modeling-conversion-metrics
modeling-conversion-metrics is a Product analytics & metrics skill for AI agents, published by PostHog in the posthog.com repository on GitHub. Skillspace rates modeling-conversion-metrics D (62/100) and it passed the safety scan; the rating is based on static analysis only.
Build reusable conversion models — funnel/step conversion rates, drop-off, and time-to-convert — on either PostHog data-warehouse views (HogQL) or an external dbt project. Use when the user wants to model, define, or compute a conversion rate, funnel, step completion, drop-off, activation-funnel, signup-to-paid, or any "what % of users who did A went on to do B (within N days)" metric. Covers the funnel model (ordered steps, the conversion-window time-box, strict vs any-order), the person-vs-group aggregation unit, overall vs step-to-step conversion (two different numbers), breakdown attribution, and when a saved funnel insight beats a warehouse view. On PostHog, model funnels in HogQL with windowFunnel; in dbt, stage the event stream and compute an fct_conversion mart with tests. Read modeling-warehouse-foundations first for the view-vs-dbt mechanics; pairs with query-funnel for interactive analysis.
- Grade
- D
- Quality
- 62 / 100
- Safety
- Passed
- GitHub stars
- 1,138
Unproven: rated by static analysis only, not yet compared head-to-head.
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Our review
- Architecture
- 78 / 100
- Maturity
- Structured: ships references or scripts
- 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)
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- 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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