18-referral-program-global

# Referral Program (Global)

> Word of mouth is the highest-LTV acquisition channel in every region. But the LEGAL framework around how you contact referred prospects differs HUGELY: TCPA (US, SMS), GDPR (EU, all channels), PDPA (SEA), LGPD (LATAM). Pick the right region variant or get fined.

---

## For newbies

### Who is this skill for?

| Audience | Concrete example |
|----------|------------------|
| DTC brand wanting cheaper acquisition | Already at USD 30 CAC; want USD 10 CAC via referral |
| SaaS adding viral loop | Existing PMF; want negative CAC growth |
| Service business (coaching, agency) | High-LTV; want client referrals |
| Subscription brand | High retention; turn customers into ambassadors |
| E-commerce wanting AOV growth | Refer a friend = both get discount |

### Who is this NOT for?

- **Vietnam-only referral** -> Use `18-referral-program` (VN skill) — Zalo / Messenger optimized
- **B2B enterprise sales** -> ABM / partnership programs are different motion (not covered here)
- **Brand ambassador / affiliate** -> Use `27-personal-brand-monetize-global` for influencer-affiliate (when available)

### 30-second pre-read

This skill produces ONE referral program design with 6 components: model selection (1-way / 2-way / multi-tier), incentive math (% of LTV), tracking infrastructure, anti-fraud measures, launch sequence, and KPIs (K-factor, viral coefficient). Pick 1 of 4 region variants — the variant tunes the LEGAL rules for contacting referred prospects (especially via SMS/email).

### 3 common errors

1. **SMS-based referral in US without TCPA consent** -> Up to USD 1,500 per text fines + class actions
2. **Email-blast referred contacts in EU** -> GDPR violation; referral programs touching EU prospects need explicit consent from the prospect, NOT just the referrer
3. **Cash incentives that violate FTC endorsement rules** -> "Refer a friend, get USD 100" requires disclosed material connection if referrer posts publicly

---

## Why do you need this skill?

Without proper referral design:
- US: Risk TCPA class action (USD 500-1,500 per message)
- EU: GDPR violation if you store referred-prospect data without their consent
- SEA: PDPA Singapore strict — most referral programs need both-side consent
- LATAM: Brazil LGPD treats referred contacts as data subjects requiring consent
- Universal: incentive math wrong -> losing money instead of growing
- Universal: no anti-fraud -> 30-50% of "referrals" are self-referrals or bots

Plan the legal foundation correctly, get the incentive math right, ship a working viral loop.

---

## Workflow

```
Step 0: Check global context file
    |-- exists -> read product / customer / region
    |-- missing -> suggest user run product-marketing-context-global first
Step 1: Pick region variant (US / EU / SEA / LATAM)
Step 2: Confirm prerequisites (NPS, AOV, LTV, customer base)
Step 3: Choose model (1-way / 2-way / multi-tier affiliate)
Step 4: Calculate incentive (15-25% of LTV)
Step 5: Set up tracking + anti-fraud
Step 6: Design referral flow (7 steps)
Step 7: Launch sequence (30-day plan)
Step 8: Measure K-factor / viral coefficient
```

---

## Step 0: Check global context

Check `.agents/product-marketing-context-global.md`:
- **Yes** -> Read product, customer, region. Do NOT re-ask.
- **No** -> Suggest running `product-marketing-context-global` first.

---

## Step 1: Pick region variant

Ask: **"Which is your PRIMARY region: US, EU, SEA, or LATAM?"**

```
Where do most of your customers (and their referrals) live?
    |-- US / Canada       --> 01-us.md    (TCPA SMS rules; CAN-SPAM email; CCPA data)
    |-- EU / EEA / UK     --> 02-eu.md    (GDPR consent for ALL channels)
    |-- Southeast Asia    --> 03-sea.md   (PDPA per country; mostly opt-in)
    |-- Latin America     --> 04-latam.md (LGPD Brazil; LFPDPPP Mexico)
    |-- Vietnam only      --> Use `18-referral-program` (VN skill)
```

---

## Step 2: Prerequisites — does referral make sense?

### When referral works

- NPS >= 40 (customers actively like you)
- Customer has natural reason to share (visible result, social currency, peer-relevant)
- AOV high enough to fund meaningful incentive (USD 50+ ideal)
- LTV high enough to justify CAC investment
- Existing base of 100+ happy customers to seed

### When referral does NOT work (skip this skill)

- NPS < 20 (customers don't like you yet — fix retention first)
- Sensitive product category (financial advice, intimate health) — referrals feel weird
- Very low AOV (< USD 10) — incentive economics don't work
- Pre-launch or no customer base — no one to refer

### Ask the user

1. Product type? (DTC / SaaS / Service / Subscription)
2. Average AOV and LTV?
3. Existing happy customer count?
4. Goal: more new customers, lower CAC, or higher engagement?

---

## Step 3: Referral models

### Model 1: One-way (referrer gets reward, referee gets nothing)

**When:** Premium product where referee will buy regardless of incentive
**Examples:**
- Tesla referral program (referrer gets credit, new buyer pays full price)
- Robinhood (referrer gets free stock; referee just signs up)

**Pros:** Lower cost
**Cons:** Lower conversion (referee has no extra reason to buy now)

### Model 2: Two-way (BOTH referrer and referee get rewards) — DEFAULT CHOICE

**When:** 80% of cases; psychological "win-win" feels generous to referrer
**Examples:**
- Airbnb (both get USD 25-50 credit)
- Uber (both get USD 5-15 credit)
- Dropbox (both get +500MB)

**Pros:** Higher conversion; referrer feels good giving "gift"
**Cons:** Higher cost per acquisition

**Standard 2-way structure:**

```
Referrer gets: Discount / credit / free product / cash / reward
Referee gets: Discount / free trial / bonus on first order
```

### Model 3: Multi-tier affiliate (% commission on revenue)

**When:** SaaS, high-ticket courses, premium DTC; want power-users / influencers
**Examples:**
- ConvertKit / Kit (30% recurring affiliate)
- Shopify (200% of monthly fee per signup)
- AWeber, Teachabl