Google Analytics 4's new explorations are a versatile solution to a problem that is becoming more difficult to tackle, that analysis is different for every business.
The explorations in GA4 gives you the creative freedom to construct and rebuild your analysis model depending on your needs. However, this open canvas of creativity opens a host of complexity, especially following on from Universal Analytics where we all got used to doing things one way.
Before we dive into the explorations and how we best use the tools, a key concept to understand is the difference between Universal Analytics (UA) and GA4’s data model.
You may already be very familiar with UA’s data model, but in case you aren’t, we’ve written an extensive blog post explaining the differences between Universal Analytics and GA4’s data model and how it affects your analysis reporting. For more information, you can find our blog here.
Once you’re familiar with the differences between UA and GA4’s data model and their differences, you’ll be ready to dive straight into how we report in GA4 using Explorations.
How to Report in GA4
There are a few key differences to take note of when comparing reporting styles between UA and GA4.
Doing analysis on UA relies primarily on the pre-defined reports configured on the interface. This was a welcomed design as it reduced the need for creating custom reports for day-to-day analysis.
Fast forward to a more digitally advanced time, tracking and reporting are becoming more complex as all clients have different configurations. This means that a one size fits most is no longer applicable.
This is where Google changes the reporting style in the GA4’s advanced analysis to be focused on creating customised reports that provide flexibility, while not taking away pre-defined reports already set up in GA4’s main interface.
At the time of writing this, there are seven analysis techniques available in GA4’s Exploration, these are:
Free Form: free form report technique is the most flexible and customisable. This means that most of your analysis can be done using this technique, which means that this analysis technique isn’t barred to one analysis strategy but can be manipulated to what you need. And as you may have seen in the interface, this visualisation is familiar to most of us, where we apply dimensions and metrics to create a table of data.
Cohort Exploration – cohort exploration analysis groups users that share a common characteristic and displays to you the behaviour of these groups over time.
Funnel Exploration – funnel exploration analysis shows you the steps users take to complete a task or journey and can show you the level drop-off at each stage in the funnel. This is usually most relevant for ecommerce checkout journeys but can also be applied to user engagement journeys and lead generation such as account registrations or event sign-ups.
Segment Overlap – segment overlap technique lets you compare up to 3 user segments to see how these segments overlap and relate to each other. This can help you isolate and create audiences. You can then create new segments based on your findings, which you can apply to other Analysis techniques and Google Analytics reports.
Path Exploration – path exploration analysis allows you to see users next steps after an initial interaction, a few examples can include finding the top pages users open after opening the home screen, identifying what actions users take after an app error, identify if users are stuck in a loop in the app by finding looping behaviours.
User lifetime – The user lifetime technique shows how your users behaved during their lifetime as a customer of your site or app.
User Explorer – the user explorer analysis technique is very handy for isolating users or groups of users to identify and analyse common data. Examples of a couple things you can do here is identify users who generate the most/least activity or revenue, or debug configuration
Knowing what you know now from reading this run through of GA4’s Explorations, have a wander around the platform yourself and see if you can re-create some of your favourite reports using your app and web data, or try playing around with the interface and see if you can create something new that might be of benefit to your team’s analysis.
If you or your business requires professional consultancy to make the most out of your new GA4 property, or if you don’t know where to start and would like some support getting the ball rolling, don’t hesitate to reach out to our Experience Analytics team for more information!
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