5 Startup Validation Free Online FlashCards

What is the purpose of startup validation?

Startup validation tests whether a venture’s assumptions are supported by evidence. It reduces uncertainty but cannot prove that the startup will succeed.

What are the three dimensions of startup assumptions?

Desirability asks whether customers want the solution, feasibility whether the venture can deliver it reliably, and viability whether revenue can cover costs.

Which assumptions should founders test first?

Prioritize assumptions that are both highly uncertain and crucial to the venture’s success.

What makes a startup hypothesis testable?

A useful hypothesis names a customer group and an observable outcome, and focuses on one claim that evidence could support or contradict.

How should founders choose an experiment?

Choose a test that directly examines the riskiest hypothesis while requiring reasonable time and resources.

What four elements should an experiment plan specify?

Specify the hypothesis, the test, the observable measure, and the decision rule for interpreting the result.

Why set an experiment’s decision rule before testing?

Set the decision rule in advance to reduce the temptation to reinterpret disappointing results. A suitable threshold depends on the venture’s context.

What can customer interviews reveal—and what can’t polite interest prove?

Interviews can reveal whether a problem exists and how people handle it, but polite interest alone does not show that customers will pay.

What often provides more direct evidence of demand than stated intentions?

Observable actions such as signing up, returning, referring others, or paying usually test demand more directly than general opinions or stated intentions.

Why can observed customer behavior still give misleading evidence?

Behavior may mislead when participants are unrepresentative, the test is poorly designed, or results depend on an unusual discount or personal favor.

What should founders document after an experiment?

Record who participated, what was tested, what happened, and any limitations that could affect the conclusion.

What does it mean when evidence supports a hypothesis?

Support means the evidence justifies the next, often more demanding test; it does not guarantee the startup will succeed.