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ai-opportunity-analyzer

Score and rank AI product opportunities using a three-dimensional framework.

Updated Apr 7, 2026
Search Tags:#ai#user needs#prioritization#feasibility#product strategy#jTBD
One-click install
npx skills add https://github.com/uh-joan/ux-research-skills --skill ai-opportunity-analyzer
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ai-opportunity-analyzer
Source: https://github.com/uh-joan/ux-research-skills/tree/main/.claude/skills/ai-opportunity-analyzer
Command: npx skills add https://github.com/uh-joan/ux-research-skills --skill ai-opportunity-analyzer

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill helps product teams systematically evaluate and prioritize AI-related opportunities by integrating user research insights with technical and business feasibility metrics.

Core Features & Use Cases

  • Opportunity Scoring: Evaluates AI features across user needs, business impact, and technical feasibility dimensions.
  • Prioritization: Maps opportunities into a feasibility matrix to identify quick wins, strategic bets, or items to avoid.
  • Use Case: A UX team uses this Skill to rank five AI-enhanced features from user transcripts, enabling targeted roadmap planning and resource allocation.

Quick Start

Input your JTBD analysis files and project context to generate a prioritized list of AI opportunities ready for executive review.

Frequently Asked Questions about ai-opportunity-analyzer

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I prioritize AI product features based on user research and technical feasibility?▼

You can prioritize AI product features by scoring user research data and technical factors across a three-dimensional framework, mapping opportunities into a feasibility matrix to identify quick wins and strategic bets.

What is the best way to rank AI opportunities for a product roadmap?▼

The best way to rank AI opportunities is using a structured framework that evaluates user needs, business impact, and technical feasibility, generating a prioritized list ready for executive review and resource allocation.

How do I use JTBD analysis to evaluate AI feature ideas?▼

You use JTBD analysis files as input alongside project context, allowing the system to analyze user needs and technical factors to systematically score and rank your AI feature ideas.

Can I integrate user transcripts into an AI product strategy prioritization process?▼

Yes, you can input user transcripts as your user research data, which the system analyzes to evaluate AI-enhanced features and enable targeted roadmap planning based on structured scoring.

Does this approach distinguish between quick wins and strategic bets for AI planning?▼

Yes, this approach maps scored opportunities into a feasibility matrix, explicitly categorizing AI features into quick wins, strategic bets, or items to avoid for targeted resource allocation.

What metrics are needed to score AI opportunities effectively?▼

Scoring AI opportunities effectively requires metrics across three dimensions: user needs derived from research data, business impact, and technical feasibility factors.

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