Intro
In this series we will review some of the key features of the latest iteration of Google Analytics, GA4, including changes to the interface, advanced analysis through Explorations, GA4’s Data Studio Integration, and to ecommerce reporting functionality.
In this introductory blog we begin by covering the fundamental differences between Universal Analytics and Google Analytics 4, and the impact this has on each of these modes of reporting in turn.
Data Streams
One benefit of GA4 over its predecessor Universal Analytics, ‘UA’, is the ability to report on multiple platforms in the same property. This means data from iOS and Android apps can sit alongside web data, and more, in your reports.
This is clearly demonstrated within the interface, where built-in reports are preconfigured to show data from all your connected data streams in the same place. GA4’s Advanced Analysis, or Exploration, mode similarly allows you to mix and match dimensions and metrics across all of your data streams when creating custom reports.
This also gives you the ability to connect all your data to Data Studio via a single source, and hence to see data from multiple platforms in the same widgets. With the built in ‘Platform’ dimension, you can easily display the platform split for any metric being recorded, and even add a filter to switch between platform views within your dashboard.
The Data Model
The reason this is now possible is due to a fundamental change to GA4’s underlying data model.
In UA, all web data points are categorised into one of four levels: Hit, Session, Product and User-level. Data from the different levels cannot be easily reported on in the same table, which in turn cannot be displayed alongside app data collected from Firebase, which has a different structure again.
In GA4 things are greatly simplified. All data is initially collected as Hit-level events, with the option to set up a User Id and User Properties at User-level, while Session and Product levels have been, or will be, deprecated.
With this change, user interaction becomes the primary focus and scope-mismatch becomes less of a concern, since all of your web data takes the same shape, which also – coincidentally – matches the underlying structure of your app data!
With regards to reporting, this means we have more flexibility over what we can display in the same table, exploration, or widget. For instance, we gain the ability to show pageviews alongside other, custom events in the same table, since in GA4 these are all classified as hit-level events.
Hit-Level Structure
The internal structure of Hit-level data has also been updated. UA distinguishes between different types of hits, such as pageviews, events and social hits. Each of these hit types functions quite differently and is reported on in different sections of the platform. For instance, event hits in UA come with Category, Action and Label dimensions, forming a three-tier hierarchy, while page hits can only be supplemented with custom dimensions and metrics.
GA4 tracks all web and app interactions as hit-level, named events associated with custom parameters. By moving away from Category, Action, Label, GA4 gives us the freedom to tailor our data collection to our own needs. Pageviews can of course still be captured but will be events named ‘pageviews’ as opposed to a separate pageview-type hit.
By setting these parameters as custom dimensions, we can use them to further slice our data, by dimensions specific to our business, in custom reports or in Data Studio.
Data Layer Structure
If you have already implemented Universal Analytics using a data layer and are looking to move over to GA4, there is no need to worry, as, with a couple of adjustments to GTM, it is possible to re-use the Universal Analytics data layer structure as-is in your GA4 set up. This is demonstrated most clearly below for an ecommerce data layer push, but standard events can also be set up this way, at least to begin with (you’ll probably want to make use of the new event parameter structure by redesigning this later on).
This means you do not need to completely reconfigure your data layer implementation in order to get started with GA4.
Summary
You should now have a good understanding of the differences between UA and GA4, the underlying changes responsible, and the additional functionality they unlock in the interface - and elsewhere - as a result.
If you are thinking of making the jump from UA to GA4, or have questions about anything else analytics-related, you can reach out to our team of experts at https://www.merkle.com/emea/contact.
For all blogs in our GA4 series, please see below:
1. Intro to GA4: Universal Analytics Versus GA4
2. Intro to GA4: Cross Data Stream Reporting
3. Intro to GA4: Advanced Analysis with Explorations
4. Intro to GA4: Data Studio Integration
5. Intro to GA4: Ecommerce in GA4
