Metrics question
How would you change the Amazon Fresh experience and how would you measure them?
- Amazon
- Metrics
- Medium
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What this question tests
Tests linking a proposed product change to a measurement plan for a grocery vertical with unique freshness and substitution challenges.
How to approach it
- Identify Fresh's unique pain points versus standard Amazon shopping: item substitutions when out of stock, delivery time windows, and produce quality variance.
- Propose a change: let customers pre-approve specific substitutions per item (accept similar brand, reject entirely) instead of a blanket policy.
- Propose a second change: real-time delivery window narrowing (like a 30-minute arrival alert) to reduce the 'stuck at home waiting' problem.
- Define measurement for substitutions: substitution acceptance rate and post-substitution return/complaint rate.
- Define measurement for delivery windows: on-time delivery rate and customer satisfaction score specific to Fresh orders.
What a strong answer includes
- Targets substitution handling specifically, which is a well-known, real pain point in grocery delivery, showing domain awareness.
- Pairs each proposed change with its own specific metric rather than one vague satisfaction score for everything.
- Uses an illustrative number, e.g. assume 15% of orders currently have at least one unwanted substitution, to size the opportunity.
- Distinguishes operational metrics (on-time rate) from experience metrics (satisfaction), showing both matter for a grocery vertical.
Common mistakes
- Proposing changes without pairing each one to a specific, measurable metric.
- Ignoring the operational/supply-chain reality of grocery, like perishability, that makes this different from standard Amazon retail.
Likely follow-up questions
- How would you balance giving customers more substitution control against added complexity for pickers?
- How would you measure the freshness/quality problem specifically?
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Learn the skill behind it
Chapters of the AI PM course that teach what this question tests.
- Chapter 9: Prove it paid off: outcomes, economics, and pricing
- Chapter 2: Data fluency: SQL, logs, and reading the truth yourself
- Chapter 14: Get the job: the AI PM interview loop