Design an In-App Restaurant Table Booking Product for Meta's Apps
Company: Meta
Role: Product Manager
Category: Product Design & Strategy
Difficulty: medium
Interview Round: Other
You are a product manager at Meta. Design a product that lets people reserve a table at a restaurant.
```hint Start from Meta's edge
Ask what Meta's apps can offer a diner or a restaurant that a standalone booking app cannot, then pick the users and the moment in their journey where that advantage matters most.
```
### Clarifying Questions
- Should the product live inside the existing apps (Facebook, Instagram, WhatsApp, Messenger), or can it be a new standalone app?
- Is Meta expected to hold restaurants' table inventory itself, or can it connect to the reservation systems restaurants already use?
- Are both sides in scope, diners booking and restaurants managing bookings, or only the diner experience?
- Is there a launch market in mind, or should I choose one and justify it?
### What a Strong Answer Covers
- A goal for Meta grounded in its mission and business, with the reasoning for why Meta should build this at all
- A chosen diner segment and restaurant segment, with concrete pain points across discovering, booking and showing up
- Prioritized solutions with a clear first version, including how table availability is sourced
- A north-star metric with supporting and guardrail metrics, and how the launch would be tested
- Risks such as cold-start supply, partner dependency, no-shows and privacy, with mitigations
### Follow-up Questions
- Most restaurants already run a booking system. How would you get live availability without asking them to maintain a second calendar?
- How would you tell whether reservations made through Meta are new demand or simply moved from other channels?
- Restaurants report more no-shows from Meta bookings than from their other channels. What would you change?
Overview: A product design prompt asking a Meta product manager to design a way for people to book restaurant tables. It tests choosing diner and restaurant segments, using Meta's discovery and messaging strengths, sourcing table availability, prioritizing a first version, and defining success and guardrail metrics.