attribution-reconciler
FeaturedUse when platform-reported conversions disagree with GA4/ecommerce, when you suspect Meta and Google are double-counting the same sales, or for a standing (monthly) reconciliation workbook that de-dups stacked credit against an order-ID truth set, normalizes attribution windows and currency, compares attribution models, and reads incrementality from a geo/holdout test. Not for the point-in-time R2 veto or RQS gate — use ad-account-auditor; not for the ROI/ROAS ratio math itself — use roi-calculator; not for organic dark-social share attribution or GA4 direct-traffic decomposition — use dark-social-attributor. 付费广告归因对账/去重/增量
Install
Quality Score: 99/100
Skill Content
Details
- Author
- aaron-he-zhu
- Repository
- aaron-he-zhu/aaron-marketing-skills
- Created
- 8 months ago
- Last Updated
- today
- Language
- Python
- License
- Apache-2.0
Bundled in these plugins
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attribution-reconciler
Use when platform-reported conversions disagree with GA4/ecommerce, when you suspect Meta and Google are double-counting the same sales, or for a standing (monthly) reconciliation workbook that de-dups stacked credit against an order-ID truth set, normalizes attribution windows and currency, compares attribution models, and reads...
conversion-verifier
Verify whether the purchases your ad platform reports actually exist in your store, and produce a client-ready reconciliation report. Use this whenever someone questions their ad numbers, wonders if their ROAS is real, says their Meta/Google/TikTok conversions do not match Shopify or Stripe, sees a ROAS that feels too good, suspects over-attribution or double counting, is about to scale or kill a campaign based on platform-reported results, or asks how to audit, validate, sanity-check or reconcile ad conversion data against actual orders or revenue. Also use it when someone mentions attribution discrepancies, inflated conversions, phantom sales, view-through conversions, or asks "are these numbers real". Produces a professional report that separates the legitimate part of the gap from the part that has no explanation.
attribution-report
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.