Google Analytics 4. The result is a platform that manages to satisfy each individual company’s needs to monitor its site’s progress. In the following lines, we will see what exactly Google Analytics is, what it does, and what has changed compared to previous versions.
What Is Google Analytics?
Google Analytics is free software capable of collecting and analyzing detailed statistics on website visitors and their actions. It is also data about traffic sources, devices, operating systems, and browsers. Google Analytics 4 was born as a replacement for Universal Analytics (the previous version of the software) and is based on the 2019 app-web beta version, which was intended to merge tracking data between the web and mobile apps, previously managed separately. It is a radical renewal compared to the previous versions, and starting from the name, (almost) everything changes. Google Analytics 4, therefore, changes its skin compared to its predecessor and today presents itself as a more complex tool to use, especially for users with little experience, but more reliable and “intelligent.”
How Has Google Analytics Changed? All The News
The idea behind this new tool is to provide users with the possibility of carrying out any web analytics in a personalized way, depending on your company’s model and business objectives. To do this, Google has revolutionized the logic underlying the structure of data and their management, has changed the graphical interface, and has chosen an approach strongly oriented towards machine learning. But let’s go in order.
You first notice a simplified interface compared to Universal Analytics upon logging in. But be careful. This simplification also derives from the fact that some reports present in the UA are no longer shown, making reading the data more complex and less immediate.
However, the most significant change is the transition from a model based on the concept of a session (hit) to one based on the event concept. If previously UA monitored user interactions with a site in a given period, Analytics 4 transforms each interaction into an event. Google Analytics allows you to analyze events by clicking a link, downloading a document, and playing a video. Google Analytics 4 events are divided into four types:
- The automatically collected events, events automatically organized by GA4, such as the start of the Session, the language, and the place from which the user connects to the network;
- Enhanced measurement events, measurement events that need to be configured and activated. They are essential for tracking key events and can be customized depending on the business model. Prominent examples include downloads, searches, page views, and scrolls ;
- I recommended events that must be activated and that Google recommends for a more accurate analysis. These include logins, shares, and purchases;
- Custom events are to be implemented but without predefined parameters and, therefore, entirely at the discretion of the web analyst.
We will come back to talk about it in more detail later.
Each user interaction is interpreted as an event involving different platforms and devices. As a result, the infamous Bounce Rate (bounce rate) is eliminated in favor of a new concept: the Engaged Session (involvement). The Bounce Rate indicates the percentage of sessions for a single page without interacting with the page itself. This parameter, in practice, showed how many users left it without performing any other action after opening a specific page. The Engaged Session, on the other hand, keeps track of all sessions with a duration greater than 10 seconds or with several pageviews of 2 or more pages.
This change allows for a more precise analysis since, as has often been said, the Bounce Rate was a misleading parameter: it is, in fact, possible that a user affects a visit to a page, finds what he was looking for, but still “bounces ” out of it (think of a news page which, once read, has no other possible interactions). On the other hand, the new model based on the Engaged Session is more flexible and provides a wide variety of helpful information to monitor the user experience on your site.
Recent restrictions on privacy and data processing have led to incredible difficulty in tracking data for AI (Artificial Intelligence). To overcome this problem, Google has implemented a machine-learning system to provide predictive insights (knowledge) on trends relating to web users.
Another eliminated parameter is that relating to the views, the Data Stream is introduced in its place. It allows you to manage data from multiple sources (web, app) and, thanks to data filters, allows for in-depth analysis of the latter.
Enhancements And Additions
Finally, the latest news concerns the enhancement of some tools and the integration with other software. Among the tools that have undergone an upgrade are the cross-domain monitoring tools for eCommerce and DebugView. However, Google ADS stands out among the software that has undergone an enhancement of integration. By linking the Google ADS account to Analytics, it is possible to monitor user behavior toward your advertising campaign.
How To Use Google Analytics 4
Once the news and the differences with the previous versions have been clarified, let’s now see, in practice, how to use Google Analytics 4. The first step is to create an Analytics property for each site you want to monitor in the Administration section. After clicking Create Property, you will be asked for the site name, time zone, currency, and URL information. Enter the requested data and confirm by selecting the Create item.
Once this is done, Google Analytics will automatically generate a tracking code which must be inserted in the header of each page of your site and which you can find in the Tracking code section shown in the figure. This operation allows you to connect Google Analytics to the site to be monitored and can be done in three ways:
- manually, through a trivial copy/paste of the snippet inside the <head> of each page (yes, exactly all, one by one);
- through Google Tag Manager, another exciting tool that will be the subject of future discussions;
- through a plugin if your site was created with a CMS.
In the Advanced Measurement section (Administration > Data Streams > Advanced Measurement), it is possible to measure user interactions through some easy options provided by GA4 without modifying the code. The events tracked by default include page views, scrolls, clicks out, and site searches, but they can be changed through the settings (gear symbol on the right). If the events you are interested in monitoring are not in any of the sections described above, Google Analytics allows you to create custom events.
Click on Events > Create Event to get started. First of all, the choice of the name you decide to give to the Event is essential: it is a good rule that the name is as identifying and unambiguous as possible to avoid confusion and be easily traceable. If you intend to monitor the files downloaded by users of your site, for example, the Event will take the name of Downloads or something very similar. Google also places a limit of 500 words for each GA4 property, so avoid going overboard with creating too many event names. You will then be asked to enter the parameters that govern your Event, i.e., what you want to monitor about your Event.
In the case of a login event, for example, it could be helpful to use the method as a parameter to receive information on which methods are used to log in to your site (e.g., via email, via Facebook, with username and password). Finally, you need to set up a trigger or, in other words, the action that generates the Event. To resume the previous login example, the Event is triggered when a user logs in with credentials to your site. Of course, manually entering all this information can be long and tedious, especially with many pages, sites, or properties to manage. The solution comes from a previously mentioned tool, which will be the subject of future discussions: Google Tag Manager.
Nowadays, in the marketing world, data analysis is becoming more and more critical, and analysis tools are becoming more and more complex and challenging to use but, at the same time, more precise and reliable. The advent of Google Analytics 4 is an example of this trend since it represents the future (at least near) in the web analytics field and lays the foundations for future analysis models.
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