Metrics question

How would you measure the success of Uber Grocery?

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 defining success for a new vertical launch where trust in delivery quality (perishables, substitutions) is the key adoption barrier.

Clarify the launch stage: early pilot versus scaled rollout, since success looks different (learning versus growth) at each stage.
Set an adoption metric: percent of existing Uber users who try Grocery within their first month of availability in their city.
Set a quality metric: order accuracy rate (correct items, correct substitutions) and on-time delivery rate, since grocery has a lower tolerance for errors than food delivery.
Set a retention metric: repeat order rate within 30 days, since grocery is a recurring-need category and habit formation is the real long-term signal.
Add a guardrail: complaint/refund rate, since a bad first grocery experience is likely to churn a user from the category entirely.

Separates adoption, quality, and retention into distinct metrics rather than one blended 'success' score.
Identifies order accuracy as uniquely important for grocery versus standard delivery, since substitutions and perishables raise the error stakes.
Uses an illustrative number, e.g. assume repeat-order rate needs to hit 40% within 30 days to signal real habit formation, versus a one-time trial.
Ties quality metrics to trust, recognizing a single bad grocery experience is more damaging to retention than a bad ride.

Measuring only order volume without checking whether quality (accuracy, substitutions) is good enough to sustain repeat usage.
Ignoring that grocery is a fundamentally different, higher-frequency, lower-margin category than rides or standard food delivery.

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