Attribution in Plain English: Why Google and Meta Both Take Credit for the Same Sale
You spend ten thousand dollars across Google and Meta. At the end of the month, Google says it drove 80 sales. Meta says it drove 70. You open Shopify and there are 100 orders in total. Add the two platforms together and they are claiming 150 sales out of 100. Someone is clearly lying.
Except no one is. Both platforms are telling the truth. They are just answering different questions, measuring different things, and quietly taking credit for the same customer. Once you understand why, you stop panicking at the mismatch and start making better decisions. This is one of the most expensive misunderstandings in paid media, and almost nobody explains it in plain English.
Every platform grades its own homework
The first thing to accept is that Meta and Google are not neutral referees. They are players in the game, and they keep their own score.
Meta uses what is politely called self-attribution. If a purchase falls inside Meta's window, Meta claims the whole thing, regardless of how many other channels touched that customer along the way (Measured). Google does the same inside its own world. So when a customer sees a Facebook ad, later Googles your brand name, then buys, both platforms raise their hand and say "that one was me." Neither is wrong by its own rules. They are simply both counting a sale that only happened once (Tailored Edge Marketing).
Meta counts sales from people who never clicked
Here is where the gap really opens up. Meta's default setting for website conversions is a 7-day click and 1-day view window (Meta). That "view" part matters more than most people realise. It means Meta can claim credit for a purchase that happens within a day of someone merely being shown your ad, with no click required at all (Tailored Edge Marketing).
Google Analytics has no way of seeing that impression. It cannot watch someone scroll past an ad. So if the person never clicks, GA4 hands that sale to whatever channel did produce a click, which is often branded search, email, or direct (Tailored Edge Marketing). One sale, two completely different stories, and both systems following their own logic perfectly.
The windows and the calendars don't line up
Even the clocks disagree. Meta removed its longer view windows in early 2026, so a one-day view is now the longest impression window it offers, with clicks tracked up to seven days (Meta). GA4, meanwhile, looks back up to 90 days by default (Google).
Picture a customer who clicks a Meta ad, thinks about it for three weeks, then buys after a branded search. That sale is outside every Meta window but comfortably inside GA4's. Meta reports nothing. GA4 reports a sale and gives the credit to search.
Then there is the date itself. Meta books a conversion on the day of the ad interaction, while GA4 books it on the day the purchase actually happened (Tailored Edge Marketing). Click on the 28th, buy on the 2nd, and the same order lands in two different months. This is why short date ranges look wildly off and longer ones settle down.
They also do the maths differently
When a sale falls inside its window, Meta counts all of it. Google Analytics, by contrast, now runs a data-driven model by default that splits the credit across the whole click path, so a single order might show up as 0.6 of a sale to paid social and 0.4 to email (Google). GA4 even retired its old rule-based models, like first click and linear, back in late 2023 (Google). So one platform takes the full mark and the other shares it around. Of course the totals never match.
Layer privacy on top of all this. Since Apple's iOS 14.5 update, both platforms fill the tracking gaps they can no longer see with statistical modelling (Tailored Edge Marketing). They are estimating different blind spots with different maths, so even the modelled portions were never going to reconcile.
What most people get wrong about it
The common instinct is to treat the mismatch as a bug and try to force the numbers to agree. That is the wrong goal. The gap is not a fault in your setup. It is a permanent property of two systems watching different slices of the same journey.
The more expensive mistake is trusting platform ROAS at face value and moving budget based on it. If you scale whatever reports the highest return, you tend to reward the channels that are best at claiming credit rather than the ones actually creating demand. Branded search looks incredible because it harvests intent that your social ads and your reputation created. Meta looks strong partly because it counts people who only glanced at an ad. This is textbook attribution bias, where the measurement quietly shapes the decision (Realize). It matters even more because Google and Meta are built for different jobs in the first place, one capturing existing demand and one creating it, so comparing their self-reported numbers head to head was never fair (upGrad).
And here is the part almost no dashboard will tell you: none of these numbers measure incrementality. Not one of them can tell you whether a sale would have happened anyway without the ad. For that you need holdout tests, or at the very least a blended view of the whole business (Tailored Edge Marketing).
The one number that can't take credit it didn't earn
So which report do you trust? The honest answer is none of them, on their own. Each is an instrument built for a specific job. Meta's report is the right tool for decisions inside Meta, like judging one creative or audience against another. GA4 is the right tool for questions about your channel mix. But neither should be your source of truth for how the business is actually doing.
That job belongs to your blended numbers. Total revenue divided by total ad spend does not care about windows, view-throughs, or which platform shouted loudest. It ignores the attribution theatre entirely, which is exactly what makes it the tiebreaker when the platforms disagree. Feed real outcomes back from your own systems, watch the blended picture, and let each platform report do the narrow job it is good at, rather than the big job it was never designed for.
Attribution stops costing you money the moment you stop asking the platforms to agree and start giving each number a defined role. The businesses that get this right are calmer, spend smarter, and stop lurching their budgets around every time a dashboard flinches. At Dadek Digital, this is one of the first things we untangle, rebuilding tracking so your marketing is measured against real revenue rather than platform illusion. That is the difference between scaling on reality and scaling on a number that was always grading its own homework.