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user-research-synthesis

Transforms raw research data into prioritized recommendations with traceable sources.

Updated Aug 23, 2026
Search Tags:#research#prioritization#synthesis#themes#jtbd#product-decision
One-click install
npx skills add https://github.com/jupitermoney/pm-superic-skills --skill user-research-synthesis-jupitermoney
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: user-research-synthesis
Source: https://github.com/jupitermoney/pm-superic-skills/tree/main/pm-market-research/skills/user-research-synthesis
Command: npx skills add https://github.com/jupitermoney/pm-superic-skills --skill user-research-synthesis-jupitermoney

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Synthesize a corpus of user research into structured insights to guide product decisions, replacing scattered notes with a coherent, strategic narrative.

Core Features & Use Cases

  • Ingests multiple sources (interviews, surveys, usability tests, NPS responses, and support tickets) and surfaces JTBD themes and segment patterns.
  • Produces actionable recommendations with confidence ratings and next steps, anchored in evidence.
  • Enables traceability by mapping conclusions back to original sources to support stakeholder alignment.

Quick Start

Paste your raw research materials (transcripts, notes, survey results, and NPS data) and specify the decision you want to inform.

Frequently Asked Questions about user-research-synthesis

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

FAQPage Schema
How do I synthesize user research from multiple sources into actionable insights?▼

Synthesize user research by ingesting raw interviews, surveys, and support tickets to extract JTBD themes, segment patterns, and recommended actions with confidence ratings to guide product decisions.

What is the best way to turn scattered user interview notes into product decisions?▼

Turn scattered interview notes into product decisions by clustering signals into structured JTBD themes and mapping conclusions back to original sources to ensure stakeholder alignment.

Can I combine NPS responses and usability test data for theme clustering?▼

Combine NPS responses and usability test data through multi-step ingestion to extract consistent signals, cluster them into unified JTBD themes, and generate actionable product recommendations.

How do I extract Jobs-to-be-Done themes from a large corpus of support tickets?▼

Extract JTBD themes from support tickets by processing the corpus through signal extraction and theme clustering, which translates raw qualitative feedback into structured product insights.

Does user research synthesis provide traceable recommendations for stakeholders?▼

User research synthesis provides traceable recommendations by mapping generated actionable insights and confidence ratings directly back to the original source materials and evidence.

What do I need to prepare to start synthesizing my user research corpus?▼

Prepare to synthesize your user research corpus by gathering raw materials like transcripts and survey results, then specifying the exact product decision you want the analysis to inform.

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