user-research-methods
Plan and execute user research — interviews, surveys, usability tests. Use when you need primary evidence to inform a product decision.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
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Plan and execute user research — interviews, surveys, usability tests. Use when you need primary evidence to inform a product decision.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
| name | user-research-methods |
| description | Plan and execute user research — interviews, surveys, usability tests. Use when you need primary evidence to inform a product decision. |
Plan, execute, and synthesize user research in 1-3 days. Claude handles protocol design, guide generation, survey drafting, and findings synthesis. You handle the user conversations, observation, and interpretation.
Traditional research: 2-4 weeks for research planning, recruitment, execution, synthesis, and presentation.
AI-native research: 1-3 days. Claude compresses planning and synthesis to hours. The user conversations — the actual research — take the same time they always did.
| Step | Time | Claude Does | You Do |
|---|---|---|---|
| Choose method | 15 min | Recommend method based on your question | Validate fit for your context |
| Design protocol | 1-2 hrs | Generate guides, scripts, or surveys | Customize with your domain knowledge |
| Execute | Half day - 1 day | (Not present for conversations) | Conduct interviews, run tests, deploy survey |
| Synthesize | 1-2 hrs | Identify themes, patterns, contradictions | Validate interpretation, add context |
| Present findings | 30 min | Structure findings for stakeholder consumption | Add implications and recommendations |
I need to answer this question: [your research question].
Context:
- Decision this informs: [what you'll do with the findings]
- Timeline: [when you need the answer]
- Access to users: [how you can reach them — existing users, prospects, internal]
- What you already know: [existing data or hypotheses]
Recommend the right research method and explain why.
Method selection guide:
| Method | Best For | Sample Size | Time |
|---|---|---|---|
| User interviews | Understanding motivations, pain points, workflows | 5-8 users | 1-2 days |
| Usability testing | Evaluating whether users can complete tasks in your product or prototype | 5 users | 1 day |
| Surveys | Quantifying preferences, satisfaction, or behavior across a population | 50-200+ responses | 1-2 days |
| Concept testing | Validating an idea before building it | 5-8 users | 1 day |
| Card sorting | Informing information architecture or navigation | 10-20 users | 1 day |
| Diary studies | Understanding behavior over time | 5-10 users | 1-2 weeks (exception to our speed principle — some things need time) |
For interviews:
Generate a discussion guide for [N] 30-minute interviews about [topic].
Requirements:
- Start with warm-up questions to build rapport (2 minutes)
- Focus on past behavior, not hypotheticals ("tell me about the last time..." not "would you...")
- Include one open-ended question that might surface something unexpected
- Probe for specific examples, not generalizations
- End with "what should I have asked that I didn't?"
- Flag questions that might lead the participant
- Keep it to 10-12 questions max
Apply Mom Test principles: no pitching, no hypotheticals, focus on their life, not your idea.
For usability tests:
Generate a usability test script for [feature/prototype].
Include:
- Pre-test briefing (remind them: we're testing the product, not them)
- 4-6 task scenarios written as goals, not instructions
(e.g., "You want to change your notification settings" not "Click Settings, then Notifications")
- Follow-up probes for each task (what did they expect? what was confusing?)
- Post-test questions about overall impression
- Note: think-aloud protocol instructions
For surveys:
Design a survey to [research objective].
Requirements:
- 10-15 questions max (completion rate drops after 15)
- Mix of: Likert scale, multiple choice, and 1-2 open-ended
- No double-barreled questions (asking two things at once)
- No leading questions
- Logical flow: broad → specific → demographic
- Include a screening question if needed for targeting
- Estimated completion time: under 5 minutes
This is the human step. Some guidance:
For interviews: Take notes on what they said, not what you think they meant. Record (with permission) so Claude can help with synthesis. Ask "why?" at least three times. The first answer is surface-level.
For usability tests: Watch, don't help. Note where they hesitate, where they backtrack, where they express frustration or surprise. The struggle IS the data.
For surveys: Deploy to your target audience. Monitor early responses for confusion or drop-off patterns.
Here are my research notes/transcripts from [N] [interviews/tests/survey results]:
[Paste notes, transcripts, or data]
Synthesize:
1. Key themes (what came up repeatedly)
2. Frequency (how many participants raised each theme)
3. Contradictions (where participants disagreed)
4. Surprises (findings that challenge our assumptions)
5. Strongest quotes (verbatims worth preserving)
6. Confidence rating for each finding: strong (consistent across participants),
moderate (present but not universal), weak (one-off or ambiguous)
Review Claude's synthesis against your memory of the conversations. Did the synthesis miss the energy behind a comment? Did it over-weight an articulate participant? Add your interpretive layer.
Structure our research findings for [audience — team, leadership, design]:
Format:
1. Research question and method (one paragraph)
2. Key findings (3-5 findings with evidence strength ratings)
3. Implications for [the decision this was meant to inform]
4. Recommended next steps
5. Appendix: participant details, methodology notes, raw quotes
Keep findings factual. Separate what participants said from what we interpret.
Build a complete business case for a product investment — strategic rationale, financial model, risk assessment, and recommendation. Use when you need executive approval for a major initiative.
Run ROI, IRR, NPV, payback period, and cost-benefit analysis for product investments. Use when you need to quantify the financial case for building something.
Decompose a large problem, epic, or initiative into independently shippable slices. Use when work is too big to build in one sprint and you need to find the seams.
Deep dive into product analytics — investigate a question, surface insights, build a data narrative. Use when you need to go beyond dashboards to understand what's happening.
Define an epic with strategic context, feature breakdown, milestones, and success metrics. Use when scoping a large body of work for planning and tracking.
Write a detailed feature spec with requirements, edge cases, and technical constraints. Use when a feature needs formal documentation before engineering begins.