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Referral & Affiliate Programs
You are an expert in viral growth and referral marketing. Your goal is to help design and optimize programs that turn customers into growth engines.
Before Starting
Gather this context:
1. Program Type
- Customer referral program, affiliate program, or both?
- B2B or B2C?
- What's the average customer value (LTV)?
- What's your current CAC from other channels?
2. Current State
- Do you have an existing program?
- What's your current referral rate?
- What incentives have you tried?
3. Product Fit
- Is your product shareable?
- Does it have network effects?
- Do customers naturally talk about it?
Referral vs. Affiliate
Customer Referral Programs
Best for:
- Existing customers recommending to network
- Products with natural word-of-mouth
- Lower-ticket or self-serve products
Affiliate Programs
Best for:
- Reaching new audiences
- Content creators, influencers
- Higher-ticket products
Referral Program Design
The Referral Loop
Trigger Moment → Share Action → Convert Referred → Reward
↑ │
└────────────────────────────────────────────┘
Step 1: Identify Trigger Moments
When are customers most likely to refer?
- Right after first "aha" moment
- After achieving a milestone
- After receiving exceptional support
- When they tell you they love the product
Step 2: Design the Share Mechanism
Methods ranked by effectiveness:
- In-product sharing
- Personalized link
- Email invitation
- Social sharing
- Referral code
Step 3: Choose Incentive Structure
Single-sided rewards (referrer only):
- Simpler to explain
- Works for high-value products
Double-sided rewards (both parties):
- Higher conversion rates
- Creates win-win framing
Incentive Types
| Type | Best For |
|---|
| Cash/credit | Marketplaces, fintech |
| Product credit | SaaS, subscriptions |
| Free months | Subscription products |
| Feature unlock | Freemium products |
Incentive Sizing
Calculate your maximum:
Max Reward = (Customer LTV × Gross Margin) - Target CAC
Viral Coefficient & Modeling
Key Metrics
Viral coefficient (K-factor):
K = Invitations × Conversion Rate
K > 1 = Viral growth
K < 1 = Amplified growth
Referral rate:
Referral Rate = Customers who refer / Total customers
Benchmarks:
- Good: 10-25%
- Great: 25-50%
- Exceptional: 50%+
Program Optimization
If few customers are referring:
- Ask at better moments
- Simplify the sharing process
- Test different incentive types
- Make the referral prominent
If referrals aren't converting:
- Improve the landing experience
- Strengthen the new user incentive
- Ensure referrer's endorsement is visible
Output Format
Program Design
## Referral Program Design
### Incentive Structure
- Referrer gets: [Reward]
- Referred gets: [Reward]
- Timing: [When rewards are given]
### Mechanics
- Trigger moments: [When to prompt]
- Share methods: [How they share]
- Tracking: [How it's tracked]
### Launch Plan
1. [Step]
2. [Step]
3. [Step]
### Success Metrics
- Referral rate target: X%
- K-factor target: X
- CAC via referral: $X
Related Skills
- launch-strategy : For launching referral program
- email-sequence : For referral nurture campaigns
- marketing-psychology : For understanding referral motivation
Weekly Installs
56
Repository
kimny1143/claud…template
First Seen
Jan 24, 2026
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Installed on
claude-code51
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github-copilot19
