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synthesize-research

Synthesize user research inputs into prioritized findings with evidence and recommendations.

1|Updated Mar 30, 2026
Search Tags:#insights#personas#synthesize#user-research#thematic-analysis#research-synthesis#opportunity-sizing
One-click install
npx skills add https://github.com/ilove323/comlan-skills --skill synthesize-research-ilove323
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: synthesize-research
Source: https://github.com/ilove323/comlan-skills/tree/main/product-management/skills/synthesize-research
Command: npx skills add https://github.com/ilove323/comlan-skills --skill synthesize-research-ilove323

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Research inputs (interviews, surveys, support tickets, analytics) are often fragmented and noisy, making it hard to extract reliable, prioritized findings that product teams can act on. This Skill organizes raw qualitative and quantitative evidence into clear findings, confidence levels, and actionable recommendations so teams can make evidence-backed product decisions.

Core Features & Use Cases

  • Multi-source synthesis: Combine interview transcripts, survey responses, support tickets, and analytics summaries into a unified set of observations.
  • Thematic analysis & prioritization: Group observations into themes, count frequency across sources, assess impact, and produce a prioritized matrix (frequency × impact) with confidence levels.
  • Evidence attribution & deliverables: Extract representative quotes, behavioral signals, personas, opportunity estimates, research gaps, and roadmap recommendations formatted as a structured synthesis report.
  • Use cases: Rapidly preparing a research brief for a roadmap meeting, converting support ticket trends into product opportunities, or turning open survey responses into prioritized findings for engineering planning.

Quick Start

Synthesize these interview notes and survey responses into a prioritized research report with the top five findings, supporting evidence, confidence levels, and concrete roadmap recommendations.

Frequently Asked Questions about synthesize-research

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I synthesize user research into prioritized findings?▼

To synthesize user research, group raw qualitative and quantitative inputs into structured themes, count frequency across sources, assess impact, and produce a prioritized matrix with confidence levels and supporting evidence.

What is thematic analysis for user research data?▼

Thematic analysis for user research involves extracting observations from fragmented inputs like interviews and support tickets, grouping them by frequency and impact, and attributing representative quotes to form structured findings.

How do I turn support tickets and survey responses into product opportunities?▼

Turn support tickets and survey responses into product opportunities by combining multi-source inputs into unified observations, estimating confidence and opportunity sizing, and formatting them into a synthesis report with roadmap recommendations.

Can I combine interview transcripts and product analytics into one research brief?▼

Yes, you can combine interview transcripts and product analytics. Multi-source synthesis merges qualitative and quantitative evidence into a single set of observations, creating a unified research brief with prioritized findings.

What is the best way to prepare a research synthesis report for a roadmap meeting?▼

The best way to prepare a research synthesis report for a roadmap meeting is to structure findings by frequency and impact, include representative quotes, estimate confidence levels, and provide concrete suggested roadmap actions.

How does confidence estimation work when synthesizing research findings?▼

Confidence estimation works by evaluating the consistency and volume of evidence across multiple sources, attributing supporting quotes or behavioral data, and assigning a confidence level to each finding within the prioritized matrix.

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