referral-program-design
GitHub设计驱动增长的可裂变推荐计划，涵盖循环机制、激励结构、病毒数学估算（k因子）、反欺诈措施及成功指标。适用于构建邀请循环或优化口碑增长。
Trigger Scenarios
Install
npx skills add mohitagw15856/pm-claude-skills --skill referral-program-design -g -y
SKILL.md
Frontmatter
{
"name": "referral-program-design",
"description": "Design a referral or viral-loop program that actually drives growth. Use when asked to design a referral program, build a viral\/invite loop, set referral incentives, or improve word-of-mouth growth. Produces a referral design — the loop mechanics, incentive structure (who gets what, when), the viral-math estimate (k-factor\/cycle time), fraud guardrails, placement & messaging, and success metrics."
}
Referral Program Design Skill
A referral program is a growth loop, not a coupon. It only compounds if each new user invites more than they cost and the cycle is fast. This skill designs the mechanics and incentives, then sanity-checks them with the viral math — because most referral programs fail not on creativity but on a k-factor below 1.
Required Inputs
Ask for these only if they aren't already provided:
- Why users would share — the genuine reason (status, mutual benefit, the product is better with others).
- Economics — the value of a new customer (so the incentive budget is grounded) and current organic word-of-mouth.
- The moment of delight — when users are happiest (the best time to ask for a referral).
- Goal — what the program must do (lower CAC, accelerate growth) and over what horizon.
Output Format
Referral Program: [product]
1. The loop — map it: a user does X → is prompted to invite → friend accepts → friend activates → becomes a referrer. Name every step; the loop is only as strong as its weakest conversion.
2. Incentive structure — who gets what and when it unlocks (one-sided vs. two-sided; reward on signup vs. on the friend's activation — gating on activation kills fraud and aligns value). Ground the reward in customer value.
3. Viral math — estimate k = invites sent × conversion rate, and the cycle time. State honestly whether k approaches/exceeds 1 (true virality) or simply lowers CAC (the common, still-useful case). Don't promise exponential growth from a k of 0.2.
4. Placement & messaging — where the ask appears (anchored to the delight moment, not signup), the share channels, and copy that gives the sharer a reason that makes them look good.
5. Fraud & abuse guardrails — self-referral and fake-account defenses, reward gating on real activation, and limits/velocity checks.
6. Metrics — share rate, invite→signup→activation conversion, k-factor, referred-user retention vs. baseline, and CAC of referred vs. paid.
Quality Checks
- The reward unlocks on the referred friend's activation, not just signup (aligns value, blocks fraud)
- The viral math (k-factor + cycle time) is estimated honestly — including admitting when it's a CAC-reducer, not true virality
- The ask is placed at a delight moment, not bolted onto signup
- Fraud guardrails (self-referral, fake accounts, velocity limits) are specified
- Referred-user retention is measured, not just signups (referred users can be low quality)
Anti-Patterns
- Do not pay for signups instead of activations — you'll fund fraud and low-quality users
- Do not claim virality from a k-factor below 1 — be honest that it's lowering CAC, which is still worth doing
- Do not bolt the ask onto onboarding before the user has felt value — nobody refers a product they haven't experienced
- Do not ignore the sharer's social risk — give them a reason that makes them look generous/smart, not spammy
- Do not skip fraud guardrails — an ungated incentive is an arbitrage opportunity, not a growth loop
Based On
Viral-loop / referral practice — k-factor and cycle-time math, activation-gated two-sided incentives, and abuse-resistant design.
Version History
- a38bc30 Current 2026-07-05 11:42
