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Customer Discovery Interview (Mom Test Style)

A voice AI discovery interview that follows Mom Test rules automatically: past behavior, not hypotheticals; specifics, not compliments. It asks about the last time the problem happened, what it cost, and what they've already tried — the questions founders forget to ask when a polite prospect starts flattering their idea.

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샘플 질문

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질문 6개 · 약 10분
Q01
메시지

Thanks for sharing 10 minutes! This is a conversation about how you handle a specific part of your work today — real stories, not opinions about product ideas. Your responses are completely confidential and anonymized. There's nothing to prepare and no pitch coming.

Q02
음성 AI 인터뷰

Customer discovery interview

Run a Mom Test-style discovery interview about the problem space. Rules: ask about SPECIFIC past events, never hypotheticals or opinions about ideas. Learn: (1) walk me through the LAST TIME you dealt with this problem —…

Q03
객관식필수

When did you last personally deal with this problem?

  • This week
  • In the past month
  • In the past 6 months
  • Longer ago
  • I never have — it's someone else's job
Q04
객관식필수

What have you already done about it? Select all that apply.

  • Built a spreadsheet or manual process
  • Bought or subscribed to a tool
  • Asked a colleague or hired help
  • Searched for solutions but didn't commit
  • Nothing — lived with it
Q05
숫자

Roughly how many hours per month does this problem cost you (your best estimate)?

Q06
메시지

That's a wrap — thank you! Your stories (not our assumptions) are what shape whatever we build next.

포함된 기능

  • AI 후속 질문

    정형화된 설문이 놓치는 세부 내용을, 주관식 답변에 맞춰 AI가 심층 질문으로 끌어냅니다.

  • 주의력 확인 장치

    성의 없는 답변과 저품질 응답자를 걸러내는 내장 안전장치입니다.

  • AI가 작성한 문안

    문구, 질문 순서, 분기 로직까지 AI가 연구 목표에 맞춰 작성합니다.

  • 자동 리포트

    응답이 모이면 주요 주제, 인용문, 이해하기 쉬운 요약이 자동으로 작성됩니다.

다른 서비스와 비교

다른 설문 도구의 가장 유사한 템플릿을 검토했습니다. 그 도구들이 잘하는 점과, 이 템플릿이 한발 더 나아가는 지점을 정리했습니다.

이 템플릿을 선택하는 이유

  • Mom Test rules are enforced by the interviewer itself: past behavior only, no hypotheticals, compliments redirected to what the person actually did
  • Evidence-of-demand questions are built in — what they've tried, what they've paid, and what the problem costs in hours
  • Voice format gets the rambling, specific stories that checkbox surveys flatten — transcribed and themed automatically

Great Question

Customer Discovery Interview Template

A technology-agnostic discovery template framed around understanding a problem space (what to build, what problems to solve, where the opportunities are) rather than evaluating solutions. The public page is strong on methodology framing but hides the actual questions behind a sign-up, and it is a manual moderated-interview guide.

잘하는 점

  • Clear problem-space framing: explore behaviors, attitudes, and experiences without prematurely evaluating a solution
  • Anchors the interview to concrete research questions (what should we build, what problems can we solve, what are the opportunities)
  • Honest about method limitations (small sample sizes, reliance on participant memory vs. observation)
  • Lives inside a research repository so discovery interviews can be tagged and reused

아쉬운 점

  • Actual template questions are gated behind sign-up rather than transparently shown
  • Positioned as a guide for human-moderated interviews, not an AI interviewer that runs the discovery conversation itself
  • No voice-AI or auto-scheduling to scale beyond what one researcher can personally moderate
  • No auto-generated synthesis report; analysis still depends on manual tagging in the repository

IdeaPlan

Customer Discovery Interview Template (Mom Test)

A Mom Test-based downloadable template (Slides/PowerPoint/Notion) with strong methodology scaffolding: interview volume targets, when patterns emerge, anti-confirmation-bias guidance, and a 3-question validation framework. The specific questions ship in the downloadable file, and the whole flow is a manual founder-run process.

잘하는 점

  • Explicit Mom Test discipline: ask about past behavior ('tell me about the last time...') instead of future intent, and defer product pitches to the end
  • Concrete cadence guidance: 15-20 interviews per segment, patterns around interview 5-7, convergence by ~interview 10-15
  • Actively-seek-disconfirming-evidence guidance to counter confirmation bias
  • 3-question validation framework (what is the problem, who has it acutely, what do they do today and why is it insufficient)

아쉬운 점

  • Ships as static slide/Notion files, so it is a script a human must run, not an adaptive AI interviewer
  • No voice-AI interview mode to conduct discovery calls automatically
  • No automated transcript synthesis into the 3-question validation output; the founder codes quotes by hand
  • Discipline (avoiding leading questions, chasing disconfirming evidence) depends entirely on interviewer skill rather than being enforced by the tool

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