Skills Agentes

Referral Program

Diseña programas de referidos y loops de crecimiento viral: usarlo para sistemas de referidos, mecánicas virales, campañas de boca a boca o programas de embajadores.

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688

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25

0–100, la ruta de este skill

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hace 7 meses

último commit aquí

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últimos 90 días

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Instalar

Funciona con cualquier agente que lea SKILL.md

npx -y skills add OpenClaudia/openclaudia-skills --skill referral-program --agent claude-code

Se instala solo en este repositorio.

Qué hace

  • Diseña estructuras de programas de referidos (unilateral, bilateral, escalonado)
  • Calcula el coeficiente viral (K) y el tiempo de ciclo viral
  • Genera plantillas de landing page, emails y mensajes para canales sociales
  • Aporta checklist de implementación técnica y prevención de fraude
  • Define métricas clave y tests A/B para medir el programa

Úsalo cuando

  • Se pide crear sistemas de referidos, mecánicas virales o campañas de boca a boca
  • Se necesitan loops de crecimiento, sistemas de invitación o programas de ambajadores
  • Se busca calcular o mejorar el coeficiente viral de un producto

No lo uses cuando

    Qué lo activa

    Di cualquiera de estas frases y el agente debería cargar este skill.

    • Diseña un programa de referidos bilateral para mi app
    • Calcula el coeficiente viral de mi producto con estos datos
    • Necesito plantillas de email para mi campaña de referidos
    • Crea una landing page para referidos estilo Airbnb

    SKILL.md

    En inglés

    Referral Program Design

    Design effective referral programs and viral loops that drive sustainable growth.


    1. Referral Program Frameworks

    One-Sided Incentives

    Only the referrer gets rewarded.

    Best for:

    • Products with strong organic word-of-mouth
    • Low-friction signups where the referred user needs no extra motivation
    • Cost-sensitive businesses

    Examples:

    • Uber: "$10 credit for every friend you refer"
    • Amazon Associates: Commission on referred purchases

    Template:

    Refer a friend and get [reward].
    Share your unique link: [referral_url]
    

    Two-Sided Incentives

    Both referrer and referred user get rewarded.

    Best for:

    • Products requiring activation effort from new users
    • Competitive markets where new users need a nudge
    • Subscription businesses

    Examples:

    • Dropbox: Both get 500MB extra storage
    • Airbnb: Referrer gets $25 credit, friend gets $40 off first stay
    • PayPal: Both get $10 when friend makes first transaction

    Template:

    Give [friend_reward], get [referrer_reward].
    Share your link and you both win: [referral_url]
    

    Tiered Incentives

    Rewards increase with number of successful referrals.

    Example tier structure:

    Referrals Reward
    1 Free month
    3 Exclusive feature unlock
    5 Premium plan for 3 months
    10 Lifetime premium access
    25 Cash payout or swag box

    Best for:

    • Creating power referrers / ambassadors
    • Products with passionate user bases
    • Building a referral leaderboard culture

    2. Viral Coefficient Calculation

    The viral coefficient (K-factor) determines whether your referral loop is self-sustaining.

    Formula

    K = i * c
    
    Where:
      i = number of invites sent per user
      c = conversion rate of each invite
    
    If K > 1: viral growth (each user brings more than one new user)
    If K < 1: referrals supplement but don't replace other acquisition
    

    Example Calculation

    Users send an average of 5 invites (i = 5)
    15% of invites convert to signups (c = 0.15)
    K = 5 * 0.15 = 0.75
    
    With 1,000 initial users:
    - Cycle 1: 1,000 * 0.75 = 750 new users
    - Cycle 2: 750 * 0.75 = 563 new users
    - Cycle 3: 563 * 0.75 = 422 new users
    - Total after 10 cycles: ~3,570 additional users from referrals
    

    Viral Cycle Time

    The speed of the viral loop matters as much as K:

    Effective growth = K / cycle_time
    
    A K of 0.5 with a 1-day cycle > K of 0.8 with a 30-day cycle
    

    How to Improve K

    Lever Action
    Increase invites (i) Make sharing frictionless, prompt at key moments
    Increase conversion (c) Better landing page, stronger incentive, social proof
    Reduce cycle time Instant reward delivery, real-time notifications

    3. Referral Channels

    Email Referral

    Pros: High conversion, personal, trackable Cons: Lower volume, requires email access

    Template:

    Subject: I thought you'd like [Product] -- here's [reward] to try it
    
    Hey [Name],
    
    I've been using [Product] for [time] and it's been great for [specific benefit].
    
    I wanted to share my referral link so you can get [friend_reward]:
    [referral_url]
    
    [Your name]
    

    Social Media Sharing

    Pros: High reach, low effort, viral potential Cons: Lower conversion rate, less personal

    Platform-specific templates:

    Twitter/X:

    I just [achievement/milestone] with @Product! If you want to try it,
    use my link and we both get [reward]: [referral_url]
    

    LinkedIn:

    I've been using [Product] to [professional benefit] and the results
    have been impressive: [specific metric].
    
    If you're looking for [solution], here's my referral link
    (we both get [reward]): [referral_url]
    

    WhatsApp/SMS:

    Hey! I've been using [Product] and really like it. They have a
    referral deal -- we both get [reward] if you sign up through my link:
    [referral_url]
    

    In-App Referral

    Pros: Highest intent, contextual, frictionless Cons: Only reaches existing users

    Best practices:

    • Show referral prompt after a success moment (completed task, achievement, positive outcome)
    • Pre-populate sharing message
    • Show referral progress and rewards earned
    • Add referral widget to account/settings page

    Unique Link vs. Referral Code

    Method Pros Cons
    Unique link Frictionless, works in any channel Harder to share verbally
    Referral code Easy to remember, shareable verbally Extra step at signup
    Both Maximum flexibility More complex to implement

    4. Referral Landing Page Template

    The page a referred user sees when they click the referral link.

    Structure

    [Hero Section]
    - Headline: "[Referrer's name] invited you to [Product]"
    - Subheadline: "Sign up now and get [friend_reward]"
    - CTA button: "Claim your [reward]"
    
    [Social Proof]
    - "[Referrer's name] and X others use [Product]"
    - Logos of known customers
    - Key metric: "Trusted by X users"
    
    [Value Proposition]
    - 3 key benefits with icons
    - Brief product description
    
    [How It Works]
    - Step 1: Sign up (takes 30 seconds)
    - Step 2: [Key activation action]
    - Step 3: Enjoy [reward] + the product
    
    [CTA Repeat]
    - "Join [Referrer's name] on [Product]"
    - Urgency: "This offer expires in [X days]"
    
    [FAQ]
    - When do I get my reward?
    - What does [Product] do?
    - Is there a catch?
    

    5. Case Studies

    Dropbox (2008-2010)

    • Mechanic: Two-sided -- both get 500MB extra storage
    • Result: 3,900% growth in 15 months (100K to 4M users)
    • Key insight: The reward (storage) was the product itself, making it self-reinforcing
    • Viral coefficient: Estimated ~0.6-0.7 (supplemental, not purely viral)

    Airbnb (2014)

    • Mechanic: Two-sided -- $25 travel credit for referrer, $40 off first booking for friend
    • Result: 300% increase in bookings from referral program 2.0
    • Key insight: Redesigned referral page to feel like a gift, not spam. Personalized with referrer's photo and travel history
    • Viral coefficient: Low K but high LTV per referred user

    PayPal (1999-2000)

    • Mechanic: Two-sided -- $20 per referral (later reduced to $10, then $5)
    • Result: 7-10% daily growth, reaching 1M users in first year
    • Key insight: Cash incentive drove massive initial growth, then reduced as network effects kicked in
    • Cost: $60-70M in referral bonuses, but each user was worth much more in LTV

    Robinhood (2014-2015)

    • Mechanic: Wait-list with move-up-the-line incentive + free stock for referrals
    • Result: 1M waitlist signups before launch
    • Key insight: Scarcity (waitlist) + social proof (your position) + tangible reward (free stock)

    6. Implementation Checklist

    Technical Setup

    • Generate unique referral links/codes per user
    • Build referral tracking (link clicks, signups, activations, rewards)
    • Set up attribution window (how long after click does signup count?)
    • Implement fraud detection (self-referral, fake accounts, VPN abuse)
    • Build reward fulfillment (automatic credit, manual approval, or hybrid)
    • Create referral dashboard for users (invites sent, pending, completed, rewards earned)

    Fraud Prevention

    • Block self-referrals (same IP, same device, same email domain)
    • Require activation action before reward (not just signup)
    • Set daily/weekly referral limits per user
    • Flag suspicious patterns (bulk signups from same IP range)
    • Implement clawback for fraudulent referrals

    Program Design Decisions

    Decision Options
    Reward type Cash, credit, product features, swag, charity donation
    Reward timing On signup, on activation, on first purchase
    Reward amount Test multiple amounts; higher is not always better
    Expiration Referral links expire after X days? Rewards expire?
    Limit Max referrals per user per month?
    Eligibility All users or only paid/active users?

    7. Referral Email Sequences

    Invite Reminder (to existing users)

    Subject: You have [X] invites waiting
    
    Hey [Name],
    
    Did you know you can give your friends [reward] and get [reward] for yourself?
    
    You've invited [0/N] friends so far. Share your link:
    [referral_url]
    
    Here's what [Product] users are saying:
    "[Testimonial]" -- [Customer name]
    

    Referred User Welcome

    Subject: [Referrer] sent you a gift -- [reward] inside
    
    Hey there!
    
    [Referrer's name] thinks you'd love [Product], so they're giving you [reward] to try it.
    
    [CTA: Claim your reward]
    
    What is [Product]?
    [1-sentence description]
    
    What you'll get:
    - [Benefit 1]
    - [Benefit 2]
    - [Benefit 3]
    - Plus [friend_reward] from [Referrer's name]
    
    This offer expires in [X] days.
    

    Referral Success Notification

    Subject: [Friend's name] just signed up -- you earned [reward]!
    
    Great news, [Name]!
    
    [Friend's name] accepted your invitation and signed up for [Product].
    Your [reward] has been added to your account.
    
    Keep sharing: you've referred [X] friends so far.
    [referral_url]
    
    [Show progress toward next tier if using tiered rewards]
    

    8. Measuring Success

    Key Metrics

    Metric Formula Good Benchmark
    Participation rate Users who share / total users 15-25%
    Shares per user Total shares / participating users 3-5
    Click-through rate Link clicks / shares 20-40%
    Conversion rate Signups / link clicks 10-25%
    Viral coefficient (K) Invites * conversion rate 0.3-0.7 typical
    Viral cycle time Avg days from invite to new user's first invite 1-7 days
    Referral revenue Revenue from referred users Track separately
    CAC via referral Reward cost / acquired users Compare to paid CAC

    A/B Tests to Run

    1. Reward amount ($10 vs $20 vs $50)
    2. Reward type (credit vs cash vs feature unlock)
    3. One-sided vs two-sided incentive
    4. Referral prompt timing (after signup vs after first success)
    5. Landing page copy (gift framing vs deal framing)
    6. Email subject lines for referral invites
    7. Social sharing copy variations

    Reproducido de OpenClaudia/openclaudia-skills bajo licencia MIT. Leer esta página en markdown.

    Archivos

    1 archivo en el paquete. Solo se lee SKILL.md al activarse — las referencias se cargan si el skill decide que las necesita.

    Detalles

    Categoría
    Marketing
    Licencia
    MIT
    Recursos incluidos
    Solo SKILL.md
    Código fuente
    Ver SKILL.md

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