New skills (14): - nestjs-best-practices: 40 priority-ranked rules (kadajett) - fastapi: Pydantic v2, async SQLAlchemy, JWT auth (jezweb) - architecture-patterns: Clean Architecture, Hexagonal, DDD (wshobson) - python-performance-optimization: Profiling and optimization (wshobson) - ai-sdk: Vercel AI SDK streaming and agent patterns (vercel) - create-agent: Modular agent architecture with OpenRouter (openrouterteam) - proactive-agent: WAL Protocol, compaction recovery, self-improvement (halthelobster) - brand-guidelines: Brand identity enforcement (anthropics) - ui-animation: Motion design with accessibility (mblode) - marketing-ideas: 139 ideas across 14 categories (coreyhaines31) - pricing-strategy: SaaS pricing and tier design (coreyhaines31) - programmatic-seo: SEO at scale with playbooks (coreyhaines31) - competitor-alternatives: Comparison page architecture (coreyhaines31) - referral-program: Referral and affiliate programs (coreyhaines31) README reorganized by domain: Code Quality, Frontend, Backend, Auth, AI/Agent Building, Marketing, Design, Meta. Mosaic Stack is not limited to coding — the Orchestrator serves coding, business, design, marketing, writing, logistics, and analysis. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
135 lines
3.0 KiB
Markdown
135 lines
3.0 KiB
Markdown
# Referral Program Examples
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Real-world examples of successful referral programs.
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## Dropbox (Classic)
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**Program:** Give 500MB storage, get 500MB storage
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**Why it worked:**
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- Reward directly tied to product value
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- Low friction (just an email)
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- Both parties benefit equally
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- Gamified with progress tracking
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---
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## Uber/Lyft
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**Program:** Give $10 ride credit, get $10 when they ride
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**Why it worked:**
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- Immediate, clear value
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- Double-sided incentive
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- Easy to share (code/link)
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- Triggered at natural moments
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---
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## Morning Brew
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**Program:** Tiered rewards for subscriber referrals
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- 3 referrals: Newsletter stickers
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- 5 referrals: T-shirt
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- 10 referrals: Mug
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- 25 referrals: Hoodie
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**Why it worked:**
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- Gamification drives ongoing engagement
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- Physical rewards are shareable (more referrals)
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- Low cost relative to subscriber value
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- Built status/identity
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---
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## Notion
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**Program:** $10 credit per referral (education)
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**Why it worked:**
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- Targeted high-sharing audience (students)
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- Product naturally spreads in teams
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- Credit keeps users engaged
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---
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## Incentive Types Comparison
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| Type | Pros | Cons | Best For |
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|------|------|------|----------|
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| Cash/credit | Universally valued | Feels transactional | Marketplaces, fintech |
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| Product credit | Drives usage | Only valuable if they'll use it | SaaS, subscriptions |
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| Free months | Clear value | May attract freebie-seekers | Subscription products |
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| Feature unlock | Low cost to you | Only works for gated features | Freemium products |
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| Swag/gifts | Memorable, shareable | Logistics complexity | Brand-focused companies |
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| Charity donation | Feel-good | Lower personal motivation | Mission-driven brands |
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---
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## Incentive Sizing Framework
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**Calculate your maximum incentive:**
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```
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Max Referral Reward = (Customer LTV × Gross Margin) - Target CAC
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```
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**Example:**
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- LTV: $1,200
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- Gross margin: 70%
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- Target CAC: $200
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- Max reward: ($1,200 × 0.70) - $200 = $640
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**Typical referral rewards:**
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- B2C: $10-50 or 10-25% of first purchase
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- B2B SaaS: $50-500 or 1-3 months free
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- Enterprise: Higher, often custom
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---
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## Viral Coefficient & Metrics
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### Key Metrics
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**Viral coefficient (K-factor):**
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```
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K = Invitations × Conversion Rate
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K > 1 = Viral growth (each user brings more than 1 new user)
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K < 1 = Amplified growth (referrals supplement other acquisition)
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```
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**Example:**
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- Average customer sends 3 invitations
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- 15% of invitations convert
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- K = 3 × 0.15 = 0.45
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**Referral rate:**
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```
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Referral Rate = (Customers who refer) / (Total customers)
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```
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Benchmarks:
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- Good: 10-25% of customers refer
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- Great: 25-50%
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- Exceptional: 50%+
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**Referrals per referrer:**
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Benchmarks:
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- Average: 1-2 referrals per referrer
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- Good: 2-5
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- Exceptional: 5+
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### Calculating Referral Program ROI
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```
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Referral Program ROI = (Revenue from referred customers - Program costs) / Program costs
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Program costs = Rewards paid + Tool costs + Management time
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```
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**Track separately:**
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- Cost per referred customer (CAC via referral)
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- LTV of referred customers (often higher than average)
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- Payback period for referral rewards
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