Introduction
The sudden 30% increase in average handle time for Talkdesk's live chat support feature last week is a critical issue that demands immediate attention. This significant spike could impact customer satisfaction, agent productivity, and overall operational efficiency. I'll approach this problem systematically, focusing on identifying the root cause, 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 performance shifts. Expected answer: Yes, a new UI was rolled out. Impact on approach: If confirmed, I'd focus on UI-related hypotheses.
Why it matters: Segmentation could reveal targeted issues. Expected answer: Enterprise customers show a higher increase. Impact on approach: I'd prioritize investigating enterprise-specific factors.
Why it matters: Ensures we're addressing a real issue, not a measurement anomaly. Expected answer: No changes in measurement. Impact on approach: If confirmed, I'd focus on actual performance issues rather than data discrepancies.
Why it matters: External shifts can drive internal metric changes. Expected answer: Some increase in product-related queries. Impact on approach: I'd investigate if there's a correlation with recent product changes or market events.
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