Ad platforms report numbers that are technically accurate and often practically misleading. Five checkable signs reveal when your ads data can't be trusted: blended conversion counts, stale exported reports, unverified "done" status on tracking changes, screenshot-transcribed numbers with no audit trail, and disagreeing systems with no owner for the gap. Every sign below can be checked in minutes against your own account.
Ad accounts rarely fail loudly. They fail by reporting numbers that are technically true and practically misleading, and the gap runs quietly until it costs something. These five signs show up across accounts of every size. Each one is checkable, and none of them require taking anyone's word for it.
If your "conversions" include both purchases and sign-ups, or new customers and returning ones, the headline number describes neither. On one account we worked on, reported conversions ran 6.5x above actual purchases because the platform was summing every tracked action into one figure. Everything downstream, cost per acquisition, return on spend, budget decisions, inherited the distortion. Ask what, exactly, your conversion number counts. If the answer takes more than one sentence, that is the sign.
A downloaded report describes the account at the moment of download. Campaigns get renamed, budgets move, products go out of stock, and the file does not know. If your reporting chain includes a step where someone exports a file and works from it for days, your decisions are running on a delay you cannot see. The question to ask: when your team reports a number, how old is the data underneath it?
Tracking fixes, campaign changes, feed updates: at some point somebody says it is done, and the account either agrees or it does not. We pulled one account where conversion goals had been marked complete on a checklist five days earlier; the account contained zero of them, and campaigns depending on them were already spending. Assigned and done are different claims. If nothing in your process checks the live system, you only find out which claim you had when the money is gone.
Somewhere in a lot of reporting chains, a person reads a number off a dashboard or a screenshot and retypes it into a slide. Every retyped number is a small bet that nobody transposed a digit, grabbed the wrong row, or cropped the date range out of frame, and there is no trail back to the source when the bet loses. The check is one question: for any number in your report, can someone show you the query that produced it? If the trail ends at a screenshot, that is the sign.
Your ad platform, your store, and your analytics will never fully agree, and they are not supposed to; they measure different things. The failure is when nobody can explain the gap. On one account, the ads platform claimed roughly 8,291 products while the actual catalog held 4,076 active ones, and decisions had been reasoning from the bigger number for months. A healthy setup assigns each system one job and can state, in a sentence, why the numbers differ. If your team cannot, the gap is running the account.
None of these require new software to detect. They require someone querying the actual systems and comparing answers, which is most of what an honest account evaluation is.
That is what the Akorn AI-Stack Evaluation does: a structured read of your ad account, product feed, tracking configuration, and analytics, cross-referenced against each other, with every finding traceable to a query you can see.
A structured read of your account, feed, tracking, and analytics — every finding traceable to a query you can see.
Get in touchMy agency sends detailed reports. Doesn't that cover this?
Detail is not verification. A report can be beautifully detailed and built on a conversions number that blends purchases with sign-ups. The check is whether anyone confirms the numbers against the live systems, not how thoroughly the numbers are formatted.
How would I check sign 1 myself?
In Google Ads, look at your conversion actions list and ask which ones feed the headline conversions column. If more than one action feeds it and they are not the same kind of event, your number is a blend.
Is this an AI thing?
The querying is AI-assisted because that makes it fast and repeatable. The discipline, deciding what each number should mean and holding every report to it, is human, and that part does not automate.