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Investigate Reasons for Higher Instagram Story Consumption

Last updated: Mar 29, 2026

Quick Overview

Evaluates diagnostic analytics for explaining why Instagram users consume more Stories than Facebook users. Strong answers validate metric parity, decompose supply and demand drivers, use cohort and within-user comparisons, and propose experiments for UI, ranking, content, or notification hypotheses.

  • hard
  • Meta
  • Analytics & Experimentation
  • Data Scientist

Investigate Reasons for Higher Instagram Story Consumption

Company: Meta

Role: Data Scientist

Category: Analytics & Experimentation

Difficulty: hard

Interview Round: Onsite

##### Scenario Instagram users consume more Stories than Facebook users. ##### Question How would you investigate the reasons behind higher Story consumption on Instagram compared with Facebook? ##### Hints User demographics, content mix, UI differences, cohort analysis, controlled experiments.

Quick Answer: Evaluates diagnostic analytics for explaining why Instagram users consume more Stories than Facebook users. Strong answers validate metric parity, decompose supply and demand drivers, use cohort and within-user comparisons, and propose experiments for UI, ranking, content, or notification hypotheses.

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|Home/Analytics & Experimentation/Meta

Investigate Reasons for Higher Instagram Story Consumption

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Meta
Jul 12, 2025, 6:59 PM
hardData ScientistOnsiteAnalytics & Experimentation
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Investigate Reasons for Higher Instagram Story Consumption

You observe that Stories are consumed more on Instagram than on Facebook. Assume Story consumption means a normalized metric such as views per Story viewer per day, Story minutes per viewer, or completion rate.

Constraints & Assumptions

  • The goal is to diagnose why the gap exists, not simply restate that Instagram has higher usage.
  • Start by ensuring measurement definitions are comparable across apps.
  • Consider user mix, content supply, product design, social norms, ranking, notification/entry points, and logging differences.
  • Prefer analyses that can quantify contribution and support decisions.

Clarifying Questions to Ask Guidance

  • Which exact consumption metric is showing the gap?
  • Are we comparing all users, daily active users, Story viewers, or eligible users?
  • Are Stories implemented and logged identically across Instagram and Facebook?
  • Is the gap global, or concentrated in certain countries, cohorts, devices, or app versions?

Part 1 - Validate the Metric

How would you confirm that the Instagram versus Facebook comparison is valid?

What This Part Should Cover Guidance

  • Consistent definitions for view, completion, skip, exit, session, viewer, and eligible user.
  • Checks for instrumentation differences, sampling, cross-posting, bot filtering, autoplay behavior, and app-version rollouts.
  • Normalization by eligible users and segmentation by market, device, cohort, and tenure.

Part 2 - Diagnose Drivers

How would you investigate the reasons behind higher Story consumption on Instagram?

What This Part Should Cover Guidance

  • Decomposition of demand and supply: who watches, who posts, how much content is available, and how fresh it is.
  • Product differences such as tray placement, navigation, ranking, latency, notifications, and creator/friend mix.
  • Social norms and graph structure, including close-friend density, creator following, public sharing norms, and cross-posting.
  • Within-user comparisons for people who use both apps, plus matched cohorts to reduce confounding.

Part 3 - Decide What to Test

What analyses or experiments would you run after forming hypotheses?

What This Part Should Cover Guidance

  • Controlled experiments for UI placement, ranking, notifications, content seeding, or creator tools where feasible.
  • Quasi-experimental or difference-in-differences methods when full randomization is not possible.
  • Metrics for incremental Story consumption, overall app engagement, creator posting, retention, and guardrails.

What a Strong Answer Covers Guidance

A strong answer starts with metric parity, decomposes the gap into measurable drivers, uses within-user and cohort comparisons, and proposes experiments that can separate correlation from causation.

Follow-up Questions Guidance

  • How would you handle users who cross-post the same Story to both apps?
  • What if Instagram has more Story supply but Facebook viewers are more retained?
  • Which hypothesis would you test first and why?
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