Product design question
Facebook wants to enter the fashion space. What would you build?
- Meta
- Product design
- Hard
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What this question tests
Product strategy and design thinking for entering a new adjacent market from an existing social platform.
How to approach it
- Users: fashion-conscious Facebook and Instagram users, especially small fashion brands and resellers already active on Marketplace.
- Pain points: discovering trustworthy fashion sellers and getting outfit inspiration is fragmented across influencers, ads, and Marketplace.
- Prioritize: leverage Facebook's existing strengths, social graph and Marketplace infrastructure, rather than building a new fashion e-commerce platform from scratch.
- Solution: a shoppable, social-driven fashion discovery feed connecting Marketplace fashion listings with creator and friend recommendations.
- Success metric: fashion category GMV on Marketplace, and conversion rate from social discovery to purchase.
- Confirm scope: whether this targets resale and small sellers, or competes with large fashion e-commerce brands directly.
What a strong answer includes
- Leverages Facebook's actual existing assets, the social graph and Marketplace, rather than proposing an unrelated standalone app.
- Picks a defensible angle, social-driven discovery, where Facebook has a real advantage over pure e-commerce fashion players.
- Defines success with a business-relevant metric, fashion category GMV, tied directly to the strategic goal.
Common mistakes
- Proposing a generic fashion app with no tie to Facebook's existing social graph or Marketplace.
- No mention of leveraging existing infrastructure, effectively describing a new company instead.
- Vague success metric unrelated to commerce outcomes.
Likely follow-up questions
- How would you differentiate this from Instagram Shopping, which already exists?
- Which seller segment would you prioritize first, resellers or established brands?
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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