Pawel Huryn
122 lines
4.2 KiB
Markdown
122 lines
4.2 KiB
Markdown
---
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description: Comprehensive user research — build personas, segment users, and map the customer journey from research data
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argument-hint: "<research data, survey results, or product description>"
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---
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# /research-users -- User Research Synthesis
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Turn raw research data into actionable user personas, behavioral segments, and customer journey maps. Accepts survey data, interview notes, feedback, analytics, or a product description for exploratory research.
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## Invocation
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```
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/research-users [upload survey results, interview notes, or feedback data]
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/research-users B2B project management tool for agencies — help me understand our users
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/research-users [paste user feedback or support ticket data]
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```
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## Workflow
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### Step 1: Accept Research Inputs
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Accept from any combination:
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- Survey responses (CSV, spreadsheet, pasted)
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- Interview notes or transcripts
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- Support tickets or feature requests
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- Product analytics / behavioral data
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- NPS or satisfaction data
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- Product description (for exploratory research without data)
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Ask:
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- What research do you have? What format?
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- What do you want to understand? (who are our users, how do they differ, where's the friction)
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- What decisions will this inform? (roadmap, positioning, pricing, onboarding)
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### Step 2: Build Personas
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Apply the **user-personas** skill:
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- Identify 3-4 distinct personas from the data
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- For each persona: name, role, goals (JTBD), pains, gains, behavioral patterns
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- Include unexpected insights — things that surprised you in the data
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- Note persona prevalence (what % of your base each represents, if data allows)
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### Step 3: Segment Users
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Apply the **user-segmentation** and **market-segments** skills:
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- Create behavioral segments (not just demographics)
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- For each segment: size, JTBD, product fit, willingness to pay, engagement level
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- Identify the highest-value segment and the highest-growth segment
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- Map segments to personas (how they overlap)
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### Step 4: Map the Customer Journey
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Apply the **customer-journey-map** skill:
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- Map the end-to-end journey: Awareness → Consideration → Onboarding → Active Use → Expansion → Advocacy
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- For each stage: touchpoints, emotions, pain points, aha moments
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- Identify the biggest drop-off points
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- Highlight moments of delight worth amplifying
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### Step 5: Generate Research Report
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```
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## User Research Report: [Product]
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**Date**: [today]
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**Data sources**: [what was analyzed]
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**Sample size**: [if applicable]
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### Executive Summary
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[3-5 sentences: key findings and implications]
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### Personas
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#### Persona 1: [Name] — "[Quote that captures them]"
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- **Who**: [role, context, experience level]
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- **Primary JTBD**: [When..., I want to..., so I can...]
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- **Key pains**: [top 3]
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- **Key gains**: [what delights them]
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- **Behavioral pattern**: [how they use the product]
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- **Prevalence**: [X% of user base]
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[Repeat for each persona]
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### User Segments
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| Segment | Size | Primary JTBD | Product Fit | Value | Growth |
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|---------|------|-------------|-------------|-------|--------|
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### Customer Journey Map
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| Stage | Touchpoints | Emotion | Pain Points | Opportunities |
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|-------|------------|---------|-------------|---------------|
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### Key Insights
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1. [Insight with supporting evidence]
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2. ...
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### Recommendations
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1. [Actionable recommendation tied to findings]
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2. ...
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### Open Questions
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[What the data didn't answer — suggested follow-up research]
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```
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Save as markdown.
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### Step 6: Offer Next Steps
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- "Want me to **create interview scripts** to go deeper on a specific persona?"
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- "Should I **analyze sentiment** across these segments?"
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- "Want me to **build a value proposition** for the top persona?"
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- "Should I **prioritize the journey map pain points** as feature opportunities?"
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## Notes
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- If data is thin, be transparent about confidence levels — 5 interviews → hypotheses, not conclusions
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- Personas should be useful, not decorative — every persona should influence a product decision
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- Behavioral segments are more actionable than demographic segments for product decisions
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- The journey map should surface emotions, not just actions — where users feel frustrated vs. delighted drives prioritization
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- If no data is provided, generate research-informed hypotheses and recommend how to validate them
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