Building a restaurant‑recommendation feature with Nearby Friends signals

Scenario: Leveraging real‑time location, Meta wants to suggest nearby eateries. Outline data requirements, forecast behavioural change, validate model effectiveness, measure success, and mitigate privacy concerns. ​ Question 1: How would you use Nearby Friends location to build a new feature? (Hint: live coordinates, activity patterns, social graph) Question 2: Why create restaurant recommendations and how might behaviour change? (Hint: offline conversion, social sharing) Question 3: What data sets are required? (Hint: merchant POI, user preference profile, time‑of‑day context) Question 4: How would you validate model effectiveness? (Hint: A/B test, click‑to‑visit rate) Question 5: Which key metrics post‑launch? (Hint: recommendation uptake, purchase conversion) Question 6: What negative impacts could arise? (Hint: privacy concerns, merchant bias, battery drain) Question 7: How does restaurant recommendation differ from ‘People You May Know’? (Hint: real‑time context, content diversity)