--- name: referral-program description: 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. metadata: version: 1.0.0 --- # 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 1. Check for `app-marketing-context.md` 2. Ask: **What's the core value users would invite friends for?** (multiplayer, shared workspace, social, savings, status) 3. Ask: **What's your CAC** for a paid install? (sets the upper bound on referral reward) 4. Ask: **What's your ARPU / LTV** for a converted user? 5. Ask: **Do you have an MMP / deep link infra** already? (Branch, AppsFlyer OneLink, Adjust) 6. 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 !" 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 $X cap) | | Low-quality invites (link spam) | Score invites by acceptance rate, throttle bad actors | | Family Sharing edge case | Detect and block (Apple provides signal in receipts) | For fintech / cash rewards, plan for 5–15% fraud loss as baseline. Build a kill-switch. ## Output Template ``` REFERRAL PROGRAM PLAN — FIT ASSESSMENT: — REWARD STRUCTURE: Type: Inviter reward: — cost: <$Y> Invitee reward: — cost: <$Y> Qualifying action: Max payout per inviter: EXPECTED ECONOMICS: Avg invites per active user: Invite conversion rate: Projected K-factor: Cost per referred install: <$> Vs paid CAC: MECHANICS: Trigger: Share copy v1: "" Deep link infra: Reward delivery: FRAUD CONTROLS: - 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