Product design question

As a PM for Google Maps, how would you improve the restaurant search?

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

Product sense focused on a specific search vertical, showing understanding of both user and business needs.

Define the user: someone deciding where to eat right now, often with situational constraints like time, group size, or dietary needs.
Identify a pain point: current restaurant search on Maps handles broad queries well but struggles with nuanced situational needs, like 'quiet place for a work lunch.'
Prioritize improving query understanding for situational intent over adding new listing features, since this is the moment of highest friction.
Propose a solution: richer semantic search combined with real-time signals like current wait time, noise level, and available seating.
Define success metrics: search-to-visit conversion rate and reduction in repeated, refined searches (a sign the first result wasn't good enough).

Names a specific, realistic query type, 'quiet place for a work lunch,' rather than a generic 'better search' pitch.
Proposes combining semantic understanding with real-time signals like wait time, showing a concrete technical direction.
Gives an illustrative metric, e.g. reducing repeated searches per session by 20%, marked as an assumption.
Considers business impact: better situational matching increases restaurant foot traffic, aligning user and business value.

Proposing generic filters (price, cuisine) that already exist instead of a genuinely new improvement.
Ignoring real-time signals like wait time that materially affect restaurant choice.

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