Introduction
The sudden 40% spike in customer service calls related to LendingTree's credit card marketplace is a critical issue that demands immediate attention. This analysis will systematically identify, validate, and address the root cause while considering both short-term and long-term implications for our product and users.
I'll approach this problem by first clarifying key details, ruling out external factors, and then diving deep into our product, user journey, and metrics. From there, I'll form data-driven hypotheses, conduct root cause analysis, and propose validation methods and solutions.
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 sudden metric shifts. Expected answer: Yes, we launched a new UI for card comparisons. Impact on approach: If yes, I'd focus on the new feature's impact on user behavior.
Why it matters: Helps narrow down potential causes and affected users. Expected answer: The spike is more pronounced among first-time users. Impact on approach: If segmented, I'd investigate what's unique about the affected group.
Why it matters: External changes could drive increased user inquiries. Expected answer: No significant changes in partner offerings. Impact on approach: If yes, I'd consider how to better communicate these changes to users.
Why it matters: Identifies specific pain points causing the increase. Expected answer: Confusion about approval odds, difficulty comparing cards, and login issues. Impact on approach: This would directly inform which areas of the product to investigate first.
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