Product design question
Imagine you are a PM for UBER for a default pickup location feature. How would you improve this feature?
Practice this question out loud. An AI interviewer asks it, follows up like a real interviewer would, and scores your answer. Type or speak.
Start a mock interview on this question · Mock interview from a job description
What this question tests
Product improvement thinking for a narrow, well-defined feature, finding real friction and proposing a targeted fix.
How to approach it
- Clarify the current experience, how default pickup locations are currently set and how often they are wrong.
- Identify pain points, GPS inaccuracy in dense urban areas, multi-entrance buildings, and stale saved locations.
- Segment by context, home and work locations versus one-off addresses like airports or event venues.
- Propose a fix, crowd-sourced pickup point suggestions at common locations, refined by driver and rider feedback over time.
- Consider rider control, letting users fine-tune a pin before confirming rather than trusting GPS blindly.
- Define success metrics, reduction in pickup-related cancellations and average wait time at pickup.
What a strong answer includes
- Names a real, specific failure mode, GPS drift in dense areas or large buildings with multiple entrances, not a vague 'improve accuracy' claim.
- Proposes a crowd-sourced correction mechanism, using aggregated rider and driver adjustments to improve the default over time.
- Balances automation with user control, letting riders confirm or adjust the pin rather than fully trusting an algorithm.
- Sets a concrete, measurable outcome, reduced cancellation or wait time at pickup, tied directly to the friction identified.
Common mistakes
- Proposing a generic 'use better GPS' fix with no mechanism.
- Ignoring dense urban and multi-entrance building edge cases.
- Not defining a metric to measure whether pickup accuracy improved.
Likely follow-up questions
- How would you handle locations with multiple entrances, like a mall or airport.
- How would you use crowd-sourced data without introducing errors.
- What would you measure to know this feature is working.
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Learn the skill behind it
Chapters of the AI PM course that teach what this question tests.
- Chapter 4: Discovery and strategy for AI products
- Chapter 7: AI UX and human oversight: design for a system that is wrong sometimes
- Chapter 14: Get the job: the AI PM interview loop