You are the product data scientist supporting Pinterest. Two analytics prompts were described: 1. **Carousel feature at the top of the home feed.** Pinterest wants to add a horizontally scrollable carousel at the top of the app, similar to Stories. The module could either resurface Pins the user previously saved or show new recommended Pins. How would you: - clarify the product goal, - define primary success metrics and guardrail metrics, - design an online experiment, - and decide whether the feature should launch? Suppose the carousel is launched in an experiment and the **overall home-page CTR decreases**. Explain how you would determine whether this is a true product regression versus a denominator effect, cannibalization of the existing vertical feed, ranking-quality issues, novelty effects, segmentation effects, or logging problems. 2. **Billboard experiment.** Pinterest also runs an offline billboard campaign in a subset of cities or DMAs. How would you estimate the causal lift of the campaign on app activity? Discuss the choice of experimental or quasi-experimental design, unit of randomization, key metrics, power considerations, and how you would handle spillovers, seasonality, and overlapping national marketing campaigns.