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referrals

When the user wants to create, optimize, or analyze a referral program, affiliate program, or word-of-mouth strategy.

From Corey Haines' marketingskills, MIT, pinned at 365b412. Updated 2026-10-15.

The file, as Kwern runs it

Nothing below is rewritten or cut. The description a model routes on comes first, then the file itself. The whole thing, frontmatter included, is at /skills/referrals.md.

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.

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


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. 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

For product-embedded virality, value-presentation rules, and affiliate power-law mechanics: See 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

ProblemFix
Low awarenessAdd prominent in-app prompts
Low share rateSimplify to one click
Low conversionOptimize referred user experience
Fraud/abuseAdd verification, limits
One-time referrersAdd 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

For affiliate power-law mechanics (buyout clauses ~12× monthly commission, the 20/80 super-promoter rule, launch-affiliate tactics): See 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. Platform rules differ, so check 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. Key tools for referral programs:

ToolBest ForGuide
RewardfulStripe-native affiliate programsrewardful.md
ToltSaaS affiliate programstolt.md
Mention MeEnterprise referral programsmention-me.md
Dub.coLink tracking and attributiondub-co.md
StripePayment processing (for commission tracking)stripe.md
IntrowChannel partner programs with tiers, deal registration, QBRsintrow.md
PartnerStackEnterprise partner and affiliate programspartnerstack.md

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

From your accounts to a proposal

  1. 01

    Connect what it reads

    Give the Influencers agent the accounts it works on. Kwern never asks for a password, and an agent missing a connection says so instead of guessing.

  2. 02

    The loop runs weekly

    Before it writes a word it reads the foundation doc, which holds the positioning, the audience and the voice, and whatever its connectors return that day.

  3. 03

    The referrals skill runs

    The agent activates it when the run calls for it, and what the model then reads is the file on this page, word for word.

  4. 04

    A proposal waits for you

    Nothing is published and nothing is spent until you approve it. Approve and Kwern posts it where it holds the keys; where it does not, it hands you the text and the link.

The file, the agency, and the agent

On your ownAn agencyKwern
The methodWhatever you remember to do that weekTheirs, and you never get to read itThis file, open on this page
Who runs itYou, when there is timeAn account manager, between other accountsThe Influencers agent, weekly
What it readsWhat you can pull by handWhat you remembered to send themYour connected accounts and your foundation doc
What comes outA draft, sometimesA deck, and a report at the end of the monthA proposal you approve or throw away
What it costsYour eveningsA retainerOne subscription, and the model on your own key

Questions about referrals

Someone is asking for what you built today.

On Reddit, on X, in ChatGPT's answers. Kwern finds them every morning and drafts the reply in your voice; you decide what goes out.