The 5-step interview framework + beta-test design that surfaces the real must-have and willingness to pay.
By Iris Wei (生姜) · ex-COO of AFFiNE (60K+ GitHub stars) · 30× Product Hunt #1
Most "user feedback" is vanity — happy users being polite. This playbook gets the real must-have and the real willingness to pay: who to interview, a structured 30–45 minute script, a 3-layer beta test, and a 5-question close that forces honest signal.
| Interview script length | 30–45 min |
| Interview script parts | 5 |
| Synthesis cadence | every 5–10 sessions |
| Beta-test layers | 3 |
1 · Target & screen
Prioritize by value: P0 paid users and power users (highest-signal), P1 competitor users and churned users (competitive view + real problems), P2 registered-but-unpaid (conversion blockers).
2 · Invite & schedule
Reach out and book sessions with the right mix, weighting toward P0 and churned users.
3 · Run the interview (30–45 min)
Five parts: background (role, channels, tenure, competitors) → workflow (what problem, how before, what changed) → competitor comparison → pain mining (bugs, friction, the "magic wand" question) → willingness to pay (what they've paid, how much, upgrade triggers).
4 · Close & follow up
Wrap cleanly, confirm next steps, and keep the relationship open for beta access and follow-up.
5 · Synthesize (every 5–10 sessions)
Aggregate findings every 5–10 interviews to spot patterns rather than over-indexing on any single voice.
Not all feedback is equal; weight toward the users whose signal predicts revenue.
| Priority | User type | Why |
|---|---|---|
| P0 | Paid users | Validated willingness to pay — highest value |
| P0 | Power users | Deep product knowledge — most actionable |
| P1 | Churned users | Expose the product's real problems |
| P2 | Registered, unpaid | Reveal conversion blockers |
Who should I interview first?
P0 — paid users (validated willingness to pay) and power users (deepest product knowledge). Then P1 churned users, who expose the real problems happy users won't mention. Registered-but-unpaid (P2) reveal conversion blockers.
How do I get honest willingness-to-pay signal?
Ask what they've actually paid for before, how much, and what triggered an upgrade — then the 5-question close including "would you pay if we launched tomorrow, and why?". Past behavior and a concrete commitment beat hypothetical enthusiasm.
How many interviews before I trust the data?
Synthesize every 5–10 sessions to spot patterns. One vivid interview is an anecdote; recurring themes across a batch are signal.
Who built this?
Iris Wei (生姜) — ex-COO of AFFiNE (60K+ GitHub stars), advisor to 150+ AI startups on PMF and user research.