Uber Eats morning daypart: growing breakfast orders through demand and supply levers
Company: Uber
Role: Product Manager
Category: Product Design & Strategy
Difficulty: medium
Interview Round: Other
You are a product manager at Uber Eats, and the company wants to win more of the morning meal. How would you grow the number of breakfast orders placed on Uber Eats? Explain why breakfast ordering may be lagging, which customers you would target, what you would build or change, and how you would measure whether it worked.
```hint Find what makes mornings different
Mornings differ from dinner in time pressure, order size relative to fees, and existing routines. Work out which of these holds breakfast orders back before choosing features.
```
### Clarifying Questions
- Should the growth come from current Uber Eats customers ordering breakfast more often, from people who have never ordered in the morning, or both?
- Which hours count as breakfast, and do coffee-only and grocery orders count?
- Must each extra breakfast order be profitable after delivery costs, or can growth be subsidized for a while?
- Should we start in a few markets or launch everywhere at once?
### What a Strong Answer Covers
- A diagnosis of why breakfast lags other meals, with the data that would confirm it
- A chosen customer segment and breakfast-specific pain points
- Solutions on both the demand side and the supply side (merchants open early, couriers online), prioritized
- A breakfast volume metric with guardrails for margin, delivery time and cannibalization of other meals
- Risks and trade-offs, such as fee discounts versus profitability
### Follow-up Questions
- A breakfast promotion raises morning orders, but many come from customers who moved their lunch order earlier. How would you detect this, and what would you change?
- How would you persuade restaurants that do not open early to serve breakfast on Uber Eats?
- How would you size the breakfast opportunity before committing a team to it?
Overview: An Uber Eats product question on growing the number of breakfast orders placed in the morning. It tests diagnosing why one meal time underperforms, choosing a customer segment, balancing demand-side and supply-side ideas, and defining metrics with guardrails for margin and cannibalization.