Hypothesis Prioritization Matrix

Pro v1.0.0 1 view

Generate structured hypothesis prioritization matrices for PM interview root cause analysis with MECE categorization, scoring, and investigation sequences.

What You Get

Get interview-ready hypothesis frameworks with 15-20 MECE hypotheses, prioritization matrices, and data request sequences in minutes instead of hours of preparation.

The Problem

PM interview candidates struggle to demonstrate structured root cause analysis thinking. They need comprehensive hypothesis frameworks, proper prioritization, and clear investigation sequences but creating these from scratch under time pressure is difficult and error-prone.

The Solution

Analyzes metric change scenarios (DAU drops, conversion declines, activation rate changes) and generates complete hypothesis prioritization matrices. Produces 15-20 MECE hypotheses across Technical, Product, External, User Behavior, and Data Quality categories. Each hypothesis is scored on impact, likelihood, and ease-to-check (1-5). Creates 2x2 prioritization visualization, Wave 1/2/3 investigation sequences, specific data requests with time estimates, and polished interview talking points.

How It Works

  1. 1 Extract scenario details: metric affected, direction, magnitude, timeframe, and product context
  2. 2 Generate 15-20 hypotheses organized across MECE categories (Technical, Product, External, User Behavior, Data Quality)
  3. 3 Score each hypothesis on impact, likelihood, and ease-to-check using 1-5 scales
  4. 4 Build 2x2 prioritization matrix based on impact and likelihood dimensions
  5. 5 Organize hypotheses into Wave 1/2/3 investigation sequence based on composite priority scores
  6. 6 Create specific data requests with expected verification times and information gain
  7. 7 Generate 60-90 second interview talking points demonstrating structured thinking

What You'll Need

  • Metric change scenario (metric name, direction, magnitude, timeframe)
  • Product context (mobile app, web platform, B2B SaaS, e-commerce, etc.)

Get This Skill

Requires Pro subscription ($9/month)

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Examples

Mobile App Revenue Drop (Android-Specific)

Complex scenario with constraints: 25% revenue drop in 2 days, Android-specific, no recent deployments. Shows how the skill adapts hypotheses to platform-specific issues and considers non-deployment changes like A/B tests.

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B2B SaaS Sign-ups Drop (Incomplete Information)

Edge case with vague input: 'dropped significantly' without specific numbers. Demonstrates how the skill handles incomplete information by stating explicit assumptions, providing clarifying questions, and still delivering a complete analysis.

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E-commerce Conversion Rate Drop

Baseline scenario analyzing a 5% conversion rate drop over one week for a generic web product. Demonstrates standard MECE hypothesis generation across Technical, Product, Platform, External, and Data Quality categories.

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