Attribution in ad platforms
Each ad platform measures and attributes conversions within its own boundary: its own conversion windows, its own default model, and counts it reports for itself. Because platforms attribute independently and cannot see each other's touchpoints, their self-reported conversions overlap — the same sale can be claimed by several platforms. This page describes that data-model posture without ranking any platform.
What this means
An ad platform attributes conversions from the inside. It defines its own conversion windows (how long after a click or view a conversion can still count), applies its own default attribution model, and reports the conversions it believes it drove. Those are self-reported counts produced within that platform's data boundary.
Because a platform can only see interactions that happened on its own surface, it has no visibility into the touchpoints a user had on other platforms. So it credits itself for conversions where it played a part — even if other platforms also played a part.
Why the numbers overlap
The structural consequence is double counting across platforms. If a buyer interacted with two or more platforms before converting, each may count that single conversion as its own under its own window. Add the platforms' self-reported totals together and you can exceed the true number of conversions, sometimes substantially.
The remedy is not to trust any one platform's self-report as the whole truth, but to reconcile against a neutral, cross-channel source that sees the full path. This page is a data-model description: platforms differ in windows and defaults, but those differences are about how each counts, not about which is 'best' — a judgment this reference does not make.
- Each platform uses its own windows and default model
- Platforms cannot see each other's touchpoints
- Summed self-reports overstate true conversions
How it appears in analytics and logs
When platform-reported conversions exceed your actual total, it reflects independent self-attribution and overlapping windows — not extra sales — and needs reconciliation against a neutral source.
Diagnostic use case
Interpret platform-reported conversions knowing each uses its own windows and model and claims credit independently, so summing them overstates total conversions.
What WebmasterID can help detect
WebmasterID gives you a neutral, first-party baseline outside any single platform's boundary, which is what you need to reconcile competing self-reported conversion claims.
Common mistakes
- Summing platform self-reports as if they were unique conversions.
- Trusting one platform's count as the cross-channel truth.
- Ignoring differing conversion windows when comparing platforms.
Privacy and accuracy notes
Platform attribution operates inside each platform's data boundary. This page describes data models only and makes no ranking, pricing, or 'best platform' claims.
Related pages
- Walled-garden attribution and its self-reporting
Walled gardens are closed ad platforms that measure and report the conversions they claim credit for, inside their own systems. Each marks its own homework with its own window and rules, so summed across platforms the attributed conversions routinely exceed the real total — double-counting is structural, not accidental.
- Cross-channel attribution
Cross-channel attribution distributes conversion credit across all the channels a user touched — paid search, organic, social, email, referral, direct — rather than crediting only what one platform can observe. It is the antidote to siloed, self-reported platform counts: by viewing the whole path in one place, it can apportion credit coherently and reveal how channels actually work together.
- Self-reported attribution: asking 'how did you hear about us?'
Self-reported attribution asks the buyer directly — usually a 'how did you hear about us?' field — instead of inferring from tracking. It captures untrackable and dark-funnel influence that analytics miss, but it trades cookie blind spots for human memory bias. The two methods are complements, not rivals.
- Attribution analytics
A neutral baseline to reconcile platform self-reports.
Sources and verification notes
- Google Ads Help — Conversion windowsDocuments per-platform conversion windows and independent counting.
Last reviewed 2026-06-24. Facts are checked against primary/official sources where available; uncertain specifics are marked “Data not yet verified” rather than guessed.