Google recently released a new version of the Analytics series, presenting it as the new default version of its well-known data collection and online traffic analysis program.
Most businesses are familiar with Google Analytics platform to track web traffic, evaluate digital marketing channels, and assess key performance indicators (KPIs).
And now, with Google Analytics 4, the company has released the latest version that differs significantly from the conventional “Universal” Analytics or UA.
The new Google Analytics 4 includes many significant features that distinguishes it from the previous edition. The latest data modeling function, which employs AI to fill in gaps in data where cookie-based rules restrict conventional Analytics, is one of the most notable distinctions.
Furthermore, the user interface for the new default Google Analytics is much different. So, here’s a rundown of some of the most significant distinctions.
Universal Analytics (UA) tracks only page views across your page/website by default. While it is possible to configure it to track additional interactions, it requires a more advanced understanding of event tracking and Google Tag Manager.
GA4, on the other hand, comes pre-configured to collect additional data. “Enhanced measurement” feature automatically gathers data on scrolling, outbound clicks, video engagement, file downloads, and other metrics.
Another significant distinction between GA4 and its predecessor UA, is the emphasis on merging mobile and web data; now, you can view, track, and manage it all from a single platform.
Previously, tracking mobile and app data relied on Firebase and GA integrations, and it was often difficult to comprehend how your web and app data worked together. GA4 is built on Firebase, enabling seamless app and web tracking.
GA4 has also improved the utility of “time” metrics. “When we think about time in GA right now, we just think about time for pages, sessions, or users.”
Time tracking can be a challenging task to use in Google Analytics if you want to answer queries about how long it takes for customers to do a particular task.
This is why GA4’s “elapsed time” tool can be great for you as it can check how long it takes for a user on average to finish specific steps or actions.
For example, you can observe how long it takes for a person to complete a survey or how much time a consumer spends reading your blog before moving on to your product page.
It’s no longer necessary to rely on web developers for all tracking needs. With GA4, you don’t need to consult a developer every time you need something tracked.
GA4 already tracks almost all important events for you between the automatically tracked events and enhanced measurement events. But Don’t worry if the events you wish to track aren’t on any of those lists. With GA4, you can create and track new events on your own.
The best part is that you can create up to 300 events per property.
Machine learning insights have been around for a while, but GA4 can now identify data trends such as rising demand for a product or service.
This technology can forecast outcomes like churn rates and the potential revenue a company could get from a specific customer category.
GA4 allows all users to access funnels previously only available to GA360 users. The new
funnel features are far more configurable, allowing you to create segmentable, retroactive funnels.
As Google states, “A GA360 feature introduced for free in GA4 gives you the ability to design user-based, configurable funnels.”
Debugging has long been an issue with the current edition of Google Analytics i.e Universal Analytics.
If you’re using the Google Tag Manager Chrome plugin, you can also import your data straight to see where the problem is in real-time.
These insights can predict what your customers will do in the future—allowing you to concentrate on higher-value customers.
GA4 makes it simple to export all of your data to BigQuery, which was previously only available with GA360.
The BigQuery integration allows you to import raw event data directly into a data warehouse, performing predictive analytics, machine learning models, and almost unlimited customizations.
It contains a new streaming export that updates every 10–15 minutes, substantially faster than the GA360 export.
You can also pick where you want your data to be stored to comply with your data governance guidelines. Google also made sure that the export works with BigQuery’s sandbox so that you can get started for free.
With the latest update, Google has rolled out some great additional features like:
This feature allows you to analyze effectiveness using several attribution models and assess how each model affects your marketing channels in order to identify which model is best for your company’s objectives.
Using this feature can help you figure out what percentage of your conversions & revenue has increased or decreased.
Have something more to add? Or did we miss anything? Let us know in the comments below.