GA4 is Google's vision for the next generation of Google Analytics and represents a dramatic shift in how we record site interactions. The changes this new platform brings are many and varied. For example, the way GA4 tracks data, opportunities for advanced customisation and analysis, more robust cross-device tracking, and more make GA4 a significant upgrade on its predecessor.
We could spend a long time discussing every change the new platform brings, but the following five features are the most notable.
1. Events Focus
The most significant change in GA4 is the change to the measurement model. Unlike Universal Analytics (which relied on a session and pageview model), GA4 centres events at the core of its measurements.
Under GA4, every site interaction, from clicks to scrolls, is captured as events. This means you can track many more site interactions (such as downloads, video plays, external link clicks and site searches) with minimal to no customisation.
In those instances where you require customisation, your custom tracking is consistent with how GA4 tracks standard events, making it far easier to compare and manipulate tracked data, no matter the source.
2. App and website tracking combined
Before Google Analytics 4, tracking website and app data with Google's Analytics products meant dealing with two different analytics platforms (Universal Analytics and Analytics for Firebase), each with its own metrics and reports. If you are a business running both a website and an app, this system made understanding each property's role in your customers' journeys significantly more challenging.
With GA4, this is no longer an issue thanks to how it combines website and app analytics in one. With a single analytics platform responsible for both website and app data, businesses obtain a more comprehensive view of user behaviour, as movement between app and website can be tracked as part of one seamless journey.
Combined with cross-device tracking, GA4 provides a truly end-to-end view of the customer journey, providing invaluable data for businesses seeking to optimise their marketing strategies and enhance their online platforms.
If you're looking for help with your Analytics and optimisation, we offer a GA4 set up and management service.
3. Cross-device tracking
A significant limitation of the Universal Analytics model was its difficulty tracking the same user across multiple devices. For example, users who visited your site on their desktop computer and later visited it on their mobile phone were frequently treated as two separate users with completely different journeys.
By incorporating features such as User IDs and Google Signals, GA4 is better at connecting user journeys when they span multiple devices. The User ID feature lets you associate your own identifiers (such as account logins) with a single user so you can connect their journeys on different platforms. On the other hand, Google Signals uses data from people signed into Google accounts to identify them regardless of platform.
This information is invaluable in understanding your users' multi-device journeys and evaluating the actual value of your digital traffic acquisition channels.
For example, a business may see that a customer began their journey by reviewing product information on their mobile phone, but waited until they were on their desktop computer before making the purchase. With this information, the business can adjust its marketing spend or optimise cross-device journeys accordingly.
In this example, we could respond to this observation by changing ad creative so that mobile ad content focuses more on consumer education and desktop ads take more of a direct response approach. And thanks to cross-device tracking, we have a complete picture when analysing the results of any change we make.
4. Simpler, more flexible reporting
Reporting in Universal Analytics has always been a mixed bag. While the platform provides many default reports, only a minority are worthy of frequent review by most users. Most reports serve better as forensic tools for exploring data. Unfortunately, those reports lack the flexibility advanced users demand, occasionally forcing them to turn to other data analysis tools such as BigQuery or Looker Studio (formerly Data Studio).
GA4 addresses this issue by reducing the number of default reports and focusing on the kind of reporting that has the most value for your average user, significantly improving the signal-to-noise ratio of the application.
But reducing the number of default reports does not mean decreased reporting capability. Instead, GA4 offers a variety of customisation features to its standard reporting, allowing you to tweak it to your needs. More importantly, GA4 introduces exploration reports, a free-form data analysis tool where you can build complex reports on the fly when you need to conduct investigative data analysis.
For example, let's say your current online marketing could be better targeted, and you suspect your analytics data holds the answers. One strategy would be to use the Explore tool to identify different combinations of visitor segments (e.g. age, device, time spent on site) that appear to have a high likelihood to convert, build audiences from those combinations and use historical data to verify the most valuable audience types.
5. AI-driven insights
GA4 puts the power of machine learning at website owners' fingertips.
As GA4 grows familiar with your site data, it becomes increasingly better at making predictions about that data and identifying outliers.
Say you run a website for which referral traffic from other websites suddenly starts converting much more readily than previously. GA4's machine learning will identify and alert you to the outlier.
In addition, GA4 not only alerts you to anomalies, but tries to provide rationales for why they happen. Using the example above, GA4 might identify that traffic from a specific website started converting more readily from traffic from other websites. By investigating further, you may discover that the site in question uses particularly compelling content to link to your website that you may want other referral partners to emulate.
Essentially, these insights ensure that those analytics users without the resources to devote to dedicated, on-going analysis don't miss out on the opportunities that website tracking provides.
The final benefit of GA4 integration with AI pertains to addressing holes in your data. With more and more users blocking cookies and using browser extensions to block tracking applications such as Google Analytics, website user data is becoming increasingly prone to gaps which can lead to misanalysis if not accounted for. Machine learning and predictive modelling come to the rescue here as GA4 applies its predictive models to fill those gaps above and maximise confidence in your data.