Diagnose a 10% Fall in Notification Click-Through Rate on a Meta App

Quick Overview

A metric-diagnosis question for a Meta product manager: the click-through rate on an app's notifications has dropped 10%, and the candidate must work out why. It tests defining the ratio precisely, separating numerator, denominator and mix effects, segmenting by notification type and platform, and judging whether the drop really matters.

Diagnose a 10% Fall in Notification Click-Through Rate on a Meta App

Company: Meta

Role: Product Manager

Category: Analytics & Experimentation

Difficulty: medium

Interview Round: Other

You are a product manager at Meta. The click-through rate on notifications in one of the company's apps has fallen by 10%. Explain how you would figure out why it fell, and what you would recommend depending on what you find. ```hint Pull the ratio apart A rate moves when its top moves, when its bottom moves, or when the mix of things inside it shifts. Decide which of these happened before you look for a story. ``` ### Clarifying Questions - How is the rate defined: notification taps divided by notifications sent, delivered or actually displayed? Does it cover push notifications, the in-app notifications list, email, or all of them? - Is the 10% a relative drop (for example from 5.0% to 4.5%) or 10 percentage points, and did it happen suddenly or build up over weeks? - Which app is affected, and is the drop concentrated in particular notification types such as comments, friend requests, birthday reminders or video recommendations? - Did the number of notifications sent per user change over the same period? ### What a Strong Answer Covers - A precise definition of the metric and a check that the drop is real: click logging, deep-link attribution, and changes to what counts in the denominator. - Separating a numerator effect, a denominator effect and a mix effect, then segmenting by notification type, channel, platform, OS version and user activity level. - Internal hypotheses (changes to notification volume or ranking, new notification types, delivery delays, broken deep links, copy or preview changes, running experiments) and external ones (OS features that group or silence notifications, permission changes, seasonality, privacy news). - Judging whether the drop actually hurts the product by looking at total sessions started from notifications, notification opt-out and disable rates, and engagement with the underlying content. - A recommendation tied to each likely cause. ### Follow-up Questions - Total notification taps are flat, but the number of notifications sent grew over the same period. What happened, and is it a problem? - The drop is limited to iOS push notifications and started the week a new OS version shipped. How do you confirm the link, and what can you do about it? - Should the notifications team be judged on click-through rate at all? What would you measure instead?

Overview: A metric-diagnosis question for a Meta product manager: the click-through rate on an app's notifications has dropped 10%, and the candidate must work out why. It tests defining the ratio precisely, separating numerator, denominator and mix effects, segmenting by notification type and platform, and judging whether the drop really matters.

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Meta
Mar 10, 2025
mediumProduct ManagerOtherAnalytics & Experimentation
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You are a product manager at Meta. The click-through rate on notifications in one of the company's apps has fallen by 10%. Explain how you would figure out why it fell, and what you would recommend depending on what you find.

Clarifying Questions Guidance

  • How is the rate defined: notification taps divided by notifications sent, delivered or actually displayed? Does it cover push notifications, the in-app notifications list, email, or all of them?
  • Is the 10% a relative drop (for example from 5.0% to 4.5%) or 10 percentage points, and did it happen suddenly or build up over weeks?
  • Which app is affected, and is the drop concentrated in particular notification types such as comments, friend requests, birthday reminders or video recommendations?
  • Did the number of notifications sent per user change over the same period?

What a Strong Answer Covers Guidance

  • A precise definition of the metric and a check that the drop is real: click logging, deep-link attribution, and changes to what counts in the denominator.
  • Separating a numerator effect, a denominator effect and a mix effect, then segmenting by notification type, channel, platform, OS version and user activity level.
  • Internal hypotheses (changes to notification volume or ranking, new notification types, delivery delays, broken deep links, copy or preview changes, running experiments) and external ones (OS features that group or silence notifications, permission changes, seasonality, privacy news).
  • Judging whether the drop actually hurts the product by looking at total sessions started from notifications, notification opt-out and disable rates, and engagement with the underlying content.
  • A recommendation tied to each likely cause.

Follow-up Questions Guidance

  • Total notification taps are flat, but the number of notifications sent grew over the same period. What happened, and is it a problem?
  • The drop is limited to iOS push notifications and started the week a new OS version shipped. How do you confirm the link, and what can you do about it?
  • Should the notifications team be judged on click-through rate at all? What would you measure instead?