A product team is redesigning a **pricing tier page**. Historically the page only offered a **monthly** plan; the redesign adds an **annual** plan option. You are the Data Scientist partner for the launch. ## Questions 1. **Impact sizing:** What are the key ways this change could impact the business (positive and negative), and how would you estimate the expected impact magnitude before running anything? 2. **Metrics:** Propose a metric framework: - Primary success metric(s) - Diagnostic metrics (to understand *why* it moved) - Guardrail metrics (to prevent harm) 3. **Experiment design & ship decision:** Describe how you would design the experiment and make a ship / no-ship decision, including: - Unit of randomization and key segments to monitor - Sample size / power approach (MDE) and duration considerations - How you would analyze results (e.g., confidence intervals) and handle pitfalls (SRM, novelty, repeated exposure) 4. **No experiment possible:** If you cannot run an A/B test (policy, engineering constraints, or all-users launch), how would you measure impact as credibly as possible?