Synthesize Research

If you see unfamiliar placeholders or need to check which tools are connected, see CONNECTORS.md.

Synthesize user research from multiple sources into structured insights and recommendations.

Workflow

1. Gather Research Inputs

Accept research from any combination of:

• Pasted text: Interview notes, transcripts, survey responses, feedback
• Uploaded files: Research documents, spreadsheets, recordings summaries
• ~~knowledge base (if connected): Search for research documents, interview notes, survey results
• ~~user feedback (if connected): Pull recent support tickets, feature requests, bug reports
• ~~product analytics (if connected): Pull usage data, funnel metrics, behavioral data
• ~~meeting transcription (if connected): Pull interview recordings, meeting summaries, and discussion notes

Ask the user what they have:

• What type of research? (interviews, surveys, usability tests, analytics, support tickets, sales call notes)
• How many sources / participants?
• Is there a specific question or hypothesis they are investigating?
• What decisions will this research inform?

2. Process the Research

For each source, extract:

• Key observations: What did users say, do, or experience?
• Quotes: Verbatim quotes that illustrate important points
• Behaviors: What users actually did (vs what they said they do)
• Pain points: Frustrations, workarounds, and unmet needs
• Positive signals: What works well, moments of delight
• Context: User segment, use case, experience level

3. Identify Themes and Patterns

Apply thematic analysis — see the user-research-synthesis skill for detailed methodology including affinity mapping and triangulation techniques.

Group observations into themes, count frequency across participants, and assess impact severity. Note contradictions and surprises.

Create a priority matrix:

• High frequency + High impact: Top priority findings
• Low frequency + High impact: Important for specific segments
• High frequency + Low impact: Quality-of-life improvements
• Low frequency + Low impact: Note but deprioritize

4. Generate the Synthesis

Produce a structured research synthesis:

Research Overview

• Methodology: what types of research, how many participants/sources
• Research question(s): what we set out to learn
• Timeframe: when the research was conducted

Key Findings

For each major finding (aim for 5-8):

• Finding statement: One clear sentence describing the insight
• Evidence: Supporting quotes, data points, or observations (with source attribution)
• Frequency: How many participants/sources support this finding
• Impact: How significantly this affects the user experience or business
• Confidence level: High (strong evidence), Medium (suggestive), Low (early signal)

Order findings by priority (frequency x impact).

User Segments / Personas

If the research reveals distinct user segments:

• Segment name and description
• Key characteristics and behaviors
• Unique needs and pain points
• Size estimate if data is available

Opportunity Areas

Based on the findings, identify opportunity areas:

• What user needs are unmet or underserved
• Where do current solutions fall short
• What new capabilities would unlock value
• Prioritized by potential impact

Recommendations

Specific, actionable recommendations:

• What to build, change, or investigate further
• Tied back to specific findings
• Prioritized by impact and feasibility

Open Questions

What the research did not answer:

• Gaps in understanding
• Areas needing further investigation
• Suggested follow-up research methods

5. Review and Extend

After generating the synthesis:

• Ask if any findings need more detail or different framing
• Offer to generate specific artifacts: persona documents, opportunity maps, research presentations
• Offer to create follow-up research plans for open questions
• Offer to draft product implications (how findings should influence the roadmap)

Output Format

Use clear headers and structured formatting. Each finding should stand on its own — a reader should be able to read any single finding and understand it without reading the rest.

Tips

• Let the data speak. Do not force findings into a predetermined narrative.
• Distinguish between what users say and what they do. Behavioral data is stronger than stated preferences.
• Quotes are powerful evidence. Include them generously, with attribution to participant type (not name).
• Be explicit about confidence levels. A finding from 2 interviews is a hypothesis, not a conclusion.
• Contradictions in the data are interesting, not inconvenient. They often reveal distinct user segments.
• Recommendations should be specific enough to act on. "Improve onboarding" is not actionable. "Add a progress indicator to the setup flow" is.
• Resist the temptation to synthesize too many themes. 5-8 strong findings are better than 20 weak ones.