Types of MVP: How to Choose the Right Format
A skill from the The Lean Startup: Build-Measure-Learn Methodology method.
Compare the types of MVP, from landing page and concierge to Wizard of Oz, piecemeal and single-feature, and pick one that tests your riskiest assumption.
Compare the types of MVP, from landing page and concierge to Wizard of Oz, piecemeal and single-feature, and pick one that tests your riskiest assumption.
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At a Glance
| Field | Value |
|---|---|
| Difficulty | Beginner |
| Time to Learn | An hour or two to learn the types, then practice on real questions |
| Outcome | You match the question you need answered to the cheapest MVP type that can answer it, and you can explain why the other types were ruled out. |
| Prerequisites | A testable hypothesis, a rough sense of budget and time, knowledge of the target segment |
| Part of | Lean Startup |
Overview
There are many types of MVP, and they answer different questions. A landing page can tell you whether people want something enough to sign up or pay. A concierge MVP tells you whether the service is valuable when a person delivers it by hand. A Wizard of Oz MVP tells you how customers respond to what looks like a working product. This skill covers the common types of minimum viable product and how to choose among them so you build the smallest thing that answers your most important question.
Eric Ries defines an MVP as the version of a new product that collects "the maximum amount of validated learning about customers with the least effort," and he stresses that choosing one "requires judgment to figure out, for any given context, what MVP makes sense" (Ries, MVP guide). The type is the main judgment call. The same hypothesis can often be tested three ways at very different costs, and the cheapest adequate option is usually right.
The Lean Startup method covers where MVPs sit in the Build-Measure-Learn loop, and how to build a minimum viable product covers scoping and launching one. This page covers the choice that comes between: which kind of thing to build.
Well-known cases show the range. Dropbox used a short demonstration video of the product working, and Ries writes that it validated the founder's leap-of-faith assumption because people actually signed up (Ries on TechCrunch). Food on the Table began with one customer served by hand and added customers one at a time (Food on the Table case study). Groupon's first version used WordPress and other existing tools rather than custom technology (CRV, What is an MVP?).
The output of this skill is a short decision record: the hypothesis, the MVP type chosen, the reason, and the types ruled out and why. That record makes the choice easy to revisit if the test gives an unclear answer.
How It Works
Each type trades cost against the strength of the evidence it produces. The table summarizes the common types, with a source for each definition.
| MVP type | What it is | Best for |
|---|---|---|
| Landing page | A page describing the offer with a sign-up or buy action (CRV) | Demand and messaging |
| Explainer video | A short demo of the product as it is meant to work (Ries on Dropbox) | Demand for a product that is hard to describe |
| Concierge | Manually helping users reach their goal (OpenClassrooms) | Value of the outcome, customer needs |
| Wizard of Oz | Looks automated while humans do the work (CRV) | Response to the product experience |
| Piecemeal | Existing tools combined into an offering (CRV) | Whether the full service works end to end |
| Single-feature | One key feature at launch (CRV) | Use and retention of the core feature |
Landing page and video MVPs test demand. They are cheap and fast, and they can reach many people through ads or communities. Their weakness is that a sign-up is a small commitment. Asking for a deposit or a pre-order makes the signal stronger. OpenClassrooms cites Buffer, whose founder collected sign-ups through a landing page describing the product (OpenClassrooms).
Concierge and Wizard of Oz MVPs test value. Customers receive the actual outcome, so you learn whether it helps them and whether they come back. The difference is what the customer knows. In a concierge MVP they see the person helping them, which makes it a good way to learn what they need. In a Wizard of Oz MVP they see a product interface, which lets you test the experience before the automation exists. OpenClassrooms gives Aardvark as a Wizard of Oz example: questions were routed to experts by hand behind what looked like an automated system.
Piecemeal and single-feature MVPs test a working product at small scale. A piecemeal MVP strings together existing services, such as a website builder, a form tool and a payment link, to deliver the full offer without new technology. A single-feature MVP builds one feature properly and leaves the rest out. CRV's example is Uber's early product, which offered only smartphone-based ride requests (CRV). These cost more than a landing page but produce evidence about real, repeated use.
The choice starts from the hypothesis. If the question is whether anyone wants this, start with demand tests. If it is whether the outcome is worth paying for, use a concierge or Wizard of Oz MVP. If it is whether people will keep using a working product, use piecemeal or single-feature. Strategyzer's advice to decide what to learn and measure before choosing the test applies directly (Strategyzer).
Step-by-Step Guide
Step 1: State the question the MVP must answer
Take the hypothesis you are testing and classify its question: demand, value, experience or sustained use. Write the question in one sentence. If the hypothesis covers more than one kind of question, split it and choose an MVP for the most important part first.
Step 2: Shortlist the types that fit
Use the table to list every type that could answer the question. For a demand question, that might be a landing page, a video or an ad smoke test. For a value question, a concierge or Wizard of Oz MVP. Keep two or three candidates.
Step 3: Rate each candidate on cost and signal
For each candidate, estimate the time and money to run it and how strong its evidence would be. Behavior that costs the customer something, such as payment or repeated use, is stronger than a click. Note any practical limits, such as how many customers a concierge approach can serve by hand.
Step 4: Check the constraints
Consider what could make a type unsuitable. A Wizard of Oz MVP needs a plan for how customers would react if they learned people were behind it. A public landing page can reveal your idea to competitors. A concierge MVP may not reach enough people to show a trend. Drop candidates that fail a constraint.
Step 5: Choose and record the decision
Pick the cheapest candidate whose evidence would be strong enough to change your decision. Write down the type, the reason, the candidates ruled out and the pass mark. Then move to building the MVP with that scope.
Step 6: Plan the next type in the sequence
Most products move through several MVP types as questions are answered. A passed landing page test often leads to a concierge MVP, and a passed concierge MVP to a Wizard of Oz or single-feature product. Note which type you expect to use next if this one passes, so the team knows what a pass leads to.
Best Practices
- Start with the cheapest type that could change your mind. A landing page or video can rule out a weak idea before any service is delivered.
- Ask for a real commitment when you test demand. A deposit, pre-order or booked call is stronger evidence than an email address.
- Use a concierge MVP to learn, then automate. The Food on the Table team coded only the tasks that became too time consuming to do by hand (case study).
- Keep a Wizard of Oz MVP honest. Deliver what you promise, protect customer data handled by people and be ready to explain how the service works.
- Build a single feature well. A single-feature MVP only tests use if that feature is reliable.
- Record the types you ruled out. If the result is unclear, the record shows what to try next.
Common Mistakes
- Defaulting to a coded product: Teams often build software because it is what they know how to do. Check whether a landing page, concierge or piecemeal MVP could answer the question first.
- Treating sign-ups as proof of value: A landing page shows interest in a description. It does not show that the product helps once people use it.
- Scaling a concierge MVP too long: Serving customers by hand is meant to teach you what to build. When the manual work stops producing new learning, move to the next type.
- Picking the type the team is most comfortable with: Designers reach for prototypes and engineers for code. Start from the question and let it choose the type.
- Mixing types in one test: Combining a new landing page and a new concierge service in one test makes it unclear which drove the result. Change one thing at a time.
References
- Examples: Worked examples and scenarios
- FAQ: Frequently asked questions
- Parent Method: Lean Startup
Related Skills
- How to Build a Minimum Viable Product (MVP)
- Designing Validated Learning Experiments
- Lean Startup Hypothesis Template: Testable Hypotheses
- Running the Build-Measure-Learn Loop
- Innovation Accounting Metrics: Tracking Real Progress
- Customer Discovery Interview Questions and Technique
- Pivot or Persevere: When to Pivot a Startup
Sources
- Eric Ries: Minimum Viable Product, a guide
- Eric Ries: How DropBox started as a minimal viable product
- Manuel Rosso: Food on the Table case study
- CRV: What is an MVP?
- OpenClassrooms: The 4 types of minimum viable product
- Strategyzer: Don't build when you build-measure-learn
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Other Skills in This Method
How to Build a Minimum Viable Product (MVP)
How to build a minimum viable product: scope the smallest version that tests your riskiest assumption, instrument it, launch it and decide what's next.
Customer Discovery Interview Questions and Technique
Customer discovery interview questions and technique: recruit the right people, ask about past behavior, avoid leading, and turn notes into evidence.
Pivot or Persevere: When to Pivot a Startup
Run pivot or persevere decisions on a schedule: judge experiment evidence, know when to pivot a startup, and pick a pivot type that keeps what you learned.
Designing Validated Learning Experiments
Design validated learning experiments: pick the test, from landing page to concierge MVP or Wizard of Oz test, and set pass marks before any data arrives.
Lean Startup Hypothesis Template: Testable Hypotheses
Use a lean startup hypothesis template to turn vague business assumptions into falsifiable statements with a metric and pass mark set before testing.
Running the Build-Measure-Learn Loop
Run the build-measure-learn loop as short, planned cycles that each end with a recorded lesson and a decision, so every iteration adds validated learning.
Innovation Accounting Metrics: Tracking Real Progress
Track innovation accounting metrics: set a baseline, pick actionable over vanity metrics, read cohorts and keep a scorecard that shows real progress.
Related Methods and Skills
Running Assumption Tests for Product Discovery
Identify the riskiest assumptions behind a product idea and run small, fast experiments that produce evidence before your team commits to building.
Define MVP Scope with MoSCoW: Drawing the Must Line
How to define MVP scope with MoSCoW: use the Must haves to draw the boundary of a first release, check it against what you need to learn, and hold it.
Designing Assumption Tests for OST Solutions
Design assumption tests for solutions on your opportunity solution tree: surface hidden assumptions, map the riskiest, and test them with set criteria.
Designing Step-Projects to Validate Product Ideas
Design GIST step-projects as small, time-boxed experiments that test an idea's riskiest assumption and end in a clear continue, change or stop call.
Building Opportunity Solution Trees for Product Discovery
Build and maintain an opportunity solution tree that links one measurable outcome to customer opportunities, candidate solutions, and assumption tests.
Iterative Design Process User Feedback Loops in Practice
Run repeated build, test and refine cycles with real users, turn feedback into specific revisions, and decide when to pivot, persevere or stop.
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