Product design question
Facebook wants to enter the house hunting business. If you were assigned to develop a product for the new business, what would you build?
- Meta
- Product design
- Hard
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What this question tests
Product design leveraging platform-unique assets for a high-stakes, trust-sensitive vertical.
How to approach it
- Define the user: someone searching for a rental or home, wanting more trustworthy signals than a typical listing site provides.
- Identify Facebook's advantage: existing Marketplace listings, local Groups, and social graph trust signals like mutual friends or neighborhood connections.
- Prioritize building a dedicated house-hunting hub that surfaces Marketplace and Groups listings with social trust overlays, rather than a from-scratch listings database.
- Design a key feature: a 'neighborhood insider' layer showing local group activity, reviews, and community sentiment about an area.
- Address the biggest risk directly: fraud and fake listings, requiring identity verification for anyone posting a housing listing.
- Define success metrics: search-to-contact conversion rate and fraud/scam report rate.
What a strong answer includes
- Builds on Facebook's actual existing assets (Marketplace, Groups) rather than proposing a from-scratch Zillow clone.
- Proposes a specific trust feature, like showing mutual friends or local group membership overlap with a landlord.
- Gives an illustrative metric, e.g. 20% higher contact rate on listings with visible social trust signals, marked as an assumption.
- Names fraud prevention as a first-class design requirement given housing scams are common and high-stakes.
Common mistakes
- Proposing a generic listings site that ignores Facebook's unique social graph advantage.
- Underestimating fraud risk in a high-value, high-stakes vertical like housing.
Likely follow-up questions
- How would you verify listing authenticity at scale?
- How would this differentiate from Zillow or Craigslist?
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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