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Free Interactive Tool

Do Your Platforms Claim More Than You Sold?

Add up what each ad platform reports, compare it against the orders in your store admin, and see the ratio. Nothing here is estimated from an industry average: it is your two figures divided.

Size your attribution gap

Your two numbers, divided. No industry averages involved.

Pick last month. Add up the conversions each platform reports for that period, across every platform you run.

The same dates, from your store admin. Use the same definition on both sides, usually a completed purchase.

Add this to see what an order actually cost you, against what the platform figures imply.

Every ad platform counts the same customer.

Meta claims the sale. So does Google. Add up what each platform reports and the total comfortably exceeds the orders in your store admin. No single platform is lying: each one genuinely touched that customer. The problem is that nobody deduplicates across them.

Enter both numbers to see your own ratio. Nothing here is estimated from an industry average.

Why the gap exists

Both figures are yours: this divides them and adds no benchmark and no assumption. It sizes the problem, not the payoff. The return comes from what you do next, moving budget toward the channels that genuinely convert, and that is a decision better information lets you make rather than one we can forecast for you.

Why The Numbers Disagree

Nobody is lying to you. Each platform is correctly reporting that it touched the customer. The gap opens because no one deduplicates across them.

By design

Each platform counts its own way

Google Ads credits a conversion to the time of the ad click, and says differences from other systems persist because platforms use different attribution models and lookback windows.

Google Ads Help (opens in a new tab)

Routinely

Platform and store figures disagree

Common enough that Adobe publishes a guide to diagnosing the discrepancy between the two.

Adobe Commerce (opens in a new tab)

How We Calculate

No black boxes, no benchmarks and no modelling. Four steps, and two of them are yours.

1

You supply both numbers

The conversions your ad platforms claimed last month, summed across every platform you run, and the orders your store actually recorded over the same dates. Use the same conversion definition on both sides, usually a completed purchase rather than an add to cart.

2

We divide them

That is the whole calculation. Claimed divided by actual is your over-report ratio, and claimed minus actual is the number of conversions nobody can match to something you shipped. There is no industry average anywhere in the arithmetic, no assumption about your channel mix, and nothing modelled on your behalf.

3

Add your spend to see the real cost per order

Optional, and it changes nothing else. Your spend divided by claimed conversions is the cost per order your platforms imply and optimise towards. Your spend divided by real orders is what an order actually cost. The distance between those two is where budget decisions go wrong.

4

Then you decide what to do about it

This is a measurement, not a forecast. What it gives you is the basis for moving budget toward the channels that genuinely convert, and for giving your ad platforms cleaner input to optimise against. That is where the return comes from, and it is your decision to make: we will not put a percentage on it, because any number we invented before seeing your data would be worth exactly nothing.

Sourced explanation

The causes are linked and checkable, the figures are yours

Measured, not estimated

Your two figures divided, with no benchmark applied

Checkable tonight

Verify it against your own store admin

Attribution Gap Questions

What this tool measures, what it refuses to, and how to check it yourself.

What exactly does this calculator work out?
The difference between what your ad platforms say they sold and what your store actually sold. You supply both numbers, we divide them. If your platforms collectively claim 150 conversions and your store recorded 85 orders, they are claiming 1.8 times your real sales, and 65 of those claimed conversions cannot be matched to anything you shipped.
Where do I find the two numbers?
Pick last month. In each ad platform, note the conversions it reports for that period and add them up across every platform you run. Then open your store admin and count the orders over the same dates. Use the same conversion definition on both sides, usually a purchase rather than an add to cart, and the comparison holds.
Is this an estimate?
No, and that is the point. There is no industry benchmark anywhere in the arithmetic and no assumption about your business. It is your two numbers divided, so the only thing that can make the answer wrong is the figures you put in.
My platforms claim fewer conversions than my store recorded. What does that mean?
Usually signal loss rather than accurate reporting. Cookie restrictions, iOS privacy changes and ad blockers stop platforms seeing conversions they genuinely influenced, so they under-count. It is the same measurement problem viewed from the other side: the platform numbers still do not describe your customer journeys, they just miss them instead of duplicating them.
Why does the gap exist at all?
Each platform reports independently, and none of them can see the others. A customer touched by three platforms is counted by all three. A customer who saw an ad without clicking is often counted anyway. Nobody removes conversions that would have happened regardless. None of this is a platform lying, and none of it is a fault in your setup: it is what happens when nobody deduplicates across the whole journey.
Does a big gap mean I am wasting that money?
Not wasting it, misreading it. A contested conversion is one whose true owner is unclear, not one that was worthless. The practical cost is that your cost per order looks lower than it is, so some channels look cheaper than they are and budget follows the wrong signal. Seeing the disagreement is what lets you move that budget deliberately.
Will better attribution actually improve my returns?
That is the point of it, and the mechanism is worth being precise about. Once you can see which channels genuinely convert rather than which one happened to be last, you can move budget toward the ones earning it, and your ad platforms get cleaner input to optimise against. The gain comes from that reallocation, which is a decision you make with better information. What we will not do is put a number on it: a projected percentage from a vendor who has never seen your data is worth nothing. Treat a guaranteed ROAS lift on a fixed timeline with suspicion, because passing more conversions back to the ad platforms makes the reported figure rise while actual sales stay flat, and that is usually what is being sold. The distinction worth holding onto is that forwarding conversions you actually made, deduplicated against real orders, gives the platform a truer signal to optimise on, while inventing conversions you did not make raises the reported figure and nothing else. The first is checkable against your own store admin, and the second is not.

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