What is an MVP? - Explanation & Meaning
Learn what an MVP (Minimum Viable Product) is, how the lean startup build-measure-learn cycle works, and why an MVP is essential for validating ideas fast.
Definition
An MVP (Minimum Viable Product) is the most stripped-down version of a product that contains just enough functionality to serve early users and gather valuable feedback. It enables you to validate an idea with minimal investment.
Technical explanation
The MVP concept comes from Eric Ries' lean startup methodology and follows the build-measure-learn cycle. Build: develop the minimal set of features that solve the core problem. Measure: collect quantitative data (conversions, retention, NPS) and qualitative feedback from real users. Learn: analyze results to decide whether to continue (persevere), adjust (pivot), or stop. An MVP is not a prototype or proof of concept: it must be a working product that delivers real value. Scope definition is crucial: identify the core value proposition and eliminate all features that do not directly contribute to validating your hypothesis. Technically, an MVP can use no-code/low-code tools, build on an existing platform, or be a "Wizard of Oz" MVP where manual processes simulate automation. After validation, iterative improvement follows based on data, with each iteration getting closer to product-market fit.
How MG Software applies this
MG Software guides clients from idea to MVP and beyond. We help define the minimal scope needed to validate the core hypothesis. We build MVPs with modern technologies that can grow into a full product after validation. Our approach combines fast delivery with a solid technical foundation so successful MVPs do not need to be completely rebuilt.
Practical examples
- A startup validating a food delivery platform by first building a simple web page with an order form and processing orders manually, before building a fully automated system.
- A SaaS company launching an MVP of a project management tool with only task management and team communication, without advanced reporting, to validate whether teams actually switch from their current tool.
- An enterprise organization building an internal MVP for an AI chatbot with three core functions, measuring how often employees use it, and deciding on further investment based on the results.
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