Product design question
How would you improve Google Home?
- Product design
- Easy
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What this question tests
Product sense for a smart speaker, picking a real user pain point and proposing a scoped improvement rather than a feature dump.
How to approach it
- Segment users: single-person households using it for music and timers, families using it for routines, and users controlling smart-home devices.
- Identify the biggest pain point: multi-step voice commands failing or the assistant misunderstanding context in noisy homes.
- Prioritize the family and smart-home segment, where friction and switching cost to a competitor like Alexa is highest.
- Propose a solution: better multi-turn conversation handling so users don't repeat the wake word for follow-up commands.
- Describe rollout: starting with common routines like "goodnight" that chain multiple actions.
- Define success: reduction in failed or repeated commands per session.
What a strong answer includes
- Picks one concrete, high-frequency pain point, command failure in noisy multi-person households, instead of a feature wishlist.
- Explains why fixing it matters commercially: it is a top reason users switch to a competitor.
- Proposes a testable success metric, command success rate, not just satisfaction.
- Considers rollout risk, false positives from unintended follow-up triggers.
Common mistakes
- Listing many small feature ideas with no prioritization.
- Ignoring how success would be measured.
- Not naming a specific user segment or pain point.
Likely follow-up questions
- How would you detect when a command has failed?
- How would you test this without a full launch?
- What is the privacy tradeoff if the mic stays open longer for follow-ups?
More product design questions
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- How would you go about designing a new location sharing app for Google?Google · Product design · Medium
- How would you improve Google Home?Google · Product design · Easy
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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