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.
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---
name: discover-interview-synthesis
description: 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.
phase: discover
version: "2.0.0"
updated: 2026-01-26
license: Apache-2.0
metadata:
category: research
frameworks: [triple-diamond, lean-startup, design-thinking]
author: product-on-purpose
---
# 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:
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.
## 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.
