Love it or hate it, Google Analytics 4 (GA4) is often the default data gathering tool for many businesses who want to understand more about who is using their website or app, and why shouldn't it be? While it's not perfect, it gives digital marketers an insight into their users, for free.
Is Your GA4 Data Accurate?
While the concept of capturing data about your users and using it to make marketing or business decisions seems simple enough, have you ever asked yourself the question of whether you can truely trust your GA4 data though?
Sure, you followed instructions like our on how to install GA4 and set up a data stream to collect data, so what could go wrong? Everyday you log in and check the stats to see users coming to your website, they must all be real people who've found your business? That's not always the case and we're going to take a look at what could potentailly cause you to have flse data in your GA4 account which could lead to bad choices.
What "bad data" Could Impact Your Business?
There are a few types of bad data that can impact your GA4 and knowing about them can help to improve your data quality.
Bot Spam
Before GA4, one of the biggest problems we saw with data gathering in Google Analytics was known as "bot spam" where unscrupulous users would send large amounts of fake data you a Google Analytics account using a tracking pixel.
This tracking pixel is called "Measurement Protocol" and is a legitimate GA feature, but it was easily misued as there was no validation of who was sending the data. Since GA4 this tracking pixel has been made more secure,now requiring a tracking ID generated by GA4.
UTM Tag Spam
If you're familiar with tracking marketing campaigns you'll also be familiar with UTM tags and using them on links (if you're not, read our article on creating UTM links). Unfortunately UTM links also send data directly to your GA4 account and can be created by anyone. This means that anyone can send any UTM data into your GA4 account and potentially affect the quality of your campaign data reporting.
Tracking Internal Traffic
There may be instances where you want to actively track use of your website or app in GA4 by employees, but more often than not the traffic data sent to GA4 by your staff can potentially impact important decisions.
A great example would be a short marketing campaign, it gets shared on social media and CRM with little response, but also internally where staff really engage with it. The data from your internal users could lead some people to believe the campaign was a good traffic driver and awareness builder, when in reality it was not.
How Can You Mitigate Poor Quality GA4 Data?
If you're concerned about poor quality data in your GA4 installation, there are a number of steps you can take to improve the accuracy of your data and we're going to run you through them.
Set Up GA4 Filters on Data Collected
Filters are set up at an account level and prevent any traffic matching your filter criteria from being recorded in the first place. This is great if you have defined sources of data that you don't want to record in GA4 such as internal traffic as you can block this using your office IP address, of course if you have staff working from home you'll need to add their IP addresses also.
Other use cases of using filters to block traffic in GA4 could include:
- Partners who drive traffic to your site
- Existing customers if they need to log in
Filters on a data stream are easy to add and our 90 Second Knowledge video and guide shows you how to add filters to a GA4 account.
Build Filters in Your GA4 Reports
Don't forget, that as you move through GA4, there are lots of options which can be used to filter and refine the data you see. While you can't filter by IP address at this stage, you can filter traffic in or out using many other metrics, so if you do have bad data, then you can probably filter it our here.
Create Multiple GA4 Profiles or Data Streams
Creating and implementing different instances of GA4 across different areas of your website is a great way to keep data separate.
A great example is for SaaS businesses where you have a website and a separate product, having separate GA4 accounts for each of these means that product user data is not confused with data form prospects on the website. Why does it matter? These are two very different user groups who will behave differently.
Be Alert For Bad Data
It's not possible to eliminate all types of bad data in GA4, UTM spam for example is easy to create and sent to a website to a platforms' GA4 account. However if your team are aware that it exists, they can be alert for the potential impacts on data quality and exclude it where they find it.
Better Data Means Better Decisions
While creating and implementing filters on your GA4 data may take time and effort, the potential to improve data quality could be vital for you business in terms of decision making.
In some cases it can only take a small amount of data to create a completely different view of what's happened, which could drastically change the choices you make for your business.
