“I hate GA4 and my clients don’t like it too”.
I’ve heard several variations of this statement ever since June 2023, and prospects are not getting brighter for Google Analytics 4 (GA4). This guide will not be a rant about how the GA4 UI sucks and why you should ditch it for another tool. Instead, we are going to talk about how the concept of data maturity changed after the introduction of GA4 and what to about it.
Data maturity is just a fancy way to describe the different stages a business goes throughout as its data stack becomes more sophisticated.
As you grow, your digital analytics must evolve to match your new requirements.
Data to value did a great job explaining what I call the digital maturity cycle, which I’m going to rephrase here with my own words:
Most of us started with Google Analytics because it checked all the boxes that are important for small businesses:
✅ It’s free: a small business can have ample data with minimal investment.
✅ It was easy to use: the interface was quite simple and in a few clicks you can find pretty much anything as long as you are tracking it.
These two points were the main selling points of Google Analytics, until GA4 took over.
Google Analytics is not really free anymore. To truly get value out of it, you need to take the data to a warehouse, among other actions.
Gone are the days when you used to get your data from Google Analytics. GA4 has too many flaws to work as a standalone tool, and if I dare to say, it was never intended to be one.
As you start investing in other channels (SEO, social media…), just looking at your GA4 data won’t tell you the whole story. You need data from other sources. That’s where a dashboard comes to play.
Done correctly, a dashboard can be more than an arrangement of pretty charts. Having one place where you can find all your data and compare performance across different channels is definitely an advantage.
Here is where most agencies and their clients’ data maturity comes to a halt. Investments are still minimal: at best, you will find a license or two for data connectors to plug Facebook data to a BI solution like Looker Studio, and that’s that.
At some point, just adding more tables and graphs to your dashboard stops being helpful. You need a place to store your data and get insights when you need them.
This is where a data warehouse comes in.
A data warehouse lets you do more than just store data. You can create your own models to understand what’s driving your results. Now, you’re getting into data engineering. At this point, having someone who just sets up tracking and charts isn’t enough to handle the new challenges.
By this time, you have a well oiled machine to generate insights. Only a handful of organizations can reach such heights of data maturity. You move from merely storing data to feeding it to your tools (Google Ads, Facebook Ads…).
In short, data activation is how you can customize your marketing channels at scale.
You might be wondering what all this talk about data maturity has to with your case?
Well, for better or worse, GA4 changed the model of data maturity. The number of business that started using a data warehouse (mainly Bigquery) saw a drastic increase.
GA4 made organizations jump up the maturity ladder to bypass the limitation of the UI.
This brings us back again to tools selection: If you stick to GA4, you will have to move a step-up into the data maturity ladder. The UI will simply waste your time. So you can either:
Either way, keep GA4 running and consider enabling the export to Bigquery (the cost vary depending on your traffic).
Everyone has his two cents on the topic. The issue of tool selection can be solved in my opinion by considering the following factors:
Below in my opinion some notable alternatives and how they compare according to the 3 criteria:
Piwik pro is just an overall robust analytics tool. It has all the features you find in Google Analytics and new ones where it stands out, like their consent management platform (CMP). You can become acquainted with the interface in very short time.
Lastly, Piwik pro is also compliant with regulation like GDPR which is definitely something to consider if you have client in EU or based in the region.
The only reason why Matomo doesn’t have a higher score is the issue of scale. It’s a great solution until you reach a certain point. Aside from this, it’s an overall decent solution that is compliant with major regulations.
I have to admit that I don’t use Adobe Analytics as much in my client work. There is a good reason for this: it has a high price tag. This will be a major deterrent for most businesses who don’t have thousands of dollars to spend on an analytics tool.
Another point in favor of Adobe Analytics is customization. There are very few tools that come close to Adobe’s ability to dig deeper into your data. The learning curve is one of the steepest among the tools, but you can get a lot out of it.
I tried to make this tutorial less about specific tools and more related to the stage where you are actually in. What you tool you will end up using will largely depend on your budget and if you like the interface.
My biggest tip is to ask for demos of each tool you are interested in. Spend sometime familiarizing yourself with the interface before making the decision.
Finally, I don’t recommend switching off GA4. Even if you don’t use it, just try to keep it running on the side. This is especially important if you are using Google Ads, for example.