Design analytics for a new-market launch

Q: Design analytics for a new-market launch

This question evaluates a data scientist's competency in product analytics and causal inference, focusing on metric definition, guardrail setting, and experimental rollout design for a new-market launch.

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Question

DoorDash New-City Launch: Metrics, Guardrails, and Causal Rollout Design

Task

Define success metrics and guardrails for three phases of a new-city launch, and design an experiment to estimate causal impact.

Phases

Pre-launch (readiness)
Soft launch (limited zones/hours)
Full ramp

For each phase

(a) List 3–5 core metrics with precise definitions (units, numerator/denominator, time window). (b) Identify which are leading indicators vs outcome metrics. (c) Propose guardrail thresholds that would trigger a rollback or hiring freeze.

Experiment design

Design a geo A/B or staggered rollout to estimate causal impact on orders and ETAs. Address:

Seasonality
Matched-control selection
Spillovers across adjacent zones
Novelty effects
Minimum-detectable-effect (MDE) assumptions

Specify the decision rules you would present to leadership to proceed or hold after two weeks.

Design analytics for a new-market launch

DoorDash New-City Launch: Metrics, Guardrails, and Causal Rollout Design

Task

Phases

For each phase

Experiment design

Solution

Comments (0)

Design analytics for a new-market launch

Overview

DoorDash New-City Launch: Metrics, Guardrails, and Causal Rollout Design

Task

Phases

For each phase

Experiment design

Solution

Comments (0)