customer-research

Installation
SKILL.md

Customer Research

Overview

Customer research systematically gathers insights about target users to inform product and market decisions. This skill covers methodologies for understanding customer needs, behaviors, and preferences.

Required Frameworks

Framework Output Section Required Condition
Persona Development Customer Personas yes
Jobs-to-be-Done JTBD Analysis yes
Journey Mapping Customer Journey yes
Segmentation & Prioritization Customer Segments yes

Trend Indicators: Load and apply the trend indicator definitions from protocols/TREND-INDICATORS.md.

Research Types

Quantitative Research

  • Surveys and questionnaires
  • Usage analytics
  • A/B testing results
  • Market share data
  • NPS/satisfaction scores

Qualitative Research

  • Customer interviews
  • Focus groups
  • Observation studies
  • Support ticket analysis
  • Review mining

Persona Development

Core Elements

Demographics

  • Age range
  • Job title/role
  • Industry
  • Company size
  • Location

Psychographics

  • Goals and motivations
  • Pain points and frustrations
  • Decision-making style
  • Information sources
  • Technology comfort

Behaviors

  • Current solutions used
  • Buying process
  • Key triggers
  • Evaluation criteria

Persona Template

## [Persona Name]

### Profile
- **Role**: [Job title]
- **Company**: [Size, industry]
- **Experience**: [Years in role]

### Goals
1. [Primary goal]
2. [Secondary goal]
3. [Tertiary goal]

### Pain Points
1. [Major frustration]
2. [Secondary frustration]
3. [Minor annoyance]

### Quote
"[Representative statement capturing mindset]"

### Buying Behavior
- **Trigger**: [What prompts search]
- **Research**: [How they evaluate]
- **Decision**: [Who/what influences]
- **Timeline**: [Typical cycle length]

### Preferred Channels
- [Channel 1]
- [Channel 2]

Jobs-to-be-Done Framework

Focus on what customers are trying to accomplish:

Functional Jobs

  • Core task to complete
  • Measurable outcomes desired

Emotional Jobs

  • How they want to feel
  • Social perception goals

Related Jobs

  • Before/after the core job
  • Supporting tasks

JTBD Statement Format

"When [situation], I want to [motivation], so I can [expected outcome]."

Example: "When I'm preparing a market analysis, I want to quickly find reliable data, so I can make confident recommendations to leadership."

Customer Journey Mapping

Journey Stages

  1. Awareness

    • How do they discover they have a need?
    • What triggers the search?
  2. Consideration

    • What options do they evaluate?
    • What criteria matter most?
  3. Decision

    • Who influences the choice?
    • What tips the decision?
  4. Purchase

    • What friction points exist?
    • What enables conversion?
  5. Onboarding

    • First experience expectations
    • Success metrics
  6. Retention/Advocacy

    • What drives continued use?
    • What triggers referrals?

Journey Map Template

Stage Actions Thoughts Emotions Pain Points Opportunities
Awareness
Consideration
Decision
Purchase
Onboarding
Retention

Data Collection Methods

Interview Framework

Note: This section applies when conducting primary research interviews. For AI secondary research synthesis, use these as topic weighting guides rather than time allocations.

Opening (5 min)

  • Build rapport
  • Explain purpose
  • Get permission to record

Current State (15 min)

  • Walk me through your typical workflow
  • What tools do you use?
  • What's working well?

Pain Points (15 min)

  • What's most frustrating?
  • Tell me about a recent challenge
  • What would make your life easier?

Ideal State (10 min)

  • If you could wave a magic wand...
  • What would success look like?
  • How would you measure it?

Closing (5 min)

  • Anything else to add?
  • Can I follow up?
  • Referrals?

Review Mining

Extract insights from:

  • G2, Capterra, TrustRadius
  • App store reviews
  • Reddit discussions
  • Twitter/social mentions
  • Support forums

What to look for:

  • Repeated complaints
  • Feature requests
  • Competitor comparisons
  • Use case descriptions
  • Emotional language

Segmentation

Segmentation Criteria

Demographic: Company size, industry, role Behavioral: Usage patterns, buying frequency Needs-based: Problem severity, sophistication Value-based: Revenue potential, strategic fit

Segment Prioritization

Segment Size Need Intensity Accessibility Competition Priority
[Name] S/M/L H/M/L H/M/L H/M/L 1-5

Output Structure

## Customer Research Summary

### Key Segments
1. [Segment 1]: [Description, size]
2. [Segment 2]: [Description, size]

### Personas
[Persona summaries]

### Jobs-to-be-Done
1. [Core job]
2. [Supporting job]

### Journey Insights
- **Awareness**: [Key finding]
- **Consideration**: [Key finding]
- **Decision**: [Key finding]

### Pain Points (Ranked)
1. [Most severe]
2. [Second]
3. [Third]

### Opportunities
1. [Unmet need 1]
2. [Unmet need 2]

### Trend Indicators
- Customer sophistication: INC/DEC/CONST
- Willingness to pay: INC/DEC/CONST
- Switching propensity: INC/DEC/CONST

Mandatory Output Rules

  1. Every persona must include: name, role, company size, key pain points, buying triggers
  2. Every segment must include: size estimate, growth direction (INC/DEC/CONST), confidence level
  3. All claims must cite specific sources (see protocols/TREND-INDICATORS.md)
  4. NEVER use placeholder values ($X, TBD, [insert])
  5. Minimum 3 customer segments identified

Pre-Output Validation Checklist

  • All personas have complete fields (name, role, company size, pain points, buying triggers)
  • All segments have size estimates with sources
  • No placeholder values remain
  • Confidence levels assigned per universal scale
  • Gaps documented in findings.gaps[]
  • Trend indicators (INC/DEC/CONST) applied to customer behavior metrics
  • At least 3 customer segments identified
  • Pain points ranked by severity with evidence

Best Practices

  • Talk to actual customers, not just internal assumptions
  • Include churned customers and non-customers
  • Distinguish between stated and revealed preferences
  • Update research regularly (behaviors change)
  • Quantify qualitative insights where possible

Additional Resources

For detailed frameworks, see:

  • references/interview-guide.md - Interview techniques
  • references/persona-examples.md - Sample personas
  • examples/journey-map.md - Complete journey map

Orchestration Hints

Confidence tiers (universal scale):

  • High: 3+ independent, recent (<12mo) sources that converge
  • Medium: 2 sources OR sources >12mo old OR indirect evidence
  • Low: Single source, inference, or extrapolation

Dimension-specific confidence criteria below REFINE (not replace) these universal definitions.

  • Cross-reference dimensions: competitive (feature gaps map to unmet needs), financial (willingness to pay, price sensitivity)
  • Alert triggers:
    • Unmet customer need with no existing solution in market
    • Customer segment not previously identified in scope
    • Switching cost barrier that invalidates competitive assumptions
  • Confidence rules:
    • High: Multiple customer data sources (surveys, reviews, interviews) align
    • Medium: 2 data sources or strong proxy indicators
    • Low: Single source or inferred from adjacent markets
  • Conflict detection:
    • Customer willingness-to-pay vs financial dimension's pricing models
    • Feature importance ranking vs competitive dimension's feature matrices
    • Segment sizes vs sizing dimension's SAM calculations
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