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discover-interview-synthesis

Discover-Interview-Synthesis aggregates raw user research data from multiple interviews into structured patterns, insights, and actionable recommendations for product decisions. Use this skill after completing rounds of user interviews, customer discovery calls, or usability testing sessions to extract evidence-backed findings and communicate research results to stakeholders before ideation or problem definition work.

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git clone --depth 1 https://github.com/product-on-purpose/pm-skills /tmp/discover-interview-synthesis && cp -r /tmp/discover-interview-synthesis/skills/discover-interview-synthesis ~/.claude/skills/discover-interview-synthesis
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SKILL.md

<!-- PM-Skills | https://github.com/product-on-purpose/pm-skills | Apache 2.0 -->
# 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

## When NOT to Use

- You are summarizing one internal meeting for its attendees -> use `foundation-meeting-recap`
- You need patterns across multiple meetings over time -> use `foundation-meeting-synthesize`
- Your data is survey responses rather than interviews -> use `measure-survey-analysis`
- The findings are synthesized and you are ready to frame the problem -> use `define-problem-statement`

## Instructions

When asked to synthesize interview findings, follow these steps:

1. **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.

2. **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.

3. **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.

4. **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.

5. **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.

6. **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.

7. **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. A complete synthesis fills every template section: Research Overview; Key Themes; Notable Quotes; Insights; Recommendations; and Appendix.

## 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.