Skip to main content

Google Analytics 4

Mark Rochefort14 October 20202 min read
Google Analytics 4

The new future version of Google Analytics has been announced - now branded as Google Analytics 4. Building on the "App + Web" property that was released last year, this sets the direction for Google Analytics going forwards. It is now the default experiences for all new properties and is where all product developments will be focussed.

Google Analytics 3, commonly known as Universal Analytics, was released in October 2012. This next product iteration for Google Analytics is a major step on from that - and has re-built the entire approach to implementation, reporting and analysis.

Bringing together insights across platforms and devices, at its heart are powerful machine-learning models, enabling predictions for things like churn rates and revenue. Such modelling will also be used to fill the gaps in data, caused by opt-outs and cookie blocks for example, in specific sets of data. Indeed, features such as "consent-mode" and "data deletion" directly address the need to provide a customer with greater control of their analytics data collection and management.

While Google Analytics 4 is a new version, the underlying paradigm  has actually been around a while - and it is something we are very familiar with. Both in the App + Web property released last year and, since before that, when it was powering the analytics within Firebase (Google's mobile application framework). So, if you have seen Firebase or App + Web, you are likely to recognise the direction this is headed.

This is where Google are investing any future product improvements. Game changing features such as BigQuery export (something that was previously a Google Analytics 360 - i.e. enterprise - feature only), e-commerce reporting, Data Studio connectors and much more are rolling out as we speak! Google Analytics 3 will not be developed much further - to gain from any of these new features you should be looking to make the switch to Google Analytics 4. At the moment, we suggest this is done in parallel to your existing setup so you can reasonably compare and contrast between the versions.

Speak to one of our experts to find out more about how we can help you with this transition.


Suggested content

Measurelab awarded Google Cloud Marketing Analytics Specialisation

At the start of the year, if you’d asked us whether Measurelab would be standing shoulder to shoulder with Europe’s biggest consultancies by September, we would've been surprised. Not because we don't believe in ourselves, but because these things feel so distant - until suddenly, they’re not. So, here it is: we’ve been awarded the Marketing Analytics Services Partner Specialisation in Google Cloud Partner Advantage. What’s the big deal? In Google’s own words (with the obligatory Zs): “Spec

Will Hayes11 Sept 2025

BigQuery AI.GENERATE tutorial: turn SQL queries into AI-powered insights

BigQuery just got a major upgrade, you can now plug directly into Vertex AI using the new AI.GENERATE function. Translation: your analytics data and generative AI are now best friends, and they’re hanging out right inside SQL. That opens up a whole world of new analysis options for GA4 data, but it also raises some questions: * How do you actually set it up? * What’s it good for (and when should you avoid it)? * Why would you batch the query? Let’s walk through it step by step. Step 1: H

Katie Kaczmarek3 Sept 2025

How to start forecasting in BigQuery with zero training

If you’d told me five years ago that I’d be forecasting product demand using a model trained on 100 billion time points… without writing a single line of ML code… I probably would’ve asked how many coffees you’d had that day ☕️ But its a brand new world. And it’s possible. Let me explain What is TimesFM? TimesFM is a new foundation model from Google, built specifically for time-series forecasting. Think of it like GPT for time, instead of predicting the next word in a sentence, it predicts t

Katie Kaczmarek14 Jul 2025