Writes a story-based customer interview guide timed to your slot, with screener lines, questions anchored in one past instance, probes, a consent note and a note-taking template. Use for "run pm-customer-interview-guide", "customer interview guide", "interview questions for users", "prep my customer call", "discovery interview script", "what should I ask customers", "30 minutes with a customer", "avoid leading questions", part of the AI for Product Management Pack by Polar Bear.
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---
name: pm-customer-interview-guide
description: Writes a story-based customer interview guide timed to your slot, with screener lines, questions anchored in one past instance, probes, a consent note and a note-taking template. Use for "run pm-customer-interview-guide", "customer interview guide", "interview questions for users", "prep my customer call", "discovery interview script", "what should I ask customers", "30 minutes with a customer", "avoid leading questions", part of the AI for Product Management Pack by Polar Bear.
---
# Customer Interview Guide
## When To Use
You have 30 minutes with a customer between sprints and cannot waste it on opinions. Sales owns most calls, so the one you get has to count. This guide answers one question: what do I ask so I come back with what they actually did, not what they say they would do?
## When Not To Use
If the notes are already in and you need to make sense of them, run Interview Synthesis. If you want to know why a deal was won or lost against another product, that is a win/loss interview and belongs to Competitive Analysis.
## Inputs
- The learning goal: the decision this interview should inform, in one line
- Who to talk to: the behaviour or situation that qualifies someone (for example "exported a report last month")
- The slot length and format (call, video, on site)
If you have none of this, I start from the product area you name and mark the output as a first draft with the learning goal to confirm.
## Approach
Story-based interviewing as set out by Teresa Torres (Product Talk, producttalk.org), with the question and probing rules from "User Interviews 101" (Nielsen Norman Group, nngroup.com). The judgment: people are poor at predicting their own behaviour and generous with compliments, so ask about a specific time that already happened. The failure it prevents is the interview that ends with "yes, I would definitely use that", which sounds like evidence and is not.
## Workflow
1. Ask three questions: what decision this informs, which past behaviour qualifies a participant, and how many minutes you have.
2. Write screener lines on behaviour, not attributes: "In the last [period], have you [done X]?" Screen out people who have only thought about it.
3. Open with one anchor: "Tell me about the last time you [did X]." Add two or three follow-ups that walk the story in order: what triggered it, what they did first, where it got hard, what they did instead.
4. Write the probes: "Tell me more about that", "What happened next?", "Why was that important?". Add the return line for drift: when they say "usually" or "I would", wait for a pause, then "Going back to that time last [week], what did you do?"
5. Strike leading questions: no yes/no, no future intentions, no "how often do you", no pitching the idea. Mark the moments where you would need to watch them do it, because an interview only gives reported behaviour.
6. Timebox against the slot: consent and warm-up, the story, probes, close. Cut questions until it fits with room to spare; a guide that runs over always loses the ending.
7. Add the consent note and a note template with participant codes (P1, P2), one observation per line, their words marked as quotes only when said verbatim.
## Output Format
```markdown
# Customer Interview Guide
Learning goal: [decision this informs] | Slot: [minutes] | Interviewer: [role] | Note-taker: [role]
## Screener
- In the last [period], have you [behaviour]? [keep if yes]
## Consent Note
[What we record, why, who sees it, how long we keep it, that they can stop any time. Recording and data rules: check with a qualified adviser.]
## Questions
| Minute | Question | Probes | Return line if they drift |
|---|---|---|---|
| [0-3] | [warm-up] | [probe] | [line] |
| [3-20] | Tell me about the last time you [did X]. | Tell me more about that. What happened next? | Going back to that time, what did you do? |
## Watch For
- [Where observation would be needed instead of a report]
## Notes Template
| Code | Time | Observation (one per line) | Verbatim? |
|---|---|---|---|
| P[n] | [mm:ss] | [what they did or said] | [yes / no] |
## Decision
[Who approves the guide and books the first [n] interviews: the [product manager], by [date].]
```
## Done When
- The opening question points at one specific past instance
- No question is yes/no, hypothetical or a pitch
- The timing fits the slot with minutes to spare
- The consent note and the notes template are in
## Quality Bar
- Screeners select on what people did, never on who they are.
- Collect only the personal data the learning goal needs; names stay out of the notes.
- Never ask Claude to play the customer or answer the guide; a simulated interview is not discovery.
- Every probe is open and neutral; no probe hints at the answer you hope for.
- Claude writes the guide; the team talks to the customer.
## Next
Run pm-interview-synthesis (Interview Synthesis) to turn the notes into needs.
## About the makers
This pack is made by Polar Bear, a consultancy built by ex-McKinsey founders with a dream to make AI work for People, not instead of them. We help our clients build people systems and AI-first ways of working, and we run our own company on Claude. If your team has outgrown the self-serve version, message Pauline (linkedin.com/in/paulinebertry).