Lean Analytics

Lean Analytics starts from the Lean Startup framework and discusses how entrepreneurs and product owners can use data to answer a core question: does anyone actually need what I am building? Combining Lean Startup, customer development, the Business Model Canvas, agile development, and continuous integration, the book proposes replacing gut decisions with a "Build-Measure-Learn" loop. The authors first dissect common self-deceiving metrics—"vanity metrics" such as cumulative sign-ups and page views that look impressive but cannot guide decisions—then introduce the concept of the One Metric That Matters (OMTM), urging teams to focus at any given moment on the single number that best reflects the current risk. The book divides business into six business models—e-commerce, SaaS, free mobile apps, media sites, user-generated content, and two-sided marketplaces—and provides a core metric system for each. It also divides a startup into five stages—empathy, stickiness, virality, revenue, and scale—emphasizing that "model × stage" jointly determines which metrics you should track. Part Three further provides reference baselines for each model (conversion rate, retention rate, churn rate, viral coefficient, etc.) to help readers judge whether their performance is "good enough" or whether they need to revise their assumptions. Part Four discusses innovation within enterprises and lean practice in large companies, and includes author interviews, acknowledgments, and references. Drawing on the experience of more than 100 founders, investors, and intrapreneurs, with over 30 case studies, the book is well suited as a methodology handbook for repeated reference.