When the user wants to create, optimize, or analyze a referral, affiliate, or word-of-mouth program — 'ambassador,' 'viral loop,' 'refer a friend,' 'partner program,' 'referral incentive,' 'affiliate payout.' For launch-specific virality, see launch-strategy.
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Design and optimize programs that turn customers into growth engines.
Product context: If .agents/product-marketing-context.md exists (or .claude/product-marketing-context.md in older setups), read it first and tailor output to it; only ask for what it doesn't cover.
Gather (ask if not provided):
Customer referral programs — best for existing customers recommending to their network, products with natural word-of-mouth, lower-ticket or self-serve products. 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) and higher-ticket products that justify commissions. Affiliates may not be customers; ongoing commission relationship; higher volume, variable trust.
Trigger Moment → Share Action → Convert Referred → Reward → (Loop)
High-intent moments: right after first "aha" moment, after achieving a milestone, after exceptional support, after renewing or upgrading.
Ranked by effectiveness:
For examples and incentive sizing: See references/program-examples.md
Few customers referring: ask at better moments, simplify sharing, test different incentive types, make referral prominent in product.
Referrals not converting: improve landing experience for referred users, strengthen incentive for new users, make referrer's endorsement visible.
| 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 |
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, program ROI.
Typical findings: referred customers have 16-25% higher LTV, 18-37% lower churn, and refer others at 2-3x rate.
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]
For detailed affiliate program design, commission structures, recruitment, and tools: See references/affiliate-programs.md
For implementation, see the tools registry. Key tools:
| Tool | Best For | Guide |
|---|---|---|
| Rewardful | Stripe-native affiliate programs | rewardful.md |
| Tolt | SaaS affiliate programs | tolt.md |
| Mention Me | Enterprise referral programs | mention-me.md |
| Dub.co | Link tracking and attribution | dub-co.md |
| Stripe | Payment processing (for commission tracking) | stripe.md |
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Act as a Senior Accessibility Engineer to audit a page, component, or design against WCAG 2.2 AA. Produces a triaged finding list (critical/serious/moderate), focus-order map, contrast report, ARIA decision tree, and a screen-reader test plan. Use when shipping new UI, hardening an existing flow, or preparing for VPAT/accessibility conformance.
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When the user wants to plan, design, or implement an A/B test or experiment — "split test," "variant copy," "multivariate test," "hypothesis," "statistical significance," "how long should I run this test," or comparing two versions. For tracking implementation, see analytics-tracking. For page-level conversion optimization, see page-cro.
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When the user wants to generate, iterate, or scale ad creative — headlines, descriptions, primary text, full variations — for any paid platform; 'ad copy variations,' 'RSA headlines,' 'bulk ad copy,' 'creative testing,' 'write me some ads.' For campaign strategy and targeting, see paid-ads. For landing page copy, see copywriting.
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When the user wants content cited by LLMs or surfaced in AI-generated answers — 'AI SEO,' 'AEO,' 'GEO,' 'LLMO,' 'answer engine optimization,' 'AI Overviews,' 'optimize for ChatGPT/Perplexity/Claude,' 'AI citations,' 'zero-click search.' For traditional technical/on-page audits, see seo-audit. For structured data, see schema-markup.
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When the user wants to set up, improve, or audit analytics tracking and measurement — "GA4," "conversion tracking," "event tracking," "UTM parameters," "tag manager," "GTM," "tracking plan," "attribution," "Mixpanel," "Segment," "are my events firing," or how to measure marketing results. For A/B test measurement, see ab-test-setup.
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Architectural decision advisor for cloud, data, and SaaS distributed systems. Use when the user asks "should we use X or Y", weighs a tradeoff, or needs a decision matrix, scaling analysis, cost-at-scale review, data-tier design, multi-tenancy model, or API/resilience guidance. For full technical blueprints, use enterprise-design.
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