Diagnose and Respond to a 10% Drop in Airbnb's Monthly Bookings

Quick Overview

A product manager metrics question about Airbnb: total bookings fell 10% this month, and the candidate must work out why and decide what to do. It tests validating the metric, accounting for calendar and seasonal effects, decomposing the guest funnel and host supply, localizing the drop, and matching actions to root causes.

Diagnose and Respond to a 10% Drop in Airbnb's Monthly Bookings

Company: Airbnb

Role: Product Manager

Category: Analytics & Experimentation

Difficulty: medium

Interview Round: Other

You are a product manager at Airbnb. This month, total bookings on the platform are down 10%. Explain how you would figure out what is driving the decline and what you would do next. ```hint Break bookings into its drivers A booking happens only when guests show up, search, find a listing they like at a price they accept and complete the reservation, and when hosts keep enough nights open. Find which of those pieces moved before deciding why it moved. ``` ### Clarifying Questions - Down 10% compared with what: the previous month, the same month last year, or the forecast? Is the month complete, or is this a month-to-date figure? - Does "bookings" mean reservations created this month, nights booked, or stays checked in this month, and are cancellations netted out? - Is the decline spread across markets, devices and both Stays and Experiences, or concentrated in a few places? - Did gross booking value and nights booked fall by the same amount, or only the number of reservations? ### What a Strong Answer Covers - Confirming the drop is real and unexpected: metric definition, data quality, calendar length and seasonality. - A decomposition across the guest booking funnel and the host supply side of the marketplace. - Segment cuts that localize the decline, such as destination, origin market, platform, new versus returning guests and booking lead time. - Internal and external hypotheses checked in a sensible order, each with the evidence that confirms or rules it out. - Responses tied to the confirmed cause, with success metrics and guardrails. ### Follow-up Questions - Reservations fell 10%, but nights booked and booking value were flat. Is this still a problem, and what would explain it? - The decline turns out to be concentrated in a few large cities that recently tightened short-term rental rules. What do you do this quarter and over the next year? - How would you tell a real loss of demand apart from guests simply booking closer to their travel dates?

Overview: A product manager metrics question about Airbnb: total bookings fell 10% this month, and the candidate must work out why and decide what to do. It tests validating the metric, accounting for calendar and seasonal effects, decomposing the guest funnel and host supply, localizing the drop, and matching actions to root causes.

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Airbnb
Dec 7, 2025
mediumProduct ManagerOtherAnalytics & Experimentation
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You are a product manager at Airbnb. This month, total bookings on the platform are down 10%. Explain how you would figure out what is driving the decline and what you would do next.

Clarifying Questions Guidance

  • Down 10% compared with what: the previous month, the same month last year, or the forecast? Is the month complete, or is this a month-to-date figure?
  • Does "bookings" mean reservations created this month, nights booked, or stays checked in this month, and are cancellations netted out?
  • Is the decline spread across markets, devices and both Stays and Experiences, or concentrated in a few places?
  • Did gross booking value and nights booked fall by the same amount, or only the number of reservations?

What a Strong Answer Covers Guidance

  • Confirming the drop is real and unexpected: metric definition, data quality, calendar length and seasonality.
  • A decomposition across the guest booking funnel and the host supply side of the marketplace.
  • Segment cuts that localize the decline, such as destination, origin market, platform, new versus returning guests and booking lead time.
  • Internal and external hypotheses checked in a sensible order, each with the evidence that confirms or rules it out.
  • Responses tied to the confirmed cause, with success metrics and guardrails.

Follow-up Questions Guidance

  • Reservations fell 10%, but nights booked and booking value were flat. Is this still a problem, and what would explain it?
  • The decline turns out to be concentrated in a few large cities that recently tightened short-term rental rules. What do you do this quarter and over the next year?
  • How would you tell a real loss of demand apart from guests simply booking closer to their travel dates?