Lean Analytics

Alistair Croll and Benjamin Yoskovitz provide a comprehensive guide on harnessing data to drive startup innovation and growth, emphasizing "Instincts are experiments. Data is proof." The book introduces five distinct startup stages (Empathy, Stickiness, Virality, Revenue, Scale) and the "One Metric That Matters"—the single most critical metric for your current stage. Analyzing six common business models from online retail to dual-sided marketplaces, it offers practical frameworks for tracking key metrics at each lifecycle phase to prevent entrepreneurs from lying to themselves.

13 sections · 51 lessons

Course outline

Metrics Fundamentals

  1. One Metric
  2. Evolving OMTM
  3. Vanity Metrics
  4. Actionable Metrics
  5. Qualitative & Quantitative
  6. Systematize Qualitative
  7. Metrics Fundamentals

Analytics Frameworks

  1. AARRR Framework
  2. Acquisition & Activation
  3. Retention & Revenue
  4. Analytics Cycle
  5. Cycle Practice
  6. Analytics Frameworks

Startup Stages: Empathy

  1. Real Problems
  2. Market Fit
  3. Startup Stages: Empathy

Startup Stages: Stickiness

  1. Product-Market Fit
  2. Retention Curves
  3. Startup Stages: Stickiness

Startup Stages: Virality

  1. Viral Mechanics
  2. Viral Cycle
  3. Startup Stages: Virality

Startup Stages: Revenue

  1. Unit Economics
  2. Monetization
  3. Startup Stages: Revenue

Startup Stages: Scale

  1. Scale Strategy
  2. Competitive Moat
  3. Startup Stages: Scale

Core Engagement Metrics

  1. Cohort Analysis
  2. Segmentation
  3. DAU/MAU Ratio
  4. Stickiness
  5. Core Engagement Metrics

Unit Economics

  1. LTV
  2. CAC Ratio
  3. Churn Rate
  4. Reduce Churn
  5. Unit Economics

Conversion Optimization

  1. Conversion Funnels
  2. Optimize Funnels
  3. Conversion Optimization

Business Models

  1. E-commerce Revenue
  2. E-commerce Optimization
  3. MRR
  4. SaaS Economics
  5. Mobile Metrics
  6. Mobile Engagement
  7. Marketplace Liquidity
  8. Marketplace Metrics
  9. Media Advertising
  10. Creator Dynamics
  11. Business Models

Growth and Experimentation

  1. Growth Engines
  2. Engine Metrics
  3. A/B Testing
  4. Test Execution
  5. Hypothesis Testing
  6. Validation Framework
  7. Pivot Signals
  8. Persevere Signals
  9. Growth and Experimentation

Data-Driven Culture

  1. Data Infrastructure
  2. Data Culture
  3. Data-Driven Culture

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