The most common mistake at the start of an app project is too many ideas, not too few. A founder wants accounts, notifications, referrals, chat, analytics and ten settings screens at launch. Development stretches to a year, and the money runs out before the first real user arrives.
An MVP (minimum viable product) is not simply a reduced version. It is a way to test the central business hypothesis with real people as quickly as possible. This article explains how to distinguish essential features from extras, build an MVP that genuinely tests the hypothesis and avoid common early mistakes.
What an MVP really is
An MVP is a product version with the smallest set of features needed to solve one core user problem and test whether people will use it or pay for it. Its purpose is not to show an investor an attractive app. It is to gather evidence: do people use the product, return to it and pay?
An MVP is different from a poor product. It should not be unfinished or buggy. It should have a narrow scope while remaining functional and understandable. Users must be able to complete the main journey smoothly; they simply will not have dozens of secondary features.
Defining the core product hypothesis
Before designing features, answer one question: what user problem does the product solve, and how will you know it solves it well? If the answer is vague, such as ‘a convenient app for everything’, you cannot design an MVP because there is no clear hypothesis to test.
Frame the hypothesis as follows: a user with a particular need will take a specific action in the app because it is faster or easier than their current method. Choose one success metric—repeat use, payment, an enquiry or a completed order—that will show whether it worked. Describe one main journey from start to finish without branches or alternative routes.
Anything that does not directly help test that hypothesis is a candidate for a later release.
Separating essential features from extras
The first filter is simple: would the main user journey fail without this feature? If someone can still go from opening the app to the intended outcome—a purchase, enquiry or completed task—then the feature does not belong in the MVP.
The second filter is whether the task can temporarily be handled manually. You could message early customers personally instead of building notifications, or send order updates through a messenger instead of creating account histories. Manual processes are acceptable in an MVP when they help test demand sooner.
The third filter is whether the feature supports the core hypothesis. Referral schemes, polished animation and dark mode generally support growth or retention rather than hypothesis testing. They make sense after demand for the core journey has been demonstrated.
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What an MVP usually needs
A complete core journey from the first action to the intended result. Only the registration or sign-in fields and steps the service actually needs. Basic feedback: action confirmations, clear statuses and understandable errors. A way to accept payment or enquiries if those are part of the hypothesis—otherwise willingness to pay cannot be tested. A minimal admin interface or a way to manage data manually so the team can support early users even without automation.
What can usually wait
Personalisation and recommendations need data you do not yet have. Advanced in-product analytics can wait; external analytics tools are sufficient initially. Referral schemes, rewards and gamification support retention but have little value before the first users arrive. If only one user group uses the product, a complex roles and permissions system can be designed later. A mobile app can wait if a web version can test the hypothesis, since native development usually takes longer and costs more than a website or web service. Deep external integrations can also wait if the process can be handled manually for early users until demand is confirmed.
Common mistakes in MVP planning
Trying to cover every use case instead of one core journey. Adding features for the future because ‘we are writing the code anyway’, which extends delivery and blurs the test. Confusing an MVP with a prototype: it must work with real users and real data, not merely be a clickable mock-up. Failing to measure the outcome, leaving no way to tell whether the hypothesis was confirmed. Avoiding manual processes even when user volume does not yet justify automation.
How an MVP becomes a full product
After launch, decisions are based on evidence rather than assumptions. If the core journey supports the hypothesis, development follows priorities revealed by user behaviour: where people get stuck, what they request most often and what they would pay more for. If the hypothesis fails, discovering that through an MVP in a few weeks is cheaper than learning it after a year of full product development.
Development after the MVP usually follows a cycle: observe user behaviour, prioritise features using evidence rather than instinct, then introduce automation gradually where manual processes can no longer handle the volume.
