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
- Category is a classifier prediction; no model has read this skill yet
- 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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