attribution-report

attribution-report is a Marketing analytics & attribution skill for AI agents, published by indranilbanerjee in the digital-marketing-pro repository on GitHub. Skillspace rates attribution-report D (68/100) and it passed the safety scan; the rating is based on static analysis only.

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.

Grade
D
Quality
68 / 100
Safety
Passed
GitHub stars
815

Unproven: rated by static analysis only, not yet compared head-to-head.

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Our review

Architecture
100 / 100
Maturity
Basic: a single SKILL.md
Security scan
No issues found
License
Not declared. Check the repository before reusing it.

Not checked yet

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  • Not judged on the rubric yet (not a contender in its category)
  • No blind task eval yet
  • Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
  • Sibling files (scripts, references) not fetched; security scan covers SKILL.md only

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