Product design question
How would you increase the usage of YouTube?
- Microsoft
- Product design
- Easy
Practice this question out loud. An AI interviewer asks it, follows up like a real interviewer would, and scores your answer. Type or speak.
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What this question tests
Whether the candidate can identify a specific, high-leverage growth angle rather than proposing generic feature additions for a mature product.
How to approach it
- Clarify what 'increase usage' means: more time watched per session, more frequent visits, or growing a specific underused surface like Shorts or live streaming.
- Identify an underserved segment or use case, for example casual viewers who watch YouTube through a smart TV but rarely engage (like, comment, subscribe).
- Name a pain point: discovery on TV interfaces is weaker than mobile, with less personalized browsing and clunkier navigation.
- Propose a focused fix, such as improving TV-specific recommendation surfaces and simplifying remote-based search and browsing.
- Define success as watch time per TV session and TV-to-mobile cross engagement (subscribing or commenting after watching on TV).
What a strong answer includes
- Picks a specific surface, TV viewing, rather than a vague 'add more features' answer for a mature, broad product.
- Names a concrete, real gap, weaker TV discovery and engagement tools, grounded in how people actually use YouTube on different devices.
- Defines success with a cross-device metric, connecting TV viewing to broader platform engagement.
Common mistakes
- Proposing generic content or creator incentives without picking a specific usage surface or segment.
- Ignoring device-specific differences in how YouTube is actually used.
Likely follow-up questions
- How would you measure whether TV viewing is cannibalizing mobile watch time or adding incrementally?
- What would you prioritize next if TV engagement improves but overall usage doesn't?
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More questions from Microsoft
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