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This is a medium difficulty Machine Learning question, commonly asked during Onsite rounds at DoorDash.

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This question is commonly asked for Machine Learning Engineer candidates at DoorDash during technical interviews.

How would you target promotions to grow consumers?

Last updated: Mar 29, 2026

Quick Overview

This question evaluates the ability to design and operationalize ML-driven promotion targeting and measurement systems, assessing competencies in causal inference and uplift estimation, experimentation design, metric selection, budget-aware optimization, and monitoring for long-term impact.

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How would you target promotions to grow consumers?

DoorDash

Oct 17, 2025, 12:00 AM

mediumMachine Learning EngineerOnsiteMachine Learning

ML / Growth Scenario

You own a system that sends promotion offers (e.g., "$10 off", "free delivery") to consumers to increase growth.

Prompt

Design an approach to decide:

Who should receive a promo
What promo to send (offer type/amount)
When to send it

Constraints and concerns:

Limited promo budget
Risk of giving discounts to users who would have ordered anyway
Need to measure incremental lift (not just conversion)
Avoid harming long-term margin or creating promo addiction

Explain your modeling/experimentation strategy, data needs, evaluation metrics, and how you would deploy and monitor it.

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