# Product Value Proposition

> Rapidly craft, prototype, and validate differentiated value propositions before committing engineering cycles.

- Skill: `tjboudreaux/product-value-proposition` (Agent Skill)
- Install (CLI): `npx skillmds@latest add tjboudreaux/product-value-proposition`
- Raw SKILL.md: https://api.skillmd.com/api/skills/tjboudreaux/product-value-proposition/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: tjboudreaux (https://skillmd.com/u/tjboudreaux)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/tjboudreaux/product-value-proposition

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# Value Proposition Lab

## Intent
- Turn opportunity theses into sharp promises that resonate with target personas and platforms.
- Use lightweight artifacts (narratives, prototypes, landing pages) to test resonance and pricing early.

## Inputs
1. Target persona canvas + JTBD statements.
2. Competitive teardown (positioning, pricing, retention hooks).
3. Measurement plan (success metrics, experiment KPIs, survey scripts).

## Workflow
1. **Promise crafting**
   - Write 3–5 alternative promise statements highlighting outcome, emotional payoff, and proof.
   - Stress-test for clarity, distinctiveness, believability.
2. **Artifact production**
   - Choose fastest medium: storyboard, Figma mock, interactive prototype, gameplay video, tokenomics sim.
   - Include pricing/commitment ask if relevant.
3. **Signal testing**
   - Run rapid qualitative tests (5–8 target users) plus at least one quantitative signal (ad test, waitlist opt-in, fake door).
   - Collect friction language and willingness-to-pay indicators.
4. **Decision log**
   - Rank propositions by signal strength vs. confidence; document go/hold/kill decisions.

## Verification
- Experiments include control + clear success thresholds.
- Learnings and next steps stored in shared experiment log.
- Downstream teams notified when a proposition graduates to build stage.