mkurman |---|---| | When [situation], I want to [motivation], so I can [outcome] | X of N sources | Segment names | High/Med/Low |
Actionable Insights
Numbered list of insight statements using the format: "We learned that [finding] which means [implication] so we should [recommendation]."
Open Questions
What the data did NOT answer and recommended next research steps.
Frameworks & Best Practices
- Jobs to Be Done (JTBD). Frame every finding as a job the customer is trying to accomplish, not a feature they want. Customers hire products to make progress in their lives.
- Read before you summarize. Always process the complete transcript before writing any summary. Partial reads produce biased synthesis.
- Plain language over jargon. Write summaries that are accessible to anyone on the team, including non-technical stakeholders. Avoid PM jargon unless the team uses it consistently.
- Preserve direct quotes. The most powerful data points are verbatim quotes that capture the participant's emotion, specificity, and language. "I spent 3 hours last Tuesday rebuilding the report" beats "reporting is hard."
- Separate satisfaction from problems. Explicitly track what users like about current solutions alongside what frustrates them. Knowing strengths prevents accidentally breaking them.
- Current solutions reveal competitors. Documenting what participants use today (including spreadsheets, manual processes, and workarounds) reveals the true competitive landscape, which is broader than direct product competitors.
- Frequency is not importance. A pain point mentioned by 2 of 10 users may be more critical than one mentioned by 8 if those 2 users represent your ideal customer profile.
- Bias awareness. Note recruitment bias (who was NOT interviewed), leading question bias (review the interview script), and survivorship bias (current users vs. churned users).
- Minimum viable sample. For qualitative research, 5-8 interviews per segment typically reach thematic saturation. Flag if the sample is below this threshold.
- Triangulation. Cross-reference findings across data types. An insight supported by interviews AND support tickets AND survey data is stronger than one source alone.
- Continuous discovery. Treat interview synthesis as an ongoing practice, not a one-time project. Regular weekly interviews compound into deep customer understanding over time.
Related Skills
prd-writing-- Chain research synthesis directly into the Background and Market Segments sections of a PRD.competitive-analysis-- Combine customer insights with competitive data to identify underserved jobs where competitors fall short.feedback-synthesis-- Chain when you have a mix of structured feedback data (tickets, NPS) alongside interview transcripts.
Examples
Example 1: Single interview summary
User: "Here's a transcript from our discovery interview with a logistics manager. Summarize it."
Good output excerpt:
Metadata: March 10, 2026 | Sarah Chen, Logistics Manager at MidCo (150 employees)
Current solutions: Uses a combination of Excel spreadsheets and email chains to coordinate shipments. Satisfaction: 3/10. "It works but I lose about 5 hours a week just keeping everything in sync."
Problems identified:
- No single source of truth for shipment status (mentioned 4 times)
- Cannot see driver availability in real time; relies on phone calls
- Reporting to management requires manual data compilation every Friday
Key discovery: Sarah's team has built an informal Slack channel as a workaround for real-time updates. This was not anticipated in our research plan and suggests messaging integration may be higher priority than dashboard features.
Example 2: Multi-interview synthesis
User: "I just finished 8 customer interviews for our B2B scheduling tool. Here are the transcripts. What are the key takeaways?"
Good output excerpt:
JTBD #1 (7/8 interviews, High confidence): "When I'm coordinating meetings across 3+ time zones, I want to see everyone's availability in one view, so I can book a slot without 6 back-and-forth emails."
Insight: We learned that multi-timezone scheduling is the primary job, not calendar management broadly. This means our positioning should lead with "global team coordination" rather than "smart calendar." We should prioritize the timezone overlay feature in the next sprint.
Open question: None of the 8 participants were solo users. We still do not know whether the product has value for individuals without teams.