Lean, MVP, and Experimentation
Free AIPMM Certified Digital Product Manager practice — 6 questions on Lean, MVP, and Experimentation, with explanations. No sign-up. Full 12-question mixed test →
A startup wants to validate demand for an AI-powered meal-planning subscription. Instead of building the recommendation engine, the founders personally create each user's meal plan by hand and email it to them, openly telling subscribers during onboarding that a human is preparing their plan manually for now. Which MVP type does this describe?
A concierge MVP delivers the service manually while customers are fully aware a human is doing the work behind the scenes, allowing the team to learn about the value proposition with maximum direct customer interaction.
A team runs an A/B test on a new checkout flow. After only 2 days and 45 users per variant, the variant shows a 15% conversion lift with a p-value of 0.18. The product manager decides to ship the new flow immediately based on this trend. What critical experimentation principle did the PM violate?
A p-value of 0.18 is well above the conventional 0.05 significance threshold, and the sample size (45/variant) is likely far too small to draw a reliable conclusion — this is the classic 'peeking' error of stopping an experiment early on a favorable but statistically weak trend.
A team labels their new insurance-quote product an 'MVP' before testing it with real customers. In reality, they spent 9 months building a fully automated underwriting engine integrated with 12 external data providers, supporting all 50 US states, with a polished mobile app and 24/7 live support — all before showing it to a single prospective customer. What is the PRIMARY problem with calling this an MVP?
An MVP exists to test the riskiest assumption with the least investment; building a fully automated, fully integrated, all-state product for 9 months before any customer contact is a full product launch mislabeled as an MVP, not a genuine minimum-viable test.
A product team believes customers will pay $49/month for a not-yet-built 'AI contract review' feature. They have no working AI model yet. What is the CHEAPEST valid test to validate willingness to pay for this specific value proposition before building anything?
A landing page (smoke test) MVP requires no product build at all and directly measures purchase intent through the click/signup rate on the stated price point — this is the lowest-cost way to test willingness to pay for this exact value proposition.
After several build-measure-learn iterations, a team discovers that hobbyist bakers largely ignore their recipe-scaling app, but professional catering companies enthusiastically adopt it for the identical core scaling feature. The team keeps the product completely unchanged but redirects all marketing, sales, and onboarding toward catering companies. Which type of pivot does this represent, per the Lean Startup pivot taxonomy?
A customer segment pivot occurs when the product-problem hypothesis was correct but the wrong customer segment was targeted; the team keeps the same product and shifts focus to the segment that actually values it, exactly as described.
A fintech startup plans a personal-finance app whose business model depends on: (1) users trusting the app enough to link their bank accounts, (2) users converting to a $9.99/month premium tier, (3) the app store approving the finance category listing, (4) push notifications driving daily engagement. Which assumption should the team test FIRST as the riskiest, highest-uncertainty leap-of-faith assumption?
Bank account linking trust is the foundational value hypothesis — every other outcome (monetization, engagement) is entirely dependent on users first being willing to connect sensitive financial data, making it the highest-uncertainty, existential assumption to test first.
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