Estimate daily active usage of Reservations in a priority market at global scale

Problem Statement Description

Product context: Uber is a mobility and delivery platform; its products include rides, Uber Eats, grocery and retail delivery, freight, driver and courier tools, and marketplace pricing.

Uber Reservations lets riders schedule rides in advance, with airport trips as a high-intent use case where reliability, timing, and driver availability matter more than in a typical on-demand ride. In this guesstimate, estimate the daily active usage of Reservations for airport travelers in a priority market, while keeping the reasoning applicable to a global mobility marketplace.

Clarify what “daily active usage” means for this product: for example, whether you are estimating unique riders who create or complete a reserved airport trip per day, total reservation trips per day, or another usage unit. You should define the market scope, the airport-traveler segment, and any assumptions about inbound vs. outbound airport trips, business vs. leisure travel, and local alternatives such as taxis, Lyft, Grab, Bolt, or other regional providers.

The estimate should be built from a defensible bottom-up or top-down structure, not from a single guessed number. Consider how airport passenger volume, Uber penetration, reservation awareness, suitability of scheduled rides, pricing, reliability expectations, and marketplace supply constraints influence adoption.

The experience should consider:

- The exact unit being estimated: unique daily users, reserved airport trips, completed reservations, or booking attempts.

- The geographic scope of the “priority market” and why it is representative or strategically important.

- The relevant population base, such as daily airport passengers, airport ground-transport users, or Uber airport riders.

- Adoption assumptions for Reservations among airport travelers, including first-time vs. repeat usage.

- Frequency assumptions, especially for business travelers, frequent flyers, and occasional leisure travelers.

- Marketplace constraints such as driver availability, pickup regulations, surge pricing, cancellation risk, and reservation lead time.

- Sensitivity of the estimate to major assumptions like airport volume, Uber modal share, and reservation conversion.

- Sanity checks against comparable airport ride volumes, ride-hailing penetration, and expected operational capacity.

Your goal is to produce a clear, structured estimate with explicit assumptions, a reasonable range, and a way to explain which variables matter most if Uber were using this estimate to size the Reservations opportunity or prioritize operational investment in that market.