18 Referral Program Global Agent Skill

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

• SMS-based referral in US without TCPA consent -> Up to USD 1,500 per text fines + class actions
• Email-blast referred contacts in EU -> GDPR violation; referral programs touching EU prospects need explicit consent from the prospect, NOT just the referrer
• 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

• Product type? (DTC / SaaS / Service / Subscription)
• Average AOV and LTV?
• Existing happy customer count?
• 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, Teachable, Coursera (10-50% per sale)

Pros: Attracts professional affiliates / influencers; scalable

Cons: Requires legal disclosures (FTC US), tracking infrastructure (Rewardful, FirstPromoter), tax forms (W-9 in US, equivalents elsewhere)

Standard tier structure:

• Tier 1: 10-30% commission on first purchase
• Tier 2: 5-15% on recurring (next 90 days or lifetime)
• Top tier: 30-50% for super-affiliates (negotiated)

Step 4: Incentive math (CRITICAL)

The formula

Total incentive (both sides combined) <= 15-25% of customer LTV

Worked example (Saas)

Product: Project management SaaS
Pricing: USD 49/month
Average tenure: 18 months
LTV: USD 882 (49 x 18)

Incentive cap: 15-25% of LTV = USD 130-220 total

Two-way structure:
  Referrer: 1 month free (USD 49 value) + USD 30 credit = USD 79 cost
  Referee: 50% off first 2 months = USD 49 cost
  Total: USD 128 (within cap)

Or simpler:
  Both get 1 month free = USD 98 total cost
  ROI: USD 882 LTV - USD 98 incentive = USD 784 net per successful referral

Worked example (DTC)

Product: Skincare subscription
AOV: USD 50 / box
Average orders: 10
LTV: USD 500

Incentive cap: USD 75-125 total

Two-way structure:
  Referrer: USD 30 credit (next box)
  Referee: USD 20 off first box
  Total: USD 50 (well within cap)

Reward formats — pros and cons

| Format | Pros | Cons | Best for |

|--------|------|------|---------|

| Cash | Highest motivation | Highest cost (out of pocket) | Affiliate, B2B |

| Account credit | Keeps customer | Useless if customer leaves | Subscription, marketplace |

| Discount on next purchase | Pay-on-purchase | Customer may not return | E-commerce |

| Free product / service | Higher perceived value | Logistics complexity | Service, beauty, F&B |

| Physical gift | Tangible delight | Operational burden | Premium DTC |

| Points / rewards | Habit-forming | Requires loyalty system | Retailers, airlines |

Step 5: Tracking + anti-fraud

Tracking tools (region-agnostic)

| Tool | Best for | Pricing |

|------|---------|--------|

| ReferralCandy | Shopify DTC | USD 49+/mo |

| Rewardful | SaaS affiliate | USD 49+/mo |

| FirstPromoter | SaaS affiliate | USD 49+/mo |

| Friendbuy | Mid-market DTC | USD 249+/mo |

| Mention Me | Premium DTC | Enterprise |

| PartnerStack | B2B SaaS partnerships | USD 500+/mo |

| Talkable | Enterprise DTC | Enterprise |

| Build in-house | Full control | Custom |

Anti-fraud measures

| Risk | Defense |

|------|---------|

| Self-referral via second account | Match phone, address, payment, IP, device fingerprint |

| Public posting on coupon sites | Limit 3-5 redemptions per code; require minimum AOV |

| Bot / script signups | Captcha; rate limit; manual review for large batches |

| Cancel-after-reward | 30-day reward holding period (after return window) |

| Influencer abuse | Cap individual referrer rewards monthly; flag outliers |

| Referee buys then refunds | Hold rewards until past return window; partial reward if partial refund |

Step 6: 7-step referral flow

Step 1: Customer has good experience
   |--> Trigger when NPS >= 7 OR after 2nd purchase OR completion of service

Step 2: Customer sees referral CTA
   |--> Email after delivery, dashboard widget, post-purchase page, account menu

Step 3: Customer gets unique code/link
   |--> Personalized: "JANE25" or unique link with UTM tracking

Step 4: Customer shares (multiple channels)
   |--> Built-in share: WhatsApp, Email, SMS, Copy link, Twitter/X
   |--> Pre-filled message in customer's voice

Step 5: Friend clicks / enters code
   |--> Landing page tailored to referral (not generic homepage)
   |--> Reward visible upfront ("Get USD 20 off")

Step 6: Friend converts (purchase)
   |--> Tracking pixel fires; both parties receive notification
   |--> Reward delivered automatically (or held for 30 days)

Step 7: Cycle continues
   |--> Friend now eligible to refer; nudge after first delivery
   |--> Top referrers get bonus tiers ("3 referrals = VIP")

Step 7: 30-day launch sequence

Week 1: Setup

• Choose model (1-way / 2-way / multi-tier)
• Finalize incentive math (LTV calculation, reward structure)
• Pick tool (ReferralCandy / Rewardful / build)
• Create landing page for referee
• Set up email/SMS automation flows
• Set up tracking + attribution
• Legal review (per region variant)

Week 2: Soft launch (seed)

• Email top 50-100 happiest customers (NPS 9-10)
• Track first referrals; fix bugs
• Iterate on copy / friction points
• Verify reward delivery automation

Week 3: Public launch

• Email full customer base
• Add referral CTA to:
• Order confirmation page
• Post-delivery email
• Account dashboard
• Receipt PDF / packaging insert (offline)
• Social posts on owned channels
• Optional: paid promotion to existing customers ("Tell friends, both save")

Week 4: Optimize

• Identify top sharers (top 10%)
• Bonus push: "You're in top 10 — extra reward this month"
• A/B test:
• Landing page (referral vs. cold)
• Reward amount (USD 20 vs USD 30)
• Channel emphasis (email vs. SMS vs. WhatsApp)

Step 8: KPIs and viral coefficient

Key metrics

| Metric | Formula | Benchmark |

|--------|---------|-----------|

| Share rate | Referrers / total customers | 10% basic, 20% good, 30%+ excellent |

| Conversion rate | Successful redemptions / shares | 15% basic, 25% good, 40%+ excellent |

| Average referrals per sharer | Successful refs / sharers | 1.2 basic, 2+ good, 3+ excellent |

| K-factor (viral coefficient) | Share rate x Conversion rate x Avg refs | 0.3-0.5 typical, 1.0+ true viral |

| CAC via referral | Reward cost / referred customers | 30-50% of paid CAC |

| Referred customer LTV | Avg LTV of referred customers | Often 1.2x non-referred |

K-factor interpretation

K = 0.3 -> 100 customers bring 30 new -> sub-viral, supplements other channels
K = 0.7 -> 100 customers bring 70 new -> strong supplement
K = 1.0 -> 100 customers bring 100 new -> equilibrium (each customer replaces one)
K > 1.0 -> Viral loop! Exponential growth (rare but transformative)

Most healthy referral programs target K = 0.4-0.7. K > 1 is rare and usually requires unique product mechanics (Dropbox, WhatsApp, Calendly).

Output template

# Referral Program - [Brand]
Region: [US/EU/SEA/LATAM]
Date: [YYYY-MM-DD]

## 1. Goal
[New customers / Lower CAC / Higher LTV / Multiple]

## 2. Prerequisites confirmed
- NPS: [X]
- AOV: [USD/EUR/etc.]
- LTV: [calculated]
- Customer base: [N]

## 3. Model
[1-way / 2-way / multi-tier]

## 4. Incentive structure
- Referrer gets: [reward + cost]
- Referee gets: [reward + cost]
- Total cost: [USD X, ~Y% of LTV]

## 5. Tracking tool
[ReferralCandy / Rewardful / etc.]

## 6. Anti-fraud measures
[List all 5-7 measures applied]

## 7. Referral flow (7 steps)
[Description per step]

## 8. Launch sequence (30 days)
[Week 1-4 plan]

## 9. KPIs
[Share rate, Conversion rate, K-factor target]

## 10. Legal compliance
[Per region variant — see specific variant file]

Quality checklist

• [ ] Region variant chosen (US/EU/SEA/LATAM)
• [ ] NPS >= 40 confirmed (have happy customers)
• [ ] Total incentive cost <= 25% of LTV
• [ ] 2-way model unless strong reason for 1-way
• [ ] Tracking tool integrated and tested
• [ ] Anti-fraud measures live (5+)
• [ ] Reward delivery automated within 24h
• [ ] Legal compliance per region (TCPA / GDPR / PDPA / LGPD)
• [ ] Landing page for referees built
• [ ] K-factor target documented; measure at 30 / 60 / 90 days

Related skills

• product-marketing-context-global — foundation
• 14-email-marketing-global — email-driven referral mechanics
• 27-personal-brand-monetize-global — affiliate / creator program (when available)
• references/global-legal-compliance — deep legal reference

*Global Skill 18 (Referral Program) | Over Powers Agency | v1.0.0*