User Research Synthesizer

Synthesizes interviews, surveys and feedback into insights with affinity maps and prioritization.

Free plan: up to 10 private skills and 3 members, no credit card.

What this skill does

Synthesize user research interviews, surveys, and feedback into actionable insights. Provides affinity mapping frameworks, persona development templates, and insight prioritization methods. Use for research analysis, persona creation, or translating user feedback into product decisions.

  • research
  • synthesis
  • personas
  • insights
  • qualitative
  • UX
  • discovery
  • analysis

SKILL.md

Overview

Transform scattered user feedback into structured insights that drive product decisions. This skill encodes the frameworks for synthesizing qualitative research into actionable findings.

Research Synthesis Process

RAW DATA → OBSERVATIONS → PATTERNS → INSIGHTS → RECOMMENDATIONS

Step 1: Extract Observations

From each interview/feedback source, capture:

  • Direct quotes (verbatim)
  • Behaviors observed
  • Pain points mentioned
  • Goals expressed
  • Context details

Observation Format:

[Source ID] [Quote/Observation]
"I spend 2 hours every Monday just compiling reports" - User 5, Sales Manager

Step 2: Affinity Mapping

Group observations into themes:

Theme Observations Frequency
Reporting pain U1, U3, U5, U7, U9 5/10
Mobile needs U2, U4, U6 3/10
Integration gaps U1, U2, U8, U10 4/10

Step 3: Pattern Identification

Pattern Statement Format:

[WHO] experiences [WHAT problem/need]
when [CONTEXT/TRIGGER]
because [ROOT CAUSE]

Example:

Sales managers experience time-consuming manual reporting when preparing for weekly meetings because data lives in multiple disconnected systems.

Step 4: Insight Generation

Insight Format:

INSIGHT: [Actionable finding]
EVIDENCE: [Supporting data points]
CONFIDENCE: [High/Medium/Low]
IMPACT: [If we solve this, then...]

Example:

INSIGHT: Users need automated cross-system reporting
EVIDENCE: 5/10 users mentioned manual reporting pain, avg 2+ hrs/week
CONFIDENCE: High (consistent across segments)
IMPACT: Solving this would save ~100 hrs/month across user base

Persona Development

Persona Template

NAME: [Representative name]
ROLE: [Job title]
SEGMENT: [Customer segment]

GOALS
- Primary: [Main objective]
- Secondary: [Supporting goals]

PAIN POINTS
- [Pain 1]: [Impact]
- [Pain 2]: [Impact]

BEHAVIORS
- [How they work today]
- [Tools they use]
- [Decision-making style]

QUOTES
"[Verbatim quote that captures their perspective]"

SUCCESS METRICS
[How they measure success in their role]

Persona Validation Checklist

  • Based on actual research (not assumptions)
  • Represents a significant segment
  • Distinct from other personas
  • Actionable for product decisions
  • Includes both goals and frustrations

Insight Prioritization

Impact/Frequency Matrix

                HIGH FREQUENCY
                     │
   Address First     │    Top Priority
   (Common but       │    (Common and
    low impact)      │     high impact)
                     │
─────────────────────┼─────────────────────
                     │
   Monitor           │    Opportunistic
   (Rare and         │    (Rare but
    low impact)      │     high impact)
                     │
                LOW FREQUENCY

                LOW ←──────────────→ HIGH
                        IMPACT

Prioritization Criteria

Factor Weight Questions
Frequency 30% How many users mentioned this?
Severity 25% How painful is this problem?
Business Impact 25% Does this affect revenue/retention?
Solvability 20% Can we realistically address this?

Research Report Structure

EXECUTIVE SUMMARY
- Key findings (3-5 bullets)
- Recommended actions

METHODOLOGY
- Research type and sample
- Limitations

KEY INSIGHTS
- Insight 1 + evidence
- Insight 2 + evidence
- Insight 3 + evidence

PERSONAS (if applicable)
- Persona summaries

RECOMMENDATIONS
- Prioritized actions
- Quick wins vs. long-term

APPENDIX
- Raw data summary
- Full observation list

Quality Checklist

Before presenting findings:

  • Insights are based on patterns, not single data points
  • Direct quotes support each finding
  • Confidence level is stated
  • Recommendations are actionable
  • Limitations are acknowledged

Resources

references/

  • interview-guide.md — Research interview question templates
  • analysis-methods.md — Qualitative analysis techniques

assets/

  • persona-template.pptx — Persona presentation format
  • affinity-map-template.xlsx — Affinity mapping spreadsheet

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