Blended vs platform-reported attribution
Blended attribution takes total business results — say, all orders — and relates them to total spend across every channel, ignoring per-platform claims. Platform-reported attribution is what each ad platform credits itself using its own model and self-reporting. Because platforms can double-count and credit non-incremental conversions, summed platform numbers often exceed reality. This page contrasts the two views and where each is useful.
The double-counting problem
Each ad platform attributes conversions using its own model and only its own touches. When a journey involves several platforms, each can claim the same conversion, so adding up platform-reported conversions overstates the true total.
Platform attribution is still useful for in-platform optimization — it is the signal the platform's own bidding uses — but it cannot be summed across platforms as a measure of total performance.
- Each platform credits itself with its own model
- Summed platform conversions can exceed reality
- Useful for in-platform optimization, not totals
What blended adds
Blended attribution sidesteps the double-counting by working from totals: total conversions or revenue against total spend, computing a blended efficiency that cannot exceed actual results. It gives an honest ceiling and a portfolio view, at the cost of per-channel granularity.
The complete picture uses both: platform numbers for tactical optimization, blended numbers for the truthful aggregate, and experiments to allocate incremental credit. Neither is 'better' — they answer different questions.
How it appears in analytics and logs
When summed platform-reported conversions exceed total actual conversions, platforms are double-counting; the blended view caps the total at what truly happened.
Diagnostic use case
Sanity-check inflated platform-reported conversions against a blended, top-down view of total results versus total spend that no single platform can overstate.
What WebmasterID can help detect
WebmasterID's observed, de-duplicated conversion total is a neutral denominator for blended analysis, independent of any platform's self-reported credit.
Common mistakes
- Summing platform-reported conversions as if they were unique.
- Using blended numbers alone for per-channel decisions.
- Ignoring that platform credit is optimization signal, not truth.
Privacy and accuracy notes
Both views use aggregated totals, not individual tracking. Definitions of 'blended' vary by team; this is educational, not legal advice.
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.
- Duplicate conversion counting
Duplicate conversion counting happens when a single real conversion is recorded more than once — for example by both a browser pixel and a server event, by a tag firing twice, or by two platforms each claiming it. It silently inflates reported conversions and value, distorts ROAS, and misleads bidding unless deduplication via shared event IDs and clear ownership is in place.
- Reconciling media mix modeling and MTA
Media mix modeling (MMM) and multi-touch attribution (MTA) often disagree because they measure differently: MMM is top-down and aggregate, capturing offline and brand effects; MTA is bottom-up and user-path-based, granular but blind to unobservable touches. Reconciliation treats them as complementary lenses to be aligned, not rivals to be ranked. This page explains why they diverge and how teams triangulate between them.
- Attribution analytics
A de-duplicated conversion total for blended analysis.
Sources and verification notes
- Google Analytics Help — Attribution and attribution modelingExplains cross-channel attribution versus single-platform self-reported credit.
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.