/suede-referrals

name: suede-referrals
description: "Suede AI referral and affiliate program design: refer a friend and ambassador mechanics, incentive sizing from LTV and margin, affiliate commission structures, payout logic, fraud controls, attribution, FTC endorsement disclosure and incentivized-review rules, and viral loop measurement (K-factor, cohort LTV of referred customers). Returns a program spec with economics, rules, tooling options, and a launch checklist. Use when designing refer-a-friend mechanics, ambassador or partner incentives, affiliate programs, payout logic, or viral-loop measurement. NOT FOR: executing payouts or changing billing, co-marketing with a partner brand (use suede-co-marketing), launch-wide packaging (use suede-launch-packaging), lifecycle messaging (use suede-emails), or reporting unverified referral lift."
metadata:
  version: 2.1.0

Suede Referral & Affiliate Programs

Suede AI Referrals designs measurable customer, affiliate, and partner loops from incentive economics through attribution and fraud controls. It separates modeled loop performance from observed results and keeps activation and payouts behind approval.

Before Starting

**Check for product marketing context first:** If `.agents/product-marketing.md` exists (or `.claude/product-marketing.md`, or the legacy `product-marketing-context.md` filename, in older setups), read it before asking questions. Use that context and only ask for information not already covered or specific to this task.

Gather this context (ask if not provided):

1. Program Type

• Customer referral program, affiliate program, or both?
• B2B or B2C?
• What's the average customer LTV?
• What's your current CAC from other channels?

2. Current State

• Existing referral/affiliate program?
• Current referral rate (% who refer)?
• What incentives have you tried?

3. Product Fit

• Is your product shareable?
• Does it have network effects?
• Do customers naturally talk about it?

4. Resources

• Tools/platforms you use or consider?
• Budget for referral incentives?

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Referral vs. Affiliate

Customer Referral Programs

**Best for:**

• Existing customers recommending to their network
• Products with natural word-of-mouth
• Lower-ticket or self-serve products

**Characteristics:**

• Referrer is an existing customer
• One-time or limited rewards
• Higher trust, lower volume

Affiliate Programs

**Best for:**

• Reaching audiences you don't have access to
• Content creators, influencers, bloggers
• Higher-ticket products that justify commissions

**Characteristics:**

• Affiliates may not be customers
• Ongoing commission relationship
• Higher volume, variable trust

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Referral Program Design

The Referral Loop

Trigger Moment → Share Action → Convert Referred → Reward → (Loop)

Step 1: Identify Trigger Moments

**High-intent moments:**

• Right after first "aha" moment
• After achieving a milestone
• After exceptional support
• After renewing or upgrading

**Prompt cadence for customers who have not referred:** day 7, day 30, day 60, and after any milestone. The timing is this skill's call; the message copy is not: hand that to `suede-emails`.

Step 2: Design Share Mechanism

**Ranked by effectiveness:** 1. In-product sharing (highest conversion) 2. Personalized link 3. Email invitation 4. Social sharing 5. Referral code (works offline)

Step 3: Choose Incentive Structure

**Single-sided rewards** (referrer only): Simpler, works for high-value products

**Double-sided rewards** (both parties): Higher conversion, win-win framing

**Tiered rewards**: Gamifies referral process, increases engagement

**For program patterns and incentive sizing**: See [references/program-examples.md](references/program-examples.md)

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Program Optimization

Improving Referral Rate

**If few customers are referring:**

• Ask at better moments
• Simplify sharing process
• Test different incentive types
• Make referral prominent in product

**If referrals aren't converting:**

• Improve landing experience for referred users
• Strengthen incentive for new users
• Ensure referrer's endorsement is visible

A/B Tests to Run

**Incentive tests:** Amount, type, single vs. double-sided, timing

**Messaging tests:** Program description, CTA copy, landing page copy

**Placement tests:** Where and when the referral prompt appears

Common Problems & Fixes

| Problem | Fix | |---------|-----| | Low awareness | Add prominent in-app prompts | | Low share rate | Simplify to one click | | Low conversion | Optimize referred user experience | | Fraud/abuse | Apply the fraud controls below | | One-time referrers | Add tiered/gamified rewards |

Fraud Controls

Read [references/affiliate-programs.md](references/affiliate-programs.md) §Fraud Prevention before designing rewards or writing program terms: it carries the technical, policy, and structural control set (delayed payout after activation, device and IP signals, clawback on refunds, per-period caps, manual review of suspicious patterns). Every program in this skill uses it, customer referral programs included, not only affiliate programs.

Set these thresholds explicitly, because the reference leaves them open:

• Name the qualifying downstream event that releases a reward (a paid conversion

or day-N retention, N stated), never signup alone.

• Hold payouts until the refund/chargeback window has closed, and state that

window in days.

• State the dollar amount above which a payout goes to manual review before it

is released.

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Measuring Success

Key Metrics

**Program health:**

• Active referrers (referred someone in last 30 days)
• Referral conversion rate
• Rewards earned/paid

**Business impact:**

• % of new customers from referrals
• CAC via referral vs. other channels
• LTV of referred customers
• Referral program ROI

Typical Findings

Peer-reviewed field research (for example "Referral Programs and Customer Value," Journal of