
Ideal Customer Profile
This synthesizes customer research data into a structured Ideal Customer Profile with demographics, behaviors, Jobs to Be Done, and pain points. You'd use it when analyzing PMF survey responses, defining target segments from interview transcripts, or figuring out which customer cohorts actually retain and expand. It follows Clayton Christensen's JTBD framework and pushes you to look at both firmographics and the underlying motivations driving purchase decisions. The output includes disqualification criteria and go-to-market implications, which is helpful since knowing who not to sell to matters as much as knowing your ideal buyer. Best when you have actual customer data to feed it rather than hunches.
- skills.sh installs
- 3.1K
- GitHub stars
- 27.8K
- last updated
- Aug 21, 2026
Install
$ npx -y skills add phuryn/pm-skills --skill ideal-customer-profile --agent claude-codeInstalls into .claude/skills of the current project.
Files
Ideal Customer Profile
Overview
Identify your Ideal Customer Profile (ICP) from research and survey data. This skill synthesizes customer research to define the customer most likely to find value, retain, and expand with your product.
When to Use
- Defining ICP from product-market fit survey data
- Targeting high-value customer segments
- Analyzing customer success and expansion patterns
- Prioritizing sales and marketing efforts
- Evaluating new customer opportunities for fit
- Refining target market definition
ICP Framework Components
Demographics
Who are they from a firmographic and personal perspective?
- Company size (employees, revenue)
- Industry or vertical
- Geographic location
- Job title and department
- Years of experience in role
- Education and background
- Organizational structure and reporting
Behaviors
How do they work and make decisions?
- How they discover and evaluate solutions
- Buying process and decision-making timeline
- Technical literacy and product adoption speed
- Collaboration style (solo decision vs committee)
- Change management and adoption style
- Tool switching frequency
- Community involvement and peer influence
Sponsors
Details
- Repository
- github.com/phuryn/pm-skills
- Category
- Data Science & ML
- First seen
- May 16, 2026
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