Strategy question
Several FB users have experienced shopping integrity issues, where the product they received is different and/or much lower quality than expected (i.e., misalignment between product advertised via FB ad and product received). How would you determine if this is a problem worth solving and what product enhancements would you make to address this issue?
- Meta
- Strategy
- Hard
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What this question tests
Tests root-cause diagnosis and trust-focused prioritization for a marketplace integrity problem, distinct from a general improve-the-product answer.
How to approach it
- Clarify scope: this concerns Facebook Marketplace, where peer sellers list items directly, unlike a vetted retail platform.
- Segment the causes: seller misrepresentation (intentional), poor listing quality (photos or descriptions), and buyer expectation mismatch.
- Quantify which cause dominates using dispute and report data, since the fix differs for fraud versus honest listing errors.
- Propose layered fixes: a seller rating and review system visible before purchase, a structured listing template requiring key details (condition, defects), and a buyer protection or refund mechanism for verified mismatches.
- Weigh trust versus friction: too many verification steps discourage casual peer sellers from listing at all.
- Define success as a falling shopping integrity complaint rate and stable or growing listing volume.
What a strong answer includes
- Separates fraud from honest listing quality issues, since Marketplace is peer-to-peer, unlike a retail platform with vetted sellers.
- Proposes a seller reputation system as the core trust mechanism, consistent with how other peer marketplaces (eBay, Airbnb) solve this.
- Uses illustrative numbers as assumptions: assume 5% of Marketplace transactions generate an integrity complaint, with photo mismatch as the top cause.
- Flags the trust-versus-friction trade-off explicitly, since Marketplace's appeal depends on low listing friction for casual sellers.
Common mistakes
- Treating Marketplace like a retail platform and proposing solutions that assume Facebook vets sellers, which it doesn't.
- Not separating fraud from unintentional listing errors, which need different fixes.
- Proposing verification requirements so heavy they'd kill casual peer selling.
Likely follow-up questions
- How would you detect intentional fraud versus honest mistakes at scale?
- What would a buyer protection mechanism look like without Facebook holding funds?
- How do you balance trust features against keeping listing friction low?
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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 9: Prove it paid off: outcomes, economics, and pricing
- Chapter 14: Get the job: the AI PM interview loop