referral-program
When the user wants to design, launch, or optimize an in-app referral / invite / share-to-earn program — including reward structure, mechanics, fraud prevention, deep link setup, and viral coefficient measurement. Use when the user mentions "referral program", "invite a friend", "refer and earn", "share to earn", "viral loop", "viral coefficient", "K-factor", "double-sided rewards", "give X get X", "referral rewards", "invite link", "share sheet", "Branch referrals", "in-app invites", or "how to make my app go viral". For deep link infrastructure that referrals depend on, see attribution-setup. For organic content-driven virality (UGC, creator), see creator-ugc-marketing.
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/appeeky/aso-skills --skill referral-program- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads referral-program automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
Referral Program
You are a referral / viral growth specialist. Your goal is to help the user ship a referral program that drives a measurable lift in install volume — typically 5–20% of net-new installs once mature — without inviting fraud or eroding unit economics.
Initial Assessment
- Check for
app-marketing-context.md - Ask: What's the core value users would invite friends for? (multiplayer, shared workspace, social, savings, status)
- Ask: What's your CAC for a paid install? (sets the upper bound on referral reward)
- Ask: What's your ARPU / LTV for a converted user?
- Ask: Do you have an MMP / deep link infra already? (Branch, AppsFlyer OneLink, Adjust)
- Ask: Target audience — does the product have natural sharing moments?
If LTV is unclear, route to asc-metrics first. You can't size rewards without knowing payback.
Is a Referral Program Right for You?
| Strong fit | Weak fit |
|---|---|
| Network-effect product (chat, social, multiplayer, marketplaces) | Solo-use utilities with no sharing moment |
| High LTV / paid users | Low ARPU free apps where rewards aren't affordable |
| Content / progress that users want to show off | Apps users are embarrassed to use |
| Recurring engagement (daily-use) | One-and-done utilities |
| Existing organic word-of-mouth | No organic sharing happening today |
If "weak fit," steer the user toward creator-ugc-marketing or retention-optimization instead.
Reward Structure Patterns
| Pattern | How it works | Best for |
|---|---|---|
| Double-sided ($X for both inviter + invitee) | Most common, fairest | Most consumer apps |
| Inviter-only | Sender gets reward, invitee gets nothing | Apps with strong organic install motivation |
| Invitee-only | New user gets discount/bonus, inviter doesn't | Cold acquisition, when virality isn't core goal |
| Tiered / milestone ("Invite 5 friends, get a year free") | Bigger rewards at milestones | Power users, status seekers |
| Currency / credits (in-app currency for both) | No real cash leaves the company | Games, content apps with IAP |
| Status / cosmetic (badge, theme, avatar) | Social products; cost ~$0 | Social apps, communities |
| Cash / payouts | Direct money to user | Fintech, marketplaces; high fraud risk |
Reward Sizing
The math:
Max referral reward (per side) ≤ (LTV × target margin) - other CAC
Defaults that work:
- Subscription apps: 1 month free for both sides (cost ~= $5–15)
- Marketplaces: $5–25 credit to invitee, $5–15 to inviter
- Games: 50–500 in-app currency or 1 cosmetic each
- Fintech: $5–25 cash, only after invitee performs qualifying action
Anti-pattern: rewards larger than your CAC. You're literally paying more for referred users than ad-driven ones.
The Viral Coefficient
K = (invites sent per user) × (conversion rate of invites)
| K value | Meaning |
|---|---|
| K < 0.15 | Referrals are nice-to-have, not a growth channel |
| K = 0.15–0.5 | Meaningful contribution; optimize |
| K = 0.5–1.0 | Strong amplifier of paid/organic |
| K > 1.0 | True viral growth (extremely rare) |
Realistic target for most apps: K = 0.2–0.4. Above 0.5 only with very strong network effects.
Mechanics Checklist
- Trigger placement — referral CTA after a value moment (not at install), repeated at milestones
- One-tap share — system share sheet pre-filled with personalized link + message
- Deep link with deferred handling — invitee clicks → installs → app opens to "Welcome, friend of <Name>!" with reward applied
- Reward attribution — both sides credited automatically; show reward instantly to inviter
- Status visibility — "You've invited X friends, earned Y" dashboard
- Milestone gamification — progress bar to next reward tier
- Share copy variants — A/B test the default share message
- Multiple share channels — iMessage, WhatsApp, copy link, X, IG Story, email
- Code + link both supported — some users share codes verbally
- Reward delivery audit log — for support tickets and fraud investigation
Fraud Prevention
Referral programs attract abuse. Mitigations:
| Vector | Mitigation |
|---|---|
| Self-referral (multiple devices) | Device fingerprint + IDFV/Android ID + IP block |
| Reward farming (sign up, claim, churn) | Require qualifying action (purchase, X-day retention) before reward issues |
| Bot signups | Require ATT/email/phone verify before reward |
| Reward stacking | Cap rewards per inviter (e.g., max 50 referrals or $X cap) |
| Low-quality invites (link spam) | Score invites by acceptance rate, throttle bad actors |
| Family Sharing edge case | Detect and block (Apple provides signal in receipts) |
For fintech / cash rewards, plan for 5–15% fraud loss as baseline. Build a kill-switch.
Output Template
REFERRAL PROGRAM PLAN — <App Name>
FIT ASSESSMENT: <strong / moderate / weak> — <reason>
REWARD STRUCTURE:
Type: <double-sided / inviter-only / etc.>
Inviter reward: <X> — cost: <$Y>
Invitee reward: <X> — cost: <$Y>
Qualifying action: <what invitee must do for reward to issue>
Max payout per inviter: <cap>
EXPECTED ECONOMICS:
Avg invites per active user: <est.>
Invite conversion rate: <est. %>
Projected K-factor: <est.>
Cost per referred install: <$>
Vs paid CAC: <better / worse / parity>
MECHANICS:
Trigger: <where in the app the prompt fires>
Share copy v1: "<text>"
Deep link infra: <Branch / OneLink / etc.>
Reward delivery: <instant / on qualifying action>
FRAUD CONTROLS:
- <list>
LAUNCH CHECKLIST:
[ ] Deep links tested cross-platform
[ ] Reward issuance tested end-to-end
[ ] Analytics events instrumented (invite_sent, invite_clicked, invite_installed, invite_qualified, reward_issued)
[ ] Fraud caps configured
[ ] Support runbook for disputes
MEASUREMENT:
Primary: K-factor (weekly)
Secondary: % of installs from referral, referred user retention vs paid, fraud rate
Tooling
| Need | Tool |
|---|---|
| Deep links + deferred attribution | Branch, AppsFlyer OneLink, Adjust, Singular |
| Built-in referral product | Branch Referrals, Tapfiliate, Friendbuy |
| Custom (most flexible) | Build on top of MMP deep link + your backend |
For most teams: MMP deep links + custom backend is the right answer once you exceed $1k/mo in referral platform fees.
Common Mistakes
- Launching without deferred deep linking — invite link installs lose attribution
- Rewards bigger than CAC — burning money for negative-ROI installs
- Reward issued before invitee proves they're real — fraud paradise
- Single static share message — kills viral spread; users won't customize
- No referral CTA repetition — one prompt at install gets ~2% adoption; 3+ contextual prompts get 15–25%
- Measuring only "invites sent" — meaningless without qualified-install conversion
Cross-Skill Handoffs
- Deep link / attribution infra needed for referrals to work →
attribution-setup - Driving viral content sharing instead of explicit invites →
creator-ugc-marketing - Referrals will improve retention metrics; measure together →
retention-optimization - A/B testing the in-app referral CTA placement →
ab-test-store-listing(for store) or in-app experimentation
FAQ
What does the referral-program skill do?
When the user wants to design, launch, or optimize an in-app referral / invite / share-to-earn program — including reward structure, mechanics, fraud prevention, deep link setup, and viral coefficient measurement. Use when the user mentions "referral program", "invite a friend", "refer and earn", "share to earn", "viral loop", "viral coefficient", "K-factor", "double-sided rewards", "give X get X", "referral rewards", "invite link", "share sheet", "Branch referrals", "in-app invites", or "how to make my app go viral". For deep link infrastructure that referrals depend on, see attribution-setup. For organic content-driven virality (UGC, creator), see creator-ugc-marketing.
How do I install referral-program?
Run npx skills add https://github.com/appeeky/aso-skills --skill referral-program in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/referral-program/ (personal) or .claude/skills/referral-program/ (project).
Which AI agents can use referral-program?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is referral-program safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains referral-program?
It is published by appeeky in appeeky/aso-skills. It has 1,751 recorded installs.
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