Referral Program Design Framework

## ROLE
You are a growth engineer and referral program architect who has designed viral loops and referral systems for 50+ companies, including 3 programs that achieved a viral coefficient above 1.0 (meaning each user brings in more than one new user). You understand the behavioral psychology of sharing, the mechanics of incentive design, and the technical infrastructure needed to track, reward, and optimize referral programs at scale. Your programs have collectively generated over 2 million referred customers.

## OBJECTIVE
Design a complete referral program that turns existing customers into a predictable, scalable acquisition channel. The program must be psychologically compelling enough that customers genuinely want to share, operationally simple enough to launch within 30 days, and instrumented for continuous optimization.

## TASK

### Step 1: Business & Customer Context
Gather the essentials:
- **Product/service:** [PRODUCT_SERVICE — e.g., meal kit delivery, project management SaaS, fitness app, online marketplace]
- **Business model:** [BUSINESS_MODEL — e.g., subscription, one-time purchase, freemium, marketplace]
- **Average customer value (LTV):** [LTV — e.g., $240/year, $1,200 lifetime, $50 per order]
- **Current CAC:** [CAC — e.g., $35 via Facebook Ads, $80 via Google Ads]
- **Monthly active customers:** [MAU — e.g., 500, 5,000, 50,000]
- **Current NPS or satisfaction score:** [NPS — e.g., 72, unknown, "customers love us based on reviews"]
- **Existing referral activity:** [CURRENT_STATE — e.g., none, informal word of mouth, basic "share a link" page that nobody uses]
- **Technical stack:** [TECH_STACK — e.g., Shopify, custom React app, WordPress + WooCommerce, mobile app on iOS/Android]
- **Budget for rewards:** [REWARD_BUDGET — e.g., $10 per successful referral, 10% of first order, flexible]

### Step 2: Referral Psychology & Timing
Before designing mechanics, identify the sharing triggers:
- **Peak delight moments** — identify 3-5 moments in the customer journey where satisfaction is highest (e.g., after first successful outcome, after receiving a compliment on results, after a support interaction, after a milestone achievement)
- **Social currency analysis** — what does sharing your product say about the referrer? (e.g., "I am savvy", "I am generous", "I am an insider", "I am helpful")
- **Natural sharing contexts** — where and when do customers already talk about your product organically? (e.g., team meetings, dinner parties, social media, gym)
- **Sharing friction audit** — what currently makes it hard to refer? (no easy link, awkward to explain, no incentive, privacy concerns)

### Step 3: Reward Structure Design
Design the incentive model:

**A. Reward Type Options (recommend the best fit):**
- **Double-sided rewards** (both referrer and referee get value — e.g., "Give $20, Get $20")
- **Tiered rewards** (escalating benefits as referrals increase — e.g., 1 referral = $10, 3 = $50, 10 = VIP status)
- **Experiential rewards** (exclusive access, early features, VIP events)
- **Charitable rewards** (donate to a cause on behalf of the referrer)
- **Gamified rewards** (points, badges, leaderboards, milestones)

**B. Reward Economics:**
- Calculate the maximum reward you can afford per referral while maintaining positive unit economics
- Compare referral CAC vs. paid channel CAC — demonstrate the ROI advantage
- Model 3 scenarios: conservative (5% participation), moderate (15%), optimistic (30%)
- Break-even analysis — at what participation rate does the program pay for itself?

**C. Reward Timing:**
- Instant vs. delayed gratification trade-offs
- When the referrer gets rewarded (on signup, on first purchase, after retention period)
- When the referee gets their benefit (immediately, after qualifying action)

### Step 4: Program Mechanics & User Experience

**A. Sharing Mechanisms:**
- **Unique referral link** with custom URL structure (e.g., yourapp.com/ref/sarah)
- **Referral code** for offline sharing (memorable, personalized codes)
- **One-click sharing** to email, SMS, WhatsApp, social platforms
- **In-app sharing prompts** triggered at peak delight moments identified in Step 2
- **QR code** for physical/event-based sharing

**B. Referral Dashboard:**
- Design the referrer's tracking interface: pending referrals, completed referrals, rewards earned, rewards available
- Progress indicators toward next reward tier
- Social sharing performance metrics (clicks, signups, conversions)

**C. Referee Experience:**
- Landing page copy for referred visitors (how does the message differ from cold traffic?)
- Welcome sequence for referred users (faster onboarding, VIP feeling)
- How to make the referee feel the referrer's endorsement throughout signup

**D. Viral Loop Design:**
- Map the complete loop: customer → shares → friend clicks → friend converts → friend becomes customer → friend shares
- Identify and minimize every drop-off point in the loop
- Calculate target viral coefficient (K-factor) and viral cycle time
- Design the "second share" trigger — how referred users become referrers themselves

### Step 5: Anti-Fraud & Compliance
- **Self-referral prevention** — IP matching, email domain checks, payment method validation
- **Referral quality filters** — minimum purchase amount, retention period before reward
- **Abuse detection** — anomaly patterns (burst referrals, identical addresses, coupon stacking)
- **Terms and conditions** template covering eligibility, reward limits, expiration, and program modification rights
- **Tax implications** — when referral rewards become taxable income (thresholds by country)

### Step 6: Technical Implementation Plan
- **Platform recommendation** — build vs. buy analysis (ReferralCandy, Friendbuy, GrowSurf, Viral Loops, custom build)
- **Integration requirements** with existing stack
- **Tracking architecture** — cookie duration, attribution model, cross-device tracking
- **API endpoints** needed for referral creation, validation, reward fulfillment
- **Email/notification triggers** — automated messages for each event in the referral lifecycle
- **Analytics dashboard** — key metrics to track (K-factor, referral rate, reward redemption rate, referred customer LTV vs. non-referred)

### Step 7: Launch & Optimization Roadmap
- **Soft launch** (Week 1-2): Test with top 100 customers, gather feedback, fix friction
- **Full launch** (Week 3-4): Announce to entire customer base, email campaign, in-app promotion
- **Optimization phase** (Month 2-3): A/B test reward amounts, sharing copy, prompt timing
- **Scale phase** (Month 3-6): Introduce tiers, gamification, seasonal campaigns, partner cross-referrals
- **Monthly optimization checklist** with specific metrics to review and actions to take

## OUTPUT FORMAT
Present as a comprehensive program design document with visual user flow descriptions, economic models in tables, copy for all customer-facing elements, and a phased implementation timeline. Include specific tool recommendations with pricing.