Investigating and Fixing Falling Satisfaction on Uber Airport Trips

Quick Overview

A product manager metric-diagnosis case in which rider experience on Uber's airport trips has declined over six months. It tests validating the metric, separating pickups from drop-offs, testing airport-specific causes such as wayfinding, driver queues and pricing, and choosing measurable fixes.

Investigating and Fixing Falling Satisfaction on Uber Airport Trips

Company: Uber

Role: Product Manager

Category: Analytics & Experimentation

Difficulty: medium

Interview Round: Other

Uber has seen rider experience on its airport rides decline over the last six months. As the product manager responsible for airport trips, explain how you would work out what is behind the decline and what you would do about it. ```hint Walk the airport trip An airport trip has steps that an ordinary city trip does not, such as finding a designated pickup zone or racing a departure time. Settle how experience is measured first, then ask which step of the airport trip the decline is concentrated in. ``` ### Clarifying Questions - How is rider experience measured here: the star rating riders give after a trip, the share of trips rated low, survey scores, complaints and support contacts, or a mix? Has the rating prompt or the metric definition changed during these six months? - Does "airport rides" mean pickups at the airport, drop-offs at the airport, or both, and does the decline look different for each? - How large is the decline, did it build gradually or drop at a specific point, and is it concentrated in particular airports, cities or countries? - Have non-airport trips in the same cities declined over the same period, or only airport trips? ### What a Strong Answer Covers - Confirming the metric is measured consistently and the decline is real before explaining it, including whether the mix of airport trips shifted. - Localizing the decline by pickup versus drop-off, airport, ride product, rider type, time of day and app version. - Airport-specific hypotheses (pickup wayfinding, driver queues and cancellations, wait times, pricing and fees, airport rules, luggage, flight-time pressure), each paired with the data that would confirm or rule it out, checked in a sensible order. - Fixes matched to the confirmed cause and prioritized, with a success metric, a way to test them, and guardrails covering drivers, trip volume and margin. ### Follow-up Questions - The decline turns out to be confined to pickups at a few large airports that recently moved rideshare pickups to a parking structure away from the terminals. What would you do next? - Ratings on airport trips fell while airport trip volume grew. How does that change your interpretation? - Many low airport ratings seem to reflect problems a driver cannot control, such as a crowded pickup area. Should those ratings still count against drivers, and how would you decide?

Overview: A product manager metric-diagnosis case in which rider experience on Uber's airport trips has declined over six months. It tests validating the metric, separating pickups from drop-offs, testing airport-specific causes such as wayfinding, driver queues and pricing, and choosing measurable fixes.

Uber logo
Uber
Dec 9, 2025
mediumProduct ManagerOtherAnalytics & Experimentation
0
0

Uber has seen rider experience on its airport rides decline over the last six months. As the product manager responsible for airport trips, explain how you would work out what is behind the decline and what you would do about it.

Clarifying Questions Guidance

  • How is rider experience measured here: the star rating riders give after a trip, the share of trips rated low, survey scores, complaints and support contacts, or a mix? Has the rating prompt or the metric definition changed during these six months?
  • Does "airport rides" mean pickups at the airport, drop-offs at the airport, or both, and does the decline look different for each?
  • How large is the decline, did it build gradually or drop at a specific point, and is it concentrated in particular airports, cities or countries?
  • Have non-airport trips in the same cities declined over the same period, or only airport trips?

What a Strong Answer Covers Guidance

  • Confirming the metric is measured consistently and the decline is real before explaining it, including whether the mix of airport trips shifted.
  • Localizing the decline by pickup versus drop-off, airport, ride product, rider type, time of day and app version.
  • Airport-specific hypotheses (pickup wayfinding, driver queues and cancellations, wait times, pricing and fees, airport rules, luggage, flight-time pressure), each paired with the data that would confirm or rule it out, checked in a sensible order.
  • Fixes matched to the confirmed cause and prioritized, with a success metric, a way to test them, and guardrails covering drivers, trip volume and margin.

Follow-up Questions Guidance

  • The decline turns out to be confined to pickups at a few large airports that recently moved rideshare pickups to a parking structure away from the terminals. What would you do next?
  • Ratings on airport trips fell while airport trip volume grew. How does that change your interpretation?
  • Many low airport ratings seem to reflect problems a driver cannot control, such as a crowded pickup area. Should those ratings still count against drivers, and how would you decide?