Multi-Touch Attribution Calibration overview

Calibrates multi-touch attribution models for accuracy and actionability — comparing rule-based models against data-driven algorithmic attribution, conducting path analysis to understand common conversion journeys, running incrementality holdout tests to validate model outputs, reconciling attribution credit with actual channel performance changes, adjusting model weights based on cross-channel interaction effects, and documenting model limitations and confidence intervals for stakeholder consumption. Produces attribution model comparison reports, incrementality test results, and model calibration recommendations. Excludes attribution platform implementation and data integration.