Switching to Google Analytics 4 is now marketers’ priority

Grant Collins
By Grant Collins | 19 April 2022
Grant Collins

Grant Collins is digital experience director at Alpha Digital.  

The recent finalising around Google Analytics 4 would not have surprised observant marketers, after initial announcements were made back in March 2021. For those still utilising UA (Universal Analytics), the biggest message is now that in a little under 18 month’s time their current universal data won’t exist. Google plans to stop collecting UA data from the 1st July 2023 and then delete UA properties six months after that sunset. 

Which is exciting for us in the digital space, as the new solution (well relatively having debuted in Oct 20), introduces a new approach to privacy, increases customisation, data-driven attribution, along with even more advanced AI-based predictions. But what does the Universal Analytics sunset timeline mean for your business and how can you prepare for the switchover?

The time to act is now. Without switching organisations will not be able to run year on year data comparisons within all reports. While previously a major focus of preparation was centred around the incremental value GA4 could bring, it is now critical to decide if your business wishes to leverage Google’s web analytics tools for data-led decision making. While there are still features on the roadmap many of us would like to see live. We are counseling our clients to complete their customisations of the new GA4 reports now, to ensure they are sufficiently set up prior to May 31st 2022.

Preparation is key

One of the more obvious needs for the update was the requirement for flexibility around measuring a larger range of data types as the digital space has evolved. GA4 steps up to the plate here with customisation that allows marketers to include up to 125 custom dimensions, 400 audiences and 50 conversion types per property. 

This is important on a few levels – with great power comes great responsibility. A lot of the default UA reports now need to be ‘built’ within GA4’s analysis hub. Whilst the changes equate to considerably more customisation, the onus is now on the user to define and ‘explore’ their data in a way that meets their reporting needs.

Something to note is that GA4 operates with only two data scopes instead of four. This means that all information that used to fit within hits, sessions, users and e-commerce scopes, are now condensed to just user and event scopes. 

As a result, one key consideration for transition planning will be the introduction of strong naming conventions for existing parameters, as they will be added as ‘events’ and need to serve both as a concise measurement ID and logical description. 

Google has conveniently supported select events automatically, and many core metrics are collected in GA4 by default. These include: Language, Page location, Scrolls, Link clicks, and YouTube video views. The new model replaces the Event Category, Event Action, Event Label, and Event Value used in UA with 25 event parameters which can be configured and sent with each event.

The power in Advanced Predictive Audiences

Another major driver is the need to predict persona behaviour with a higher degree of accuracy. With the introduction of data-driven attribution and improved insight prediction (provided by Google Machine Learning), digital marketers will have the ability to leverage smarter insights such as potential ‘churn’ and identify the optimal re-engagement times for specific audience segments. The potential here is genuinely exciting.

These predictive audiences in GA4 put advanced AI at your fingertips, allowing organisations to go past predicting which users will churn, but also who are most likely to convert, as well as providing insights into lifetime value based on the data available in GA. These audiences can be fed into your other marketing efforts and often far-outperform broader retargeting audiences.

A potential drawback to observe here is that a lot of these insights will be coming from ‘modelled’ use, and this is data Google doesn’t share. A lot of ‘actual hard numbers’ seen in UA will be numbers ‘determined’ by Google AI and exactly how those numbers are determined is not provided. 

Update benefits marketers need to know

In the past, organisations required GA360, Google’s premium analytics service, to automatically export GA data into BigQuery. Now, BigQuery exports using the data transfer service are available to all GA4 properties, free and paid. 

BigQuery is Google’s cloud-based analytics software. This new feature opens up a new world of reporting, insights, and modeling capabilities to more organisations.

While the addition of new features to GA4 provides added value to the analytics service, key functionalities from Universal Analytics are already available in GA4:

  • Premium Version with Higher Hit Limits. The premium (paid) version of GA4 called “The New GA” can now be procured through GA resellers. There is also a new pricing model which will make the service more accessible for small to mid-sise organisations.

  • Display & Video 360 Integration (DV360). The DV360 integration also just went live in The New GA in February 2022. This allows for the creation of powerful (ML-driven) audiences for retargeting or lookalike audiences.

  • Google Optimise Integration. Companies can now gain greater value from Google Optimise with GA4. The key difference here is that experiments can be run using user-metrics instead of looking through the session scope of UA. For many CRO professionals, this is seen as a positive move towards more user-centric experience optimisation.

  • Data-Driven Attribution Modelling. Anyone familiar with GA360 will know the value brought by the data-driven attribution modelling reports. In Q1 2022, GA4 launched data-driven attribution, even for non-premium properties. Further to this, Data-Driven Attribution isn’t just available in a separate attribution report, you can use it in any of the key reports in the platform.

This is a big change to Last Click reporting, so marketers should be sure to start having this discussion with any stakeholders they are reporting site performance to.

  • Channel Groupings. A mainstay of the UA platforms is the ability to classify traffic from multiple sources into a clean, condensed set of channel groupings (e.g. Paid Search vs Organic Search vs Email). The ability to create and manage these channel groupings was implemented in Q4 2021, bringing a much-needed feature back to the platform.

  • Google Search Console Linking. For Search Engine Optimisation (SEO) professionals, the Search Console linking in UA was an easy and efficient way to see organic search terms and statistics quickly and easily from the one platform. In Q4 2021, this feature was added to GA4.

Impacting your business

After the July 2023 cut-off date, organisations can still access previously processed data in  their Universal Analytics property for at least six months.

However, it is strongly encouraged to export historical reports during this time as a failure to do so could result in the loss of significant historical data and valuable insights. 

So if you want to build up at least a year of historical data in GA4 before the hard cutover, then you have until May 31 this year to ensure your set up of GA4 is complete. Many users will find that some customisation is going to be necessary to retain all the insights they currently rely on. It will take time to transition an organisation without carrying over all technical debt to GA4, so I recommend that if you haven’t already started the process, it is best to start now. 


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