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referral

推荐系统 - 推荐计划,病毒式循环。用于推荐。

person作者: jakexiaohubgithub

Referral Guideline

Tech Stack

  • Analytics: PostHog
  • Database: Neon (Postgres)

Non-Negotiables

  • Referral rewards must have clawback capability for fraud
  • Attribution must be auditable (who referred whom, when, reward status)
  • Velocity controls must exist to prevent abuse

Context

Referral programs can drive explosive growth — or become fraud magnets. The best referral programs make sharing natural and rewarding. The worst become liability when abusers exploit them.

Consider both sides: what makes users want to share? And what prevents bad actors from gaming the system? A referral program that's easy to abuse is worse than no referral program.

Driving Questions

  • Why would a user share this product with someone they know?
  • How easy is it for a bad actor to generate fake referrals?
  • What fraud patterns exist that we haven't addressed?
  • What is the actual ROI of the referral program?
  • Where do users drop off in the referral/share flow?
  • If we redesigned referrals from scratch, what would be different?