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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.

Investigate Causes of Decline in Facebook Group Comments

Last updated: Mar 29, 2026

Quick Overview

This question evaluates a data scientist's skills in product analytics, metric instrumentation, causal inference, segmentation, and experimentation for diagnosing a drop in comments-per-post within social network group engagement.

Scenario

A sharp decline in Comments per Post (CPP) was observed in Facebook Groups last week.

Task

Outline a step-by-step investigation plan to diagnose and address the drop. Your plan should include:

Definitions and sanity checks for the metric.
Key data cuts/segmentations to localize the issue.
A hypotheses tree structured by: user, content, product, and external factors.
Metrics and analyses to validate or falsify each hypothesis, including how to quantify each factor's contribution to the drop.
Follow-up experiments or mitigations, with success metrics and guardrails.

Hints

Be explicit about ratio-metric pitfalls (numerator vs denominator) and cohorting choices.
Include time comparisons (WoW, DoW, YoY) and seasonality checks.
Incorporate experiment flags, app versions, geo/language, group types/sizes, and post types.
Quantify impact by segment and roll up contributions to explain the total drop.
Propose rapid mitigations (e.g., rollback/ramp holds) when warranted.

Solution

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