Estimate infrastructure or operational capacity needed for Ads

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 is exploring or scaling an Ads offering within its global mobility, delivery, and logistics marketplace, with particular relevance to driver-facing surfaces and marketplace participants. Your task is to estimate the infrastructure or operational capacity required to support this Ads business at meaningful scale.

Think of this as a guesstimate exercise, not a system design deep dive. You should define what “capacity” means for the scope you choose—for example, ad impressions served, requests processed, campaigns managed, advertiser support volume, moderation workload, or operations staffing needed to run ads reliably across markets.

The estimate should reflect Uber’s marketplace context: high-frequency app usage, real-time user sessions, geographic variability, driver supply dynamics, advertiser demand, safety and reliability expectations, and the need to avoid degrading core mobility or delivery experiences.

The experience should consider:

- The specific Ads surface or workflow being estimated, such as driver app placements, in-trip surfaces, delivery-related ads, or advertiser campaign operations

- The relevant unit of capacity, such as impressions per day, ad requests per second, campaigns per operations manager, reviewed creatives per day, or support tickets per advertiser

- The target population and usage base, including drivers, riders, eaters, couriers, merchants, or advertisers, depending on the chosen scope

- Adoption and frequency assumptions, including active users, sessions per user, trips or deliveries, ad load, fill rate, and seasonality

- Geographic and marketplace variation across large cities, smaller markets, and regions with different regulatory or operational complexity

- Key constraints such as latency, reliability, data privacy, safety, brand suitability, and avoiding negative impact on driver or rider experience

- Sensitivity analysis around the biggest assumptions and how the estimate changes under conservative, base, and aggressive scenarios

- Sanity checks using comparable marketplace, mobility, delivery, or digital advertising benchmarks

The goal is to produce a clear, structured estimate that shows how you scope ambiguity, choose defensible assumptions, calculate capacity needs, and identify the variables that would most influence Uber’s planning decisions for Ads infrastructure or operations.