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.
Sample questions
A preview of what’s in the template. Every question is editable before you launch.
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 —…
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
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
Roughly how many hours per month does this problem cost you (your best estimate)?
That's a wrap — thank you! Your stories (not our assumptions) are what shape whatever we build next.
What’s included
AI follow-ups
Adaptive probes on open-ended answers that pull out detail a static form would miss.
Attention checks
Built-in safeguards against rushed answers and low-quality respondents.
AI-drafted copy
Wording, ordering, and branching written by the AI — tuned to your research goal.
Auto report
Themes, quotes, and a plain-English summary write themselves once responses come in.
How it compares
We reviewed the closest templates from other survey tools. Here’s what they do well — and where this template goes further.
Why this template
- 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 TemplateA 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.
What it does well
- 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
Where it falls short
- 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.
What it does well
- 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)
Where it falls short
- 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
Ready to launch?
Open this template in the editor. Every part is yours to change before the first respondent sees it.