Best for
- Use when customers should bring other customers — one-way versus two-way incentives, reward structure and economics, trigger moments, referral messaging, tracking and attribution, fraud controls, and anti-spam complianc…
minhnv0807/ai-business-skills/skills/en/18-referral-program-global/SKILL.md
Use when customers should bring other customers — one-way versus two-way incentives, reward structure and economics, trigger moments, referral messaging, tracking and attribution, fraud controls, and anti-spam compliance by region: TCPA for US, GDPR for EU, PDPA for SEA, LGPD for LATAM. Trigger on 'referral program', 'refer a friend', 'word of mouth', 'viral loop', 'how do I get customers to bring friends', 'affiliate rewards'. Also use when the user has happy customers and no system to use them
Decision brief
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.
Compatibility matrix
| Platform | Status | Evidence | What to check |
|---|---|---|---|
| Codex | Not declared | No explicit evidence | Portability before use |
| Claude Code | Not declared | No explicit evidence | Portability before use |
| Cursor | Not declared | No explicit evidence | Portability before use |
| Gemini CLI | Not declared | No explicit evidence | Portability before use |
Installation
The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.
npx skills add https://github.com/minhnv0807/ai-business-skills --skill "skills/en/18-referral-program-global"Inspect the Agent Skill "18-referral-program-global" from https://github.com/minhnv0807/ai-business-skills/blob/958bd43b03afbc5afc42dfdb3fb2c087b23309e4/skills/en/18-referral-program-global/SKILL.md at commit 958bd43b03afbc5afc42dfdb3fb2c087b23309e4. List every install step, command, network request, credential, file read/write, external action, and rollback step. Explain whether it fits my task. Do not install or execute anything until I approve.
Workflow
Review the “Workflow” section in the pinned source before continuing.
Check .agents/product-marketing-context-global.md: - Yes - Read product, customer, region. Do NOT re-ask. - No - Suggest running product-marketing-context-global first.
Ask: "Which is your PRIMARY region: US, EU, SEA, or LATAM?"
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?
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)
Permission review
No configured static risk pattern was detected
This is not proof of safety. Runtime behavior, indirect dependencies, and hidden external systems are outside the static scan.
Evidence record
| Signal | Value | Evidence type | Meaning |
|---|---|---|---|
| Quality score | 95/100 | Computed | Documentation, specificity, maintenance, and trust rules |
| Repository stars | 553 | Source | Repository attention, not individual Skill quality |
| Compatibility | 0 platforms | Source | Declared in the catalog source record |
| Usage guide | automated source guide | Editorial | Generated or reviewed according to the visible evidence level |
Pinned source
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.
| 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 |
18-referral-program (VN skill) — Zalo / Messenger optimized27-personal-brand-monetize-global for influencer-affiliate (when available)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).
Without proper referral design:
Plan the legal foundation correctly, get the incentive math right, ship a working viral loop.
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
Check .agents/product-marketing-context-global.md:
product-marketing-context-global first.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)
When: Premium product where referee will buy regardless of incentive Examples:
Pros: Lower cost Cons: Lower conversion (referee has no extra reason to buy now)
When: 80% of cases; psychological "win-win" feels generous to referrer Examples:
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
When: SaaS, high-ticket courses, premium DTC; want power-users / influencers Examples:
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:
Total incentive (both sides combined) <= 15-25% of customer LTV
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
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)
| 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 |
| 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 |
| 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 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")
| 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 = 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).
# 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]
product-marketing-context-global — foundation14-email-marketing-global — email-driven referral mechanics27-personal-brand-monetize-global — affiliate / creator program (when available)references/global-legal-compliance — deep legal referenceGlobal Skill 18 (Referral Program) | Over Powers Agency | v1.0.0
Frequently asked questions
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.
The source record exposes this install command: npx skills add https://github.com/minhnv0807/ai-business-skills --skill "skills/en/18-referral-program-global". Inspect the command and pinned source before running it.
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