Product design question
Should Meta explore entering the delivery business? Provide your reasoning.
- Meta
- Product design
- Hard
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What this question tests
Strategic market-entry judgment: can you evaluate a big adjacent-market bet against Meta's actual capabilities, not just market size.
How to approach it
- State the framework: market size/growth, Meta's right to win (assets it already has), and cost/risk of entry.
- Market size: delivery is large but already has entrenched, capital-intensive incumbents (DoorDash, Uber Eats) with thin margins.
- Meta's assets: massive user base and ad infrastructure, but no logistics/fulfillment experience, which is the hard part of delivery.
- Consider a narrower angle instead of full delivery: Meta could power discovery/ordering (ads, Marketplace integration) while partnering with existing delivery networks for fulfillment.
- Weigh the opportunity cost: capital and focus spent here versus doubling down on core ads/Reality Labs priorities.
- Give a clear recommendation: likely no for full delivery ownership, yes for a lighter partnership/discovery play, with reasoning.
What a strong answer includes
- Uses a clear framework (market size, right to win, cost of entry) instead of a free-form opinion.
- Correctly identifies logistics/fulfillment as the hard, capital-intensive part Meta has no experience in, which is the crux of the decision.
- Proposes a scoped alternative (discovery/ads layer, not full-stack delivery) that better matches Meta's actual strengths.
- Gives a clear recommendation instead of listing pros and cons with no verdict.
Common mistakes
- Evaluating only market size without weighing Meta's lack of logistics capability.
- Refusing to give a clear yes/no recommendation.
Likely follow-up questions
- What would change your recommendation, e.g. acquiring an existing delivery company instead of building?
- What's the biggest risk if Meta partners rather than builds?
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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