The migration deadline has passed, the dust has settled, and yet, I am still seeing the wreckage.
Most e-commerce managers treated the switch to Google Analytics 4 (GA4) like a software update on their iPhone. They clicked a button, maybe installed a generic plugin, and assumed the job was done. They trusted the “automatic migration” tools provided by Google.
That was a mistake.
If you are looking at your dashboard today and thinking, “My traffic looks fine,” you are likely looking at a mirage. The automatic migration tools did not replicate your custom Universal Analytics setup. They guessed. And in my experience auditing accounts for Digital Mully, they usually guessed wrong.
The reality is that GA4 is not an upgrade; it is a completely different operating system. Treating it like the old version is not just bad Digital Strategy, it is a liability.
Bad Data Equals Burnt Cash
Why does this matter? Because you are making financial decisions based on this data.
I recently audited a Magento-based e-commerce store that was preparing for peak season. Their Marketing Director was confident because GA4 showed a steady conversion rate. However, when I cross-referenced the GA4 data with their backend sales database, the numbers were off by 35%.
Thirty-five percent.
They were allocating ad spend to campaigns that were actually bleeding money, and they were cutting budget from campaigns that were driving high-value, unassigned traffic.
This is the cost of poor Data Integrity. When your event tracking is broken, you aren’t just losing visibility; you are actively mismanaging your ROI. You are bidding on the wrong keywords and optimizing for the wrong audiences.
Where the Migration Breaks Down
I don’t deal in “it looks about right.” I deal in forensic auditing. When I open up a client’s GA4 property, I go straight to the engine room. Here are the specific failure points I find most often in e-commerce migrations.
1. The Broken Data Layer
Universal Analytics could often scrape by with sloppy coding. GA4 cannot. It relies heavily on an event-driven data model.
Many migrations failed to update the Data Layer, the invisible layer of code that translates your website’s actions into language Google understands. If your Data Layer isn’t explicitly pushing view_item, add_to_cart, and purchase events with the correct parameters (like price, currency, and item_id), GA4 receives empty shells.
I use Google Tag Manager (GTM) to debug this live. I often see “purchase” events firing, but the value parameter is reading undefined because the variable name in the Data Layer changed during a site update and no one updated the tag.
2. Thresholding and Data Sampling
This is a silent killer for mid-sized e-commerce stores. GA4 applies “thresholding” to reports to prevent the identification of individual users. If you have Google Signals enabled (which most people do by default), Google will hide data rows if the user count is low.
You might think a campaign drove zero sales, but in reality, it drove five sales that Google simply isn’t showing you in the standard report.
I bypass this by setting up BigQuery exports. If you are serious about E-commerce Growth, you cannot rely on the standard GA4 interface alone. You need raw data ownership.
3. The Cross-Domain Tracking Nightmare
If you use a third-party checkout (like Shopify’s old checkout flow or a specific payment gateway redirect), you are at high risk here.
In the old days, we hacked together cross-domain tracking. In GA4, it is a configuration setting. But if it isn’t set up perfectly, a user who leaves your site to pay and comes back is counted as a new user.
The result? Your “Direct” traffic skyrockets, and your “Paid Search” attribution plummets. You think your ads are failing, but they are actually working, you just broke the tracking chain.
4. Session Continuity Issues
GA4 defines a “session” differently than Universal Analytics. This seems minor until you try to compare year-over-year data.
I use tools like Screaming Frog to ensure that UTM parameters are consistently applied across all internal links and redirects. If a redirect strips a GCLID or UTM parameter before the GA4 tag fires, that session attribution is lost forever. It falls into the “Unassigned” bucket, rendering your analysis useless.
Automation is the Enemy of Accuracy
There is a pervasive myth in our industry that Google’s tools are “set and forget.” Agencies love to sell this idea because it requires low effort.
I disagree fundamentally.
My philosophy is that automation creates mediocrity, but customization creates competitive advantage.
When I build a measurement strategy, I don’t use the default “Enhanced Measurement” settings and walk away. I turn half of them off because they track things that don’t matter to your bottom line. I build custom event listeners in GTM that are specific to your customer journey.
I am based here in Boise, Idaho, far from the echo chambers of Silicon Valley, and that gives me a different perspective. I value craftsmanship over speed. I don’t care what the “best practice” blog post says; I care what the HTTP request logs show me.
If you are running a generic GA4 setup, you are getting generic insights. And in a crowded market, generic is the fastest way to go out of business.
Conclusion
The transition to GA4 was not a checkbox exercise. It was a mandatory restructuring of your entire data intelligence apparatus.
If you are noticing discrepancies between your backend sales and your analytics reports, or if your “Unassigned” traffic channel is your biggest source of revenue, your migration was likely botched.
You need to fix this before you plan your next quarter’s budget. You need to stop guessing and start auditing.
Would you like me to perform a “Data Integrity Health Check” on your GA4 property to identify exactly where you are losing attribution?
