Retail BTC volatility is high, but retail trading volume on Coinbase has decreased. Explain how you would investigate the issue with data and turn the analysis into an actionable recommendation. Your answer should separate measurement validation, hypothesis generation, segmentation, analysis methods, and recommended actions. ### Constraints & Assumptions - Treat this as a product or risk analytics business case. - Do not assume the drop is real until you validate metric definitions and data quality. - Consider market demand, user mix, product friction, pricing/execution, reliability, risk controls, compliance friction, and measurement artifacts. - The goal is to identify the most likely drivers and recommend practical next steps, not to list every possible metric. ### Clarifying Questions to Ask - How is retail trading volume defined: USD notional, number of trades, or asset units? - What time window and comparison baseline are we using? - Does the drop affect all assets or only BTC? - Did any product, pricing, risk, compliance, marketing, or instrumentation changes occur recently? - Are we looking at placed orders, executed trades, or settled volume? ### What a Strong Answer Covers - Metric validation using source-of-truth tables and stable definitions. - A decomposition of volume into active traders, trades per active trader, and average trade size. - Segments such as new versus existing users, geography, platform, app version, acquisition channel, product surface, and risk status. - Analyses that distinguish demand decline from product friction, risk controls, and data artifacts. - Concrete recommendations tied to the evidence found. ### Follow-up Questions - What would you do if sessions are stable but executed trades fall? - How would you test whether a risk-policy change caused the drop? - What metrics would indicate a reliability-driven issue during volatility spikes? - How would your recommendation differ if the decline is isolated to new users?