Product design question
How do you automate the return experience for an e-commerce company?
- Etsy
- Product design
- Medium
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What this question tests
Whether you can design an automated workflow that removes manual steps for both the customer and the operations team.
How to approach it
- Clarify scope: automating the return request, label generation, and refund decision, not just the physical logistics of shipping items back.
- Identify pain points today: customers waiting for manual approval, and support teams manually verifying eligibility for each request.
- Prioritize automatic eligibility checks first, since that's the step blocking instant resolution for the majority of straightforward returns.
- Propose a concrete flow: rules-based auto-approval for common cases, like unworn items within the return window, with instant label generation.
- Route only edge cases, like high-value or suspicious-pattern returns, to manual review instead of every request.
- Define success metrics: percent of returns auto-resolved instantly, with a guardrail on return fraud rate.
What a strong answer includes
- Separates straightforward returns from edge cases, automating the majority while still routing risky ones to a human.
- Proposes rules-based auto-approval as the concrete mechanism, not just a vague make it faster claim.
- Gives an illustrative number, assuming 70 to 80 percent of returns are straightforward enough to fully automate.
- Names fraud rate explicitly as the guardrail, since automating approvals without one invites abuse.
Common mistakes
- Automating every return without a fraud guardrail, exposing the business to abuse of the new speed.
- Focusing only on the customer-facing UI while ignoring the backend eligibility logic that actually creates the delay.
Likely follow-up questions
- How would you detect and route suspicious return patterns to manual review?
- What would you do about high-value items that shouldn't be auto-approved?
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More questions from Etsy
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