Product design question
You are the product manager at Facebook. Build a product to raise money for causes, considering there is no existing Facebook product for this.
- 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 for a trust-sensitive category: building a fundraising product from scratch with fraud and trust as core constraints.
How to approach it
- Clarify the user: individuals raising money for personal causes versus nonprofits raising for organizational causes, pick one focus.
- Identify the core need: an easy way to start a fundraiser and a trustworthy way for friends to give.
- Design the core flow: create a campaign with a story and goal, share via News Feed, and donate in-app.
- Address trust and fraud explicitly, such as identity verification for organizers and transparent fund disbursement.
- Define success as funds raised per campaign and donor repeat-giving rate.
What a strong answer includes
- Treats trust and fraud prevention as core to the design, not an afterthought, given the sensitivity of fundraising.
- Leverages Facebook's social graph for organic sharing and social proof, a real platform advantage.
- Proposes a concrete verification mechanism, like linking to a bank account or ID check before funds are released.
- Uses an assumed metric, e.g. average campaign reaching 60 percent of its goal within 30 days.
Common mistakes
- Ignoring fraud and trust, which is the single biggest risk in a fundraising product.
- Designing a generic crowdfunding clone with no Facebook-specific distribution advantage.
- Not addressing how funds actually get to the recipient.
Likely follow-up questions
- How would you detect and prevent fraudulent campaigns?
- How would you handle a campaign that doesn't reach its goal?
- What fees, if any, would you charge, and why?
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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