Why ad data gets harder to trust as spend grows

The short answer

Ad data gets harder to trust as spend grows because each platform counts sales its own way, and the gaps between them grow in money as the budget grows. Meta and Google use different default windows, both can credit the same sale, and both may fill in missing data with modeling. A gap of a few percent is noise at a small budget. At ten times the spend, the same percent is ten times the money, and that's enough to move budget on. So pick one number from your own payments to decide budget, and give one person the job of checking it each month.

The question

In late September 2026, someone on r/analytics wrote that once their marketing budget "got into the millions", reporting got harder, not easier. They had more dashboards and more people looking, "yet Google, Meta, analytics and the actual revenue numbers can still tell slightly different stories" (r/analytics thread).

Their worry was the size of the stakes: "when a few percentage points represent a serious amount of money it gets uncomfortable making budget decisions without knowing which signal deserves the most weight."

They asked how bigger teams decide which number becomes the source of truth. It's a question a lot of growing stores and their agencies run into.

Why the numbers drift apart

Start with how each platform counts. Meta's default attribution setting is "7-day click, 1-day view and 1-day engagement conversion" (Meta help: Results). In Google Ads, if you don't change the click-through conversion window, "the default window is 30 days" (Google Ads help: conversion windows).

So the two platforms look back over different stretches of time. Someone who clicks a Meta ad, comes back through a Google ad a few days later and pays can be counted by both. Your payments count that sale once.

Both platforms also estimate. Meta says that where results can't be measured directly, "statistical modeling may be used for some results" (Meta help: Results). Your analytics tool has its own rules again. None of this is wrong. Each tool answers its own question, and none of them checks with the others.

Small percentages, big decisions

One reply in the thread pushed back: the numbers "behave the same if it's big or if it's small", so measure errors in percentages. The poster agreed, then made the point that matters: "even a small measurement issue can influence a much bigger budget allocation".

That's the useful part. The percentage can stay the same while the money behind it grows. And a bigger budget usually means more campaigns and more channels, so more journeys touch two platforms that can each count the sale.

There's a second reason it compounds. Google says Smart Bidding strategies such as Target CPA and Target ROAS "will count and optimize conversions for any window you choose" (Google Ads help: conversion windows). The bidding follows whatever the platform counts. If that count drifts from your revenue, a bigger budget follows the drift too.

An illustrative example

Illustrative example. Made-up figures for one store at two budgets, not a benchmark.

At €10,000 a month of ad spend, Meta and Google together claim €53,000 in sales. Payments that cleared from visits tied to those ads come to €50,000. The platforms claim €3,000 more than came in, about 6%. Most people would call that noise.

A year later the store spends €100,000 a month. The same 6% overclaim now means the platforms claim €530,000 against €500,000 that cleared. That's €30,000 a month of sales nobody received. It's three times the store's whole budget at the start.

If that €30,000 sits mostly on one channel, its own report makes it look like the best place for the next budget increase. That's the decision the poster was worried about.

A check to run once a month

1. Pick the number that decides budget, and write it down. Revenue that cleared in your payment processor is the one nobody can argue with. Blended CAC built on it works too.

2. Name one person who owns the check. Not a dashboard, a person.

3. Each month, put total spend, each platform's claimed sales and the payments that cleared side by side, for the same date range.

4. Work out the gap in money as well as in percent. If the gap in money is bigger than the smallest budget move you'd make, it's no longer noise.

5. Write down which source wins when they disagree, so the same argument doesn't restart every month.

If you want a quick number for step 4, the platform vs payment gap calculator works it out from spend, claimed revenue and payments.

What the replies got right

We counted the replies on 27 October 2026. Of the 12 we could see from people other than the poster, five said the answer is one named person or team who owns the numbers. Three came with a product or consulting pitch, so we left those out here.

One reply summed up the problem with more tooling: "More data didn't give us more confidence it gave us more numbers to argue about."

Another said "every platform is grading its own homework", and that blended CAC and revenue after the spend matter more than "which dashboard claimed the conversion". The answer underneath it was shorter: "Revenue usually ends the argument pretty quickly."

They didn't ask for a better model. They asked for one number tied to the business and one person who owns it.

Where Thexly fits

Thexly covers the payments side of step 3. It matches each payment from your payment provider to the campaign visit that led to it, so you can see which campaigns brought in money that cleared. It doesn't change what Meta or Google report, and you still read spend from each platform.

What decides budget in your team today: a platform report, or the money that landed?