking capabilities go beyond web traffic to include app analytics alongside standard website analytics. New features include enhanced reporting capabilities, AI-driven predictive insights, and a host of customizations that allow for more focused tracking and bespoke data analysis.
Additionally, GA4 was designed to be a more privacy-centric solution, placing customer privacy front-and-center to adhere with compliance regulations like the European Union’s General Data Protection Regulation (GDPR) and California’s Consumer Privacy Act (CCPA). And with a renewed focus on event-based analytics, GA4 has adopted an event-driven model that provides more meaningful data behind user interactions, eschewing UA’s legacy reliance on sessions, pageviews, and other vanity metrics.
GA4 vs. UA
The crucial difference between the old UA and new GA4 is the latter’s ability to measure and report on both website and application user activity. GA4 is capable of tracking customers as they traverse multiple platforms; additionally, it leverages artificial intelligence/machine learning (AI/ML) for gleaning deeper insights from user interactions, whether it’s via a website or mobile app.
Focusing on Events
GA4 revolves around the concept of events, versus the traditional focus on web traffic and related analytics. An event in GA4 allows for the measurement of specific website or app interactions/occurrences; this critical difference between the previous UA offering (and its focus on pageviews as the central metric) allows users to gain a richer comprehension of how users are interacting with a website and app.
For example, legacy UA reports on various visitor hit types for a website, to include page hits, event hits, ecommerce hits, and social interaction hits. UA users also have access to additional fields like category, action, label, and customer, to name a few.
In contrast, GA4 is entirely event-based—as opposed to tracking and reporting on generalized data, all GA4 measurements are captured and reported as events, with any user interactions captured and reported as such.
GA4 Features and Benefits
GA4 offers a range of features and benefits for tracking users across their journeys, including both session-level reporting as well as reports broken down by interaction for deeper context/analysis and insights. Chiefly, this new array of available data structures and dimensions include engagement metrics like engaged sessions, engagement rate, and engagement time. Additionally, GA4 also tracks various other dimensions, including attribution, demographics, and events, to name a few.
New customizable platform dashboard
Naturally, the most noticeable visual difference in GA4 is the overhauled management dashboard. The new interface incorporates a streamlined navigation bar for accessing GA4’s home, reports, explore, advertising, configure, and library sections. Google has also incorporated AI-powered predictive insights directly into the UI—to tap into Google’s AI for predictive insights, click on Insights at the bottom of the navigation bar.
Google’s AI for predictive metrics and insights
In the past, UA was a useful tool for analyzing past user behaviors based on web metrics. While this functionality was adequate for gaining a general understanding of audience behavior, it lacked the robustness for predictive analysis and proactive decision-making. GA4’s predictive metrics covers this deficiency by enabling data-driven decisions for designing campaigns at scale.
For example, GA4’s AI-powered insights include:
- Purchase probability: the probability that a user will purchase a product or service from within a certain time period.
- Churn probability: the probability that a user will leave or cancel a service/subscription.
- Revenue prediction: a predicted amount that a user is likely to spend on a purchase/transaction.
Armed with these metrics and insights, GA4 users can develop highly-customized funnels for website visitors and app users based on their predicted behaviors and needs.
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Easy integration with Google Data Studio
On its own, GA4 allows for dashboard customizations that make the platform’s reporting bespoke to the unique requirements of each organization. However, when coupled with Google Data Studio, GA4 becomes a supercharged analytics platform capable of delivering custom visualizations based on collected data. Google Data Studio is an online data visualization tool for transforming data into actionable reports and interactive, compelling dashboards.
Learn more about the best tools for data visualization.
Custom segments are highly useful for better understanding user behavior, since they allow for the analysis of a subset of analytics data. Segmentation basically involves dividing users into groups defined by specific attributes—for example, customers that made purchases from a specific website or app location.
By creating custom segments based on a subset of events that occurred on a website or app (i.e., triggering events), GA4 users can create granular views of user behavior for more accurate tracking of customer interactions.
A website and app users’ combined experience, their so-called “customer journey,” consists of a unique set of interactions with a company or brand. This mapping of interactions that take place before and after a customer purchase is crucial for driving desired user behavior; however, maintaining tracking continuity between platforms with the legacy UA is, for the most part, impossible.
In contrast, the new GA4 allows for the tracking of active user behavior across multiple platforms—be it website visits or app usage—by assigning unique user IDs during website or app login. This cross-platform tracking allows for comprehensive visibility across the user experience, from start to finish, platform to platform, at any stage: acquisition, engagement, monetization, or retention.
(Re)introducing Google Signals
For much of the web’s history, cookies served as the primary mechanism for gleaning data regarding an end-user’s browser environment and settings. However, with the rise of privacy regulations like GDPR and CCPA, cookies have gone by the wayside; in fact, popular browsers like Mozilla Firefox and Apple Safari have already started blocking third-party cookies by default. Google itself plans on blocking third-party cookies in 2024.
Fortunately, online marketers have alternative mechanisms for gaining a comprehensive view of users’ online behavior. Signals, Google’s cross-device tracking and remarketing tool, has been available in beta form since July 2018, and is now integrated with GA4 for first-party data/first-party cookie-based ad personalization. With Google Signals built into GA4, marketers can access a comparable breadth of tracking without relying on third-party cookies and personal user information; instead, aggregate data is used, and personal data is anonymized and never processed by third parties.
Bottom Line: Google Analytics 4
With the new GA4, online marketers have a powerful analytics platform for achieving unprecedented situational awareness into the behavior of their audiences. Features like cross-platform tracking, AI-driven insights, custom segments, and a revamped dashboard make it a compelling level-up from the old UA; however, like its predecessor, GA4 is easy to install and integrate, so legacy Google analytics users can get up-and-running in a short amount of time. And since users’ personal data is collected and processed in a manner compliant with GDPR and other privacy laws, marketers can rest assured that their activities are in adherence with existing and future privacy legislation.
Read next: Top 8 Predictive Analytics Tools