Estimate daily active usage of Uber Eats 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 Uber Eats in a priority market, with particular attention to airport travelers as a meaningful demand segment. In this interview, you are being asked to build a practical estimate of how many people use Uber Eats on a typical day in that market.

You should clarify the scope of “priority market,” define what counts as “daily active usage,” and separate relevant user groups such as residents, business travelers, tourists, airport staff, and passengers in transit. The focus is not on finding a perfect number, but on showing a structured, business-relevant way to size demand.

Your estimate should reflect how Uber Eats fits into real user behavior: ordering before or after flights, during hotel stays, at airport-adjacent locations, or while traveling for work. You may need to account for local competition, restaurant availability, delivery reliability, travel patterns, and differences between weekday, weekend, and seasonal demand.

The experience should consider:

- The exact unit being estimated, such as daily active users, daily orders, or unique ordering customers

- The geographic scope of the priority market, including whether airport zones are included or separated

- Population segments, including residents, airport travelers, hotel guests, workers, and commuters

- Adoption assumptions for Uber Eats within each segment

- Ordering frequency and repeat usage within a day

- Market-specific factors such as income levels, restaurant density, airport passenger volume, and delivery availability

- Sensitivity checks for high-travel days, low-travel days, and seasonal peaks

- Sanity checks against broader food delivery behavior and Uber’s marketplace dynamics

Your goal is to produce a clear, defensible estimate with transparent assumptions, logical segmentation, and an explanation of which variables would most influence the final daily active usage number.