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Software Strategy

Ad Attribution When Customers See Everything

Every platform claims the conversion. Why the totals never add up, what attribution models actually do, and the test that settles it.

Updated 2 min readBy SpiderHunts Technologies

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Quick answer — TL;DR

Attribution models allocate credit by rule, not by evidence. The only reliable way to know whether a channel caused conversions is to turn it off for a period or a region and observe what happens to total enquiries.

The short answer

If you add up what each platform claims, you will get more conversions than you had. Each is reporting what it touched, by its own rules, and none of them can see the others.

The only way to know what a channel actually caused is to vary it and watch total enquiries, not platform-reported conversions.

Why the numbers exceed reality

  • Each platform counts a conversion it was involved in
  • View-through counting credits impressions nobody clicked
  • Attribution windows differ, sometimes by weeks
  • Cross-device journeys get counted twice
  • Your own analytics uses different rules again

None of this is dishonest. Each platform is answering a narrower question than the one you are asking, which is what caused the enquiry.

What attribution models do

ModelCreditsBias
Last clickThe final touchFavours search and brand terms
First clickThe initial touchFavours awareness channels
LinearAll touches equallyTreats trivial and decisive alike
Time decayRecent touches moreFavours the end of the funnel
Data drivenModelled from your dataNeeds volume, still a model

All of these are allocation rules. None of them measures causation, and switching between them changes which channel looks best without changing what actually happened.

The test that settles it

Turn a channel off, or reduce it substantially, in a region or for a period, and watch total enquiries. If they fall, the channel was producing them. If they do not, it was claiming credit for demand that existed anyway.

  1. Pick a period long enough to cover your sales cycle.
  2. Change one thing, not several.
  3. Watch total enquiries from all sources, not the platform's number.
  4. Account for seasonality by comparing against a similar prior period.
  5. Accept that the answer may be uncomfortable.

Brand terms are the classic case

Ads on your own brand name frequently show excellent cost per conversion, because the people clicking were already looking for you specifically.

Whether those conversions are incremental is a separate question, and it is testable by pausing brand bidding and watching total enquiries. Some businesses find a real effect from competitors bidding on their name; others find they were paying for clicks they would have had free.

FAQ

Frequently asked questions

The questions readers ask us after this guide.

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Which attribution model is correct?

None of them measure causation. They allocate credit by rule. Use one consistently for comparison and test causation separately.

Why does our total exceed our actual leads?

Because each platform counts conversions it touched. Reconcile to your own internal count.

Should we bid on our own brand name?

Test it by pausing and watching total enquiries. The answer differs by business and depends on whether competitors bid on your name.

How long should an off test run?

Long enough to cover your sales cycle and to distinguish the effect from normal variation. For low-volume services that can be weeks.

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