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 - You have synthesized findings and want to map them onto a customer's journey across stages and touchpoints -> use
discover-journey-map
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.
Project Memory Contract
Active only when .claude/pm-skills.local.md exists. With no file, ignore this section entirely
and behave exactly as described above.
- Reads:
phaseandactive_initiative, so findings are framed against the initiative in flight instead of asking you to restate it. - Writes: the personas and findings as an
interpretationartifact, so a later skill can consume them without you pasting them again. - Posture: propose the entry and wait for confirmation before writing, unless
memory_auto_append: trueis set, in which case append and echo what was written. - Write discipline: re-read the file immediately before writing, never from the copy that 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.
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.
