modeling-conversion-metrics
modeling-conversion-metrics is the official agent skill of PostHog published by posthog, listed under analytics & experiments. It lives in the PostHog/skills repository, which has 75 GitHub stars and is licensed under MIT; we last read it on 2026-09-16.
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.
Install
skills is a generic installer for any repository of Claude agent skills -- it reads PostHog/skills’s own structure rather than assuming one, the same way this page reads the skill’s own SKILL.md rather than assuming a format.
npx skills add PostHog/skills
What it connects to
Unverified means a mention in the skill’s own description, not a citation. A wrong claim here costs nothing to correct and nothing to trust yet.
Maintenance
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.
modeling-conversion-metrics compared with similar skills
| Skill | Publisher | What it does | Repo stars | Last update |
|---|---|---|---|---|
| modeling-conversion-metrics (this page) | posthog | Build reusable conversion models — funnel/step conversion rates, drop-off, and time-to-convert — on either Po… | 75 | 2026-10-25 |
| account-handover(same repository) | posthog | Draft structured handover notes for transitioning a PostHog account from one TAM or CSM to another. Use this… | 75 | 2026-10-25 |
| adding-warehouse-person-properties(same repository) | posthog | Sync columns from a synced data warehouse table onto PostHog person or group properties, so warehouse data be… | 75 | 2026-10-25 |
| analyzing-experiment-session-replays(same repository) | posthog | Analyze session replay patterns across experiment variants to understand user behavior differences. Use when… | 75 | 2026-10-25 |
| analyzing-task-runs(same repository) | posthog | Split a completed PostHog task run into activity records — what the agent tried, whether it worked, what bloc… | 75 | 2026-10-25 |
| assessing-heatmaps(same repository) | posthog | Assesses what a page's heatmap is telling you and recommends concrete changes. Pulls click / rageclick / scro… | 75 | 2026-10-25 |
| auditing-endpoints(same repository) | posthog | Audit every endpoint in a PostHog project for staleness, failed materialisations, and unused materialised ver… | 75 | 2026-10-25 |
Skills from the same repository first, then others for this job by repository stars. Figures are from each repository when we last read it.
Common questions about modeling-conversion-metrics
- What does modeling-conversion-metrics do?
- 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.
- How do I install modeling-conversion-metrics?
- Run npx skills add PostHog/skills. The skills installer reads the repository’s own structure, so it works for any repository of agent skills.
- Who publishes modeling-conversion-metrics?
- posthog. It is named as the official skill of PostHog.
- Is modeling-conversion-metrics maintained, and what licence does it use?
- Its repository has 75 GitHub stars and its state in our directory is listed. Its last commit we recorded was on 2026-10-25. The repository declares the MIT licence.
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