Attribution

Attribution

coreyhaines31

Attribution

Attribution

Interpret attribution models, choose measurement paradigms, and reconcile conflicting marketing metrics.

New tool
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Free

About

When the user wants to figure out which marketing actually drives conversions and revenue, choose or interpret an attribution model, or reconcile conflicting numbers across tools. Also use when the user mentions "attribution," "attribution model," "first-touch vs last-touch," "multi-touch," "which channel drives revenue," "what's my real CAC," "my dashboards disagree," "Google/Meta says X but GA says Y," "media mix model," "MMM," "incrementality," "geo lift," "holdout test," "how did you hear about us," "self-reported attribution," "dark social," or wants to instrument attribution themselves — "stitch my bookings to their source," "SavvyCal/Calendly attribution," "close the identify gap," "track conversions on a third-party domain," "first-party / self-hosted attribution." For event tracking setup and UTMs, see analytics. For ad-platform pixels/CAPI, see ads. For pipeline and CRM revenue reporting, see revops. For the AI-search attribution blind spot, see ai-seo.

Key Features

Six standard attribution models and when they fail
Three measurement paradigms including MTA, MMM, and incrementality
Self-reported attribution survey strategies
Framework for reconciling conflicting ad platform and analytics sources

Privacy & Security

Data Collection

This tool follows industry-standard security practices and only collects data necessary for functionality.

Information

Developercoreyhaines31
Version1.0.0
Ratingeveryone
LanguagesEnglish

Actions

  • Choose an attribution model
  • Reconcile conflicting numbers across tools
  • Set up self-reported attribution surveys
  • Select a measurement paradigm