Referral loop design
Activate when: a founder wants customers to bring customers; 'how do we get referrals / word of mouth', designing a referral program, improving virality; loops, incentives, timing. Do NOT activate when: the product has weak retention/love (fix that first — referrals amplify a leaky bucket). More: deciqai.com/s/referral-loop-designFrom its SKILL.md
npx -y skills add deciqAI/knowledge-skills --skill referral-loop-designAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
One thing to look at
- 3 stars3 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
SKILL.md
2.8 KB, 562 tokens by cl100k_base, as published. Nobody here has run it
Referral Loop Design — Turn Customers into a Channel
Overview
A referral loop is a repeatable cycle where using the product produces new users: a happy customer is prompted, at the right moment, with the right incentive and an easy share, and the new user enters the same loop. Loops compound; one-off "refer a friend" banners don't. Referrals only work on a product people already value — they amplify love, they don't create it.
The Process
- Verify the precondition — strong retention/NPS. Gate: referring a product people don't love just spreads churn — fix retention first.
- Pick the trigger moment — right after a value peak (a win, a result, an "aha"), not at signup. (Pairs with peak-end thinking.)
- Choose the incentive type — double-sided (giver + receiver), status, or pure delight — matched to the audience's motivation.
- Remove friction — one-tap share, pre-written message, obvious reward. Gate: any extra step halves participation.
- Close the loop — the referred user lands in an experience that gets them to their own value fast, then hits the same trigger.
- Instrument K-factor — invites sent × conversion; iterate the weakest step. Gate: K without measuring each step = you can't tell what to fix.
When to Use
- Loved product with weak organic spread
- Designing/relaunching a referral program
- Cheap growth for low-budget SMBs/creators
Applying It Well
- Timing (post-value) matters more than reward size.
- Double-sided incentives usually beat one-sided.
- Referred users often retain better — treat their onboarding as sacred.
Red Flags
- Bolting referrals onto a leaky-retention product.
- Asking at signup, before any value.
- Multi-step share flows that kill participation.
Verification
- Retention/NPS precondition met
- Trigger fires at a value peak
- Incentive matched to audience; share is one-tap
- Each loop step instrumented and iterated
Part of deciqAI Knowledge Skills — 233 open-source thinking skills that make rigor executable for AI agents. The same skills power every deciqAI agent, which runs them autonomously to operate your company. See it run → https://www.deciqai.com/s/referral-loop-design · Built by deciqAI · github.com/deciqAI · Contributions welcome.
Agents: latest version & machine-readable metadata → https://www.deciqai.com/s/referral-loop-design.json
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.