Metrics question
How do you measure the success of Instacart?
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What this question tests
Metrics fundamentals for a delivery marketplace: can you build a metric tree spanning acquisition, fulfillment quality, and retention.
How to approach it
- Acquisition: new customer signups and first-order conversion rate.
- Fulfillment quality: order accuracy (correct items, right substitutions), on-time delivery rate, and out-of-stock rate.
- Engagement/retention: order frequency per active customer and repeat purchase rate within a defined window.
- Business health: gross merchandise value (GMV), average order value, and unit economics (contribution margin per order after delivery costs).
- Supply-side: shopper/store availability and shopper fulfillment efficiency, since marketplace health depends on both sides.
- Explain how these connect: fulfillment quality drives retention, which drives GMV, tying operational metrics to the business outcome.
What a strong answer includes
- Builds a metric tree connecting operational quality (order accuracy, on-time rate) to the business outcome (retention, GMV), not a flat list.
- Includes unit economics/contribution margin, recognizing delivery businesses can grow GMV while losing money per order.
- Covers both sides of the marketplace (shopper/store supply, customer demand), reflecting Instacart's actual two-sided structure.
- Explains the causal chain between metrics rather than just naming them independently.
Common mistakes
- Listing generic e-commerce metrics without anything specific to grocery delivery's operational quality (substitutions, on-time rate).
- Ignoring unit economics, which is critical for a low-margin delivery business.
Likely follow-up questions
- Which single metric would you prioritize if you had to pick one leading indicator?
- How would you weigh GMV growth against declining contribution margin?
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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