Unlocking Product-Market Fit with Data-Driven Rigor

Most teams fail because they scale before they have proof of stickiness. The PMF Evaluator is a specialized skill for developers, founders, and product agents to diagnose, measure, and improve Product-Market Fit (PMF) using a structured "Evidence Ladder." It moves beyond gut feeling by triangulating qualitative interviews, behavioral analytics, and structured surveys.

What it does

• Audit Evidence: Analyzes your current metrics, interview notes, or survey results against five key rungs: Problem Fit, Solution Resonance, Behavioral Proof, Economic Proof, and Expansion Proof.
• Run Structured Surveys: Generates and analyzes "Must-Have" surveys (Ellis/Vohra method) to identify the "very disappointed" user segment.
• Interpret Hard Metrics: Evaluates retention cohorts, DAU/MAU, NDR, and LTV/CAC against industry benchmarks to separate vanity metrics from true growth.
• Draft Roadmaps: Identifies the exact bottleneck in your funnel and provides a "Go/Hold/Pivot" recommendation with a prioritized action plan.

Why use this skill

Prompting an AI to "analyze my PMF" usually results in generic advice. This skill implements specific frameworks from industry experts like Sean Ellis, Rahul Vohra, and Marty Cagan. It forces a rigorous segmentation check (one segment, one job) and produces a standardized PMF Scorecard. The output isn't just prose—it's a diagnostic report that identifies exactly which layer of your product strategy is leaking value.