Product design question
Create a product to monetize Facebook Marketplace.
- 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.
Start a mock interview on this question · Mock interview from a job description
What this question tests
Whether you can design a monetization model that fits a specific marketplace's users without breaking trust.
How to approach it
- Clarify today's state: Marketplace is largely free peer-to-peer listings, so monetization must not scare off casual sellers.
- Segment sellers: casual individuals selling used goods versus small businesses and resellers listing in volume.
- Identify where willingness to pay exists, mainly with higher-volume or business sellers wanting more reach or trust signals, not casual users.
- Propose targeted monetization: paid promoted listings and a verified business seller tier with lower fees for casual users.
- Address the tradeoff: any fee on casual listings risks pushing supply to free alternatives like Craigslist.
- Define success metrics: revenue per business seller and listing volume retention among casual sellers as a guardrail.
What a strong answer includes
- Segments sellers by intent and volume instead of proposing one flat fee for everyone.
- Protects the casual, high-volume supply side that makes Marketplace useful, keeping it free.
- Gives an illustrative number, assuming the top 10 percent of sellers by volume could fund most revenue through promoted listings.
- Names the guardrail explicitly, casual listing volume, to prevent monetization from killing the marketplace's core liquidity.
Common mistakes
- Proposing a universal listing fee that ignores the risk of driving casual sellers to free competitors.
- Failing to distinguish business sellers from casual sellers when designing pricing.
Likely follow-up questions
- How would you price promoted listings without favoring only the largest sellers?
- What would make you roll back a monetization feature after launch?
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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