discover-interview-synthesis
关于
This skill synthesizes raw user interview data into structured insights, patterns, and actionable recommendations. Use it after conducting 5+ user interviews or customer calls to transform observations into findings that drive product decisions. It helps identify cross-participant patterns and connect them to underlying user needs.
快速安装
Claude Code
推荐npx skills add product-on-purpose/pm-skills -a claude-code/plugin add https://github.com/product-on-purpose/pm-skillsgit clone https://github.com/product-on-purpose/pm-skills.git ~/.claude/skills/discover-interview-synthesis在 Claude Code 中复制并粘贴此命令以安装该技能
技能文档
Interview Synthesis
An interview synthesis transforms raw user research data into structured insights that drive product decisions. Rather than simply listing what participants said, a good synthesis identifies patterns across conversations, connects observations to underlying user needs, and translates findings into actionable recommendations.
When to Use
- After completing a round of user interviews (typically 5+ participants)
- Following customer discovery calls or sales feedback sessions
- After usability testing sessions to consolidate observations
- When stakeholders need a summary of research findings
- Before ideation sessions to ground the team in user reality
Instructions
When asked to synthesize interview findings, follow these steps:
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Gather the Raw Material Collect all interview notes, transcripts, or recordings. Ensure you have data from at least 3 participants to identify meaningful patterns. Note the research objective and methodology used.
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Create Participant Profiles Document each participant with relevant context: their role, segment, tenure, and any notable characteristics. This helps readers assess the representativeness of findings.
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Identify Recurring Themes Read through all notes and tag observations by topic. Look for themes that appear across multiple participants (ideally 3+). Distinguish between frequently mentioned topics and one-off comments.
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Extract Meaningful Quotes Capture 3-5 verbatim quotes per theme that powerfully illustrate the insight. Good quotes are specific, emotional, or particularly articulate. Always attribute quotes to participant IDs.
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Synthesize into Insights Transform themes into insight statements. An insight goes beyond observation ("users mentioned X") to interpretation ("users need Y because of Z"). Connect what you heard to why it matters.
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Formulate Recommendations Based on the insights, propose prioritized actions. Each recommendation should tie directly to an insight. Note confidence level based on strength of evidence.
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Document Limitations Acknowledge what you didn't learn, sample biases, or areas needing further research. Honest limitations increase credibility.
Output Format
Use the template in references/TEMPLATE.md to structure the output.
Quality Checklist
Before finalizing, verify:
- Themes are supported by evidence from 3+ participants
- Quotes are verbatim and attributed to participant IDs
- Insights explain "why" not just "what"
- Recommendations are specific and actionable
- Participant identities are protected (no PII)
- Limitations and biases are acknowledged
Examples
See references/EXAMPLE.md for a completed example.
GitHub 仓库
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