referral-program▌
kostja94/marketing-skills · updated Apr 8, 2026
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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.
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:
- Product type: SaaS, AI tool, subscription
- User base: Size, engagement, retention
- 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
- Reward structure: Type (cash, discount, credits, free service); amount (10%-30% of price); trigger; cap
- Tracking: Choose method; set attribution window; first-touch rule
- UX: One-click share; clear rules; dashboard with referral data; notify on success
- Fraud prevention: See above
- 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
How to use referral-program on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add referral-program
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches referral-program from GitHub repository kostja94/marketing-skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate referral-program. Access the skill through slash commands (e.g., /referral-program) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
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Use Cases▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ Use When
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid When
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.7★★★★★38 reviews- ★★★★★Lucas Iyer· Dec 20, 2024
Useful defaults in referral-program — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Dhruvi Jain· Dec 8, 2024
I recommend referral-program for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Oshnikdeep· Nov 27, 2024
Useful defaults in referral-program — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Tariq Singh· Nov 11, 2024
I recommend referral-program for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Ganesh Mohane· Oct 18, 2024
referral-program is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Zara Reddy· Oct 2, 2024
referral-program reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Sakshi Patil· Sep 25, 2024
Keeps context tight: referral-program is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Aanya Patel· Sep 21, 2024
Solid pick for teams standardizing on skills: referral-program is focused, and the summary matches what you get after install.
- ★★★★★Yuki Flores· Sep 9, 2024
We added referral-program from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Fatima Okafor· Sep 5, 2024
I recommend referral-program for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
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