Skill: kostja94/referral-program-channels (version 1.0.1)

--- name: referral-program description: When the user wants to plan, implement, or optimize referral program strategy. Also use when the user mentions "referral program," "referral marketing," "user referral," "refer-a-friend," "word-of-mouth growth," "referral rewards," "referral tracking," "referral code," "referral incentives," or "viral loop." For referral landing copy, use landing-page-generator. metadata: version: 1.0.1 --- # Channels: Referral Guides referral program strategy for AI/SaaS products. Leverage existing users to drive growth; 3%-5% conversion vs 1%-2% for ads; CAC 50%-70% lower; referred users LTV 30%-50% higher, retention 20%-30% higher. Referral is necessity in overseas markets, not alternative. **When invoking**: On **first use**, if helpful, open with 1-2 sentences on what this skill covers and why it matters, then provide the main output. On **subsequent use** or when the user asks to skip, go directly to the main output. ## Initial Assessment **Check for project context first:** If `.claude/project-context.md` or `.cursor/project-context.md` exists, read it for product, audience, and value proposition. Identify: 1. **Product type**: SaaS, AI tool, subscription 2. **User base**: Size, engagement, retention 3. **Goal**: Signups, purchases, or both ## Referral vs. Affiliate vs. Influencer | Dimension | Referral | Affiliate | Influencer | |-----------|----------|-----------|------------| | **Who** | Existing users | Professional promoters | KOLs | | **Incentive** | Discounts, credits | Commission | Fees, product | | **Barrier** | Low (all users) | Medium | High | | **Conversion** | 3%-5% | Varies | Varies | **Referral vs affiliate**: Referral needs no landing page or application; integrated in dashboard. Affiliate requires landing page and approval. ## Reward Models | Model | Use | |-------|-----| | **Two-way** | Both referrer and referee get rewards; highest participation | | **One-way** | Only referrer rewarded; cost control | | **Tiered** | Rewards increase with referral count (e.g. $10 for 1-5, $15 for 6-10, $20 for 11+); incentivizes volume | **Benchmark**: Rewards typically 10%-30% of product price; ~11% off or ~$21 value; weak incentives = low participation. Triggers: signup, purchase, activation, or sustained use. ## Mechanism Types | Type | Use | |------|-----| | **Link-based** | Unique referral link; easy to implement; accurate tracking; share via email, social, SMS; works for web and app | | **Code-based** | Referral code (e.g. FRIEND20); memorable; offline events; mobile-friendly input | | **Social referral** | Share buttons (Facebook, X, LinkedIn); viral spread; friend trust; young users | ## Tracking & Attribution | Method | Use | |-------|-----| | **Cookie** | Web apps; 30-90 day window | | **URL params** | All platforms; persistent in link | | **Referral code** | Mobile, offline; manual entry | | **Account association** | Long-term tracking; subscription products | **Attribution window**: 30-90 days typical; 180 days for subscription. First-touch attribution to avoid double-counting. ## Fraud Prevention | Risk | Action | |------|--------| | **Self-referral** | Detect same device, payment, IP | | **Fake accounts** | Validate email, payment; monitor patterns | | **Bulk/automation** | Rate limits; anomaly detection | | **Per-user cap** | e.g. Max 10 referrals per user | Use tool anti-fraud features; audit referrals regularly. ## Design Framework 1. **Reward structure**: Type (cash, discount, credits, free service); amount (10%-30% of price); trigger; cap 2. **Tracking**: Choose method; set attribution window; first-touch rule 3. **UX**: One-click share; clear rules; dashboard with referral data; notify on success 4. **Fraud prevention**: See above 5. **Monitor & optimize**: Referral rate, conversion, CAC, LTV; A/B test rewards and flow ## Best Practices - **Run multiple programs**: Target different audiences, stages, goals - **Tiered rewards**: Motivate top performers; progressive incentives - **Friction-free sharing**: Mobile-friendly; one-click share - **Time-boxed incentives**: "Refer this week for $15 off" creates urgency - **Placement**: Web, email, app, in-product touchpoints; dashboard integration primary ## Implementation | Approach | Use | |----------|-----| | **Self-build** | Full control; low cost; URL params or cookie + reward logic + fraud checks; open-source (e.g. RefRef) for faster start | | **Third-party** | Fast launch; Cello, Viral Loops, ReferralCandy (e-commerce), Impact (enterprise); monthly fee | **Placement**: Most programs integrate in product dashboard; no landing page or application needed. Optional landing page for value prop, rewards, and case studies. **Startup cost**: Typically hundreds for tools + dev. ## Tools | Tool | Use | |------|-----| | **Cello** | SaaS; AI-driven automation | | **Viral Loops** | Referral + waitlist + contests | | **ReferralCandy** | Shopify, e-commerce | | **Impact** | Enterprise; unified platform | | **RefRef** | Open-source; self-hosted | ## KPIs Referral rate, conversion, CAC, LTV of referred users, referred-user retention. ## Output Format - **Reward model** and mechanism type (link/code/social) - **Tracking** approach and attribution window - **Placement** (dashboard vs landing page) - **Fraud prevention** measures - **Tool** selection (self-build vs third-party) - **KPI** framework ## Related Skills - **discount-marketing-strategy**: Referral rewards (discounts, credits); 10–30% benchmark; campaign design - **affiliate-marketing**: Different audience; can run both - **influencer-marketing**: Brand building vs. user-driven growth - **directory-submission**: Directory submission for discovery; referral for user-driven growth - **analytics-tracking**: Referral link tracking, UTM


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)