Has GA4 left you questioning everything you’ve ever known about web analytics? Or maybe you’re just one conflicting metric away from giving up entirely? Don’t worry, you’re not alone!
If you have relied on Google Analytics as the go-to source of performance insight for your store or website, you’re probably experiencing a certain amount of disruption and probably frustration as you grapple with its latest version, GA4.
If that’s not you and you’ve nailed your web analytics, you deserve a big high five!
But for most people, being forced to migrate away from Universal Analytics to GA4 hasn’t been a positive experience! Which is a shame, because GA4 on paper has so much promise.
We’re seeing lots of marketers, business owners and ecommerce managers who have lived and breathed Google Analytics as their mainstay of measurement tearing their hair out because GA4 is causing more issues than it’s solving.
So, in this blog I’ll explore:
What is GA4?
GA4 is the latest version of Google Analytics, the web analytics service. It’s a tool that allows website and app owners to understand more about their users’ interactions with a digital property and track key actions, such as purchases.
The previous version of Google Analytics, called Universal Analytics or UA for short, was superseded by GA4 on 1st July 2023.
Universal Analytics was introduced in 2012 and had been the mainstay of web analytics for 11 years, so naturally, this change has been a big upheaval for many marketers, ecommerce managers and analysts alike. Some were so upset they held funerals for UA!
What’s the difference between GA4 and Universal Analytics?
The core difference, and the main cause of lots of headaches, is that GA4 runs on a different data model to UA.
GA4 is based on an event model, whereas UA was based on a page view model. Let’s unpack that a bit.
GA4 tracks individual user events. A user’s visit to a website or app will contain several different events. Some of those events might be ‘scroll’, ‘click’ or ‘video_start’ for example. As their journey continues they may also trigger ‘purchase’ or ‘form_submit’ events when they complete an action.
In contrast, the data model in UA was based on sessions and pageviews. A user session usually had multiple events within it, including page views, clicks and purchases. All bundled together, these events could be tracked separately with some custom tracking codes, but for the typical user, it wasn’t possible to break down a user’s visit into individual events.
One of the key benefits of GA4 is that individual events can now be analysed rather than looking at a collection of events bundled together at session level. It means there’s now a more granular way of looking at user behaviour – but it also comes with the challenge of reimagining what success looks like on your website or app.
The other main difference that users have encountered in GA4 is the new interface. Users have reported it’s ‘slow’ and ’usability is poor’ among other things. There are several key features in UA that haven’t been replicated in GA4 reports, which is frustrating users. For instance, if you’re used to easily selecting a segment or dimension to query, it’s now much harder to do this in GA4. In explorations, you have to import the dimension and metrics before building the report.
Lastly, one tiny but important feature that lots of people used was annotations – gone in GA4!
What are GA4 events?
Events are the central mechanism of GA4’s capability to track user behaviour on a website or app. There are 3 main categories of events in GA4.
- Automatically collected events
They can be used to track almost any kind of activity within an app or a website and are part of the default set up when you create a GA4 property.
Automatically collected events in GA4 include interaction events such as ‘click’ and ‘scroll’ and transaction events such as ‘purchase’ and ‘in_app_purchase’.
There are some automatically collected events that are suitable just for app properties, some just for web properties and others that are universal. The list of automatically collected events is available here.
- Recommended events
Recommended events are included in the GA4 configuration but they need additional information in order to be recorded.
In the example of an ecommerce store owner, you may wish to know when a shopper adds a product to cart, but collecting lots of ‘add_to_cart’ events wouldn’t be very useful without the breakdown of attributes such as product name, collection, variant, SKU and price. But all these individual attributes need to be added in the tracking code. The full list of these recommended events is here.
- Custom events
Custom events are just that, custom. Specific to your business, these are events that GA4 hasn’t seen before and aren’t included in the default set up. You can use custom events to track things that matter to your business.
For example, maybe as a charity, you want to track donations separately to purchases on your store – you can do that with a custom event. However, creating custom events requires some technical knowledge to implement.
Why is GA4 so hard?
Moving to a new platform or new software is always challenging – we’re human, we don’t like change! But the transition to GA4 is considered by many to be particularly difficult, and we’ve come up with 5 reasons why we think that could be.
- The new data model means rethinking your measurement plan
There’s no one-size-fits-all migration process from UA to GA4. The fundamental change to the measurement model in Google Analytics means it’s not possible to simply pick up the current configuration for tracking goals and measuring performance from UA and apply it to GA4. There’s a bit more thinking and planning that needs to happen.
Universal Analytics properties were due to stop processing data on 1st July 2023, but many still are. So if you’ve not started the migration to GA4, there’s still time. There’s also time to choose an alternative solution.
- You need a bit of technical skill to get tracking installed and events firing correctly
Sure, there’s the automatically tracked events being collected out of the box by GA4, but almost all the useful stuff to actually assess performance, especially in ecommerce, is either a recommended event or custom event. And that means you need some technical know-how to implement these correctly. Similarly with any sort of goal (conversion). These are set up differently in GA4 compared with UA.
- Comparing last year’s UA data with this year’s GA4 data is a no-go
The changes to the measurement model and the subsequent necessary changes to conversion measurement mean it’s unlikely that you’ll get an accurate picture of year-on-year performance changes by comparing UA data with GA4 data. You may be fairly safe comparing transactions and revenue, but users and sessions now have different definitions and can’t be compared. There’s the added difficulty that re-creating many of your go-to reports is much harder in GA4, if indeed, possible at all.
- Data sets can be really slow to process
We’ve heard reports that some data sets can take up to 72 hours to process in GA4! The documentation states the usual time frame is 24-48 hours, but we’re hearing that lots of people have a longer delay to get their final process data in their GA4 reports. Did you also know that the default duration for data retention in the platform is 2-months? You can manually change this setting, but the maximum is still relatively short at only 14 months. So there’s the added challenge of exporting your data to a data warehouse or similar if you want to preserve it.
- The black box of attribution means I can’t accurately assess marketing performance
Data-driven attribution is now the default model in GA4. This means that Google’s attribution model decides for you how much value to assign to each marketing channel that contributed to the purchase. And that’s a black box that you have no control over. So when you’re looking at your marketing analytics, GA4 has complete control over your attribution model.
Other attribution models that we know and love, like linear and position based appear to still be available within GA4 at present. However, according to the documentation, they were due to be archived in May 2023, so we expect them to disappear at any time.
What alternatives to GA4 are there?
As with any problem, there are usually several different ways to solve it. And it depends on your needs, which is best suited for your business.
Broadly speaking, there are two approaches to solving your GA4 challenges:
- Pay an expert or agency to configure GA4 for you and accept the limitations of the tool.
This may be a good option for you if you’re happy with GA4 as a tool, you can accept its limitations and challenges and you don’t want the ongoing cost commitment of an alternative platform.
- Choose an alternative tool that works with your business goals and delivers exactly what you need.
This is probably the option for you if you’re dissatisfied with GA4 as a tool – the reports, the interface, the attribution model. And you’re not alone in thinking that this could be the time to seek an alternative analytics tool.
Since Distil operates firmly in option 2, let’s explore some of the ways in which an alternative tool to GA4 could be the better option. Here we’ve got a couple of different strategic options for you.
How Distil can cure GA4 pains
- Get an attribution model you can trust, and customise if you want
Instead of a Black Box of unknown attribution, get an attribution model that does exactly what you want and assigns value exactly where you choose.
The default model in Distil is a 30-day linear model, which means every touchpoint in a customer’s journey receives an equal share of the value of the conversion.
There’s also the option for a customised attribution within our marketing analytics that does exactly what you need, specifically for your business. For example, a position-based attribution model assigns a specific percentage of the transaction to the first and last marketing touchpoints, and then divides the remaining value evenly between the other touchpoints in the middle of the journey.
- Build custom reports that answer your key business questions
Instead of being forced to use the default reports within GA4 or needing to build your own report through ‘explorations’ in the platform – Distil has an expansive set of ecommerce dashboards right out of the box. For instance, wouldn’t it be worth knowing if the visitors to your store end up purchasing?
- Get a handle on your campaign utm tracking parameters
As GA4 is now an event-based data model, whether you choose to migrate away from it or not, you will need to be much more organised with your campaign tracking parameters or UTMs.
UTM stands for Urchin Tracking Module (not important) – they are the parameters added to a URL when that URL is used in a campaign to track inbound activity. For example distil.ai?utm_source=newsletter&utm_medium=email. You can read more about UTMs here.
Without these, traffic in GA4 typically gets bundled into a category called ‘unassigned’. The official definition of unassigned traffic is “the value Analytics uses when there are no other channel rules that match the event data.” So if there are no UTMs linked with a user’s visit, their source will be defined as unassigned. This is no good for trying to optimise marketing performance or delve into which channels are working best for which outcomes – so UTMs are critical.
In Distil, our UTM manager keeps track of every UTM in play in your ecosystem. It’s the best visibility I’ve ever found to get an overview of all the UTMs in use.
- Make use of your Universal Analytics data before it disappears
Many Universal Analytics properties are still collecting data, despite the 1st July 2023 cut-off announced by Google. Instead of losing the value in years’ worth of engagement and transaction data, why not move it into a place where you can use it as a comparison against current performance. Using Distil’s data warehouse, tracking token and dashboards, you can preserve your UA data and use it to compare against current performance.
It’s one of the only ways you can use last year’s Christmas shopping season data as a basis for this year’s performance.
So, if you’re done with missing metrics, a challenging interface and reports that don’t work for you – maybe it’s time to break up with GA4.