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A minimum viable product (MVP) is the version of a new product, or any experiment standing in for it, that lets a team learn the most about customers for the least effort. Eric Ries, who popularised the term, defines it as “that version of a new product which allows a team to collect the maximum amount of validated learning about customers with the least effort.” The emphasis is on learning, not on shipping fewer features.
The definition, piece by piece
Ries gives the definition in his first-person article “What Is an MVP? Eric Ries Explains” (Lean Startup Co.). Each phrase carries weight:
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- Version of a new product: the MVP is something you put in front of customers, but its form is flexible.
- Maximum validated learning: the output is evidence about customers, such as what they do, want or will pay for. It is not a launch or a feature count.
- Least effort: you spend only as much as you need to answer the question at hand.
Ries cautions that an MVP does not mean building a minimal product for its own sake. How minimal is “minimal” depends on the situation, the customer question and the effort needed to answer it. After the first iteration, a team may find its current version is good enough, or that customers are still dissatisfied and another iteration is needed.
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What an MVP is not
- Not the smallest possible feature list. A tiny product that teaches you nothing is not a useful MVP.
- Not a finished product with features cut. It can be incomplete compared with your eventual product and still do its job if it answers the question you chose.
- Not automatically the first polished release. It is an experiment vehicle.
The cited sources give no universal feature checklist or timeline for an MVP. Choosing one takes judgment about your context.
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What an MVP can look like
Benson Garner’s May 2016 Strategyzer post “Don’t Build When You Build-Measure-Learn” describes an MVP as an artifact or representation used to test one or more assumptions. The “build” step in build-measure-learn does not always mean building the intended product. Depending on the question, the MVP might be:
- a working product or a partial experience;
- a prototype;
- a data sheet or packaging prototype that answers an early question about the value proposition;
- a simple ad test that shows whether people respond to an offer.
How to choose the right MVP experiment
- Name the assumption. Pick the hypothesis that matters most, the one that would sink the idea if it were false.
- List candidate tests. These could be anything from an ad to a prototype to a limited working product.
- Compare them. Ask which assumption each test addresses, what customer behaviour or evidence it can reveal, how much time and effort it takes, and whether the result is strong enough to guide your next decision.
- Run the cheapest test that passes. Pick the least-effort option that still produces decision-useful evidence.
- Decide. Use what you observed to persevere or pivot.
These comparison criteria are a practical synthesis of the sources’ emphasis on hypothesis testing and least effort. They are not a fixed formula.
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- Keep track of everything from attendance to test scores
- Spiral bound
- Measures 8-1/2" x 11"
Where the MVP fits in Lean Startup
The Lean Enterprise Institute describes Lean Startup as treating business ideas as hypotheses to be validated through rapid experimentation and customer feedback. It dates Ries’s book The Lean Startup to 2011. Learning from the experiment feeds a decision to persevere on the current path or pivot. The Lean Startup methodology page likewise presents the MVP as a way to begin learning quickly under uncertainty. For the full method behind the term, Ries’s book is the natural next read.
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The sources reviewed contain no directly relevant, named statistic on how effective MVPs are, so none is quoted here. Treat the MVP as a reasoning tool, not a proven guarantee of success.
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