User lifetime, Debugview, IA… The new version of Google Analytics that you won’t cut brings its share of new features.
Google Analytics got a makeover with GA4 and you will soon be forced to admire it: as a reminder, at the end of 2023, incoming data from Universal Analytics properties will no longer be processed at all. However, major changes are to be noted in the new version of the web analysis tool, including an increase in cross-device, events, AI or the possibility of creating new reports. In order to facilitate the handling of the tool, here are some of the new terms to be used from now on.
This metric shows how long your page is active or running in the foreground. This lets you know when the user is viewing your website or mobile app directly.
Churn probability predicts the likelihood that a user who was recently active in the last seven days on your site or app will not be active in the next seven days. This allows you to focus, for example, on users who can increase the growth of your business. A likely way for Google to monetize this audience through Google Ads or through a retargeting campaign.
Lifecycle is a new reporting section in GA4. It allows you to better understand the customer journey. For this, it offers reports on user acquisition, engagement, monetization and retention.
Thanks to Debugview, it is no longer necessary to wait long hours for the data to arrive in the standard reports. DebugView allows you to easily debug new implementation changes in the reporting interface, without having to wait for data to be processed in reports.
DebugView allows you to have an eye on the events coming from a device or a browser for which you have set up debugging. This is handy to see how GA4 receives your configurations. DebugView thus allows you to monitor your events in real time, as well as the custom parameters and user properties you have defined.
The “user lifetime” allows you to analyze the behavior of users during the period that they have been customers of your site or application. This is useful for displaying high-potential users in your active campaigns, for example. Note that two methods are used to identify users and create reports: with the User-ID, then by the device or with the device only.
Automatically collected events
If an interaction you’re interested in tracking doesn’t exist in the auto-collected events, you can go through the recommended events. This is where you will find attributes related to e-commerce, such as add to cart, payment or delivery. Google also offers events related to virtual currencies for example.
If your event is not mentioned 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 lifecycle more into account. For example, it is easier to see the preferential channels on which to position yourself to obtain better results. Reflecting this, “Explorations”, replacing Analysis Hub, is a set of techniques that allow you to create custom reports. Equipped with a search engine on dimensions, statistics and events, it helps analysts to cross-reference variables. With it, you can, for example, create visualizations for cohorts, paths, funnels or segments.
The Metric ID, which replaces the Tracking ID, identifies the data stream coming from your site or app. The measurement ID appears as G-XXXXXXX.
The monetization report allows you to see the revenue generated by articles, ads and subscriptions on the website and the application. “It is of primary interest to the income of mobile applications and those of websites that monetize their audiences with advertisers using advertising banners”, develops Maurice Largeron.
AI allows the user to program GA4 to receive alerts when certain trends are discovered. Machine learning should help bring this data back. Help, for example, to better prepare your stocks. Among the predictive statistics, there is the probability of purchase. It automatically predicts the likelihood that your site or app users will buy in the next seven days.
The engagement rate uses the indicator of sessions with engagement. These include sessions that lasted at least 10 seconds, recorded at least one conversion event, or counted at least two page or screen views.
Engagement rate is more accurate and fair than bounce rate. Remember that the bounce refers to a session that only triggers a single request at the analytics server level. With the bounce rate, a user who viewed a page on a site for 20 minutes and exited directly is counted with a 100% bounce and a time spent on the page of 0 seconds.