Compare Instagram and Facebook Stories Using Key Performance Metrics
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.
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Aug 4, 2025, 10:55 AM
Data Scientist
Onsite
Analytics & Experimentation
0
0
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).
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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.
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