Estimation question

Estimate the number of Uber rides.

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

Structured estimation: breaking a large unknown into a defensible chain of assumptions.

Clarify scope: estimate daily Uber rides globally, stating the assumption explicitly if the interviewer doesn't specify.
Estimate the addressable population: adult smartphone users in Uber's operating cities, roughly 400 to 500 million, as an assumption.
Estimate penetration: assume 15 to 20% of that population are active Uber users in a given month.
Estimate ride frequency: assume an active user takes 2 to 4 rides per month on average.
Multiply through to a monthly figure, then divide by 30 for a daily estimate, sanity-checking against any known public figures.
State the final number as a range, not a false-precision point estimate.

States every assumption explicitly as an assumption, e.g. '500 million addressable users, assumed', rather than presenting guesses as facts.
Shows the full arithmetic chain so the interviewer can follow and challenge any single assumption.
Sanity-checks the result against a known reference point, like Uber's reported public ride figures if recalled.
Delivers a range (e.g. 20 to 25 million rides per day) rather than one falsely precise number.

Skipping straight to a memorized number without showing the reasoning.
Using implausible assumptions, like assuming most of the global population uses Uber daily.

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