How does the ICP Analysis skill research potential customers?

It uses specialized WebSearch patterns to scan Reddit, LinkedIn, and industry forums for real user complaints, competitor reviews, and professional context to validate actual pain points.

Can this skill help me avoid the wrong customers?

Yes, it specifically identifies 'anti-personas'—segments that might appear to be a fit but are too small, too large for your current scale, or have a low willingness to pay.

Where is the analysis output stored?

The analysis is written to a structured markdown file in your product's spec directory, making it ready for use in the PDE pipeline's validation stage.

What metrics are used to rank customer segments?

Segments are scored on a 1-5 scale based on four weighted factors: pain severity (30%), reachability (25%), willingness to pay (25%), and market size (20%).

Ideal Customer Profile Analysis

Name: Ideal Customer Profile Analysis
Author: difflabai

bydifflabai

0•

Marketing Automation

Analyzes and defines the Ideal Customer Profile for a product by researching pain points, segmenting audiences, and ranking market opportunities.

The ICP Analysis skill automates the process of identifying your most valuable customers by evaluating potential segments across demographics, psychographics, behavioral signals, and economic fit. It uses a structured framework to search for real-world pain points on forums and social media, calculates weighted scores for segment viability, and helps prioritize your primary audience while explicitly identifying anti-personas to avoid. This skill is essential for founders and product teams looking to validate product-market fit and focus their go-to-market strategy on high-intent customer segments.

Key Features

01Weighted segment scoring to objectively rank market opportunities

020 GitHub stars

03Automated market research via targeted WebSearch query patterns

04Four-dimensional evaluation framework (Demographic, Psychographic, Behavioral, Economic)

05Detailed profile generation for primary and secondary segments

06Anti-persona identification to prevent wasted marketing and dev effort

Use Cases

01Evaluating product-market fit from a customer-centric perspective during the discovery phase

02Building detailed buyer personas based on real-world customer complaints and discussions

03Identifying high-value target segments for a new product or startup idea

Key Features

01Weighted segment scoring to objectively rank market opportunities

020 GitHub stars

03Automated market research via targeted WebSearch query patterns

04Four-dimensional evaluation framework (Demographic, Psychographic, Behavioral, Economic)

05Detailed profile generation for primary and secondary segments

06Anti-persona identification to prevent wasted marketing and dev effort

Use Cases

01Evaluating product-market fit from a customer-centric perspective during the discovery phase

02Building detailed buyer personas based on real-world customer complaints and discussions

03Identifying high-value target segments for a new product or startup idea