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cohort-curve-model

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Fit a retention curve to observed cohort data and project LTV — computed, not estimated. Use when someone has real cohort retention numbers (month 0, 1, 2…) and asks what lifetime value, lifetime periods, or long-run retention they imply, or whether retention is flattening or leaking. Produces a fitted power curve (parameters, R², retention floor), a 24-36 period projection, and a real .xlsx with live formulas where editing ARPU recalculates LTV — via the bundled zero-dependency script.

skills/cohort-curve-model/SKILL.md

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# Cohort Curve Model

Retention data has a shape, and the shape is the business. This skill fits the standard consumer-retention power curve r(t) = a·t^(−b) to observed cohort data by log-log least squares — actual arithmetic run by the bundled script, not model vibes — then projects it forward and prices it.

## Required Inputs

- **Observed retention by period** — from period 0 (100%) through at least period 3-4. Percent or fraction, either works. More periods = a trustworthy fit; 4 is the floor.
- **ARPU per period** (optional) — revenue per *retained* user per period. Without it, LTV is reported in lifetime-period multiples instead of currency.
- **Projection horizon** (optional, default 24 periods).

If the requester has cohort *tables* (rows of cohorts × months), take the average by period-age or fit the most recent complete cohort — say which you did.

## Output Format
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