Introduction
The sudden increase in customer support tickets related to Robinhood's crypto trading is a critical issue that demands immediate attention. This analysis will systematically identify, validate, and address the root cause while considering both short-term fixes and long-term strategic implications.
I'll approach this problem by first clarifying the context, then ruling out external factors before diving deep into the product ecosystem, user journey, and potential internal causes. We'll generate data-driven hypotheses, conduct root cause analysis, and develop a comprehensive plan for validation and resolution.
Framework overview
This analysis follows a structured approach covering issue identification, hypothesis generation, validation, and solution development.
Step 1
Clarifying Questions (3 minutes)
Why it matters: Recent changes often correlate with spikes in support tickets. Expected answer: Yes, a new cryptocurrency was added or a UI change was implemented. Impact on approach: If yes, we'd focus on that change; if no, we'd look at broader system issues.
Why it matters: Helps identify if the issue is widespread or localized to a specific group. Expected answer: New users are generating more tickets than usual. Impact on approach: If segmented, we'd tailor our solution to that group; if uniform, we'd look at system-wide issues.
Why it matters: Categorization helps pinpoint specific problem areas. Expected answer: Issues related to transaction delays, pricing discrepancies, and account access. Impact on approach: We'd prioritize investigating the systems related to the most common issues.
Why it matters: Ensures we're not dealing with a data anomaly rather than a real increase. Expected answer: No changes to monitoring or categorization systems. Impact on approach: If changed, we'd need to validate the data first; if not, we can trust the reported increase.
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