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Design A/B test for AI chat box

Last updated: Mar 29, 2026

Quick Overview

This question evaluates skills in experimental design, product analytics, metrics selection, and causal inference relevant to a Data Scientist role in the Analytics & Experimentation domain.

  • easy
  • Reddit
  • Analytics & Experimentation
  • Data Scientist

Design A/B test for AI chat box

Company: Reddit

Role: Data Scientist

Category: Analytics & Experimentation

Difficulty: easy

Interview Round: Onsite

## Context A social platform (e.g., Reddit) plans to launch an **AI chat box** that answers user questions. The functionality overlaps with the existing **Search** experience. ## Task Design an A/B test to evaluate the launch. ### Requirements 1. Define the **primary metric**, **diagnostic metrics**, and **guardrail metrics**. 2. Describe the **experiment design**: - unit of randomization (user/session/etc.) - eligibility and ramp plan - experiment duration and how to handle novelty effects 3. Identify key **product impacts and risks**, including **cannibalization** of Search. 4. List major **confounders / biases** and how you would mitigate them. 5. Specify what decision you would make based on possible outcomes.

Quick Answer: This question evaluates skills in experimental design, product analytics, metrics selection, and causal inference relevant to a Data Scientist role in the Analytics & Experimentation domain.

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Reddit logo
Reddit
Dec 11, 2025, 12:00 AM
Data Scientist
Onsite
Analytics & Experimentation
4
0
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Context

A social platform (e.g., Reddit) plans to launch an AI chat box that answers user questions. The functionality overlaps with the existing Search experience.

Task

Design an A/B test to evaluate the launch.

Requirements

  1. Define the primary metric , diagnostic metrics , and guardrail metrics .
  2. Describe the experiment design :
    • unit of randomization (user/session/etc.)
    • eligibility and ramp plan
    • experiment duration and how to handle novelty effects
  3. Identify key product impacts and risks , including cannibalization of Search.
  4. List major confounders / biases and how you would mitigate them.
  5. Specify what decision you would make based on possible outcomes.

Solution

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