Attribution Audit
- Read the main
ads contract and normalized account snapshots.
- Declare the business conversion, value, data window, timezone, currency, and
decision the attribution analysis must support.
- Inventory every browser, server, platform, analytics, MMP, offline, and app
attribution source with its identity, counting, deduplication, and privacy rules.
- Reconcile comparable events and explain differences caused by eligibility,
view-through rules, consent, modeled data, conversion lag, thresholds, or scope.
- Separate measurement quality from platform-reported performance.
- Return findings, contradictions, confidence, missing evidence, and a measurement
improvement plan through the common JSON contract.
Do not assume one platform is ground truth, add incompatible reports together, or
recommend an attribution model without the operator's decision context.
Comparability gate
Reject aggregation until the sources share, or are explicitly normalized to, the
same conversion event and value definition, attribution window, click/view scope,
counting method, deduplication identity, timezone, currency, attribution model,
and modeled-data treatment. Until then, report the values side by side with their
definitions; do not compute a total.
Example: Meta seven-day conversions and Google thirty-day conversions are
incompatible. Refuse to add them, reconcile windows and definitions first, and
only aggregate a newly comparable dataset.
1---2name: ads-attribution3description: Audit cross-platform attribution by reconciling conversion definitions, reporting windows, and data sources across browsers, servers, MMPs, and ad platforms.4---56# Attribution Audit781. Read the main `ads` contract and normalized account snapshots.92. Declare the business conversion, value, data window, timezone, currency, and10 decision the attribution analysis must support.113. Inventory every browser, server, platform, analytics, MMP, offline, and app12 attribution source with its identity, counting, deduplication, and privacy rules.134. Reconcile comparable events and explain differences caused by eligibility,14 view-through rules, consent, modeled data, conversion lag, thresholds, or scope.155. Separate measurement quality from platform-reported performance.166. Return findings, contradictions, confidence, missing evidence, and a measurement17 improvement plan through the common JSON contract.1819Do not assume one platform is ground truth, add incompatible reports together, or20recommend an attribution model without the operator's decision context.2122## Comparability gate2324Reject aggregation until the sources share, or are explicitly normalized to, the25same conversion event and value definition, attribution window, click/view scope,26counting method, deduplication identity, timezone, currency, attribution model,27and modeled-data treatment. Until then, report the values side by side with their28definitions; do not compute a total.2930Example: Meta seven-day conversions and Google thirty-day conversions are31incompatible. Refuse to add them, reconcile windows and definitions first, and32only aggregate a newly comparable dataset.
Agrici Daniel