This is basically two questions stitched together and I didn't realize it until I was halfway through.
Start by clarifying the product goal and user problem, then propose a hypothesis and define success metrics across the user journey. Outline an A/B test design with guardrail metrics, and discuss how to evaluate long-term impact and iterate.
Pro tip: Emphasize that success isn't just about click-through rates; it's about driving meaningful engagement without harming user experience or other key metrics. Show you understand trade-offs and long-term effects.
Ask clarifying questions to understand the feature's purpose, target users, and expected impact. Formulate a clear hypothesis about how the feature will improve user experience or business metrics.
Identify primary metrics (e.g., click-through rate, conversion rate) and secondary metrics (e.g., engagement, retention). Also define guardrail metrics to monitor potential negative effects (e.g., notification fatigue, unsubscribe rates).
Propose an A/B test with a control and treatment group, ensuring proper randomization and sample size. Consider segmentation and potential confounding factors.
After running the test, analyze the impact on primary, secondary, and guardrail metrics. Use statistical significance and practical significance to decide whether to launch, iterate, or abandon the feature.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.