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/growth-analysis

Use post-launch when analysing acquisition, activation, retention, referral or revenue movement — by data-analyst for the KPI report, and by product-researcher when the question is about an existing product's funnel. Same data, same tools as the analytics schema; this is the

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app-dev-team
432 skills30 agents27 commands2 hooks
Install
$ npx -y skills add vmobifystudio/app-dev-team --skill growth-analysis --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/growth-analysis

Context preview

The summary Claude sees to decide when to auto-load this skill.

Use post-launch when analysing acquisition, activation, retention, referral or revenue movement — by data-analyst for the KPI report, and by product-researcher when the question is about an existing product's funnel. Same data, same tools as the analytics schema; this is the

SKILL.md

growth-analysis.SKILL.md
name: growth-analysis
description: Use post-launch when analysing acquisition, activation, retention, referral or revenue movement — by data-analyst for the KPI report, and by product-researcher when the question is about an existing product's funnel. Same data, same tools as the analytics schema; this is the reading of it.

Growth analysis

Post-launch analysis of the funnel the studio already instruments. It is a reading, not a new data source: everything here comes from the schema in `docs/52-analytics.md`, and a metric with no event behind it is a request to `data-analyst`, never an estimate.

The funnel, one definition each

Define each stage **once**, in the report, and never redefine it between reports — a metric whose definition moves is worse than no metric because the trend is fiction:

| Stage | Definition must state | |---|---| | Install | source, and whether re-installs count | | Activation | the single event that means "this user got the point", and by when | | Retention | D1 / D7 / D30, calendar or rolling — say which | | Referral | the event, and whether the invited user is attributed | | Revenue | gross or net of store commission, trial or paid |

The rules that keep this honest

  • **Every number carries its denominator and its date range.** "Retention improved to 42%" is not a

finding; "D7 retention on the 2026-07-01 cohort is 42% of 1,204 installs, versus 38% of 980 on 2026-06-01" is.

  • **Cohorts, never period totals**, for anything a user does over time. Period totals move when

install volume moves and tell you nothing about the product.

  • **Correlation is labelled as correlation.** A release, a season, a store feature and a price change

usually land in the same week. Name the confounders you cannot separate.

  • **A metric that cannot go down is not a metric.** Cumulative installs, total sessions, all-time

revenue — track them if you like, never report them as evidence of anything.

  • **Small-n silence.** Below a stated threshold, report the count and no percentage. A 66% conversion

on 3 users has misled more roadmaps than any other single number.

  • **Consent-gated data is partial by construction.** State the consent rate; a funnel measured on

consenting users only is a funnel about consenting users only.

Output

Append to `docs/52-analytics.md` a dated `## Growth report` with: the funnel table by cohort, what moved and by how much, the one change most likely to explain it, the confounders, and **what you would need to instrument to answer the question you could not answer**. That last item is the one that makes the next report better.

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