Product design question

There is a small new grocery store in the city. They are doing well, and all the aisles are getting crowded. How would you solve 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

Practical problem solving for a physical, operational constraint, not a digital product design question.

Clarify the actual problem: is crowding hurting customer experience, safety, or throughput and revenue.
Diagnose root cause: check whether crowding is concentrated at peak hours, specific aisles, or checkout lines.
Consider low-cost fixes first: staggered restocking hours, better aisle layout, or a self-checkout addition before a physical expansion.
Consider a data-driven fix: use foot traffic data to identify the worst bottleneck aisle and widen or reroute it.
Weigh cost versus benefit: physical renovation is expensive for a small store, so prioritize cheap operational fixes first.
Define success: reduction in average time in store during peak hours, or a customer complaint rate decrease.

Diagnoses before prescribing, checking whether the problem is peak-hour concentration versus store-wide crowding.
Proposes low-cost operational fixes, like staggered restocking or self-checkout, appropriate for a small store's budget.
Ties the fix to a measurable outcome, like reduced peak-hour dwell time, rather than assuming renovation is the only answer.

Jumping straight to a costly store expansion without considering cheaper operational fixes.
No diagnosis of when or where crowding actually happens.
Treating this like a big-box retail problem when it is explicitly a small store.

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