Success Metrics and Experiment Design for a New Uber Eats Promotions Tab
Company: Uber
Role: Product Manager
Category: Analytics & Experimentation
Difficulty: medium
Interview Round: Other
Uber Eats has added a new promotions tab to its app. As the product manager responsible for it, how would you decide whether it is working?
```hint Incremental, not just used
A busy tab is not necessarily a successful one. Ask what the same customers would have ordered, and what Uber would have spent on discounts, if the tab did not exist.
```
### Clarifying Questions
- What is the tab meant to achieve: more frequent orders from existing customers, winning back lapsed ones, first orders from new customers, or more sales for merchants running their own offers?
- Who funds the discounts shown in the tab: Uber, the merchants or both?
- Has the tab already rolled out to everyone, or can a group of users still be held back from seeing it?
- Does it show only restaurant deals, or also grocery and convenience offers and membership perks?
### What a Strong Answer Covers
- A stated goal for the tab, covering both the eaters and the merchants it serves
- One primary success metric tied to incremental orders or gross bookings rather than tab visits
- A funnel for the tab itself, from opening it to placing an order, to explain why the primary metric moved
- Guardrails for discount cost, cannibalization of full-price orders, discovery elsewhere in the app, delivery reliability and merchant outcomes
- An experiment or holdout that isolates the tab's effect, with a plan for duration, novelty and long-term discount dependence
### Follow-up Questions
- Orders placed through the tab are up, but orders per customer are flat overall. What does that tell you, and what would you do?
- How would you judge whether the tab is a success for merchants?
- How would you detect customers learning to wait for discounts, and what would you change if you saw it?
Overview: A product manager metrics question about a new promotions tab in the Uber Eats app and how to judge whether it is working. It tests goal setting, choosing a primary success metric and guardrails for a three-sided marketplace, and designing an experiment that separates the tab's effect from the promotions themselves.