Google Analytics UA vs GA4

GA4 vs Universal Analytics and How to Transition to GA4

Google Analytics remains the cornerstone of all web analytics — which is why any changes to it, no matter how small, prove to be extremely important to business owners, digital marketing experts, and countless other web-based professionals.
The latest change is anything but small, as Google rolls out the latest iteration of this platform: Google Analytics V4. Now, this is nothing new or shocking — GA4 has been around since 2020. However, this year, Google announced that GA4 will not only be the default option but the only available option — starting with July 1, 2023, Universal Analytics will be sunsetted and completely phased out.
With this in mind, let’s dive into the changes that GA4 brings to how you’re used to doing things — and what you need to do to prepare for this enormous change.

What is GA4?

Before we delve into the details, it’s worth going over the most basic question: just what is Google Analytics 4?
In the past, Google Analytics has gone through plenty of updates and a couple of paradigm shifts — the first one happened in 2006, after Google’s acquisition of Urchin and the subsequent redesign of Google Analytics. And the second one happened in late 2012 when classic Google Analytics was replaced by Universal Analytics as the default solution.
The service we call GA4 nowadays was first released as App + Web Property — aptly named because it allowed users to track Web and App website visits in a single property, rather than separating the visits into two separate GA properties.
In 2020, App + Web Property was rebranded as GA4 — Google Analytics 4. And from July 2023, it will be the only kind of Google Analytics available. The G3 (or Universal Analytics) will be discontinued.

The main differences between GA3 vs GA4

Before you upgrade to GA4, you’d do well to familiarize yourself with every major difference between Universal Analytics and GA4. We’ll delve into the most important ones in more detail below.

New Measuring Model

The most obvious difference between GA4 and Universal Analytics is in their measurement models. You’re probably used to the Universal Analytics model, which was based on pageviews and sessions.
A session was defined as a group of hits — user interactions — with a monitored website, within a specific timeframe. As a result, a session could have contained multiple eCommerce transactions, events, and pageviews.
Conversely, Google Analytics 4 resorts to a measurement model based on parameters and events. The main principle here is that all interactions can be observed and captured as events. So, something that would be considered a “hit” in Universal Analytics is an “event” in Google Analytics 4.
This may be a bit confusing, considering the fact that the previously used Universal Analytics had events with their own label, action, category — and hit type.
Fast forward to GA4, and you’re not dealing with labels, actions, and categories. Instead, each hit is considered an “event”, and it can contain (though not necessarily) certain parameters.
In GA4, for example, you can find an event named “page_view”. This event has different parameters, such as:
  • page_title
  • page_referrer
  • page_location
All GA4 events fall into one of these four categories:
  • Automatically Collected — events that are tracked automatically after installing the base Google Analytics 4 code. These are events like session_start, first_visit, and page_view.
  • Enhanced Measurement — these events are also collected automatically with the base code, but you can disable or enable them depending on the website functionalities you’re tracking. They include video engagement, outbound clicks, scrolls, etc.
  • Recommended Events — basically, the events that you should set up if you want to follow Google’s recommendations. They’re split up by industry type, but they’re basically broad recommendations and not really essential; except for eCommerce recommended events.
  • Custom Events — based on your website requirements, you can also create and implement your own events and parameters. Right now, you can create 500 different custom events, but this limit may be raised in the future.

No Monthly Hit Limits

With Universal Analytics, you had a free version that came with a limit of 10 million hits per month. Naturally, plenty of digital marketers and business owners found it difficult to stay under this limit and still collect all the necessary data for their websites.
Google has recognized this, which is why there’s no limit to interactions in the free version. There’s only a limit on the different events you can capture — which is currently 500. But that doesn’t limit you in terms of the volume of events.

Free BigQuery Connection

The third big difference between Universal Analytics and GA4 is the latter’s free BigQuery connection.
Before Google Analytics V4, this was only available to Google Analytics 360 users, and one of the biggest differences between the premium and free versions of Google Analytics.
This is a true gamechanger, considering BigQuery’s ability to query incredibly complex and large data sets at amazing speeds. Anyone who’s tried to work with complex segments in Google Analytics probably knows how much sampling can impact your data analysis abilities.
BigQuery solves the issue of sampling by simply taking the data out of Google Analytics and letting you easily interrogate it without running into sampling problems.

What does this mean for GA4?

As you can see, there are some major differences between the old Universal Analytics and the new Google Analytics 4. And before you make the final switch to GA4, it’s essential to understand all the differences fully.
Still, even though this will take plenty of getting used to, that’s no reason to despair. For many reasons, Google Analytics 4 represents the future. There are plenty of benefits to making the switch to GA4, but a lot of work required if your GA3 setup is highly customize.  Don’t spend too much time mourning the loss of Universal Analytics but do realize that there are definitely pro/cons and lots of work to do to get the parity on the reporting and tracking.

Benefits of Google Analytics 4 vs. Universal Analytics

Considering all of the above, we’ll get into the details on all the advantages of the new version of Google Analytics.

BigQuery Integration

We’ve already mentioned this as one of the biggest changes — but the benefit of a newly free integration with BigQuery just can’t be understated. With GA4, you can harness the full power of Google’s sprawling infrastructure and process SQL queries at insane speeds.
That means being able to analyze literally terabytes of data, and get vital insights from the platform’s machine learning algorithms. You won’t even have to run a load job, as you can stream data to BigQuery directly. Basically, you’ll be able to leverage every piece of raw data that comes your way.
And you won’t have to pay a dime for it — up to a point. While BigQuery is no longer exclusively free to GA360 users, GA4 will have free access, but with certain data limits and quotas. With the free tier, you can’t exactly query and store infinite amounts of data. Rather, you get free processing of up to a single terabyte of query data and free storage of up to 10GB.

Unsampled Data

As we’ve mentioned above, Universal Analytics had a 10-million monthly limit on hits per property — limiting the amount of data you could collect and process.
In GA4, sampling is removed from standards reports. You can now collect unlimited data. And if you want to base all of your business decisions on firmly reliable data, having access to unsampled data is fairly significant. Sure, sampling has its uses — but using sampled data means you also risk basing your decisions on incomplete information.

More Segmentation Possibilities

The importance of audience targeting can’t be overstated — which is why you can use GA4 to segment your audiences in more detail. For instance, GA4 allows you to make segments based on different events — which wasn’t an option available in Universal Analytics. Plus, seeing as GA4 has added time counting as a concept to events.
You can now identify your users based on actions they’ve performed on the website or app during a specific timeframe. By embedding time in your segments, you can analyze your users like never before — for instance, you can see the time they spend between each step as they go down your sales funnel.
Plus, all published audiences are shared with Google Ads automatically — meaning you can run a campaign to reach a precise audience you’ve tracked through GA4 more easily.

Engagement Metrics

One of the biggest changes that GA4 has brought us is the end of bounce rate tracking — instead, GA4 introduces a new metric simply called “user engagement”. This is the opposite of bounce rates because it’s a positive metric that describes user engagement. For now, sessions are “engaged” when they last for 10 seconds or more, involve more than one page view, or have a conversion event.
The new enhanced measurement events we’ve mentioned above also help you learn precisely how users interact with your website and its content. If you want to know precisely how much users are engaging with your eBook landing page or an individual blog post, the new metrics introduced by GA4 help you do just that.
This kind of in-depth tracking was possible in Universal Analytics as well, but only with a considerable degree of custom code.

Cross-platform tracking

Before GA, app and website engagement were tracked and measured separately — and dispensing with that was one of the best things GA4 has done. It’s no wonder it was called App + Web when it was in beta.
Today, GA4 combines Google Analytics data gathered from websites and Firebase Analytics data collected from apps in a single property. You won’t have to go through a tedious process to have a complete overview of user engagement across all platforms.

Life Cycle

One of the most interesting new features of the new version of Google Analytics is the Life Cycle section — containing reports on Monetization, Acquisition, Engagement, and Retention. As you’ve probably noticed, each report category addresses a specific part of the average customer journey.
Google Analytics V4 makes it easy to gain valuable insights into customer behavior as a digital marketer or business owner. You can see which aspects of your strategy need adjustments or more attention — for example, your engagement and acquisition reports can clearly show you which paid ads or awareness campaigns are working and which content your users perceive as the most valuable — and vice versa.
Naturally, all of that serves one end goal — increased revenue. And that’s what the retention and monetization reports are for. They show you revenue data that tells you whether you’re hitting your targets and doing your best to increase customer loyalty.
The event-based data model and the user-focused analytics of GA4 definitely help it create a more robust picture of the user’s journey. These days, people interact with websites from all kinds of devices and browsers — often interchangeably.
If a user visits your website on their smartphone for the first time and then proceeds to browse your products from their computer, before finally making a purchase through your application — GA4 will provide you with the tools necessary to stitch all of these events into a single, holistic customer journey.
This is a crucial benefit for digital marketers who operate in an increasingly multi-device world.

Less Reliance On Cookies

We’re witnessing a new Internet regulatory wave across the world — with governments and international regulatory bodies constantly working on increasingly strict online privacy laws. With that in mind, it’s clear that tracking user behavior via cookies is only going to get harder in the future; if not impossible.
That puts the global digital marketing community in a bind, seeing as we get most of our user data from cookies. However, with the release of GA4, Google has assured us that it will follow the latest shifts in the wider technology landscape.
The newest version of Google Analytics was created for a future that may or may not have cookies or the identifiers we’ve grown accustomed to. Instead, GA4 uses a more flexible method of measurement.
As the future of cookies becomes clearer and new legal frameworks unfold, GA4 will use modeling to fill any data gaps created by the removal of cookies. Ultimately, this means Google Analytics will remain a reliable tool regardless of the future of data privacy and Internet tracking.
Of course, you might be prone to taking this with a grain of salt, considering all of this is coming from Google itself — but when you consider the vast investments and strides Google has made in machine learning and AI, it’s not far-fetched to trust that they’ll be able to implement more intelligent, less cookie-reliant tracking methods in the not-so-distant future.

More GA360 Tools For Free

Previously, a bunch of tools for the creation of ad hoc funnels and advanced analysis were only available through GA360. However, many of these have now been made free and available to everyone in Google Analytics 4, such as:
  • Tools for setting up extremely specific tunnels with elaborate customization options;
  • Path analysis tools that help you quickly discern the paths most commonly taken by users — like going from reading a specific article to signing up for your newsletter;
  • Heat maps that completely overhaul your analysis;
  • Segment overlap reports that give you insights into the relationships between different segments that you’re targeting;
  • User explorer reports that give you more details at specific user segments that are most relevant to your website analysis.

Predictive Analysis Metrics

Imagine being able to actually predict which of your users are more likely to make a purchase within a month? Or how much revenue you can expect from these purchases? That would make it easier to spend resources and energy on nudging your most prospective leads towards converting and making the purchase.
And that’s why GA4 provides three predictive metrics that let you do exactly that:
  • Purchase probability — the likelihood of an active (in the previous 28 days) user buying something in the next 7 days.
  • Churn probability — the likelihood of a user that was active in the previous 7 days not being active in the next 7 days.
  • Revenue prediction — the expected revenue for the following 28 days, from a user who has shown activity in the previous 28 days.
These simple, but powerful metrics can be used to come up with predictive audiences for highly targeted campaigns. Also, they’re particularly useful for critical periods of conversion probability.

Higher ROI

Most of the benefits that come with transitioning to GA4 that we’ve mentioned above allow for better campaign planning. The more insightful reports give you access to better analytics and more precise targeting of the most relevant audiences — all in the most critical timeframes.
If you use all of these to your advantage, you’ll be able to create more successful marketing campaigns and hit your goals more precisely — ultimately resulting in far higher ROI on any digital ad spending.
However, as great as GA4 is — there are some things you’ll lose when transitioning from GA3 as well.

Google Analytics 4 — The Missing Features

Google Analytics 4 does provide an entirely new approach to website analytics. However, there are still plenty of crucial functions and features from Universal Analytics that are simply not present in GA4.
With that in mind, let’s take a look at some of the things you’ll have to do without in GA4 — at least for now. One of the biggest things you’ll find is the out of the box analytics are much weaker - yes with BigQuery and analysis using other tools you can easily replace the functionality but most organizations and small businesses may not have the expertise or tools to do so.

Behavior Flow

Universal Analytics had an incredibly useful Behavior Flow report. This report made it easy to visualize a user’s path from one Event — or page — to the next. When you needed some quick and easy-to-digest insights on user behavior, it was a godsend.
Unfortunately, it’s no longer present, starting with Google Analytics 4. It’s been replaced with two overly complicated reports — the path exploration and the funnel exploration reports. Of course, this may be simplified in the future, and the two new reports will likely be improved.
But, for now, plenty of users will probably feel frustrated and disappointed at the change.

Limited Custom Dimensions

Google Analytics 4 allows you to create your own custom dimensions to capture more advanced data. For instance, if you’re interested in how users are reading your blog posts, you can supplement the data you get from the event with custom dimensions like the blog post length or the author name.
However, you only get 50 custom dimensions — which likely makes the functionality irrelevant for most webmasters.

Limitations Of Machine Learning

We’ve already mentioned that Google Analytics 4 provides powerful ML insights, predicting stuff like the probability of specific users converting depending on their online behavior. However, there’s a flip side to this — it’s not a viable feature for small and medium-sized online businesses.
These predictive analytics require plenty of data — and as a result, they’re only available if you have a thousand returning visitors per week. For most smaller online enterprises, this kind of traffic is just impossible.
And even if you do reach it, there’s still another hurdle to overcome. Google states that, should the “model quality” for your GA4 property fall below the required threshold, GA might stop updating all corresponding predictions.
In other words, not fulfilling one ML requirement might make all other ML predictions unavailable — though the jury is still out on that one.

Configurable Views

Universal Analytics had customizable views as one of its major cornerstones — allowing you to create certain analytics environments for cleaning up and testing data, after filtering out unneeded internal traffic.
All in all, views were extremely practical when you needed to easily and quickly filter your data. Casual users and smaller businesses largely benefited from preset views with the precise information they needed, allowing for an ideal analytics setup for undemanding users.
This is another feature that was cut from GA4 — though not in perpetuity. According to Google, they plan on providing a similar functionality sometime in the future. However, there are no specific dates, and the current workarounds are clunky, annoying, and messy.

Bounce Rate

For many marketers and website managers, bounce rates were the most essential metric for gauging the performance of their website. And most of them were unpleasantly surprised to learn that there’s no such feature in GA4.
As we’ve mentioned above, Google is moving away from this negative metric and trying to roll in the same functionality into their new “Engagement Rate” metric; based on Google’s proprietary formula for establishing whether website visitors are sufficiently engaged by the content.

Insufficient Integration

Right now, the new version of Google Analytics isn’t playing nice with plenty of core tools for digital marketing — and it doesn’t accept data imports from third-party sources. This makes it harder to analyze ROAS and ROI for campaigns you’re mostly tracking in other tools.

Content Grouping

This is another feature that Google has decided to remove from GA4. However, this is one of the missing features that have workarounds; but not ones that are easy to implement, at least for casual users. If you want to continue using Content Grouping until a similar feature is introduced in GA4 natively, you’ll need to create your own custom event-scoped dimensions.

Annotations

Annotations were quite a useful feature in the old Universal Analytics — they were handy for marking the dates and times of site changes for future analysis and various other notes. However, Google has decided to remove this feature and there’s currently no workaround or alternative.

No Historical Data

The completely different approach to modeling that GA4 takes does add a bunch of new functionalities that simply didn’t exist in Universal Analytics. However, this is also a double-edged sword — because it means you won’t be able to import your historical data from UA to GA4.
Right now, the official workaround from Google is to simply keep running GA4 and UA concurrently, and just duplicate the appropriate events for the GA4 property. That means you’ll have to handle two implementations that run parallel to each other — but they’ll also provide you with slightly different functionalities.
Of course, that’s not the most streamlined solution, and it does add to the complexity of GA4.

How To Migrate to GA4

If you’re using Universal Analytics, it’s a good idea to start planning your transition to Google Analytics 4 as soon as possible. That way, you’ll have enough time for orderly migration, instead of a haphazard dash in the middle of 2023.
Here are a few things to do to prepare for a transition to GA4:
  1. Make an inventory of the measurements you’re using in Universal Analytics, and note the ones you want to keep tracking in GA4.
  1. Create a design reference for GA4 solutions, and think about how you can structure your new GA4 account to make it scalable with the growth of your business.
  1. Create data streams and properties in GA4. Remember, you can now analyze and collect multiple mobile app and web data streams as a part of a single GA property.
  1. Initiate the GA4 tracking code on your website via the Google Tag Manager.
  1. Set up your basic data collection.
    1. Start using enhanced measurement events such as scroll depth, page views, on-site search results, file downloads, and (if applicable) video engagement.
    2. Create a GA4 tag management plan, and deploy custom event tracking through the event tag in Google Tag Manager. Remember to ensure these map back to custom events from Universal Analytics that you want to track in GA4.
  1. Use Google BigQuery and raw event data from GA4 properties to avoid GA4 data limits.
  1. Connect BigQuery with your BI (Business Intelligence) tool of choice for further reporting and data visualization.
  1. Remember to export historical data from Universal Analytics in July 2023 to avoid losing access.

Wrapping Up

And while abandoning your current Universal Analytics property entirely is not something you should probably do just yet, it definitely pays to start working with GA4 right now. It comes with a multitude of new, useful features that will future-proof your digital analytics strategy.
Of course, at the end of the day, GA4 will only be as useful as the amount of data you provide it. And accumulating enough data for any truly substantial analysis takes a lot of time — which is why starting your migration from Universal Analytics to GA4 sooner is a good idea. The faster you start, the quicker you’ll be able to collect crucial data and become more comfortable with some of GA4's most essential changes.