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referral-programlisted

Referral program design - referrer / referee incentive structure, viral mechanics, fraud and abuse controls, attribution, and channel placement. Use when: referral program, refer a friend, viral loop design, K-factor, advocacy referrals, partner referrals, customer referral incentives, referral attribution, viral coefficient.
varunk130/ai-gtm-skill-library · ★ 3 · AI & Automation · score 76
Install: claude install-skill varunk130/ai-gtm-skill-library
# Referral Program (RIPPLE Framework) Design a referral program with a real viral mechanic - not a "refer a friend" button buried in settings. RIPPLE forces explicit design of who refers, why they refer, what the receiver gets, where the program lives, and how it's measured against a viral coefficient. ## Core Principle **Referral programs fail because they optimize for the *sender's* reward and ignore the *receiver's* trust.** A high-K loop requires both. RIPPLE designs both sides of the exchange and instruments the loop end-to-end. ## The RIPPLE Framework | Letter | Stage | The Question | |--------|-------|--------------| | **R** | Reward Architecture | What does the referrer get, what does the referee get, and when? | | **I** | Invite Mechanic | How is the invite sent, and how low-friction is the share? | | **P** | Placement | Where in the product / journey does the ask appear? | | **P** | Proof | What social proof and trust signals accompany the invite? | | **L** | Loop Math | What's the viral coefficient target, and which lever moves it? | | **E** | Evaluate & Defend | How is fraud, cannibalization, and incremental lift measured? | ## Reward Architecture The most common failure mode is **single-sided** rewards. | Type | Pattern | Best For | |------|---------|----------| | **Double-sided** | Both referrer and referee get reward | Most consumer / SMB programs | | **Single-sided (referrer)** | Only referrer rewarded | Pure-advocacy programs (low conversion lift) | |