Product design question
How would you improve Google Chromecast?
- Product design
- Easy
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What this question tests
Product improvement for a hardware-plus-software device: can you find a real friction point in setup or daily use rather than proposing generic new features.
How to approach it
- Define the user job: quickly get content from a phone/app to the TV with minimal setup friction and reliable connection.
- Identify pain points: initial setup complexity (Wi-Fi pairing, app-device linking) and occasional connection drops during casting.
- Propose a fix: a faster, more guided first-time setup flow, and improved connection stability with clearer error recovery when casting fails.
- Consider a discovery improvement: making it easier to find and launch the right app/content directly from the Chromecast home screen rather than always through a source app.
- Address competition: compare briefly to Roku/Fire TV's more app-centric interface, since Chromecast's phone-as-remote model has real usability tradeoffs.
- Define success: setup completion rate and cast-session failure rate.
What a strong answer includes
- Identifies concrete, common pain points, setup friction and connection drops, rather than vague 'add more features'.
- Compares against real competitors' interaction models (Roku/Fire TV) to justify why a specific change matters.
- Proposes a specific fix for error recovery during a failed cast, a real and underserved moment of frustration.
- Ties success metrics directly to the pain points named, not generic engagement metrics.
Common mistakes
- Proposing generic new content features instead of fixing known reliability and setup pain points.
- Ignoring how Chromecast's phone-as-remote model differs from competitors, missing the real usability tradeoff.
Likely follow-up questions
- How would you reduce the failure rate of a caster losing Wi-Fi connection mid-stream?
- Would you consider adding a dedicated remote, and why or why not?
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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