Attribution Model

Attribution models determine how credit for a conversion is distributed among the touchpoints a user encountered before converting. Common models include last-click, first-click, linear, time-decay, and data-driven.

Last-click attribution is the simplest but most misleading -- it gives all credit to the final interaction and ignores the awareness and consideration stages. Multi-touch models distribute credit more fairly but are harder to implement.

Data-driven attribution uses machine learning to weight touchpoints based on their actual contribution to conversions. It requires significant data volume but produces the most accurate picture of channel performance.