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.

Need help with your data platform?

We build intelligence platforms on BigQuery, Dataform and Google Cloud - from setup to ongoing optimisation.

How ready is your data?

Take our short assessment to find out where your data stack stands and what to prioritise next.


Suggested content

BigQuery Tips: When your query is technically correct but BigQuery won't run it

There is a particular kind of frustration that comes from staring at a query you know is correct and watching it fail. No syntax error. No logic problem. Just a wall. We hit two of them on the same project. What we were building The job was to migrate ga4_daily_snapshot for a large enterprise client from a BigQuery scheduled query into a proper Dataform pipeline. The scheduled query had been added to over time until it was too large to maintain with any confidence. Moving it to Dataform w

Katie Kaczmarek17 Aug 2026

BigQuery Tips: The subquery in your WHERE clause that's scanning your entire table

There is a pattern that appears in a lot of BigQuery pipelines and looks completely reasonable. You have a control table that stores the latest processed date. Rather than hardcoding a date into your query, you pull it dynamically: SELECT * FROM `project.dataset.events` WHERE event_date = ( SELECT latest FROM `project.dataset.control_table` ); The query returns the right results. The logic is clean. And if your events table is large and date-partitioned, you might be scanning the entire

Katie Kaczmarek13 Aug 2026

BigQuery Tips: Arrays in BigQuery - what they are and how to get data out of them

If you have ever opened a GA4 export in BigQuery for the first time and found yourself looking at a column called event_params that seemed to contain an entire table inside each row, this post is for you. Arrays are not trying to make your life harder. Once you understand why they exist and what to do with them, they stop being intimidating. Why BigQuery uses arrays GA4 tracks events. Each event can have many parameters. A purchase event might have a transaction ID, a value, a currency an

Katie Kaczmarek10 Aug 2026