What problem does it solve? Marketers lose budget to channels that look good in one dashboard and terrible in another, because every platform claims credit for the same conversion and models quietly encode opinions as fact. This Skill helps you choose and interpret attribution models, reconcile conflicting numbers across Google, Meta, GA4, and your CRM, and instrument first-party attribution when you control the site or app. ## Core Features & Use Cases - Model interpretation and reconciliation: Compare first-touch, last-touch, linear, time-decay, position-based, and data-driven models, then triangulate platform, analytics, CRM, and self-reported data into one defensible allocation with confidence levels. - Measurement paradigm selection: Decide between multi-touch attribution, media mix modeling, and incrementality testing (geo holdouts, PSA, ghost ads) based on budget, sales cycle, and channel mix. - First-party attribution builds: Close the identify() gap, stitch conversions on third-party domains like SavvyCal or Stripe Checkout via metadata passthrough and webhook identity merges, and sync source/confidence/basis fields into the CRM. - Use Case: Your Meta dashboard claims 40 conversions, Google claims 50, and your CRM shows 35 deals. Use this Skill to establish the CRM as the source of truth, de-dupe overlapping platform claims, and deliver an attribution readout that explains the gap and recommends where next quarter's budget should go. ## Quick Start Ask the assistant to reconcile your conflicting conversion numbers across ad platforms, GA4, and your CRM and recommend an attribution model for your sales cycle.
