Introduction
The unexpected 30% rise in customer support tickets for Juniper Networks's Mist AI platform in the last month is a critical issue that demands immediate attention. This surge could indicate underlying problems affecting user experience, product performance, or both. I'll approach this analysis systematically, focusing on identifying potential root causes, validating hypotheses, and developing both short-term and long-term 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 support ticket increases. Expected answer: Yes, a major update was released. Impact on approach: If yes, we'd focus on the new features and potential bugs.
Why it matters: Helps identify if the issue is widespread or segment-specific. Expected answer: The increase is primarily in enterprise customers. Impact on approach: If segment-specific, we'd tailor our investigation and solutions accordingly.
Why it matters: Changes in issue types can point to specific problem areas. Expected answer: There's been an increase in performance-related tickets. Impact on approach: We'd focus our investigation on system performance and scalability.
Why it matters: External dependencies can impact platform performance. Expected answer: No major changes reported by infrastructure providers. Impact on approach: If no, we'd focus more on internal factors and product-specific issues.
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