Estimation question

If you were launching a bike sharing app in NYC, how many people would be interested in it?

Practice this question out loud. An AI interviewer asks it, follows up like a real interviewer would, and scores your answer. Type or speak.

What this question tests

Market sizing estimation: can you build a demand estimate from population, target segment, and realistic adoption assumptions.

Start with NYC population, assume roughly 8.5 million residents.
Filter to the relevant segment, assume adults who could plausibly bike for transport, roughly 60 percent, about 5 million.
Apply an interest rate for a new bike share option, assume 10 percent would consider trying it given existing biking infrastructure and competition from Citi Bike.
That gives roughly 500,000 interested people, then apply a realistic early adoption rate, assume 20 percent actually sign up in year one, about 100,000 users.
Sanity check against known bike share adoption elsewhere, and adjust if this feels too high or low.
State the final range as an estimate, not a precise figure, and name the biggest assumption driving it.

Builds the estimate in clear layered steps, population, relevant segment, interest, then adoption, rather than one guess.
Accounts for existing competition, like Citi Bike, which realistically caps a new entrant's adoption.
States which assumption most affects the final number, showing awareness of estimate sensitivity.

Chapters of the AI PM course that teach what this question tests.