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Get Started Free →Synthesizes user research interviews into actionable insights, patterns, and recommendations. Use after conducting user interviews, customer calls, or usability sessions to extract and communicate findings across participants. Distinct from foundation-meeting-recap, which summarizes one internal meeting for its attendees; this skill aggregates research conversations into evidence-backed findings.
.claude/skills/product-on-purpose-discover-interview-synthesis/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-08 | ✗→✓ | ▲ Improved | 172% | 0% |
| case-11 | ✗→✓ | ▲ Improved | 29% | 0% |
| case-14 | ✗→✓ | ▲ Improved | 32% | 0% |
| case-22 | ✗→✓ | ▲ Improved | 26% | 0% |
| case-17 | ✗→✓ | ▲ Improved | 31% | 0% |
<!-- PM-Skills | https://github.com/product-on-purpose/pm-skills | Apache 2.0 -->
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.
foundation-meeting-recapfoundation-meeting-synthesizemeasure-survey-analysisdefine-problem-statementdiscover-journey-mapWhen asked to synthesize interview findings, follow these steps:
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.
Document each participant with relevant context: their role, segment, tenure, and any notable characteristics. This helps readers assess the representativeness of findings.
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.
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.
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.
Based on the insights, propose prioritized actions. Each recommendation should tie directly to an insight. Note confidence level based on strength of evidence.
Acknowledge what you didn't learn, sample biases, or areas needing further research. Honest limitations increase credibility.
Active only when .claude/pm-skills.local.md exists. With no file, ignore this section entirely and behave exactly as described above.
phase and active_initiative, so findings are framed against the initiative in flight instead of asking you to restate it.interpretation artifact, so a later skill can consume them without you pasting them again.memory_auto_append: true is set, in which case append and echo what was written.
produced the proposal. If it changed in between, merge your entry into the current state and re-propose rather than overwriting; add only your own entry and leave every other field and section byte-identical. Nothing enforces this at runtime and the file is gitignored, so a careless whole-file write loses another session's work with no way to recover it.
This is the writer half of the loop the cohort exists to demonstrate: what this skill records, deliver-prd later reads.
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.
Before finalizing, verify:
See references/EXAMPLE.md for a completed example.
Other measured skills in the registry, with their headline benchmark lift.