attribution-report

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Run multi-touch attribution analysis on real conversion-path data — applies two or more models side-by-side (first-touch, last-touch, linear, time-decay, position-based, data-driven), computes per-channel attributed revenue and ROAS, assisted-conversion ratios, path-length and time-to-conversion distributions, and budget reallocation recommendations. Triggers on "/digital-marketing-pro:attribution-report", "which channels actually drive revenue", "compare first-touch vs last-touch", "run an attribution analysis", "is paid social undervalued". Pulls journeys from Google Analytics, Google Ads, Meta, and CRM MCPs and includes GA4's AI Assistant channel; model definitions come from skills/funnel-architect/attribution-models.md, strategy design from /digital-marketing-pro:attribution-model.

AI & Automation 809 stars 134 forks Updated 4 days ago MIT

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# /digital-marketing-pro:attribution-report ## GA4 AI Assistant channel (added 13 May 2026) When generating attribution reports against a GA4 property, the **AI Assistant** default channel group is now a first-class channel. GA4 automatically categorizes sessions referred by ChatGPT, Gemini, Claude, and other recognized AI assistants under this channel (and sets `Medium=ai-assistant`). For any brand running an AEO program, include the AI Assistant channel in the channel set and compare its contribution across all attribution models (first-touch, last-touch, linear, time-decay, position-based, data-driven). The model-comparison view is especially informative here: AI Assistant traffic often shows wildly different credit under first-touch vs last-touch because users frequently *discover* a brand via an AI assistant but convert via a later branded search or direct visit. Don't conclude "AI search doesn't drive revenue" from a last-touch number alone. Source: [GA4 default channel groups](https://support.google.com/analytics/answer/9164320?hl=en). For the upstream impression-side data, pair with `/digital-marketing-pro:gsc-ai-performance` (GSC AI Performance Report rolled out 3 June 2026, deliberately no click data — so GA4 is your click attribution surface). ## Purpose Generate multi-touch attribution analysis showing how different marketing channels and campaigns contribute to conversions. Compare multiple attribution models side-by-side, allocate revenue across touchpoint...

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Author
indranilbanerjee
Repository
indranilbanerjee/digital-marketing-pro
Created
7 months ago
Last Updated
4 days ago
Language
Python
License
MIT

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Run multi-touch attribution analysis on real conversion-path data — applies two or more models side-by-side (first-touch, last-touch, linear, time-decay, position-based, data-driven), computes per-channel attributed revenue and ROAS, assisted-conversion ratios, path-length and time-to-conversion distributions, and budget reallocation recommendations. Triggers on "/digital-marketing-pro:attribution-report", "which channels actually drive revenue", "compare first-touch vs last-touch", "run an attribution analysis", "is paid social undervalued". Pulls journeys from Google Analytics, Google Ads, Meta, and CRM MCPs and includes GA4's AI Assistant channel; model definitions come from skills/funnel-architect/attribution-models.md, strategy design from /digital-marketing-pro:attribution-model.

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