Do you speak Google Analytics 4?

User Lifetime, Debugview, IA… The new version of Google Analytics, which you won’t cut short, brings its share of new features.

Google Analytics has been overhauled with GA4 and you’ll soon have to admire it: As a reminder, by the end of 2023, incoming data from Universal Analytics properties will no longer be processed at all. However, there are major changes in the new version of the web analytics tool, including an increase in cross-device, events, AI and the ability to create new reports. To make it easier for you to use the tool, here are some of the new terms to use with immediate effect.

user retention

This metric shows how long your page is active or running in the foreground. This lets you know when the user views your website or mobile app directly.

churn probability

Churn probability predicts the likelihood that a user who was recently active on your website or app in the last 7 days will not be active in the next 7 days. For example, you can focus on users who can grow your business. A likely opportunity for Google to monetize this audience via Google Ads or a retargeting campaign.

life cycle

Lifecycle is a new reporting section in GA4. It allows you to better understand the customer journey. To do this, it provides reports on user acquisition, engagement, monetization, and retention.


Thanks to Debugview, you no longer have to wait hours for the data to arrive in the standard reports. With DebugView, you can easily debug new implementation changes in the report interface without waiting for data in reports to be processed.

With DebugView you can keep an eye on the events coming from a device or a browser that you have set up debugging for. This is handy for seeing how GA4 is receiving your configurations. DebugView thus allows you to monitor your events, as well as the custom parameters and user properties you have defined, in real time.

User Lifetime

“User Lifetime” allows you to analyze the behavior of users during the period they were customers of your website or application. This is useful, for example, to show potential users in your active campaigns. Note that two methods are used to identify users and generate reports: by user ID, then by device, or by device only.

Automatically collected events

With GA4, developers no longer need to implement tags to track automatically captured events. These are already configured. These include: page views, first visit, outbound link clicks, specific types of searches in the internal search engine, interaction with embedded YouTube videos compatible with the JavaScript API, or file downloads. “The event-based model is closer to actual user behavior,” says Maurice Largeron, Google Analytics trainer. “The collected interactions are natively based on their life cycle.”

Recommended events

If an interaction you want to track isn’t present in the automatically collected events, you can go through the recommended events. Here you will find attributes related to e-commerce, such as B. Add to cart, payment or delivery. For example, Google also offers events related to virtual currencies.

Custom Events

If your event is not listed in the automatically collected and recommended events, you can opt for the personalized events. Unlike recommended events, custom events require their own event names to be set up.


GA4 reports take the customer life cycle more into account. For example, it’s easier to identify the preferred channels you should position yourself on to get better results. Accordingly, Explorations, which replaces Analysis Hub, is a set of techniques that you can use to create custom reports. Equipped with a search engine for dimensions, statistics and events, it helps analysts to find cross-references to variables. For example, you can use it to create visualizations for cohorts, paths, funnels, or segments.

Measurement ID

The Metric ID, which replaces the Tracking ID, identifies the stream of data coming from your website or app. The measurement ID is displayed as G-XXXXXXX.


With the monetization report you can see the revenue generated by articles, ads and subscriptions on the website and in the application. “It is of primary interest for the revenues of mobile applications and those of websites that monetize their audience with advertising banners by advertisers,” develops Maurice Largeron.

purchase probability

AI allows the user to program GA4 to receive alerts when certain trends are spotted. Machine learning should help bring this data back. For example, help to better prepare your supplies. Predictive statistics include purchase probability. It automatically predicts the likelihood that your website or app users will buy something in the next seven days.

engagement rate

The engagement rate uses the indicator of engaged sessions. This includes sessions that lasted at least 10 seconds, recorded at least one conversion event, or counted at least two page or screen views.

The engagement rate is more accurate and fairer than the bounce rate. Remember that the bounce refers to a session that triggers only a single request at the analytics server level. The bounce rate counts a user who has viewed a page on a page for 20 minutes and left directly with a 100% bounce and a time on page of 0 seconds.

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