Build a referral program in a week

Referral programs work when (a) your customers love the product enough to share unprompted (you've seen organic referrals already), (b) the LTV is high enough to fund a meaningful incentive, (c) the customer's network looks like your ICP. If any of those is missing, a referral program will at best move zero dollars and at worst attract fraud. Pre-mortem first: do you have 1+ unprompted referrals in the last 90 days?

Bad incentive math is how referral programs lose money. Compute: cost per referred conversion = referrer reward + referee discount + platform fees + fraud allowance. The total must be less than 30-40% of LTV to make sense. If your LTV is $500 and your incentive structure costs $200/conversion, you're paying CAC$200 against LTV$500 — workable if margin allows, dangerous if cash flow is tight.

Model 3 incentive variants for this referral program.

Read the Brief for unit economics (LTV, gross margin, current CAC).

Output a table with 3 rows:
- Variant A: Cash reward (e.g. $25 referrer, $25 referee)
- Variant B: Credit reward (e.g. $50 credit referrer, $50 credit referee)
- Variant C: Subscription extension (e.g. 1 free month referrer, 1 free month referee)

For each:
1. All-in cost per conversion (incentive + processing fees + fraud allowance)
2. % of LTV that represents
3. Psychological pull (cash > credit > extension for new customer; extension > credit > cash for retention)
4. Operational complexity (cash = highest, extension = lowest)
5. A flag if any variant exceeds 40% of LTV

Recommend the variant that hits 25-30% of LTV with strong psychological pull. Show the math.

Double-sided incentives (both referrer and referee get something) outperform single-sided by 2-5x in research. The referrer's social cost of asking goes down ('here's a free thing for you'), the referee has a reason to act now. Single-sided makes sense only when the referrer reward alone is large enough to overcome social cost (e.g. cash bounties for B2B referrals at $500+ per close).

Attribution is what separates a real referral program from a wishful one. Every invite link must carry a unique referrer ID, that ID must persist through signup (cookie + URL param), and the referee's eventual conversion to paid must be traceable back. If you can't trace it, you can't pay it, and referrers stop sharing.

Referrers will share if they can see (a) who they referred, (b) what status that referral is at (signed up / paid / pending payout), (c) how much they've earned, (d) when the next payout is. The dashboard is the daily proof the program is real. Without it, referrers share once and forget.

Draft the customer-facing copy for the referral dashboard + share flows.

Read the Brief for the incentive structure + the audience.

Output:
1. Dashboard page heading + 1-line subhead
2. Empty state ("you haven't referred anyone yet — here's your link")
3. Active state copy with placeholders ("you've referred X, earned $Y, pending $Z")
4. Share buttons (Twitter, LinkedIn, email) with pre-filled copy
5. Celebration email triggered when a referee pays for the first time
6. Monthly recap email template with status + total

Constraints:
- Second-person, conversational, no marketing fluff
- Pre-filled share copy is honest about what we offer (don't oversell)
- Email subject lines under 50 chars

T&C is what saves you when a referrer tries to game the program. Spell out: who's eligible, how attribution works (last-touch / first-touch), payout window, fraud detection rules, the right to revoke for fraud, geographic exclusions if any, payment method. Bad T&C means you can't enforce; good T&C means you can revoke 1 fraudster's payout without 100 angry support tickets from confused legitimate referrers.

Day 1 of a referral program is the day fraudsters arrive. Sock-puppet rings (one person creating 10 fake accounts to refer themselves) are common. Build basic detection in: same IP across referrer + referee, same payment card hash, throwaway email domain blocklist, referrer-to-referee-conversion velocity caps. None of this is bulletproof; all of it slows fraud enough that they go pick on someone else.

Automated payouts via Stripe Connect / PayPal are the right end state but overkill for week 1. Start manual: monthly review of the conversions table, manual approve, manual issue rewards (Stripe coupons, account credits, gift cards). Automate after you've seen 100+ payouts and you know the patterns. Don't optimize the payout pipeline before you have referrers using the program.

Before the full launch, soft-launch to your most-engaged 50-100 customers. They'll find the bugs, the unclear copy, the broken share flows, the attribution edge cases. Do it for 1 week. Fix the issues. Then do the public launch announcement.

Vanity metric: 'we paid out $5K in referrals this month'. Real metric: 'referred customers from the program have a 90-day LTV of $200 vs $180 organic baseline, on $5K of payouts that drove $40K of incremental gross revenue'. Cohort the referred customers vs organic baseline by month and watch retention / expansion separately. Programs that look good on paid-out volume can be unprofitable on incremental LTV.

Compute this month's referral program ROI.

Pull from the Conversions table + your DB:
1. Total conversions in the month, % flagged for fraud
2. Total payouts (cash equivalent)
3. Referred-customer 30-day LTV vs organic 30-day LTV (cohort by signup month)
4. Incremental gross revenue (referred LTV - organic LTV) * conversion count
5. ROI = (incremental_revenue - payouts) / payouts
6. Trend vs prior month

Flag in the report:
- ROI < 0 (program is losing money — investigate)
- Fraud rate > 10% (detection is weak — tune rules)
- Referred-customer 30-day LTV < 80% of organic (audience mismatch — tune incentive structure)

Output as a 1-page summary in the Brief.