From October 14th Google Analytics App + Web will graduate out of beta and will be renamed Google Analytics 4. It will also become the default property type when creating a new property. With this move, Google is firmly positioning the new product as the future of the tool across the entire web analytics sphere (websites and apps).
Why the name Google Analytics 4?
This is a good move in the sense that it positions the product as the 'new GA' rather than something that's exclusively for those with apps. But why Google Analytics 4? To understand this we need to look back at the history of Google Analytics.
A quick history of Google Analytics
The name might be a bit confusing if you're not familiar with the evolution of Google Analytics. Still, the logic is that initially there was Urchin (#1), which was the company bought by Google in 2005. Classic Analytics (#2) was the next iteration, which was then superseded by Universal Analytics (3#), which is what you likely use now on your website.
Why should you use Google Analytics 4?
With the launch of Google Analytics 4, Google pointed to three main areas about the product:
- "Machine learning at its core to automatically uncover insights" - the utility of existing features powered by machine learning has been questionable. Still, the new churn probability and likelihood to convert metrics (only available in Google Analytics 4) have the potential to be very powerful. It'll be interesting to see how Google develops the offering in time.
- "It will provide a stronger understanding of customer journeys across devices" there's no doubt that this is the case as it unifies data models across both Web and app properties.
- "Durable & future-proof" Google has said that looking ahead, it will work with or without cookies or identifiers so that you can learn about your customers even with gaps in your data. There is nothing on the face of it that solves this problem yet, so this is another area we'll be following keenly.
The most significant benefits in my eyes are the new event-level data model and the free link with Google BigQuery. Granular hit level data opens up a world of possibilities to do advanced analysis like custom attribution modelling, propensity analysis and forecasting. To do these, you need access to your data in its rawest form outside of the reporting UI, which is now quickly done (and free!) with the BigQuery connection.
Sam Dunkley, Senior Web Analyst
Should you switch to the new version now?
The advice up to this point has always been to consider running the new property type in parallel with your existing tracking. The case for this is now stronger than ever. Google is making it clear where their focus is, with recent releases almost solely focused on the Google Analytics 4 roadmap. The language used for this full launch is also telling ("the new Google Analytics", "the future of Google Analytics"). Moving forward if you want to take advantage of all the new features you’re going to have to have a Google Analytics 4 property.
The sooner you get set up the more historical data you'll have when this becomes your main Web analytics property and by getting familiar with the new paradigm for GA tracking you'll be ahead of the curve when it comes to making use of the powerful use cases and analysis opportunities.
Google Analytics Troubleshooter
Use our free resource to quickly know if there are any critical areas of concern with your Google Analytics set-up. If you think your Google Analytics set-up is not optimal or has errors, then use our free spot check tool to check to see if there any issues. The easy-to-use tool checks ten of the most commonly found problems with Google Analytics set-ups. Once you have access, set the account you would like to be tested - you'll get the results instantly
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