Referral Engine

SKILL.md

---
name: referral-engine
description: Design a customer referral program with incentive structures, sharing mechanics, fraud prevention rules, and tracking setup that turns existing buyers into a scalable acquisition channel.
---

# Referral Engine

Design a complete customer referral program that transforms your existing buyer base into a reliable, low-cost acquisition channel. This skill walks you through building incentive structures, defining sharing mechanics across platforms, setting up fraud prevention guardrails, and establishing tracking infrastructure so every referral dollar is accountable and every new customer is attributed correctly.

## Use when

- You want to launch a refer-a-friend program for your Shopify, TikTok Shop, or Amazon storefront and need a structured plan covering incentives, rules, and tracking
- A founder or growth manager says "we need our customers to bring us more customers" and you need to design the full referral loop from scratch
- You are evaluating whether to offer cash-back, store credit, percentage discounts, or free products as referral rewards and need a framework to decide
- Your existing referral program has low participation or high fraud rates and you need to redesign the incentive structure and add abuse prevention rules

## What this skill does

This skill analyzes your product type, average order value, customer lifetime value, and existing marketing channels to design a referral program tailored to your business. It determines the optimal reward type and amount for both the referrer and the referred friend, maps out the sharing flow across email, SMS, social media, and unique referral links, defines fraud prevention rules such as self-referral blocks, IP deduplication, minimum purchase requirements, and velocity limits, and produces a tracking plan covering attribution windows, conversion events, and reporting dashboards. The output is a ready-to-implement blueprint that balances generosity with profitability.

## Inputs required

- **Product category and AOV** (required): What you sell and the average order value, so reward sizing is proportional to margin — e.g., "skincare, AOV $45"
- **Estimated customer LTV** (required): Rough lifetime value per customer so the skill can set a reward ceiling that keeps CAC below LTV — e.g., "$120 over 12 months"
- **Sales channels** (required): Where you sell (Shopify storefront, TikTok Shop, Amazon, retail) so sharing mechanics and tracking are channel-appropriate
- **Current referral setup** (optional): Describe any existing program or past attempts so the skill can diagnose issues rather than starting from zero
- **Tech stack** (optional): Tools you use (Klaviyo, ReferralCandy, Smile.io, custom code) so recommendations are compatible with your infrastructure

## Output format

The output is a structured referral program blueprint divided into six sections. First, a Program Summary with the reward model, referral flow diagram, and projected economics. Second, an Incentive Design section specifying exact reward types, amounts, and conditions for both referrer and referee, including tiered bonuses for power referrers. Third, a Sharing Mechanics section detailing channel-specific sharing flows for email, SMS, WhatsApp, Instagram, and unique referral links with sample copy for each. Fourth, a Fraud Prevention section listing specific rules — self-referral blocking, IP and device fingerprint checks, minimum purchase thresholds, velocity caps, and manual review triggers. Fifth, a Tracking and Attribution section covering UTM parameters, cookie windows, conversion pixels, and dashboard KPIs. Sixth, a Launch Checklist with phased rollout steps from soft launch to full promotion.

## Scope

- Designed for: ecommerce operators, DTC brand teams, growth managers
- Platform context: Shopify, TikTok Shop, Amazon, WooCommerce, platform-agnostic
- Language: English

## Limitations

- Does not integrate directly with referral software APIs — outputs a plan you implement in your chosen tool
- Reward economics are estimates based on inputs you provide; actual results depend on customer behavior and market conditions
- Does not provide legal advice on referral program compliance with local regulations; consult a lawyer for sweepstakes or cash-reward legality in your jurisdiction