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 |
| Interviews run by winning teams (reported) | 500-1,000 in ~6 months |
| Trust built by daily user chats (reported) | 2 months beats 1 year |
| First deep interview length | up to 2 hours |
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.
What makes a user interview useless?
Turning it into an investor pitch — you talk 80% and the user zones out. Flip it: let the user share their screen, watch their real workflow and real use cases. Your imagined user journey and their actual journey are almost never the same.
How many interviews did successful AI products run before scaling?
Reportedly, teams like Gamma, HeyGen and Lovable ran 500-1,000 user interviews within about six months before pouring money into growth. The counter-example: skipping this and buying installs at tens of dollars per signup and hundreds per paying user.
Can users tell me my own value proposition?
Often yes. Deep users know the scenario, the industry and every competitor better than you do — a single 2-hour interview can surface your real value proposition and your sharpest comparative advantage.