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.

Compare Instagram and Facebook Stories Using Key Performance Metrics

Quick Overview

This question evaluates a data scientist's competency in product analytics, causal inference, and experimentation design for comparing performance across two competing ephemeral story features, emphasizing clear metric definition for creators, viewers, monetization, and ecosystem effects.

Scenario

You are a data scientist tasked with quantitatively comparing the success of Instagram Stories versus Facebook Stories.

Question

Define what “success” means for Stories across both apps and articulate the units of comparison (e.g., per eligible DAU, per poster, per story, per viewer session).
Specify the key metrics you would track for:
- Creators (supply)
- Viewers (demand/quality)
- Business/monetization
- Ecosystem health and cannibalization
Propose experimental designs to estimate causal differences (e.g., A/B tests, geo experiments, matched-pairs), noting interference/spillover concerns between apps.
If controlled experiments are limited, propose analytical methods (e.g., matched pairs using cross-posted stories, difference-in-differences, fixed-effects models) to compare performance.
List guardrails, assumptions, and pitfalls to ensure a fair, apples-to-apples comparison.

Hints: Consider DAU posting, views per story, completion rate, time spent; consider matched-pairs or A/B tests across markets.

Quick Overview

Question

Define what “success” means for Stories across both apps and articulate the units of comparison (e.g., per eligible DAU, per poster, per story, per viewer session).

Specify the key metrics you would track for:

Creators (supply)
Viewers (demand/quality)
Business/monetization
Ecosystem health and cannibalization

Propose experimental designs to estimate causal differences (e.g., A/B tests, geo experiments, matched-pairs), noting interference/spillover concerns between apps.

If controlled experiments are limited, propose analytical methods (e.g., matched pairs using cross-posted stories, difference-in-differences, fixed-effects models) to compare performance.

List guardrails, assumptions, and pitfalls to ensure a fair, apples-to-apples comparison.

Hints: Consider DAU posting, views per story, completion rate, time spent; consider matched-pairs or A/B tests across markets.

Compare Instagram and Facebook Stories Using Key Performance Metrics

Quick Overview

Scenario

Question

Solution

Submit Your Answer to Earn 20XP

Compare Instagram and Facebook Stories Using Key Performance Metrics

Quick Overview

Scenario

Question

Solution

Submit Your Answer to Earn 20XP