Here are some of the discovery techniques described in the book:
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Build-Measure-Learn Feedback Loop: The sources describe a core feedback loop called Build-Measure-Learn. This process involves building a minimum viable product (MVP) to test a hypothesis, measuring customer response to the MVP, and learning from the data to inform the next iteration of the product.
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Leap-of-Faith Assumptions: The sources use the term "leap-of-faith assumptions" to refer to the riskiest elements of a startup's plan, the parts on which everything depends. The two most important assumptions are the value hypothesis and the growth hypothesis.
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Validated Learning: The sources emphasize the importance of "validated learning," which is learning that is demonstrated by positive improvements in a startup's core metrics and backed up by empirical data collected from real customers.
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Scientific Experimentation: The sources advocate for using the scientific method in startup product development, treating each feature, marketing campaign, and product as an experiment to test a hypothesis.
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Minimum Viable Product (MVP): The sources describe the MVP as the smallest version of a product that can be used to begin the process of learning using the Build-Measure-Learn feedback loop. The MVP is not about creating a low-quality product, but about testing assumptions as quickly as possible. Examples of MVPs include:
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Concierge MVP: This type of MVP involves manually providing a service to a small group of customers to test a specific hypothesis, even if the service is not scalable or profitable at that stage.
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Wizard of Oz Testing: This technique involves making customers believe they are interacting with the actual product, while behind the scenes, humans are doing the work.
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Innovation Accounting: This alternative to traditional accounting is designed specifically for startups. It involves turning leap-of-faith assumptions into a quantitative financial model, establishing baselines for key metrics, tuning the engine of growth, and using cohort analysis and split tests to measure progress.
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Cohort Analysis: This technique involves tracking the behavior of groups of customers (cohorts) who share a common characteristic, such as the date they signed up for a service.
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Split Tests (A/B Testing): This involves dividing customers into two or more groups and exposing each group to a different variation of a product or feature to measure the impact of the change.
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Genchi Gembutsu: This Japanese term, meaning "go and see for yourself," emphasizes the importance of firsthand observation and understanding of customers and their needs.
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Customer Archetypes: Creating detailed profiles of target customers to understand their needs, motivations, and behaviors.

The Lean Startup Eric Ries

Dmitry Nosov