##### Scenario Platform must decide how to serve three different ad categories to users in a personalized way. ##### Question Design an approach to personalize the delivery of the three ad categories. How would you decide which ad to show, measure performance, and optimize for revenue/ROI? ##### Hints Define objectives, features, model choice, exploration vs. exploitation, offline/online metrics, causal inference for lift.

This question evaluates skills in personalized ad delivery, including user-level modeling, metric design, experimental and causal inference techniques, and decision policies within a Machine Learning domain.

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This is a medium difficulty Machine Learning question, commonly asked during Technical Screen rounds at TikTok.

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This question is commonly asked for Data Scientist candidates at TikTok during technical interviews.

Personalize Ad Delivery Using Machine Learning Techniques

Personalized Delivery of Three Ad Categories

Scenario

You operate a consumer feed with a single ad opportunity per request and three possible ad categories (A, B, C). You need to decide, for each impression, which category to show to maximize business value while maintaining user experience.

Task

Design an approach to personalize the delivery of the three ad categories. Specifically:

State clear objectives and constraints (e.g., revenue, ROI, user experience).
Propose how to decide which category to show at each impression.
Describe how you would measure performance offline and online.
Explain how you would optimize for revenue/ROI, including exploration vs. exploitation and how to estimate causal lift (incrementality).

Assume you can log propensities and outcomes and you can run controlled experiments.

Personalized Delivery of Three Ad Categories

Scenario

Task

Design an approach to personalize the delivery of the three ad categories. Specifically:

State clear objectives and constraints (e.g., revenue, ROI, user experience).
Propose how to decide which category to show at each impression.
Describe how you would measure performance offline and online.
Explain how you would optimize for revenue/ROI, including exploration vs. exploitation and how to estimate causal lift (incrementality).

Assume you can log propensities and outcomes and you can run controlled experiments.

Personalize Ad Delivery Using Machine Learning Techniques

Quick Overview

Personalized Delivery of Three Ad Categories

Scenario

Task

Solution

Submit Your Answer to Earn 20XP

Personalize Ad Delivery Using Machine Learning Techniques

Quick Overview

Personalized Delivery of Three Ad Categories

Scenario

Task

Solution

Submit Your Answer to Earn 20XP