discover-interview-synthesis
Skill2 starsChanged 10 days agoMITView on GitHub
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 summarize-meeting, which summarizes one internal meeting for its attendees; this skill aggregates research conversations into evidence-backed findings.
We split this skill into the rules it gives an agent
8 rules. About 0 are common, 7 are distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈7
Distinctive · estimate
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 20
After completing a round of user interviews (typically 5+ participants)
- Distinctive: line 22
After usability testing sessions to consolidate observations
- Distinctive: line 23
When stakeholders need a summary of research findings
- Distinctive: line 24
Before ideation sessions to ground the team in user reality
- Distinctive: line 36
When asked to synthesize interview findings, follow these steps:
- Distinctive: line 42
Document each participant with relevant context: their role, segment, tenure, and any notable characteristics.
- Distinctive: line 45
Read through all notes and tag observations by topic.
- Very specific: line 61
Use the template in references/TEMPLATE.md to structure the output.
≈ “Common” is an estimate: at least 1 in 5 of the 308,232 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
<!-- 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
summarize-meeting - You need patterns across multiple meetings over time -> use
summarize-meeting - Your data is survey responses rather than interviews -> use
sentiment-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
customer-journey-map
Instructions
When asked to synthesize interview findings, follow these steps:
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
Other versions1 project uses a version of this.
Word for word · 0
None found.
Edited · 1
- product-on-purpose/pm-skills★ 77769% same
Wrote their own version · 0
None found.
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
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