Estimate daily active usage of Reservations in a priority market

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 wants to understand the daily active usage of its Reservations product in a priority market, with a particular focus on airport travelers. Reservations allow riders to schedule trips in advance, which can be especially relevant for time-sensitive use cases such as catching flights, airport pickups, business travel, early-morning rides, and planned intercity connections.

In this guesstimate, you should estimate how many users or trips use Uber Reservations on a typical day in one clearly defined priority market. You may choose a representative market, such as a large airport-heavy metro area, but you should state and justify the market scope before estimating. The estimate should focus on daily active usage, not total addressable market or annual bookings.

Your answer should show a structured sizing approach using clear assumptions, logical segmentation, and sanity checks. Consider how airport travel demand, rider behavior, reservation adoption, trip frequency, supply reliability, and competitive alternatives may affect the final estimate.

The experience should consider:

- The exact unit being estimated: reserved trips per day, unique reservation users per day, or another clearly defined usage metric.

- The chosen market scope, including airport volume, metro population, tourist/business travel, and local ride-hailing maturity.

- Relevant user segments, such as departing passengers, arriving passengers, business travelers, residents, visitors, and early/late travelers.

- Adoption assumptions for Uber overall and for Reservations specifically within airport-related and non-airport use cases.

- Frequency assumptions, including how often eligible travelers use reserved rides versus on-demand rides, taxis, rental cars, public transit, or competitors.

- Marketplace constraints, such as driver availability, reliability expectations, pricing, cancellation risk, and airport operating rules.

- Sensitivity of the estimate to the largest assumptions, especially airport passenger volume, ride-hail share, and reservation conversion rate.

- Sanity checks against overall ride-hailing demand, airport trip volumes, and what would be operationally plausible for a priority Uber market.

The goal is to produce a defensible, transparent estimate of daily active Reservations usage in a priority market and explain which assumptions matter most for the business decision.