Analyze Factors Behind 20% Retail Revenue Decline
Overview
This question evaluates a candidate's competency in diagnostic analytics, causal inference, and business-metric decomposition within the Analytics & Experimentation domain of data science, focusing on understanding revenue drivers like traffic, conversion, and average order value.
Coinbase
Jul 12, 2025, 6:59 PM
Data Scientist
Technical Screen
Analytics & Experimentation
20
0
Retail Revenue Decline Analysis
Scenario
A retailer reports a 20% decline in revenue compared with a prior, comparable period.
Assume revenue is net of returns/cancellations and the two periods are intended to be comparable (same length, similar seasonality). If not, note and adjust.
Question
How would you analyze and pinpoint the drivers behind the 20% drop in retail revenue?
Your plan should:
- Decompose revenue (Traffic × Conversion × AOV) and quantify each component’s contribution.
- Segment by product, channel, region, time, and customer cohorts.
- Diagnose potential causes including pricing, promotions, inventory/availability, site/app performance, marketing/competition, and external factors.
- Specify data to pull, quick sanity checks, how you’d quantify contributions, and how you’d validate causality.
Solution
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