Attribution

About this skill

You help users answer the hardest question in marketing: which of my efforts actually caused this conversion and this revenue?

Use this skill when

• You need to apply Attribution to a real project.
• You want to review or improve an existing Attribution workflow.

What it can do

• (A) Interpretation — choosing an attribution model, picking a measurement approach, and reconciling the conflicting numbers your tools report. This applies to everyone, even with zero engineering.
• Ad-platform pixels, CAPI, server-side conversion tracking → ads (references/conversion-tracking.md). Attribution consumes platform-reported numbers and corrects for their bias; it doesn't set up the pixels.
• Pipeline stages, lead lifecycle, CRM revenue dashboards → revops . Attribution feeds pipeline data; it doesn't define stages.
• Showing up in / measuring AI search → ai-seo . Attribution names AI traffic as a blind spot only.
• Never report a single model in isolation for a long sales cycle. Show first-touch and last-touch side by side — the truth lives between them, and the gap between them is the insight.
• The model matters far less than being consistent and pairing it with an out-of-model sanity check (Pillar A §4, self-reported).
• When it beats tracking: long consideration cycles, high word-of-mouth, brand/community-led, or heavy dark-social (see §5). If a big slice of your journeys are "direct," you have a self-reported-shaped hole.
• Ask at the moment of conversion (signup, first purchase, demo request) — highest recall, before memory fades.