Post-Launch Evaluation: Crypto Trading Feature
Context
You are a Data Scientist evaluating the post-launch performance of a crypto-trading feature integrated into an existing payments app. The goal is to grow sustainable trading usage and revenue while maintaining trust, compliance, and reliability.
Tasks
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Define the key success metrics to track after launch. Include acquisition/activation, engagement, monetization, risk/compliance, reliability, and customer satisfaction, plus a clear north-star metric and guardrails.
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Transaction volume drops after release. Outline a structured root-cause diagnosis plan: what to look at, how to segment, which analyses to run, and how to isolate causality vs. correlation.
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Propose two concrete, data-driven product improvements for the crypto feature. For each, state the hypothesis, the change, success metrics, and how you would test it (e.g., A/B or staged rollout).