Debug a spike in complaints from students on DashPass

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 has observed a sudden spike in complaints from students who use DashPass. These users may be on a student-priced membership plan, ordering around campus housing, dorms, apartments, libraries, or late-night food corridors, and their complaints could relate to membership benefits, delivery fees, order reliability, eligibility, support, merchant availability, or billing.

Your task is to frame and investigate the root cause of the complaint spike. Focus on how you would determine whether this is a real customer-experience issue, a measurement or support-channel artifact, a segment-specific problem, or a broader marketplace issue showing up first among students.

This is an RCA interview question, so the emphasis is on structured diagnosis rather than proposing a new product. You should clarify the anomaly, segment the issue, identify plausible hypotheses, describe what data you would inspect, and explain how you would prioritize mitigation while protecting customer trust, dasher reliability, merchant outcomes, and DashPass unit economics.

The experience should consider:

- How the complaint spike is defined: volume, rate per active student DashPass user, rate per order, severity, and time window.

- Whether the issue is isolated to students or also visible across non-student DashPass members, non-members, specific campuses, cities, merchants, or delivery zones.

- Instrumentation and data-quality checks across support tickets, app ratings, refund requests, cancellations, chat transcripts, billing events, and membership status changes.

- Funnel and operational cuts such as signup, student verification, checkout, fee display, order placement, delivery ETA, handoff, refund, and renewal/cancellation.

- Marketplace factors including merchant availability, late-night demand surges, dasher supply, campus access constraints, weather, events, and local promotions.

- Product and policy changes that may have recently affected DashPass benefits, pricing, eligibility, minimum order thresholds, service fees, or communications.

- Evidence needed to separate correlation from causation and to rank hypotheses by customer impact, business impact, and reversibility.

- Short-term mitigation, customer communication, monitoring, and prevention mechanisms once the likely root cause is identified.

The goal is to demonstrate how you would lead a clear, data-informed RCA for DoorDash: validate the anomaly, localize the affected population, test the most likely causes, act quickly where customer harm is high, and define follow-up instrumentation or process changes to prevent a similar student DashPass issue from recurring.