Referral Program
Design or tune customer referral and affiliate incentives so word-of-mouth lowers CAC without breaking unit economics.
Overview
Referral Program is an agent skill most often used in Grow (also Launch) that designs and optimizes customer referral, affiliate, and word-of-mouth incentive programs.
Install
npx skills add https://github.com/coreyhaines31/marketingskills --skill referral-programWhat is this skill?
- Distinguishes customer referral vs affiliate/ambassador programs and B2B vs B2C constraints
- Grounds incentives in LTV, CAC benchmarks, and current referral rate baseline
- Assesses product shareability, network effects, and whether customers naturally advocate
- Reads product marketing context first when `.agents/product-marketing-context.md` exists
- Cross-links launch-specific virality to launch-strategy when timing is launch-heavy
- Skill metadata version 1.1.0
Adoption & trust: 52.5k installs on skills.sh; 32.4k GitHub stars; 3/3 security scanners passed (skills.sh audits).
What problem does it solve?
Paid channels are expensive and you lack a structured referral or affiliate model tied to LTV, CAC, and whether users actually want to share your product.
Who is it for?
SaaS or subscription products with identifiable LTV/CAC and some existing users who could refer if the offer and UX were clear.
Skip if: Pre-PMF products with no customers to refer, or teams seeking only launch-week hype without ongoing program mechanics—see launch-strategy for launch virality.
When should I use this skill?
User mentions referral, affiliate, ambassador, word of mouth, viral loop, refer a friend, partner program, referral incentive, or affiliate payout.
What do I get? / Deliverables
You get a program design direction—incentives, eligibility, B2B/B2C fit, and optimization levers—aligned to economics and shareability, with launch-heavy virality deferred to launch-strategy when needed.
- Program type recommendation (referral, affiliate, or hybrid)
- Incentive and economics framing tied to shareability
- Optimization angles from current referral rate and past incentives
Recommended Skills
Journey fit
Spans multiple journey phases - primary shelf plus alternate fits below.
Referral loops compound after you have paying users—Grow lifecycle is the canonical home for ongoing viral and partner incentives, distinct from one-time launch spikes. Lifecycle covers retention-adjacent mechanics where existing customers and partners repeatedly bring new signups, not just top-of-funnel launch bursts.
Where it fits
Set double-sided rewards and in-app prompts when monthly active users plateau but NPS is strong.
Add a founding-member referral tier at go-live without underpricing core plans.
Stress-test whether referral credits conflict with introductory pricing before you scale ads.
How it compares
Focused on sustained referral and affiliate operations—not one-off product launch playbooks (launch-strategy) or on-site conversion tests (page-cro).
Common Questions / FAQ
Who is referral-program for?
Indie SaaS founders and small growth teams who own pricing, billing hooks, and partner payouts and need a disciplined referral or affiliate blueprint.
When should I use referral-program?
In Grow when optimizing lifecycle acquisition, at Launch when layering referrals into go-live (alongside launch-strategy), and in Validate when testing whether incentives move early adopters—not for generic brand campaigns with no share loop.
Is referral-program safe to install?
It provides strategic guidance only; confirm repo trust via the Security Audits panel on this Prism page before use.
SKILL.md
READMESKILL.md - Referral Program
# Referral & Affiliate Programs You are an expert in viral growth and referral marketing. Your goal is to help design and optimize programs that turn customers into growth engines. ## Before Starting **Check for product marketing context first:** If `.agents/product-marketing-context.md` exists (or `.claude/product-marketing-context.md` 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? --- ## 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 --- ## 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 ### 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 examples and incentive sizing**: See [references/program-examples.md](references/program-examples.md) --- ## 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 | Add verification, limits | |