Referral Program

kostja94/marketing-skills/skills/channels/partnerships/referral-program

作者 kostja948dd89c57395e无许可证1K 个星标收录于 2026年10月8日更新于 2026年10月8日仓库2天前更新

When the user wants to plan, implement, or optimize referral program strategy. Also use when the user mentions "referral program," "referral marketing," "user referral," "refer-a-friend," "word-of-mouth growth," "referral rewards," "referral tracking," "referral code," "referral incentives," or "viral loop." For referral landing copy, use landing-page-generator.

仅含说明Marketing & Sales
AI 生成的概览

为 AI/SaaS 产品提供推荐计划策略指导,涵盖奖励、追踪、防欺诈、工具与 KPI。

功能
该技能为 AI 和 SaaS 产品的推荐计划提供结构化的规划、实施与优化框架。它对比推荐、联盟与网红渠道,梳理奖励模式、机制类型、追踪与归因方法以及防欺诈措施。它还涵盖自建与第三方工具的选型以及 KPI 框架,并产出包含奖励模式、追踪、投放位置、防欺诈、工具选择和 KPI 的推荐计划方案。
适用场景
适用于规划、启动或优化推荐计划或邀请好友计划,或当用户提到推荐营销、推荐奖励、推荐码、推荐追踪、口碑增长或病毒式传播时。它面向增长与营销决策,而非撰写推荐落地页文案。
运行要求
无需脚本或特殊工具,仅为说明性内容。存在根目录 contextus.md 文件时会选择性地读取,否则依赖项目材料或用户提供的信息。

Channels: Referral

Guides referral program strategy for AI/SaaS products. Leverage existing users to drive growth; 3%-5% conversion vs 1%-2% for ads; CAC 50%-70% lower; referred users LTV 30%-50% higher, retention 20%-30% higher. Referral is necessity in overseas markets, not alternative.

When invoking: On first use, if helpful, open with 1-2 sentences on what this skill covers and why it matters, then provide the main output. On subsequent use or when the user asks to skip, go directly to the main output.

Initial Assessment

Project context: Read root contextus.md when present and load only the modules relevant to this task. Without Contextus, use available project material or user-provided facts and ask for missing information; do not create a parallel context system.

Identify:

  1. Product type: SaaS, AI tool, subscription
  2. User base: Size, engagement, retention
  3. Goal: Signups, purchases, or both

Referral vs. Affiliate vs. Influencer

DimensionReferralAffiliateInfluencer
WhoExisting usersProfessional promotersKOLs
IncentiveDiscounts, creditsCommissionFees, product
BarrierLow (all users)MediumHigh
Conversion3%-5%VariesVaries

Referral vs affiliate: Referral needs no landing page or application; integrated in dashboard. Affiliate requires landing page and approval.

Reward Models

ModelUse
Two-wayBoth referrer and referee get rewards; highest participation
One-wayOnly referrer rewarded; cost control
TieredRewards increase with referral count (e.g. $10 for 1-5, $15 for 6-10, $20 for 11+); incentivizes volume

Benchmark: Rewards typically 10%-30% of product price; ~11% off or ~$21 value; weak incentives = low participation. Triggers: signup, purchase, activation, or sustained use.

Mechanism Types

TypeUse
Link-basedUnique referral link; easy to implement; accurate tracking; share via email, social, SMS; works for web and app
Code-basedReferral code (e.g. FRIEND20); memorable; offline events; mobile-friendly input
Social referralShare buttons (Facebook, X, LinkedIn); viral spread; friend trust; young users

Tracking & Attribution

MethodUse
CookieWeb apps; 30-90 day window
URL paramsAll platforms; persistent in link
Referral codeMobile, offline; manual entry
Account associationLong-term tracking; subscription products

Attribution window: 30-90 days typical; 180 days for subscription. First-touch attribution to avoid double-counting.

Fraud Prevention

RiskAction
Self-referralDetect same device, payment, IP
Fake accountsValidate email, payment; monitor patterns
Bulk/automationRate limits; anomaly detection
Per-user cape.g. Max 10 referrals per user

Use tool anti-fraud features; audit referrals regularly.

Design Framework

  1. Reward structure: Type (cash, discount, credits, free service); amount (10%-30% of price); trigger; cap
  2. Tracking: Choose method; set attribution window; first-touch rule
  3. UX: One-click share; clear rules; dashboard with referral data; notify on success
  4. Fraud prevention: See above
  5. Monitor & optimize: Referral rate, conversion, CAC, LTV; A/B test rewards and flow

Best Practices

  • Run multiple programs: Target different audiences, stages, goals
  • Tiered rewards: Motivate top performers; progressive incentives
  • Friction-free sharing: Mobile-friendly; one-click share
  • Time-boxed incentives: "Refer this week for $15 off" creates urgency
  • Placement: Web, email, app, in-product touchpoints; dashboard integration primary

Implementation

ApproachUse
Self-buildFull control; low cost; URL params or cookie + reward logic + fraud checks; open-source (e.g. RefRef) for faster start
Third-partyFast launch; Cello, Viral Loops, ReferralCandy (e-commerce), Impact (enterprise); monthly fee

Placement: Most programs integrate in product dashboard; no landing page or application needed. Optional landing page for value prop, rewards, and case studies.

Startup cost: Typically hundreds for tools + dev.

Tools

ToolUse
CelloSaaS; AI-driven automation
Viral LoopsReferral + waitlist + contests
ReferralCandyShopify, e-commerce
ImpactEnterprise; unified platform
RefRefOpen-source; self-hosted

KPIs

Referral rate, conversion, CAC, LTV of referred users, referred-user retention.

Output Format

  • Reward model and mechanism type (link/code/social)
  • Tracking approach and attribution window
  • Placement (dashboard vs landing page)
  • Fraud prevention measures
  • Tool selection (self-build vs third-party)
  • KPI framework

Related Skills

  • discount-marketing-strategy: Referral rewards (discounts, credits); 10–30% benchmark; campaign design
  • affiliate-marketing: Different audience; can run both
  • influencer-marketing: Brand building vs. user-driven growth
  • directory-submission: Directory submission for discovery; referral for user-driven growth
  • analytics-tracking: Referral link tracking, UTM

来源与署名

来源:kostja94/marketing-skills位于skills/channels/partnerships/referral-program提交8dd89c5

许可证: 无许可证

内容归原作者所有。SourceWeft 从公开仓库中收录这些内容。

举报或申请下架