An Introduction to Google Analytics 4

overview of google analytics 4 - introduction to google analytics 4

Google have recently announced the release of a brand new version of Google Analytics.

“…we’re creating a new, more intelligent Google Analytics … It has machine learning at its core to automatically surface helpful insights and gives you a complete understanding of your customers across devices and platforms. It’s privacy-centric by design, so you can rely on Analytics even as industry changes like restrictions on cookies and identifiers create gaps in your data. The new Google Analytics will give you the essential insights you need to be ready for what’s next.”

In this post, which I will undoubtedly end up updating regularly over the coming months, I explain the timeline of Google Analytics leading up to this release, the technical difference between Google Analytics 4 and Universal Analytics, and give an overview of some of the most interesting new features in Google Analytics 4.

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The History of Google Analytics

Google Analytics “Version 1”

In November 2005, Google acquired a web statistics analysis program called Urchin – they did not immediately make any changes to the underlying javascript file – urchin.js.

Google Analytics “Version 2″

In 2007 Google released the synchronous version of the traditional GA code – ga.js. This was tweaked in 2009 when Google introduced an Asynchronous version which they recommended to place just before the closing </head> tag (as opposed to before the closing </body> tag). This update resulted in faster loading time and more accurate data collection.

Google Analytics “Version 3”

In 2013 a new Universal Analytics code was introduced – analytics.js. This new tracking code offered a lot of useful new features like multi-channel funnels, custom dimensions, user-id tracking and real time reports.

Google Analytics 4

Back in July 2019, a beta version of a new type of Google Analytics property was released called “App + Web Properties”. This beta product has now been updated and renamed Google Analytics 4 – and in essence it is basically an attempt at unification of the best aspects of both Google Analytics for Firebase (Google’s mobile app analytics product) and Google Analytics Universal Analytics.

Google Analytics 4: Unification of Firebase and Universal Analytics

When attempting to unify both Firebase and Universal Analytics, the biggest stumbling block was always going to be the fact that both tools used different data models. Without getting into too much technical detail, Universal Analytics and it’s predecessors always used a hit-driven data model, whilst Firebase used an event-driven data model.

The traditional hit-driven data model used in Google Anlaytics was built on the notion of “hits” – which are broken down into pageview hits and event hits. The model focused on the idea of a Session which was a collection of pageview hits. The Pageview metric has always been the most important metric in Google Analytics and one from which other key metrics were calculated like bounce rate, time on site, pages per session, etc.

The event-driven data model that has been used in Google Analytics for Firebase for mobile apps is a totally different way of looking at user behaviour across mobile apps which aren’t necessarily just collections of pageviews. The notion of the “pageview” as the fundamental building block of sessions and other metrics is replaced with a more flexible system of “events”.

This event-driven model is the model that will be used in Google Analytics 4.

Events in Google Analytics 4 are quite different to Events in Universal Analytics. The old, restrictive Category, Action and Label fields will no longer exist and instead Events will have a name and up to 25 flexible custom parameters each.

What’s New in Google Analytics 4?

There are a lot of new features in Google Analytics 4 – some of which webmasters, marketers and analysts have been crying out for for years (There are also a lot of features missing that we have become used to – more on that later). I’m going to write separate blog posts on some of these where I will go into more detail, but here’s a quick overview of some of the main ones.

1. Enhanced Measurement (Codeless Event Tracking)

By default, when you implemented the old Universal Analytics code on your website, the only event that was automatically tracked was Pageviews and other Pageview related metrics. Now with Enhanced Measurement you can track lots of other interactions automatically that previously may have taken hours, if not days to implement via Google Tag Manager. These events include:

  • Scrolls
  • Outbound Link Clicks
  • Site Search
  • Video Engagement (for YouTube videos)
  • File Downloads

This is a massive benefit and will somewhat appease a common cohort of DIY Google Analytics installers who expect more from the tool than what it gives them without significant technical re-configuration.

Enhanced Measurement (Codeless Event Tracking) Google Analytics 4

2. New User Interface

Another issue that I’ve previously complained about in relation to Universal Analytics is the UI – over the years it’s had bits and bobs shoehorned into the existing UI as new tracking functionality was added, but it hasn’t really had an overhaul from the ground up. The result is a UI that has loads and loads of information available to the user, but in a very unorganised manner which is not intuitive.

Google Analytics 4 makes an attempt to tackle this issue with its new UI which re-organises all reports according to business life cycle, user data and events. There are still some drill down options in each of these sections but nowhere near as many as in the old Universal Analytics interface – instead, allowing you to customise the reports on the fly (in a manner that will be familiar to users of Google Data Studio, for example) with the “Customise Report” tool

New User Interface Google Analytics 4

3. New User Identification Methods

Another real pet peeve of my own when it comes to Universal Analytics is how “users” are identified. By default, in order to associate traffic with a particular user, Universal Analytics associates a unique identifier with each user and sends this with each hit. This identifier is usually a single, first-party cookie named _ga that stores a Google Analytics client ID. This will help distinguish the person as a “new user”. When the same user visits your site at a later time, they will be counted as a “returning user”.

This method of identifying users is inherently flawed — if a person clears their browser cookies, uses incognito mode in their browser, or if they use a different browser or different device for a subsequent visit to the site, they will appear as a ‘new’ individual user each time.

If you have a website where users can log in, you could also use the User ID feature which allows you to assign a persistent ID for that user regardless of the device or browser they are visiting from – the big caveat here is AS LONG AS THEY ARE SIGNED IN. Realistically, this is not a very common use case.

In Google Analytics 4, there is a new method of user identification which we hope will offer us better user tracking across devices and browsers. In the Default Reporting Identity tab in your Property Settings you can choose to identify users “By device only” or “By User-ID, Google signals, then device”. Essentially what this does is prioritises User ID if you have that set up and if you don’t, instead uses “Google Signals” – this means, as per Google:

“When enabled, Google Analytics will collect visitation information and associate it with Google information from accounts of signed-in users who have consented to this association for the purpose of ads personalization.”

How Google Signals sits in the context of GDPR and ePrivacy regulations, I’m not so sure just yet. So if you’re in Europe, this may not be for you.

4. New Funnel Reports

We know that in Universal Analytics we could create Goal Funnels with a specific Goal (e.g. a pageview or event) as an ending point and various other pageviews as funnel steps. These were limiting in a number of ways – for example the fact that they could not be applied retroactively and each step in the funnel needed to be a pageview.

Well in Google Analytics 4, the “Funnel Analysis” option in the “Analysis Hub” offers powerful new functionality that was previously only accessible to premium users of Google Analytics 360.

These will take some getting used to but are really really powerful analysis tools. A funnel can contain up to ten steps and each step may be one of a range of dimensions, metrics or events (so not just pageviews!), the funnels are applied to data retroactively (huge improvement), and funnels can be either “open” (user can enter on any step) or “closed” (user must enter on first step).

Funnel Reports Google Analytics 4

Additionally, you can choose between the traditional “Standard funnel” visualisation (above) or a new “Trended funnel” option to allow for better visualisation of data over time.

Trended Funnels Google Analytics 4

You also have the ability to show actual elapsed time between steps!

5. New Simpler, More Flexible Conversion Tracking Options

As we’ve mentioned already, Google Analytics 4 allows you to track a lot more events out of the box thanks to Enhanced Measurement. Not only that, but you can easily turn these events (or any others you create yourself) into Goals via the “Events” > “All Events” Section by simply clicking the toggle button beside the event.

Flexible Conversion Tracking Options Google Analytics 4

Not only is it much easier to create Goals this way versus Universal Analytics, you are also allowed up to 30 goals (vs 20 in Universal Analytics) and an even more welcome improvement is that these goals are applied retroactively AND when you toggle one Goal off, it frees up room for a new slot (which was not the case in UA).

6. Integration with BigQuery

Last but certainly not least, Google Analytics 4 offers absoolutely free integration with Google BigQuery (Google Cloud Platform’s advanced database solution) – meaning you can get access to your Google Analytics raw data without Google Analytics 360 (and the hefty price tag associated with it). For Google Analytics users that get a huge amount of traffic, this allows for advanced analysis of huge, unsampled data sets from Google Analytics – either in isolation or combined with data from other 3rd party applications. You can also use BigQuery to in turn expoert data to visualization platforms like Tableau and PowerBI.

BigQuery Integration Google Analytics 4

There’s a learning curve here and BigQuery is not something I’m yet comfortable with – but now that this integration is free, I’ll be investing some time into it in the coming weeks and months.

What Next? The Best Approach to Google Analytics 4

Obviously, all of these new features sound great. But it’s important to bear in mind that there are a lot of features that Universal Analytics has which, as of right now, Google Analytics 4 does not. Google Analytics 4 is a brand new platform, and as we’ve seen with new platforms from Google previously, it is likely to continue to be updated with new features and integrations over the coming months. Universal Analytics is still around and there has been no announcement of a deprecation data from Google.

With all this in mind, I would suggest that it is too soon to fully “migrate” to Google Analytics 4 – instead I would follow the advice of many Google Analytics experts and go with a “dual tagging” approach – I.e. continue with your current Universal Analytics implementation and reporting, and alongside this implement a Google Analytics 4 property on your website. This will allow you to refine your GA4 tracking in advance of fully switching over from Universal Analytics and will also ensure that you have some level of historic data in your Google Analytics 4 property by the time you make the switch.

Get in Touch

Do you need help implementing Google Analytics 4? Or do you have any feedback on this post? Feel free to contact me at or via the form below.

    SEO Consultant at Velocity Growth | + posts

    Darren is SEO Growth Lead at Velocity Growth. He is experienced in developing bespoke SEO roadmaps and implementing long term SEO strategies to build organic visibility, traffic and conversions for clients across a diverse range of industries.