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.

Analyze Revenue Shifts to Identify Cannibalization Effects

Quick Overview

This question evaluates a data scientist's ability to apply causal inference and experimental-design principles, interpret panel and time-series revenue data, and detect cannibalization effects across mutually exclusive creation sources in the Analytics & Experimentation domain.

Cannibalization vs. Organic Growth Across Creation Sources

Scenario

Management observed strong revenue growth from one creation_source (a channel by which revenue‑generating units such as orders/ads/subscriptions are created). They want evidence on whether this growth is cannibalizing revenue from other sources versus reflecting net organic growth.

Assumptions (for clarity):

creation_source identifies mutually exclusive channels (e.g., API, mobile, web, partner) for the creation of monetizable objects.
Revenue can be measured over time (e.g., by week) and aggregated by unit (e.g., geo/market or user cohort) and source.

Question

Design an analysis to determine whether next year’s revenue increase for a specific creation_source (call it Source A) is offset by declines in other sources. Your approach should aim for causal evidence rather than correlations.

Consider methods such as:

Randomized traffic re-allocation or holdouts
Difference-in-differences with control groups
Fixed-effects panel regressions and event studies
Time-series regression/VAR
Instrumental variables or synthetic control

Quick Overview

Scenario

Assumptions (for clarity):

creation_source identifies mutually exclusive channels (e.g., API, mobile, web, partner) for the creation of monetizable objects.

Revenue can be measured over time (e.g., by week) and aggregated by unit (e.g., geo/market or user cohort) and source.

Question

Consider methods such as:

Randomized traffic re-allocation or holdouts

Difference-in-differences with control groups

Fixed-effects panel regressions and event studies

Time-series regression/VAR

Instrumental variables or synthetic control

Analyze Revenue Shifts to Identify Cannibalization Effects

Quick Overview

Cannibalization vs. Organic Growth Across Creation Sources

Scenario

Question

Solution

Submit Your Answer to Earn 20XP

Analyze Revenue Shifts to Identify Cannibalization Effects

Quick Overview

Cannibalization vs. Organic Growth Across Creation Sources

Scenario

Question

Solution

Submit Your Answer to Earn 20XP