Diagnose Revenue Decline: Key Analyses and Metrics

Q: Diagnose Revenue Decline: Key Analyses and Metrics

This question evaluates a candidate's competency in revenue diagnostics, metric decomposition, cohort and segmentation analysis, and experimentation-aware causal reasoning within product analytics.

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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.

Question

Diagnose a Sudden Revenue Drop

Scenario

A consumer fintech/trading platform (e.g., mobile/web app with transaction-fee revenue) experiences a noticeable revenue decline over the last 7–14 days compared to the prior comparable period.

Revenue comes primarily from transaction fees on trading volume (take rate × volume), plus smaller streams such as spreads, subscriptions, staking/custody, and other fees. Seasonality (day-of-week), market conditions, and release/experiment calendars can influence user behavior.

Task

Outline the analyses you would run to diagnose the cause of the revenue decline.
Specify the first metrics and data cuts you would inspect and why.
Explain how you would test potential root-cause hypotheses (both experiment-driven and organic changes).

Hints

Consider dimensions: time, product/feature, asset/pair, geography, device/app version, user cohort/tenure, acquisition channel.
Think segmentation, external factors (market price/volatility, payment rail/network outages, regulatory events), and experiment-vs-organic changes.
Aim to quantify contributions via decomposition (volume vs take rate vs mix) and validate with counterfactuals.

Diagnose Revenue Decline: Key Analyses and Metrics

Diagnose a Sudden Revenue Drop

Scenario

Task

Hints

Solution

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