Evaluate Widget Impact on User Engagement with A/B Testing

##### Scenario Company is preparing to roll out a new in-app recommendation widget and needs evidence that it improves user engagement. ##### Question Design an A/B experiment to evaluate the widget’s impact on daily active users and session length. Which primary and guardrail metrics would you track and why? How would you determine required sample size and runtime? What potential biases or implementation pitfalls must be addressed? ##### Hints Think about unit of randomization, metric sensitivity, power calculation, and avoiding novelty or logging bias.