Conversion Data Quality
How event definitions, identifiers, timing, duplicates, refunds, and CRM hygiene affect marketing measurement.
Measurement is a stack of questions
User-level attribution, experiments, media mix modeling, platform reporting, CRM analysis, and financial reporting answer different questions. Strong measurement systems define which question each method is responsible for instead of forcing one dashboard to become the universal truth.
Observed is not the same as caused
Attribution associates conversions with observed touchpoints. Incrementality asks what would have happened without the marketing exposure. Media mix modeling uses aggregated variation to estimate channel contribution. Those are related but distinct analytical jobs.
Data quality comes first
Event names, timestamps, order IDs, user identifiers, currency, refunds, lead stages, and deduplication rules determine whether later analysis can be trusted. Measurement sophistication cannot recover information that was never captured or was captured inconsistently.
Create a reconciliation routine
On a regular schedule, compare major systems against the underlying business record. Investigate large differences, document expected gaps, and record changes to tags, models, windows, or integrations so historical comparisons remain interpretable.
Use multiple lenses
The most mature approach is usually triangulation: use attribution for journey-level diagnostics, experiments for causal questions where practical, aggregate modeling for channels that are difficult to observe directly, and financial results as the ultimate constraint.
For teams that have outgrown native reporting, the next practical step is to compare independent tracking platforms against the measurement gaps you have actually documented—not against an abstract feature checklist.