# Build Referral and Affiliate Programs

Referral programs fail when incentives, timing, and tracking are unclear. This skill helps design, launch, and optimize referral and affiliate programs.

## Install

```bash
npx skillstore add coreyhaines31/referral-program
```

## Metadata

- Status: approved
- Slug: coreyhaines31-referral-program
- Skillstore revision: r1
- Version status: missing
- Tree hash: d127008b1ed696a87129f6ca3d5cca7771107b6b9cf02c1aca0ac308e9ee0cb4
- Author: coreyhaines31
- GitHub username: coreyhaines31
- License: MIT
- Repository: https://github.com/coreyhaines31/marketingskills/tree/main/skills/referral-program
- Ref: d11af420e07cd866fe39cfa937efef3223896c06
- Supported tools: Claude, Codex, Claude Code
- Audit status: complete
- Agent install advisory: allowed
- Manual install advisory: allowed
- Artifact signature: available
- Audit attestation: unavailable
- Human verification: not\_verified
- Risk factors: external\_commands
- Quality score: 78
- Quality tier: bronze
- Public page: https://skillstore.pages.dev/skills/coreyhaines31-referral-program
- Manifest: https://skillstore.pages.dev/api/skills/coreyhaines31-referral-program/manifest

## Capabilities

- Compare referral, affiliate, and hybrid program models.
- Design single-sided, double-sided, and tiered incentive structures.
- Estimate reward ceilings using LTV, gross margin, and CAC.
- Draft affiliate outreach and referral launch email sequences.
- Plan fraud prevention, dashboard metrics, and launch checklists.

## Use Cases

- Launch a Customer Referral Program: Design rewards, referral prompts, launch emails, and tracking metrics for an existing customer base.
- Structure an Affiliate Program: Choose commission rules, cookie duration, partner enablement materials, and recruitment channels.
- Improve Referral Economics: Model incentive limits, referral ROI, payback period, and fraud controls before scaling the program.

## Prompt Templates

### Choose Program Type

```
Help me choose between a referral program, an affiliate program, or a hybrid model. My product is [product], my audience is [audience], and my average customer value is [LTV].
```

### Design Incentives

```
Design three incentive options for my referral program. Use my LTV of [amount], gross margin of [percent], current CAC of [amount], and target customer behavior of [behavior].
```

### Plan Affiliate Launch

```
Create an affiliate program launch plan for [company]. Include commission structure, ideal affiliates, enablement assets, outreach sequence, and performance metrics.
```

### Audit Program Performance

```
Audit this referral program using the data below. Identify bottlenecks, incentive risks, fraud signals, cohort insights, and prioritized experiments. Data: [metrics and notes].
```

## Limitations

- Does not connect to live referral platforms or analytics tools.
- Requires user-provided LTV, CAC, margin, and conversion data for accurate modeling.
- Benchmarks are general and should be validated against your market.
- Does not provide legal review of affiliate terms or tax rules.

## Best Practices

- Provide LTV, CAC, margin, and current referral metrics when asking for incentive recommendations.
- Ask for separate plans for customer referrals, affiliates, and hybrid programs when audiences differ.
- Review fraud controls, payout timing, and terms before launching public rewards.

## Anti Patterns

- Do not set rewards before checking unit economics and payback period.
- Do not rely on one generic referral message for every customer segment.
- Do not pay rewards before verifying meaningful activation or purchase quality.

## Security Audit

- Audited at: 2026-07-06T07:02:51.436\+00:00
- Summary: All 17 external command findings are false positives caused by Markdown code fences around diagrams, formulas, and email templates in SKILL.md. The five blocker findings are business-marketing language, not system or network reconnaissance, and no prompt injection or data-exfiltration intent was found.

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