Google Analytics 4: More Than Just Reporting

June 2021

Here comes another exciting and pragmatic edition of our GA4 series for all analytics aficionados. If you somehow missed the previous 2 updates (or at least 1), or just want a recap – please visit our blog here.

This week we will discuss:

  • How to explore our data in GA4 and learn more about our users
  • How to divide our users into groups and why is it so important
  • How to manage internal and developer traffic when there is just 1 view in GA4

We hope you’ll enjoy this 5 min read. We extracted the most important information just for you!

Not sure how to get started with exploring your GA4 data? Sign up for our newsletter to stay up to date, or

GA4 Newsletter Series #3: Explore your data and users on a deeper level, learn how to segment users into business-relevant groups, and improve data quality

 

Explore – Get a deeper understanding of users and their journeys

Exploration reports that help enable us to use advanced techniques that go beyond standard reports are now available under the Explore section (formerly Analysis Hub). We use Exploration in order to slice and dice our data more in depth and answer complex questions.

The Template gallery provides us with an abundance of predefined report templates ready for use, just waiting for our data. In addition, they can be further customized so that you do not have to start from scratch, significantly reducing the time to insight.

On the other hand, Exploration analysis enables us to create our very own specific reports with complete freedom and a multitude of functionalities. We can specify the date range, choose custom dimensions and metrics, segment our data, and visualize it in the form of tables, charts, scatterplots, and geo maps.

The Exploration Hub is an essential feature and the hub of custom analysis. One of the arguably most useful exploration templates, funnel analysis, is made available for free, whereas it was a premium GA360 feature in Universal Analytics. We highlight this feature, since GA4’s pre-built reports are less extensive than what we are used to in Universal Analytics. As an analyst, you can, therefore, expect to spend some time in this environment. Mastering it will give your organization a competitive edge.

Audiences – Segment users into business-relevant groups

An Audience is a set of users defined based on specific characteristics that are important for a business, e.g. cart abandoners, foreign language enthusiasts, sports and hiking lovers or video/computer gamers. Such segmentation allows for more meaningful analysis of user behavior and website performance.

As Google Analytics records new data, users automatically fall into previously defined audiences and their memberships are evaluated on an ongoing basis to ensure the users still meet the specified criteria. If the newest data no longer meets the criteria, corresponding users are removed from those audiences.

Importantly, thanks to integration of GA4 with Google Ads, audiences are available for retargeting in ad campaigns. Targeting of users based on their actual behavior – as recorded by GA4 – allows customization of ad creative and, consequently, improved campaign performance. Integration with other tools of the Google Marketing Platform, e.g. Optimize and Display & Video 360, can be expected as GA4 matures.

More information on how to create, edit, and archive audiences is available here.

Predictive audiences are by far the most interesting update to audiences in GA. With at least one condition based on a predictive metric, we can configure a set of conditions that a user has to fulfil before becoming a part of an audience. Predictive metrics are based on machine learning predictions in order to predict the future behavior of our users based on the past data. Predictive audiences are automatically shared with any Google Ads accounts that the property is linked to. This brand new feature was not available in UA, i.e it was introduced as a part of GA4. It is further proof that GA4 was built with machine learning functionalities at its core that help you activate your data like never before.

Have a look at some of the out-of-the-box audiences, available in GA4 properties collecting ecommerce data:

Purchase prediction

The audience named ‘7-day purchasers’ will include users who are likely to make a purchase in the next 7 days.

Churn prediction

The audience named ‘7-day churning users’ will include active users who are not likely to visit the property/website in the next 7 days.

Revenue prediction

The audience named ‘28-day top spenders’ will include users who are predicted to generate the most revenue in the next 28 days.

To learn more about predictive audiences and which prerequisites have to be fulfilled in order to successfully train machine learning models visit the following link.

Data Filters – Improve data quality

Filters can include or exclude event data based on event-parameter values. They are configured at the property level and applied to all incoming data. As such, data filters are irreversible, i.e. once applied the effect on the data is permanent.

Universal Analytics has a concept of views whereas Google Analytics 4 does not. Thus, we cannot create Raw, Test, and All website data views – this makes using filters in GA4 much more important in comparison to its predecessor.

Currently, in GA4 there are 2 types of data filters: internal traffic and developer traffic. We want neither internal nor developer traffic to skew our reporting data; hence we have to configure corresponding filters properly and discard the unwanted information.

Google Analytics 4 GUI offers a straightforward and much more intuitive way to do so in comparison to UA, within just a few clicks.

Internal traffic is any traffic from an IP address or range of IP addresses we want to specify. If our IP address rule matches, the incoming event data can be assigned traffic_type parameter value set to internal.

Developer traffic, in general, is generated while debugging various implementations on the website – such as implementation of GA4, marketing pixels, etc. GA4 automatically recognizes such traffic when the developer is working in Google Tag Manager preview mode, or using a Chrome GA4 debugging extension.

We can choose to either include or exclude data coming through these filters but it makes much more sense for the latter (since we have just 1 “view” in GA4).

More information on data filters can be found here.

Closing thoughts

GA4 has much more to offer than just standard reports. In order to better understand our visitors and reach them with the relevant marketing message, we need to be able to explore user behavioral data (Exploration module) and segment the visitors (Audiences) while keeping the data clean from internal or developer traffic (Data Filters). GA4 allows all these out of the box and free of charge.

Please let us know if you are interested in discussing how GA4 would benefit your organization. We are available at florian@iihnordic.com and gunnar@iihnordic.com. Talk to you soon!

iihnordic.com   |   iih@iihnordic.com   |   +45 70 20 29 19

Gunnar Griese

Gunnar Griese

Analytics Specialist, IIH Nordic
Adam Konstantinovic

Adam Konstantinovic

Analytics Professional, IIH Nordic