Validating the Model: Lean Startup

Explain what the Lean Startup methodology is and why it proposes validating ideas with real customers instead of blindly trusting the initial plan.

The basic Lean Startup cycle is build → measure → learn. Describe what is done in each phase and explain why it is a cycle and not a line that ends in 'launch'.

The diagram shows the Lean Startup validation cycle around the minimum viable product (MVP). Identify the missing phase, marked with '?', and explain what two decisions can come out of it.

Define what a minimum viable product (MVP) is and explain why "minimum" does not mean "shoddy": it must have just enough to validate a hypothesis, but work well at that.

A team wants to validate a book-swapping app for neighbours. Propose a minimum viable product (MVP) that does not require coding the full app (for example, a messaging group and a form) and explain what hypothesis it allows them to test.

Design the minimum viable product of a maths tutoring service between students at the same school without programming any app (noticeboard, form, messaging group) and point out the key metric that would say whether the idea works.

In Lean Startup, ideas are formulated as testable hypotheses. Turn "I think people will like it" into a testable hypothesis for a dog walking app, and explain what makes it testable (who the customer is, what behaviour you expect, how you would measure it).

Explain why customer development orders you to "get out of the building" to talk to customers before building the product, and what two risks anyone who skips that step runs.

Customer development recommends 'getting out of the building' to talk to customers before building anything. Explain how you would conduct ten interviews to validate a healthy snack box service and why questions like 'do you like my idea?' should be avoided.

Order these actions in the build–measure–learn cycle and explain what follows next: counting how many visitors sign up, launching a page that advertises the product with a sign-up button, deciding whether the data confirms the hypothesis.

Explain what pivoting means in Lean Startup (changing strategy while keeping what has been learned) and give an example of a segment pivot: an app designed for students that ends up aimed at companies.

In Lean Startup, after measuring, you must decide whether to persevere (continue improving in the same direction) or pivot (change strategy while retaining what was learned). Define both options and reason what you would do if data shows that many people try your recipe app, but hardly anyone uses it again.

A meditation app boasts 50 000 accumulated downloads, but only 800 people open it each week. Explain which of the two metrics rules when deciding the product's future, why the other is a vanity metric and what two measures you would try to improve retention.

A startup's monthly report shows: 150.000 cumulative downloads (+25 %), 80.000 social media followers (+40 %), weekly retention rate of 2,3 % (-15 %), and free trial to paid subscription conversion rate of 0,8 % (-0,5 points). The marketing director proposes doubling advertising spend, arguing that "the business keeps growing." Technically refute her proposal based on the analysis and interpretation of these data, classifying and justifying each metric according to its methodological typology (vanity or actionable metric), and predict what will happen to the company's financial viability if they maintain this strategy.

A mobile language-learning application shows the following monthly figures in its funnel:

• Visits to the website and app store listing: 50.000

• Downloads and account registrations: 12.000

• Users completing their first lesson on the day of download: 1.200

• Users still practicing after 30 days: 1.050

• Users inviting a friend: 350

• Users paying for the annual premium subscription: 210

1. a) Map each data point to its stage within the pirate metrics model (AARRR) and calculate the percentage conversion rates between consecutive stages.
2. b) Interpret the results: identify with justification at which stage the main bottleneck is located.
3. c) Formulate an improvement hypothesis to fix this drop-off and design a specific Lean experiment to validate it.