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Determine Demand for WhatsApp Group Video-Calls

Last updated: Mar 29, 2026

Quick Overview

This question evaluates proficiency in opportunity sizing, metric hierarchy development, and experimental design for new product features, including clustered A/B testing and interpretation of lift versus risk.

  • hard
  • Meta
  • Analytics & Experimentation
  • Data Scientist

Determine Demand for WhatsApp Group Video-Calls

Company: Meta

Role: Data Scientist

Category: Analytics & Experimentation

Difficulty: hard

Interview Round: Technical Screen

##### Scenario WhatsApp is considering launching a group video-call feature; currently it does not exist. ##### Question a) Using the available call-level data, outline how you would determine whether there is demand for group calls. b) What additional quantitative and qualitative data would you request, and how would you analyze it? c) After launch, list success and guard-rail metrics; if you could keep only one success metric, which one and why? d) Before launch, engineering asks for an experiment design—describe step-by-step how you would run and analyze the test, including randomization unit, clustering to reduce spill-over, novelty effects, and criteria for statistical & business significance. ##### Hints Frame analysis: opportunity sizing → metric hierarchy → clustered A/B test design → interpretation of lift vs. risk.

Quick Answer: This question evaluates proficiency in opportunity sizing, metric hierarchy development, and experimental design for new product features, including clustered A/B testing and interpretation of lift versus risk.

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Meta
Jul 12, 2025, 6:59 PM
Data Scientist
Technical Screen
Analytics & Experimentation
69
0

Opportunity Sizing and Experimentation Plan for WhatsApp Group Video Calls

Scenario

WhatsApp is considering launching a new group video-call feature (not currently available).

Questions

  1. Using available call-level data, outline how you would determine whether there is demand for group video calls.
  2. What additional quantitative and qualitative data would you request, and how would you analyze it?
  3. After launch, list success and guard-rail metrics. If you could keep only one success metric, which one and why?
  4. Before launch, engineering asks for an experiment design. Describe step-by-step how you would run and analyze the test, including:
    • Randomization unit
    • Clustering to reduce spill-over
    • Novelty effects
    • Criteria for statistical and business significance

Hint: Frame the analysis as opportunity sizing → metric hierarchy → clustered A/B test design → interpretation of lift vs. risk.

Solution

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