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unit-economics

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Use when computing or improving the per-customer economics of a business — CAC, LTV, CAC payback period and contribution margin — judging whether the ratios are healthy against current norms, and naming the one lever that fixes the worst number. Covers a blended CAC that hides a bleeding channel, and a model that shows profit while each customer loses money. NOT the multi-year P&L or scenario projection (that is `financial-model`).

skills/unit-economics/SKILL.md

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# Unit economics

Answer one question honestly: **does one customer pay back more than it cost to win and serve them, and how fast?** You compute four load-bearing numbers — CAC, contribution margin, LTV, CAC payback period — plus the two ratios operators and investors actually argue about (LTV:CAC, NRR). Then you diagnose *why* a number is where it is and name the single lever that moves it.

This is a measurement-and-diagnosis skill, not a projection skill. You do not build the multi-year model here (that is the `financial-model` sibling); you build the per-customer truth that the model's growth assumptions have to rest on.

## What this skill produces

A **unit-economics worksheet** (`unit-economics.{yaml,csv,md}`) where:
- a block of **named inputs** — period S&M spend, new customers, monthly ARPA, gross margin %, monthly churn, optional segment rows — is stated explicitly;
- every **derived figure** (CAC, contribution margin, LTV, payback, LTV:CAC) is recomputed *from those inputs* so the relationships are self-consistent;
- the worst number is diagnosed and one concrete lever is prescribed.

`scripts/verify.sh` re-derives the figures and fails if the arithmetic lies (see the last section). If you only hand back prose, you have not finished — emit the worksheet.
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