01 · Explanation
Reporting, learning, and archive
Objective: Produce a decision-ready campaign report that separates observations from explanations and preserves the evidence needed for reuse or audit.
A campaign report should answer what happened, compared with what, over which period, and what decision follows. Begin with data-quality notes, objective, baseline, target, audience definition, spend, and primary result. Show the funnel with consistent denominators and segment only where the sample is adequate and ethically appropriate. Distinguish delivered, viewed, engaged, qualified, converted, retained, and revenue outcomes. Report absolute counts with rates so small denominators are visible. Platform-reported attribution and modeled conversions should be labeled, and material discrepancies with finance, commerce, CRM, or service records should be investigated rather than silently reconciled.
Learning requires competing explanations and a planned next test. A high conversion rate could reflect better creative, a narrower audience, seasonality, tracking loss, or an unusually strong offer. State what the evidence supports, what remains uncertain, and which change will be tested next. Archive the approved brief, audience and suppression logic, assets, disclosures, approvals, tracking specification, QA evidence, incident notes, report, and decision log under a retention rule. Remove unnecessary exports and revoke temporary vendor access. The archive should support responsible reuse, not preserve personal data indefinitely.
Before you begin
- Confirm F01–F12; record that final campaign period, attribution window, validated outcomes, approved exclusions, and results are absent.
- STOP. If the reporting period, attribution window, outcome definition, exclusions, or validated results are missing or conflict across F01–F12, route the metric to authorized analytics/privacy/finance owners; do not claim report approval or execute publication, and do not assert causal impact or results.

