How would you design restaurant finder app within Facebook.

In this question, the interviewer wants to understand three main things: your product design approach, your innovation, and how well you understand Facebook's platform. The 'restaurant finder app' is a hypothetical product you're being asked to design within the Facebook platform. To answer this question effectively:

1. Understand the problem: How would you identify available restaurants nearby to the Facebook community?
2. Offer a solution: Imagine how you might design a solution within the Facebook environment to solve the problem.
3. Maintain a practical approach: Consider Facebook's huge user base and how your solution would scale.
4. Demonstration: Show how user experience design, technical capabilities, data analysis, and market perception work together.

To design a restaurant finder app within Facebook, we would first need to identify our user's need. Suppose our main user base comprises individuals who enjoy trying out different restaurants and sharing their experiences.

Our feature, let's call it "DineFinder," can be a search tool with filters such as location, cuisine type, price range, etc. It incorporates Facebook's existing map services to direct users to the selected restaurant. Facebook's reactions and comments feature could also be used to display user ratings and reviews about restaurants.

Integrating DineFinder with Facebook's existing features like Events could allow restaurants to promote special events or deals to attract more customers. Leveraging the Photo and Video sharing capabilities with a specialized 'Foodie Camera' filter might enhance this feature's social and sharing aspects, encouraging more users to use and share it.

To ensure scalability, we need to have a robust data management system that can handle the huge influx of user data and preferences. We also need to monitor the use of and feedback given to this feature for continued improvement.

For the design of a restaurant finder, we have to understand fundamental Facebook users' needs and behaviors. We can call our new feature "CulinaRadar."

CulinaRadar could be a separate tab within the Facebook app, providing users with restaurant recommendations based on their, and their friends', likes and check-ins. Geo-targeting feature, which uses location-based service in mobile devices, can also be implemented to suggest restaurants in the user's vicinity.

Integrating CulinaRadar with Facebook Messenger might allow users to plan dining outings with friends directly from Messenger. Adding a group voting system to choose a restaurant could be an engaging social aspect.

To provide a personalized experience for users, we could implement machine learning algorithms that understand the user's dining preferences over time and suggest restaurants accordingly.

For the technical approach, considering Facebook's user scale, it's crucial to design an efficient back-end system capable of managing and processing large volumes of data. Entire solution should be designed keeping scalability and maintainability in mind, so as the user base grows, the application continues to perform optimally.

Lastly, it's crucial to continue testing the product and collecting user feedback for constant improvement and updates to ensure user satisfaction.