Meta says it generated 50 sales this month. Google says it generated 30. Your own e commerce recorded 60 total sales. None of the three numbers is "wrong", each platform can only see the part of the customer journey that happened within its own ecosystem, and several of those 50 and 30 sales are, in reality, the same sale counted twice. Understanding why this happens avoids one of the most common (and least productive) arguments in any ad account: fighting over which platform "deserves" credit for each result.
Why every platform attributes the same sale to itself
Each platform measures conversions within an attribution window (for example, "click in the last 7 days or view in the last day") and only sees its own interactions. If someone saw an ad on Meta, then searched for the brand on Google and bought, it's entirely possible that Meta attributes that sale to its ad, and Google also attributes it to its search, both are being honest with the data they have, but neither sees the full picture. This is exactly the problem covered in the consumer journey in your campaigns: the real journey isn't linear, and no single platform can reconstruct it on its own.
Attribution models, straightforwardly
| Model | How it assigns credit | Risk |
|---|---|---|
| Last click | 100% of the credit to the last interaction before the purchase | Ignores everything that happened before (for example, the awareness ad that sparked the initial interest) |
| First click | 100% of the credit to the first interaction | Ignores what ultimately closed the sale |
| Data driven / multi touch | Splits credit across several interactions based on estimated weight | More accurate, but each platform calculates it using only its own data, it still can't see what happened on the others |
Why this got worse with privacy changes
The privacy restrictions of recent years (iOS tracking changes, the gradual disappearance of third party cookies) reduced the amount of signal platforms can see directly. The industry's response was to move toward sending conversion data from the business's own server, the Conversions API mentioned in conversion optimized websites , and toward first party data strategies (owned data: email, phone, purchase history) to recover some of the lost signal. Neither solves the underlying problem, that each platform still can't see the full ecosystem, but both improve the quality of what each one can measure on its own.
What to look at instead of fighting over who gets credit for each sale
The practical solution isn't finding the "perfect" attribution model, it's stopping the practice of adding up every platform's ROAS as if they didn't overlap, and looking instead at MER: total business revenue over total ad spend. MER doesn't need to reconstruct each customer's exact journey, because it compares the business's final result against total spend, it's the metric that doesn't depend on one platform "trusting" another.
Common mistakes
Adding up Meta's ROAS and Google's ROAS expecting it to match total revenue. They'll add up to more than actual revenue, because several sales are counted on both sides.
Pausing a channel because "it's not generating sales" by looking only at its own report. A channel with an apparently low ROAS may be generating the initial awareness that another channel ends up closing, turning it off can lower total sales even if its own number improves.
Ignoring first party data because you think "nothing can be measured anymore." Measurement changed, it didn't disappear, investing in collecting owned data (email, purchase history) is still a real lever.
Frequently Asked Questions
Why do Meta and Google report different results for the same period?
Because each platform only sees the interactions that happened within its own ecosystem, and both can claim credit for the same sale if the customer interacted with both before buying.
Which metric should I use to know how much I'm actually selling thanks to advertising?
MER (total business revenue over total ad spend), because it compares the final result against spend without depending on any platform reconstructing the customer's full journey.
Does the Conversions API solve the attribution problem?
It improves the quality of the data each platform receives, but it doesn't solve the underlying problem: each platform still only measures its own ecosystem, not the customer's full journey.
Conclusion
No advertising platform sees a customer's full journey, and fighting over which one "deserves" each sale is an argument with no correct answer. The useful question isn't which platform generated the sale, it's whether, overall, total ad spend is generating more revenue than it costs.
Are your platforms showing you numbers that don't add up with your actual revenue? Book a free audit with KLIV and let's sort out together which metric to look at for each decision. Book a call →