Analyze why Grocery usage is growing but revenue is flat

Problem Statement Description

Product context: DoorDash is a local commerce and delivery platform; its products include restaurant delivery, DashPass, grocery and retail delivery, merchant tools, and dasher tools.

DoorDash’s Grocery business is seeing growth in usage, but reported revenue has remained flat over the same period. You are asked to investigate this as a root-cause analysis problem for the Grocery product, with particular attention to enterprise merchants such as large grocery chains and retail partners.

Assume “usage” could refer to customer activity such as orders, active users, sessions, or basket creation, while “revenue” could be affected by order value, take rate, fees, promotions, refunds, merchant economics, or accounting treatment. Your task is to clarify the anomaly, structure the investigation, identify plausible drivers, and explain what evidence you would need before recommending action.

This is not a request to redesign the Grocery product or propose a growth strategy immediately. Focus on diagnosing why increased usage is not translating into revenue growth in a three-sided marketplace involving consumers, merchants, and Dashers, where reliability, merchant ROI, customer affordability, and unit economics all matter.

The experience should consider:

- How you would define the exact metric anomaly, including the usage metric, revenue metric, timeframe, geography, merchant segment, and comparison baseline.

- How you would segment the issue across enterprise merchants, markets, new versus returning customers, order types, basket sizes, delivery versus pickup, and promotion exposure.

- How you would check instrumentation, reporting, attribution, revenue recognition, merchant contract changes, and data pipeline consistency before assuming a business issue.

- What hypotheses could explain usage growth with flat revenue, such as lower average order value, lower monetization rate, higher discounts, fee changes, refunds, cancellations, substitutions, or mix shift.

- What evidence you would seek from funnel, transaction, merchant, pricing, promotion, and operational datasets to validate or reject each hypothesis.

- How marketplace constraints such as delivery reliability, Dasher supply, merchant fulfillment quality, inventory availability, and customer experience could influence both usage and monetization.

- What near-term mitigations and longer-term prevention mechanisms you would consider once the cause is confirmed, without jumping to a premature fix.

The goal is to demonstrate a structured RCA approach: clearly frame the anomaly, separate measurement issues from business issues, prioritize the most likely drivers, and outline how DoorDash should use the findings to make a confident product, commercial, or operational decision for Grocery.