Design a referral program and test it for fraud

You are a growth engineer designing a referral program. Design the LOOP, then check the MATH, then break your own design as a fraud analyst.

MY PRODUCT:
- What it is + price/AOV + gross margin: [X]
- The moment users experience clear value (be specific — an event, not a vibe): [X]
- Current retention/repeat behavior: [X]
- Payment context: [prepaid / COD / subscription] · Market: [X]
- What I can afford to give away per acquired customer (my current CAC for reference): [X]

DESIGN:

1. THE TRIGGER MOMENT
   Pick the exact event to ask after (first result achieved / delivery confirmed &
   product loved / milestone hit). Justify it. Add one secondary moment.
   Rule: never at signup, never at checkout — nobody refers before value lands.

2. INCENTIVE ARCHITECTURE (two-sided by default)
   - Referrer reward + new-user reward, each: what, when paid, and WHY this currency
     (product credit > cash for retention; cash > credit for low-frequency purchases).
   - Price it: both rewards together must cost meaningfully less than my CAC,
     after expected fraud/breakage. Show the math.
   - The ASK copy: 2 versions of the referral message the USER sends (the real ad
     is their message, not my UI) — natural, screenshot-able, in [language].

3. MECHANICS
   Share mechanism fitted to my market (link / code / WhatsApp-first for MENA),
   reward delivery timing (after the referred user's QUALIFYING event, not signup),
   and the qualifying event definition (for COD: delivered & paid, NOT ordered).

4. FRAUD & ABUSE PASS (attack your own design)
   Self-referral, disposable emails/numbers, coupon-site leakage, COD fake orders,
   reward farming. For each: the guard, and what the guard costs in honest-user friction.

5. HONEST PROJECTIONS
   Compute with participation and conversion assumptions LABELED as assumptions:
   - % of active users who share (single digits is normal), invites per sharer,
     invite→customer conversion → implied K factor.
   - State plainly: if K < 1 (it will be), referral is a CAC-reducing amplifier,
     not an engine. Project it as % of new customers (10-30% at maturity is a
     strong program), never as exponential growth.
   Context anchors: referred customers show +16% LTV and 18% lower churn
   (Wharton/Van den Bulte study); Dropbox at PEAK ran ~35% of signups from
   referrals with K≈0.35-0.7 — that's the ceiling story, not the base case.

6. THE MVP TEST
   Smallest honest version (manual codes + spreadsheet is fine), the 2 metrics
   that decide (sharer participation rate first — if <2% share, fix the moment
   or the product before touching the reward), and the 30-day decision rule.