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

1. 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.
2. 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.
3. 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).