Root-Cause Diagnosis of an Abrupt 10% Drop in YouTube Revenue

Quick Overview

A metric diagnosis prompt asking a PM candidate to explain a sudden 10% drop in YouTube revenue. It tests clarifying the revenue definition and baseline, ruling out reporting issues, decomposing ad and subscription revenue into drivers, segmenting the decline and ordering hypotheses with evidence.

Root-Cause Diagnosis of an Abrupt 10% Drop in YouTube Revenue

Company: Google

Role: Product Manager

Category: Analytics & Experimentation

Difficulty: medium

Interview Round: Other

You are a product manager at YouTube, and YouTube's revenue has suddenly dropped by 10%. Walk through how you would work out why. Explain what you would clarify first, how you would investigate, which explanations you would consider, and what evidence would confirm or rule out each one. ```hint Break the number apart Before guessing at causes, write each YouTube revenue stream as a product of a few drivers and find which driver moved. The cause usually sits upstream of that one driver. ``` ### Clarifying Questions - Which revenue fell: total YouTube revenue, advertising only, or subscription products such as Premium? - Is the 10% measured against the preceding days, the same period last year, or a forecast, and over how long did it happen? - Where does the figure come from: a near-real-time ads dashboard or finance's booked revenue, and in which currency? - Is the drop global, or concentrated in certain countries, devices or ad formats? ### What a Strong Answer Covers - Clarifying the revenue definition, the baseline and the timeframe, and checking that the drop is real rather than a reporting or currency effect. - A decomposition of each revenue stream into drivers on both the viewer side and the advertiser side. - Segmenting the drop and lining it up against a timeline of internal changes. - Internal and external hypotheses tested in a sensible order, each with the data that would confirm it. - A conclusion naming the most likely cause and how it would be verified. ### Follow-up Questions - Watch time is flat, but the number of ads shown per day has fallen. What do you check next? - You trace the drop to a recent change in the flow advertisers use to pay for campaigns. What do you do in the first day, and afterwards? - How would you tell a drop caused by an ad-serving fault from one caused by advertisers cutting their budgets?

Overview: A metric diagnosis prompt asking a PM candidate to explain a sudden 10% drop in YouTube revenue. It tests clarifying the revenue definition and baseline, ruling out reporting issues, decomposing ad and subscription revenue into drivers, segmenting the decline and ordering hypotheses with evidence.

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Google
Nov 22, 2025
mediumProduct ManagerOtherAnalytics & Experimentation
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You are a product manager at YouTube, and YouTube's revenue has suddenly dropped by 10%. Walk through how you would work out why. Explain what you would clarify first, how you would investigate, which explanations you would consider, and what evidence would confirm or rule out each one.

Clarifying Questions Guidance

  • Which revenue fell: total YouTube revenue, advertising only, or subscription products such as Premium?
  • Is the 10% measured against the preceding days, the same period last year, or a forecast, and over how long did it happen?
  • Where does the figure come from: a near-real-time ads dashboard or finance's booked revenue, and in which currency?
  • Is the drop global, or concentrated in certain countries, devices or ad formats?

What a Strong Answer Covers Guidance

  • Clarifying the revenue definition, the baseline and the timeframe, and checking that the drop is real rather than a reporting or currency effect.
  • A decomposition of each revenue stream into drivers on both the viewer side and the advertiser side.
  • Segmenting the drop and lining it up against a timeline of internal changes.
  • Internal and external hypotheses tested in a sensible order, each with the data that would confirm it.
  • A conclusion naming the most likely cause and how it would be verified.

Follow-up Questions Guidance

  • Watch time is flat, but the number of ads shown per day has fallen. What do you check next?
  • You trace the drop to a recent change in the flow advertisers use to pay for campaigns. What do you do in the first day, and afterwards?
  • How would you tell a drop caused by an ad-serving fault from one caused by advertisers cutting their budgets?