/attribution
搞清楚到底是哪個管道真正帶來轉換與營收——選歸因模型、比對第一次接觸與最後一次接觸的差異，或解決各平台數字兜不起來的問題。
- 安裝次數
- 4.2 萬
- 專案星數
- 5.8 萬 ★
- 授權
- MIT
- 專案更新
- 2026-10-31
什麼時候用
各平台數字互相矛盾、或想知道行銷預算真正花在刀口上時用；埋點設定交給 analytics，廣告像素交給 ads。
怎麼裝
npx skills add https://github.com/coreyhaines31/marketingskills --skill attribution安裝前請先看過原文內容。中文說明是 AI 翻譯，不保證安全。
原文
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.