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Compare performance of FB vs IG Stories

Last updated: Mar 29, 2026

Quick Overview

This question evaluates a data scientist's competency in experimental design, causal inference, attribution modeling, metric selection, and decision-oriented statistical analysis within the Analytics & Experimentation domain.

  • easy
  • Meta
  • Analytics & Experimentation
  • Data Scientist

Compare performance of FB vs IG Stories

Company: Meta

Role: Data Scientist

Category: Analytics & Experimentation

Difficulty: easy

Interview Round: Technical Screen

You are asked to compare ads performance between two placements/products (e.g., **Facebook Stories vs Instagram Stories**) and make a recommendation on where to allocate budget. ### Task Describe how you would conduct a fair comparison, including: 1. What **primary metric** you’d optimize for (and why), plus diagnostic and guardrail metrics. 2. How you’d handle **attribution** and cross-platform user overlap (same user on both). 3. Key confounders (audience differences, auction dynamics, creative fit, seasonality). 4. Whether you’d use observational analysis or a controlled experiment; design the experiment if applicable. 5. How you’d present results and decide budget allocation under uncertainty. Assume you have impression-, click-, and conversion-level logs and cost data.

Quick Answer: This question evaluates a data scientist's competency in experimental design, causal inference, attribution modeling, metric selection, and decision-oriented statistical analysis within the Analytics & Experimentation domain.

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Meta
Feb 16, 2026, 9:27 AM
Data Scientist
Technical Screen
Analytics & Experimentation
8
0
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You are asked to compare ads performance between two placements/products (e.g., Facebook Stories vs Instagram Stories) and make a recommendation on where to allocate budget.

Task

Describe how you would conduct a fair comparison, including:

  1. What primary metric you’d optimize for (and why), plus diagnostic and guardrail metrics.
  2. How you’d handle attribution and cross-platform user overlap (same user on both).
  3. Key confounders (audience differences, auction dynamics, creative fit, seasonality).
  4. Whether you’d use observational analysis or a controlled experiment; design the experiment if applicable.
  5. How you’d present results and decide budget allocation under uncertainty.

Assume you have impression-, click-, and conversion-level logs and cost data.

Solution

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