Strategy question

Suppose Uber decides to launch UberEats in a few new cities. How do you choose which cities to launch?

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

Tests market-entry prioritization, turning many candidate cities into a ranked launch list using data and strategic fit.

Frame it as a ranking problem: budget and ops capacity limit how many cities can launch this quarter.
Build scoring criteria: existing Uber Rides density, restaurant supply, competitor presence from DoorDash and Grubhub, and population or income density.
Weight the criteria by goal: fastest payback versus defending share from a competitor's expansion.
Sequence the launch: pilot in the 2-3 highest-scoring cities, measure order volume and driver utilization, then scale the playbook.
Define success as orders per week per city by month 3, driver utilization rate, and CAC payback period.

Uses Uber's existing rides data as an unfair advantage for predicting Eats demand and supply in a new city.
Gives a concrete scoring rubric with weights instead of a vague list of factors to consider.
Calls out the cannibalization risk of driver hours shifting between Rides and Eats.

Picking cities on population size alone, ignoring restaurant supply or how entrenched a competitor already is.
Launching everywhere at once instead of sequencing a pilot before scaling.

How would you use existing Uber Rides data to predict Eats demand in a new city?
How do you decide when to exit a city that underperforms?