referrals

$npx mdskill add coreyhaines31/marketingskills/referrals

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.

SKILL.md

.github/skills/referralsView on GitHub ↗
---
name: referrals
description: "When the user wants to create, optimize, or analyze a referral program, affiliate program, or word-of-mouth strategy. Also use when the user mentions 'referral,' 'affiliate,' 'ambassador,' 'word of mouth,' 'viral loop,' 'refer a friend,' 'partner program,' 'referral incentive,' 'how to get referrals,' 'customers referring customers,' 'affiliate payout,' 'get more reviews,' 'G2 reviews,' 'review campaign,' or 'respond to a bad review.' Use this whenever someone wants existing users or partners to bring in new customers. For launch-specific virality, see launch."
metadata:
  version: 2.2.1
---

# 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.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?

---

## Should You Engineer Virality First?

Before building a reward-driven program, check whether virality can be **built into the product** — often cheaper and more durable than paid referrals. But **don't force virality where it doesn't naturally fit.**

Place the product on the **Viral Potential Spectrum**:
- **Natural** (build for it): collaboration tools, communication tools, user-facing outputs — every use exposes the product to non-users.
- **Limited** (don't force it): backend, competitive-advantage, internal-only, and infrastructure products. Invest in referral programs, content, and partnerships instead.

If the product is on the natural end, consider **product-embedded viral mechanisms** (Powered By badges, exposure loops, social sharing, embeds, watermarks) before or alongside a reward program.

**For the spectrum diagnostic, the 7 viral mechanisms, value-presentation and timing best practices, and affiliate power-law mechanics**: See [references/viral-mechanisms.md](references/viral-mechanisms.md)

---

## 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

For partner recruitment/activation, cohort economics, executable terms, reconciliation, and measured incremental growth, load [the operating playbook](references/affiliate-operations.md). This expands the existing affiliate branch instead of creating an overlapping skill.

**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

**Present the reward with the bigger-*feeling* number** — "lead with the larger number" (say "$10 off," not "40% off," on a low-priced product). Reward at the **aha moment or milestone**, not signup. Reduce friction: one-click share, pre-written messages.

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

**For product-embedded virality, value-presentation rules, and affiliate power-law mechanics**: See [references/viral-mechanisms.md](references/viral-mechanisms.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 |
| One-time referrers | Add tiered/gamified rewards |

---

## 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

- Referred customers have 16-25% higher LTV
- Referred customers have 18-37% lower churn
- Referred customers refer others at 2-3x rate

---

## Launch Checklist

### Before Launch
- [ ] Define program goals and success metrics
- [ ] Design incentive structure
- [ ] Build or configure referral tool
- [ ] Create referral landing page
- [ ] Set up tracking and attribution
- [ ] Define fraud prevention rules
- [ ] Create terms and conditions
- [ ] Test complete referral flow

### Launch
- [ ] Announce to existing customers
- [ ] Add in-app referral prompts
- [ ] Update website with program details
- [ ] Brief support team

### Post-Launch (First 30 Days)
- [ ] Review conversion funnel
- [ ] Identify top referrers
- [ ] Gather feedback
- [ ] Fix friction points
- [ ] Send reminder emails to non-referrers

---

## Email Sequences

### Referral Program Launch

```
Subject: You can now earn [reward] for sharing [Product]

We just launched our referral program!

Share [Product] with friends and earn [reward] for each signup.
They get [their reward] too.

[Unique referral link]

1. Share your link
2. Friend signs up
3. You both get [reward]
```

### Referral Nurture Sequence

- Day 7: Remind about referral program
- Day 30: "Know anyone who'd benefit?"
- Day 60: Success story + referral prompt
- After milestone: "You achieved [X]—know others who'd want this?"

---

## Affiliate Programs

**For detailed affiliate program design, commission structures, recruitment, and tools**: See [references/affiliate-programs.md](references/affiliate-programs.md)

**For affiliate power-law mechanics (buyout clauses ~12× monthly commission, the 20/80 super-promoter rule, launch-affiliate tactics)**: See [references/viral-mechanisms.md](references/viral-mechanisms.md)

---

## Review Programs

Reviews are the other half of customer advocacy. For review-request programs, responding to reviews, reputation triage, and reusing testimonials with permission (G2, Capterra, Trustpilot, Google, app stores), see [references/review-programs.md](references/review-programs.md). Platform rules differ, so check [references/review-platform-rules.md](references/review-platform-rules.md) before proposing incentives or automation.

## Task-Specific Questions

1. What type of program (referral, affiliate, or both)?
2. What's your customer LTV and current CAC?
3. Existing program or starting from scratch?
4. What tools/platforms are you considering?
5. What's your budget for rewards/commissions?
6. Is your product naturally shareable?

---

## Tool Integrations

For implementation, see the [tools registry](https://github.com/coreyhaines31/marketingskills/blob/main/tools/REGISTRY.md). Key tools for referral programs:

| Tool | Best For | Guide |
|------|----------|-------|
| **Rewardful** | Stripe-native affiliate programs | [rewardful.md](https://github.com/coreyhaines31/marketingskills/blob/main/tools/integrations/rewardful.md) |
| **Tolt** | SaaS affiliate programs | [tolt.md](https://github.com/coreyhaines31/marketingskills/blob/main/tools/integrations/tolt.md) |
| **Mention Me** | Enterprise referral programs | [mention-me.md](https://github.com/coreyhaines31/marketingskills/blob/main/tools/integrations/mention-me.md) |
| **Dub.co** | Link tracking and attribution | [dub-co.md](https://github.com/coreyhaines31/marketingskills/blob/main/tools/integrations/dub-co.md) |
| **Stripe** | Payment processing (for commission tracking) | [stripe.md](https://github.com/coreyhaines31/marketingskills/blob/main/tools/integrations/stripe.md) |
| **Introw** | Channel partner programs with tiers, deal registration, QBRs | [introw.md](https://github.com/coreyhaines31/marketingskills/blob/main/tools/integrations/introw.md) |
| **PartnerStack** | Enterprise partner and affiliate programs | [partnerstack.md](https://github.com/coreyhaines31/marketingskills/blob/main/tools/integrations/partnerstack.md) |

---

## Related Skills

- **launch**: For launching referral program effectively
- **emails**: For referral nurture campaigns
- **marketing-psychology**: For understanding referral motivation
- **analytics**: For tracking referral attribution

More from coreyhaines31/marketingskills

SkillDescription
ab-testingWhen the user wants to plan, design, or implement an A/B test or experiment, or build a growth experimentation program. Also use when the user mentions "A/B test," "split test," "experiment," "test this change," "variant copy," "multivariate test," "hypothesis," "should I test this," "which version is better," "test two versions," "statistical significance," "how long should I run this test," "growth experiments," "experiment velocity," "experiment backlog," "ICE score," "experimentation program," or "experiment playbook." Use this whenever someone is comparing two approaches and wants to measure which performs better, or when they want to build a systematic experimentation practice. For tracking implementation, see analytics. For page-level conversion optimization, see cro.
ad-creativeWhen the user wants to generate, iterate, or scale ad creative — headlines, descriptions, primary text, or full ad variations — for any paid advertising platform. Also use when the user mentions 'ad copy variations,' 'ad creative,' 'generate headlines,' 'RSA headlines,' 'bulk ad copy,' 'creative testing,' 'write me some ads,' 'Facebook ad copy,' 'Google ad headlines,' 'LinkedIn ad text,' 'static ads,' 'ad templates,' 'iMessage ad,' 'ChatGPT ad,' 'creative strategy,' 'creative roadmap,' 'creative retro,' 'hook writing,' 'creative review page,' 'motion video ad,' 'faceless video ad,' 'UGC ad,' 'greenscreen ad,' 'TikTok/Reels ad format,' 'Meta ad format tier list,' or 'creative format taxonomy.' Use it to produce or iterate ad copy at scale. Copy avoids AI tells like 'it's not X, it's Y' reveals. For campaign strategy and targeting, see ads. For landing page copy, see copywriting. Test hypotheses must be falsifiable, naming the metric, the comparison, and the expected direction.
adsWhen the user wants help with paid advertising campaigns on Google Ads, Meta (Facebook/Instagram), LinkedIn, Twitter/X, or other ad platforms. Also use when the user mentions 'PPC,' 'paid media,' 'ROAS,' 'CPA,' 'ad campaign,' 'retargeting,' 'audience targeting,' 'Google Ads,' 'Facebook ads,' 'LinkedIn ads,' 'ad budget,' 'cost per click,' 'ad spend,' 'should I run ads,' 'ABM,' 'account-based marketing,' 'B2B ads,' 'lead quality,' 'negative keywords,' 'Performance Max,' 'thought leader ads,' 'when should I kill an ad,' 'search terms report,' 'wasted spend,' or 'is this campaign working.' Use this for campaign strategy, audience targeting, bidding, and optimization. For bulk ad creative generation and iteration, see ad-creative. For landing page optimization, see cro. For outbound to target accounts, see cold-email. For pixels, CAPI, and tracking audits, see conversion-tracking. End every recommendation with facts, hypotheses, and missing data, and label unavailable inputs MISSING instead of estimating them.
ai-seoWhen the user wants to optimize content for AI search engines, get cited by LLMs, or appear in AI-generated answers. Also use when the user mentions 'AI SEO,' 'AEO,' 'GEO,' 'LLMO,' 'answer engine optimization,' 'generative engine optimization,' 'LLM optimization,' 'AI Overviews,' 'optimize for ChatGPT,' 'optimize for Perplexity,' 'AI citations,' 'AI visibility,' 'zero-click search,' 'how do I show up in AI answers,' 'LLM mentions,' 'optimize for Claude/Gemini,' 'llms.txt,' 'llms-full.txt,' 'OKF,' 'Open Knowledge Format,' 'knowledge bundle,' 'agent-readable site,' 'agent readiness,' 'is my site agent-ready,' 'WebMCP,' 'do listicles still work for AI,' 'ChatGPT stopped citing comparison pages,' 'how do LLMs see our brand,' 'LinkedIn for AEO,' or 'AI citation format shift.' Use this whenever someone wants their content to be cited or surfaced by AI assistants and AI search engines. For traditional technical and on-page SEO audits, see seo-audit. For structured data implementation, see schema.
analyticsWhen the user wants to set up, improve, or audit analytics tracking and measurement. Also use when the user mentions "set up tracking," "GA4," "Google Analytics," "event tracking," "UTM parameters," "tag manager," "GTM," "analytics implementation," "tracking plan," "how do I measure this," "Mixpanel," "Segment," "are my events firing," or "analytics isn't working." Use this whenever someone asks how to know if something is working or wants to measure marketing results. For getting conversions into ad platforms (pixels, conversion tags, CAPI, server-side) and verifying they arrived, see conversion-tracking. For choosing attribution models, comparing multi-touch/MMM/incrementality, or reconciling conflicting numbers across tools, see attribution. For A/B test measurement, see ab-testing. Rate metrics divide matching closed windows — never full-period spend by partial-period results.
asoWhen the user wants to audit or optimize an App Store or Google Play listing. Also use when the user mentions 'ASO audit,' 'app store optimization,' 'optimize my app listing,' 'improve app visibility,' 'app store ranking,' 'audit my listing,' 'why aren't people downloading my app,' 'improve my app conversion,' 'keyword optimization for app,' or 'compare my app to competitors.' Use when the user shares an App Store or Google Play URL and wants to improve it.
attributionWhen the user wants to figure out which marketing actually drives conversions and revenue, choose or interpret an attribution model, or reconcile conflicting numbers across tools. Also use when the user mentions "attribution," "attribution model," "first-touch vs last-touch," "multi-touch," "which channel drives revenue," "what's my real CAC," "my dashboards disagree," "Google/Meta says X but GA says Y," "media mix model," "MMM," "incrementality," "geo lift," "holdout test," "how did you hear about us," "self-reported attribution," "dark social," or wants to instrument attribution themselves — "stitch my bookings to their source," "SavvyCal/Calendly attribution," "close the identify gap," "track conversions on a third-party domain," "first-party / self-hosted attribution." For event tracking setup and UTMs, see analytics. For ad-platform pixels/CAPI and conversion tracking, see conversion-tracking. For pipeline and CRM revenue reporting, see revops. For the AI-search attribution blind spot, see ai-seo.
churn-preventionWhen the user wants to reduce churn, build cancellation flows, set up save offers, recover failed payments, or implement retention strategies. Also use when the user mentions 'churn,' 'cancel flow,' 'offboarding,' 'save offer,' 'dunning,' 'failed payment recovery,' 'win-back,' 'retention,' 'exit survey,' 'pause subscription,' 'involuntary churn,' 'people keep canceling,' 'churn rate is too high,' 'how do I keep users,' or 'customers are leaving.' Use this whenever someone is losing subscribers or wants to build systems to prevent it. For post-cancel win-back email sequences, see emails. For in-app upgrade paywalls, see paywalls.
co-marketingWhen the user wants to find co-marketing partners, plan joint campaigns, or brainstorm partnership opportunities. Use when the user says 'co-marketing,' 'partner marketing,' 'joint campaign,' 'who should we partner with,' 'integration marketing,' 'cross-promotion,' 'collaborate with another company,' 'partnership ideas,' or 'co-brand.' For customer referral programs, see referrals. For launch-specific partnerships, see launch.
cold-emailWrite and run B2B cold outbound that gets replies, from cold emails and follow-ups to sending setup, LinkedIn, multichannel cadences, and reply handling. Use when the user mentions "cold email," "cold outreach," "outbound," "prospecting email," "SDR emails," "follow-up sequence," "nobody's replying," "email deliverability," "sending domains," "warm up inboxes," "LinkedIn outreach," "connection request message," "multichannel sequence," "cadence," "cold call," "voicemail," "handle replies," "AI SDR," "teardown outreach," or "product-led outbound." Send from secondary domains, verify lists first, turn off open tracking, and stop every channel when a prospect replies. Copy avoids AI tells like 'it's not X, it's Y' reveals. For building the list and account research, see prospecting. For lifecycle email, see emails. For call scripts and sales collateral, see sales-enablement.