Google Analytics 4: What is it and how should we prepare for it?

Google Analytics 4, like Universal Analytics, is an analytics service that enables you to measure user traffic and engagements. Where GA4 differs from UA is that it can measure user journeys across both websites and apps, with UA only capturing website data. This cross-device tracking helps us to better understand the customer journey compared to UA.

Another change with GA4 is that all interactions will be classed as events, rather than session-based data found in UA. This aligns GA4 with Firebase, Google’s app development tool, where their analytics data are solely event-based. Gone are concepts like Pageviews and Sessions - now everything will be event based. Due to this change in emphasis, GA4 has reorganised reports to be based around the Customer Lifecycle, which allows users to drill down into specific aspects of the customer journey and analyse how they engage with sites across both devices and channels. Now users can see if a customer discovered a business from an ad on the web and later purchased on their app, for example.

As we move towards a world where cookies and other customer identifiers are phased out, Google Analytics 4 uses machine learning and artificial intelligence to alert users about important data trends via new insights and predictions, as well as helping to fill in any gaps in user data due to an increasingly cookie-less world. It can also help predict outcomes too, such as churn rate and potential revenue from certain customer segments. This helps drive more proactive, and reactive, decision making about future customer behaviour. Moving to GA4 also helps us, as a business, comply with evolving data privacy regulations, without having to rely on increasingly limited UA-based datasets in the long term. GA4 also comes with an Enhanced Measurement option which allows you to automatically capture certain events such as pageviews, scrolling, and site search.

However, there are several things that GA4 is unable to do, especially compared to UA. The first is around custom dimensions. In GA4, you can only have user and event-scoped custom dimensions. This means that any session-based or product-based custom dimensions that a client has in UA will not be replicable in GA4. There is also a lack of custom channel groupings and the ability to create your own groupings, meaning that clients only have the default groupings, which may not be as insightful. Looking under the bonnet of GA4, the process of excluding IP addresses is limited, linking other Google tools to GA4, such as Search Console, requires users to have high-level permissions for a range of Google tools beyond GA4, amongst others.

For our clients, we have taken two approaches to implement GA4:

Approach 1: GA4 implementation alongside UA (via GTM)

The first approach is to implement GA4 tracking alongside a client’s UA setup. The easiest way to do this is via Custom HTML tags within Google Tag Manager. Within the tags, you can refer to the existing UA implementation on site, and fire GA4-compliant implementation and tags to fire alongside UA, without having to completely reimplement a new data structure. We have taken this approach for several clients in the last few months.

Approach 2: Full GA4 dataLayer implementation (via front and back-end development)

The other approach, as briefly mentioned before, is to fully reimplemented a GA4-compliant data structure on site, known as a dataLayer. GA4 is very strict about how the dataLayer must be structured to send events, so one option, to ensure this structure is maintained, is to use development resource, rather than a tag management tool, to implement GA4. Whilst this approach has been less common for us, we have undertaken this approach for a client at the start of this year.

Having to undertake a GA4 implementation is also a good time to review existing tagging and dataLayer structures on a client site. If they decide to piggyback off the UA tracking, it is vital that their dataLayer setup is robust and complete so that you do not miss any GA4 tagging that is based on this. For one client, we even created a new tag management setup that coincided with the implementation of GA4 on their site. Clients will need to base these decisions on several resources, such as resource, development roadmaps, level of analytics usage, and quality of existing implementation, amongst others. Another thing to consider is if a client is a GA360 customer or not, as this could impact which option they take.

Deciding which option to choose is different for each business. With the deadline and sunsetting of UA fast approaching, there is less time available to undertake a full code-based implementation, so a tag management-based approach is a good option that takes relatively less time. However, this really depends on the quality of the existing implementation. Over the last year, as a team, VML Commerce data strategists have implemented GA4 using both approaches whilst encountering a range of existing implementation and dataLayer structures.

For details on our Analytics Health Check and Analytics Strategy Reviews for 2023, get in touch with our Analytics team.