Product design question
How would improve the Zillow Offers product?
- Zillow
- 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 improvement judgment for a discontinued but instructive product, focused on risk management and trust.
How to approach it
- Acknowledge the context: Zillow Offers was shut down due to pricing model losses, so improvements must address that core flaw.
- Identify the root problem: the algorithmic pricing model underestimated market volatility, leading to overpaying for homes.
- Propose tightening the pricing model with wider uncertainty buffers and faster human review for higher risk markets.
- Propose limiting exposure: capping the number of homes held in inventory at once to reduce risk during market downturns.
- Propose better seller transparency: clearer expectations upfront about how the algorithmic offer is calculated and its limits.
- Define success as reduced average holding time and improved margin per home versus the original model's performance.
What a strong answer includes
- Grounds the answer in the real, well known reason Zillow Offers failed, algorithmic mispricing during volatile conditions, rather than generic UX tweaks.
- Proposes concrete risk mitigation, tighter pricing buffers and inventory caps, directly addressing the root cause.
- Balances automation with human review for higher risk cases, showing judgment about where full automation fails.
- Picks holding time and margin per home as metrics tied directly to what actually killed the original product.
Common mistakes
- Proposing surface level UX improvements without addressing why the product actually failed.
- Ignoring the real financial and market risk that caused the shutdown.
Likely follow-up questions
- How would you decide which markets are too risky to operate in?
- How would you rebuild trust with sellers after the earlier shutdown?
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More questions from Zillow
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