Measuring marketing attribution comes down to four steps. First, connect your data: CRM, marketing automation, ad platforms, and web analytics all need to feed one place. Second, resolve identity, reconciling duplicate and conflicting records into one profile per person and account, because attribution built on fragments is attribution built on sand.
Third, choose your models. Multi-touch models (linear, W-shaped, AI-driven) show how credit spreads across the journey; marketing mix modeling estimates channel contribution top-down; incrementality testing isolates true lift. Running more than one keeps any single model honest. Fourth, tie touches through to pipeline and revenue so you are measuring influence on dollars, not just clicks.
The common failure is treating attribution as a modeling problem when it is mostly a data problem. Teams tune models while their inputs disagree across systems. RevSure inverts that: it resolves identity on a governed context layer first, then runs the models on clean data, and makes every number traceable back to its source records.
For definitions of the models, see multi-touch attribution and revenue attribution. See how RevSure measures it in its attribution platform.
Explore RevSure's attribution platform.