Reversing a falling average order value on Uber Eats while order volume grows

Quick Overview

An Uber Eats product case about average basket value falling while order volume grows, which hurts commission revenue and restaurants. It tests decomposing the metric, separating a shift in order mix from a change in ordering behavior, and proposing, prioritizing and measuring ways to raise basket size.

Reversing a falling average order value on Uber Eats while order volume grows

Company: Uber

Role: Product Manager

Category: Product Design & Strategy

Difficulty: medium

Interview Round: Other

You are a product manager on Uber Eats. The average basket value of an order has been falling steadily over a period in which the number of orders kept growing. Uber earns a commission on every order, so the decline cuts into Uber's revenue, and it also hurts the restaurants on the platform. The team wants to reverse the trend. How would you raise basket value? ```hint Split the number before fixing it Break basket value into its components and into the groups of orders that make it up, and test whether orders are getting smaller or a different kind of order now makes up more of the total. ``` ### Clarifying Questions - Is basket value measured on the food subtotal, or on the total including delivery fees, service fees and tips? - Is the decline visible across every market and customer group, or concentrated in new markets, new customers or certain types of restaurant? - Given that order volume is rising, is the goal commission revenue per order or total commission revenue? - Are fees and order minimums available as levers, or only the ordering experience? ### What a Strong Answer Covers - A precise definition of basket value and a decomposition of the decline into its drivers - A diagnosis plan that separates a change in the mix of orders from a change in how people order, with outside factors ruled in or out - Ideas aimed at the diagnosed cause, prioritized with explicit criteria that cover both customers and restaurants - A primary metric with guardrails, and a test plan - The risks and trade-offs of raising basket value, and how each would be caught ### Follow-up Questions - If the decline came entirely from newly added low-priced restaurants, would you still act? Why or why not? - How would you check that a basket-raising feature adds revenue instead of pulling spend forward from later orders? - How would restaurants react to your top idea, and what would you offer them?

Overview: An Uber Eats product case about average basket value falling while order volume grows, which hurts commission revenue and restaurants. It tests decomposing the metric, separating a shift in order mix from a change in ordering behavior, and proposing, prioritizing and measuring ways to raise basket size.

Uber logo
Uber
Feb 1, 2024
mediumProduct ManagerOtherProduct Design & Strategy
0
0

You are a product manager on Uber Eats. The average basket value of an order has been falling steadily over a period in which the number of orders kept growing. Uber earns a commission on every order, so the decline cuts into Uber's revenue, and it also hurts the restaurants on the platform. The team wants to reverse the trend. How would you raise basket value?

Clarifying Questions Guidance

  • Is basket value measured on the food subtotal, or on the total including delivery fees, service fees and tips?
  • Is the decline visible across every market and customer group, or concentrated in new markets, new customers or certain types of restaurant?
  • Given that order volume is rising, is the goal commission revenue per order or total commission revenue?
  • Are fees and order minimums available as levers, or only the ordering experience?

What a Strong Answer Covers Guidance

  • A precise definition of basket value and a decomposition of the decline into its drivers
  • A diagnosis plan that separates a change in the mix of orders from a change in how people order, with outside factors ruled in or out
  • Ideas aimed at the diagnosed cause, prioritized with explicit criteria that cover both customers and restaurants
  • A primary metric with guardrails, and a test plan
  • The risks and trade-offs of raising basket value, and how each would be caught

Follow-up Questions Guidance

  • If the decline came entirely from newly added low-priced restaurants, would you still act? Why or why not?
  • How would you check that a basket-raising feature adds revenue instead of pulling spend forward from later orders?
  • How would restaurants react to your top idea, and what would you offer them?