analyze-performance-revenue-join
Agent skill from
Step of the analyze-performance playbook: joins cleaned store or CRM numbers with ad spend to build the business-truth table, MER, new-customer cost and the overclaim ratio. Run analyze-performance instead; not for direct use.
How to install analyze-performance-revenue-join
install analyze-performance-revenue-join
# install the goose-skills pack with the skills CLI
npx skills add gooseworks-ai/goose-skills# or add only this skill to Claude Code: copy the folder
skills/marketing/analyze-performance-revenue-join/
# into
~/.claude/skills/analyze-performance-revenue-join/ (all projects)
.claude/skills/analyze-performance-revenue-join/ (one project)
1# Revenue join (atom)23**Load:** `../analyze-performance/references/revenue-join.md`.45**Inputs:** clean store/CRM numbers; total spend per platform; platform claims; break-even MER and allowable CAC (campaign brief economics box / measurement contract); last week's report (the story the marketer picked).67**Do:**81. Business-truth table: this week, last week, 4-week average, same week last year.92. MER, new-customer MER, nCAC, contribution after ads — each vs break-even / allowable / target.103. Overclaim ratio, like-for-like as in the reference (claimed purchases ÷ store orders, or claimed revenue ÷ store gross; a floor when a claimant is missing), with its 4-week trend.114. Marginal: Δ new-customer revenue ÷ Δ spend vs last week and vs the 4-week average.125. If the platform and blended stories point different ways: write both at the same grain, each ending "if true, you'd…", a recommendation, and the cheapest test that would settle it. Carry forward the story the marketer picked last time unless a test changed it.136. B2B: pipeline chain and cost per qualified lead / opportunity instead of revenue.1415**Output:** the report's Business truth, overclaim line and Two stories sections.
Excerpt shown under the repository's MIT license.