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 Onsite rounds at Meta.

What role is this question designed for?

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

Evaluating and launching Instagram Stories | Meta Interview Question

Evaluating and launching Instagram Stories

Last updated: Mar 29, 2026

Quick Overview

This question evaluates a data scientist's competency in product analytics, experimentation design, launch metric definition, and causal attribution for feature cannibalization across two social apps, and sits in the Analytics & Experimentation domain for a Data Scientist role.

Context

You are evaluating the rollout and impact of Stories, an ephemeral sharing format similar to Snapchat, across two apps: Instagram and Facebook. Stories may increase engagement but could cannibalize Feed posts. You are asked to define evaluation criteria, launch decisions, mitigation strategies for cannibalization, and explain cross‑app performance gaps, including an experiment design.

Questions

How would you evaluate Instagram Stories? (Hint: DAU lift, posting frequency, interaction time)
What criteria decide a full launch? (Hint: pilot KPIs, competitor benchmarks)
If Stories cannibalize Feed posts, how would you respond? (Hint: offset metrics, incremental revenue)
Facebook Stories views are half Instagram’s—why? Design an experiment. (Hint: audience mix, product positioning)

Solution

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