product-customer-discovery（product customer discovery 搜索）

Product Customer Discovery

Purpose

• Reduce product/market risk by learning how target users behave today, what problems they truly have, and what they already do to solve them.
• Turn qualitative conversations into decisions: who to build for (ICP), what to solve (problem framing), and what to test next (experiments).

Quick triggers

Use this skill when the user asks for:

• “product customer discovery”, “user research”, “problem interviews”, “exploratory interviews”
• “write an interview script/guide”, “what questions should I ask users”
• “define ICP/personas/segments”, “JTBD”, “pain points”, “opportunity sizing (qual)”
• “synthesize interview notes”, “extract themes/insights”, “create a discovery report”

Inputs to ask for (minimum)

1. Product/service and stage (idea, MVP, growth) + decision(s) discovery must unblock
2. Target audience hypotheses (who) and problem hypotheses (what/why)
3. Constraints: timeline, number of interviews, geography/language, incentives, recruiting channels

Outputs (suggested)

• Discovery plan: goals, hypotheses, target segments, recruiting criteria, timeline
• Interview guide: opening, context questions, story prompts, probing, wrap-up
• Synthesis: themes + evidence (quotes), JTBD/pains/gains, opportunity areas, risks/unknowns
• Next steps: prioritized experiments (e.g., landing page, concierge test, prototype test)

Core workflow (end-to-end)

1. Align on outcomes: confirm what decision will be made from the research and what “good evidence” looks like.
2. Define hypotheses: write 5–10 falsifiable statements (ICP, problem, willingness, constraints, alternatives).
3. Select participants: define inclusion/exclusion criteria, quotas across segments, and screening questions.
4. Design the interview:

- prefer “tell me about the last time…” over “would you use…” - focus on current behavior, existing alternatives, constraints, and consequences

1. Run interviews:

- start with rapport + consent; keep it conversational - ask for specific incidents; probe for frequency, severity, triggers, and workarounds - capture verbatims and observable facts; separate facts from interpretations

1. Synthesize:

- affinity-map notes into themes; label with evidence + confidence - map to JTBD (situation → motivation → desired outcome) and pains/gains - identify “strong signals” (repeated patterns, costly workarounds, high stakes)

1. Decide & recommend:

- rank opportunities by severity, frequency, reachable audience, and differentiation - propose next experiments with clear success metrics and cheapest test first

1. Share readout: present insights, what changed vs. assumptions, open questions, and the plan.

Interview guide template (outline)

1. Intro: who you are, purpose, confidentiality, recording consent, timebox
2. Background: role, context, responsibilities, tools/workflow
3. Story prompts (core): “Walk me through the last time you…”
4. Probing:

- triggers: “what started this?” - frequency: “how often?” - severity: “what happens if you don’t solve it?” - alternatives: “what did you try? why that? what did it cost?” - decision-making: “who’s involved? what’s the budget/approval path?”

1. Wrap-up: biggest pain, ideal outcome, who else to talk to, follow-up permission

Quality checklist

• Goals and hypotheses are explicit and falsifiable
• Participant criteria and screening reduce bias (no “friends and fans” only)
• Questions avoid leading language and future hypotheticals
• Notes separate verbatims/facts from interpretations
• Insights are backed by evidence, not anecdotes
• Recommendations include next experiments and success metrics

Common mistakes (avoid)

• Asking for feature opinions instead of behavior (“Would you use X?”)
• Interviewing only easy-to-reach users and generalizing
• Treating one loud quote as a “theme” without triangulation
• Skipping the decision step (insights without a recommendation and next tests)