Product design question
Design a gaming product for Meta customers.
- Meta
- Product design
- Hard
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
Product design combined with platform strategy awareness, Meta's investment in VR and Quest gaming.
How to approach it
- Clarify the platform: Quest and VR gaming, leveraging Meta's unique asset, the headset install base, rather than a generic mobile game.
- Identify an underserved segment on Quest: casual social multiplayer, since VR gaming today skews toward longer, more immersive single-player experiences.
- Propose a lightweight, social party-game app for Quest with avatars and voice chat, playable in 10-15 minute sessions, using Meta's social graph for matchmaking with friends.
- Tie it to Meta's goal: driving Quest engagement and retention, a known challenge since many headsets go unused after initial novelty, and cross-promoting via Facebook and Instagram.
- Define success as weekly active Quest users playing the game, and friend-invite conversion via the social graph.
What a strong answer includes
- Picks Quest and VR specifically as Meta's differentiated gaming asset, rather than a generic game any company could build.
- Directly addresses the known headset engagement drop-off problem with a session-length-appropriate design.
- Leverages Meta's unique social graph for matchmaking, a genuine advantage over standalone VR competitors.
Common mistakes
- Proposing a generic mobile or social-network game with no tie to Meta's actual differentiated assets.
- Ignoring Quest's known engagement drop-off problem, missing the most relevant business context.
Likely follow-up questions
- How would you get non-gamers to try this on their Quest headset?
- How would you monetize this without a paywall that kills social or friend-based virality?
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More questions from Meta
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