# Product Growth Loops

> Design compounding acquisition, engagement, and retention loops tailored to consumer product or game ecosystems.

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

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# Growth Loop Architecture

## Intent
- Replace funnel-only thinking with self-reinforcing loops that compound over time.
- Align channel, product, and community mechanics into measurable systems.

## Inputs
1. Current growth metrics (activation, retention, referrals, LTV/CAC).
2. Channel inventory (owned, earned, paid, platform-native, on-chain incentives).
3. Behavioral archetypes and motivations.

## Workflow
1. **Loop mapping**
   - Enumerate existing loops (content, UGC, social proof, rewards, UGC marketplaces, token sinks/sources).
   - Identify leakage points and missing steps.
2. **Loop design**
   - For each desired loop, define Trigger → Action → Reward → Investment elements and measurable KPIs.
   - Ensure loops respect platform policies and economic constraints (app stores, blockchain gas, privacy laws).
3. **Prioritization**
   - Score loops on strategic fit, time-to-learn, defensibility, and required capabilities.
   - Select one core loop + one accelerant loop for near-term experimentation.
4. **Experiment blueprint**
   - Specify instrumentation, success gates, and fallback plans.
   - Align cross-functional owners (product, marketing, community, data).

## Verification
- Every loop diagram has explicit metrics and data sources.
- Risk review covers abuse vectors, spam, and platform violations.
- Experiment backlog reflects selected loops with timelines and owners.