How do I approach Analytics & Experimentation interview questions?

Analytics & Experimentation questions require understanding of core concepts and practice. PracHub provides solutions with explanations to help you master analytics & experimentation interviews.

What difficulty level is this interview question?

This is a medium difficulty Analytics & Experimentation question, commonly asked during Technical Screen rounds at Meta.

What role is this question designed for?

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

Evaluate Impact of Increasing Stranger Content in Feeds

Last updated: Mar 29, 2026

Quick Overview

This question evaluates a data scientist's competence in experimentation design, causal inference, metric definition, and trade-off analysis for product metrics like engagement versus discovery in the Analytics & Experimentation domain.

Feed-Ranking Strategy: Friends vs. Stranger Content

Background

A personalized feed currently mixes posts from users' friends and posts from unconnected accounts ("strangers"). Observational data suggests users exhibit more social behavior (e.g., comments, shares, replies, messages) when viewing friends’ posts. The product team is considering surfacing a higher proportion of stranger content to increase discovery.

Task

Would you increase the proportion of stranger posts in the feed? Outline how you would evaluate and decide.

Requirements

State clear hypotheses and mechanisms.
Define success metrics, guardrails, and decision criteria.
Propose an experiment design (including dosage levels, duration, and power).
Specify key user and market segments to analyze.
Discuss trade-offs (e.g., engagement vs. discovery) and long-term effects.

Solution

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