user-research-synthesis

Name: user-research-synthesis
Availability: InStock
Author: coalesce-labs

Convert raw user interview data into themes, quotes, and prioritized recommendations.

20|4|Updated Oct 4, 2025

Search Tags:#interviews #synthesis #themes #user-research #quotes #product-insights

Ready to run

npx skills add https://github.com/coalesce-labs/catalyst --skill user-research-synthesis-coalesce-labs

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: user-research-synthesis
Source: https://github.com/coalesce-labs/catalyst/tree/main/plugins/pm/skills/user-research-synthesis
Command: npx skills add https://github.com/coalesce-labs/catalyst --skill user-research-synthesis-coalesce-labs

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Transforms raw user interview data into structured, actionable product insights by performing rigorous synthesis across observations, quotes, and themes.

Core Features & Use Cases

Upload raw data (transcripts, notes, usability comments) to begin the synthesis process.
Extract key observations including verbatim quotes, behaviors, pain points, and Jobs-To-Be-Done signals.
Cluster observations into themes (affinity mapping) and identify patterns, contradictions, and root causes.
Generate actionable recommendations and a synthesis-ready narrative for product strategy and PRD planning.
Use cases include summarizing interviews for PMs, informing feature decisions, and producing executive-ready insights.

Quick Start

Upload your raw interview notes to start extracting quotes and forming initial themes.

Frequently Asked Questions about user-research-synthesis

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

FAQPage Schema

How do I turn user interview transcripts into actionable product insights?▼

To turn user interview transcripts into actionable product insights, upload raw data to extract key observations including verbatim quotes and behaviors, cluster them into themes, and generate prioritized recommendations. The synthesis workflow applies JTBD framing to produce executive-ready narratives.

What is user research synthesis and how does affinity mapping work?▼

User research synthesis is the process of converting raw interview data into structured themes. It uses affinity mapping to cluster observations, identify patterns and contradictions, and frame root causes, ultimately producing actionable recommendations for product strategy and PRD planning.

Can I analyze usability study feedback and open-ended comments with this synthesis approach?▼

Yes, you can analyze usability study feedback and open-ended comments. The synthesis workflow accepts raw transcripts, notes, and usability comments, extracting pain points and JTBD signals to inform feature decisions and produce executive-ready product insights.

How do I extract verbatim quotes and JTBD signals from user interviews?▼

Extract verbatim quotes and JTBD signals by uploading raw interview data into the synthesis workflow. It automatically identifies behaviors, pain points, and Jobs-To-Be-Done signals, then clusters them into themes based on frequency and severity for prioritized recommendations.

What's the best way to summarize user interviews for product managers?▼

The best way to summarize user interviews for PMs is using a multi-step synthesis workflow that extracts observations, clusters themes via affinity mapping, and generates actionable recommendations. It emphasizes verbatim quotes, frequency, and severity to produce executive-ready insights.

Does user research synthesis require specific formats for interview notes or transcripts?▼

User research synthesis does not require specific formats. You can upload raw interview transcripts, notes, or usability comments directly. The workflow processes unstructured data to extract observations, cluster themes, and generate prioritized product insights.