Product and Operations Case: Grocery OOS, Delivery Radius, and Free Delivery
Context
You are a data scientist in an onsite analytics and experimentation interview. The marketplace recently launched a new grocery vertical and is observing elevated out-of-stock (OOS) rates. Current delivery radius is capped at 3 miles. There is also interest in offering free delivery for selected restaurants to non-members.
Assume you have access to order logs, item-level pick events, substitutions, cancellations, refunds, customer support contacts, dasher time-and-distance telemetry, store metadata (inventory feeds, hours), and experiment platforms that support geo and user-level randomization.
Tasks
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Diagnose the causes of high OOS in the grocery vertical and propose solutions. Specify hypotheses, key metrics, and analyses you would run.
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The current delivery radius is limited to 3 miles. Should we extend the radius? Describe the analysis and metrics you would use, including how you would model operational cost versus revenue impact, and how you would test the change.
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Should we offer free delivery for selected restaurants to non-members? How would you evaluate this? Outline experiment design, success metrics, and unit economics.