Analyze why Freight usage is growing but revenue is flat

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 Freight serves merchants and shippers who need to move goods reliably through a logistics marketplace. In this scenario, the product is showing growth in usage, but revenue is not increasing at the same pace. Your task is to investigate this apparent disconnect and determine what could be driving it.

You should treat “usage” and “revenue” as potentially different signals that may vary by merchant segment, geography, shipment type, pricing model, carrier supply, and operational behavior. The goal is not to jump to a single cause, but to structure a clear root-cause analysis that separates measurement issues from real business or marketplace dynamics.

Assume this is a medium-complexity product and business problem inside Uber, where marketplace liquidity, reliability, unit economics, and merchant retention all matter. Your analysis should show how you would narrow the issue, validate or reject hypotheses, and identify what actions or follow-up investigation would be needed.

The investigation should consider:

- How “Freight usage” is defined, such as shipments booked, active merchants, load volume, miles moved, repeat usage, or app/session activity

- How revenue is defined, including gross bookings, net revenue, take rate, fees, discounts, refunds, or recognized revenue timing

- Whether the anomaly is broad-based or concentrated in specific merchant cohorts, lanes, geographies, shipment sizes, contract types, or acquisition channels

- Instrumentation and reporting checks to confirm that usage and revenue are being measured consistently over the same time period

- Marketplace dynamics such as pricing pressure, lower-value loads, carrier incentives, supply constraints, cancellations, or service-quality issues

- Merchant behavior changes, including increased low-margin usage, promotional adoption, contract renegotiations, or shifts from premium to cheaper services

- External and competitive factors that could affect pricing, demand mix, carrier availability, or merchant expectations

- Immediate mitigations, longer-term prevention, and how you would monitor whether the issue is improving

Your goal is to present a structured RCA approach that helps Uber determine whether flat revenue is caused by data quality, mix shift, pricing, marketplace health, merchant behavior, or operational execution, and to outline how the team should prioritize evidence before deciding on corrective action.