Track Success and Guardrail Metrics for Push Notifications
Company: Meta
Role: Data Scientist
Category: Analytics & Experimentation
Difficulty: hard
Interview Round: Technical Screen
##### Scenario
Designing and evaluating push notifications for a travel-recommendation mobile app (TripAdvisor-like).
##### Question
What primary success metrics would you track for a new push-notification feature and which guardrail metrics would you include (e.g., uninstalls, unsubscribes)? The app has strong network effects (users share itineraries). How would you design an A/B test for the notification while mitigating interference? Describe the unit of randomization and why.
##### Hints
Think engagement, retention, negative‐impact guardrails, and cluster-based randomization to reduce spillover.
Quick Answer: This question evaluates a data scientist's competency in experimental design, metric selection, and causal inference for networked mobile products, focusing on defining primary success and negative-impact guardrail metrics for a push-notification feature.