Introduction
The recent increase in average response time for Chegg Tutors from 10 minutes to 25 minutes over the past two weeks is a critical issue that demands immediate attention. This significant degradation in service quality could potentially impact user satisfaction, tutor retention, and overall platform performance. To address this problem, I'll employ a systematic approach to identify, validate, and resolve the root cause while considering both short-term fixes and long-term strategic implications.
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 could directly impact response times. Expected answer: Yes, we updated the matching algorithm two weeks ago. Impact on approach: If confirmed, we'd focus on the algorithm's performance and potential rollback options.
Why it matters: Seasonal fluctuations could explain the change if not accounted for in staffing. Expected answer: User demand has increased by 20% compared to last year, but tutor availability is similar. Impact on approach: We'd need to investigate tutor capacity and recruitment strategies.
Why it matters: Uneven distribution could point to specific problem areas. Expected answer: STEM subjects and newer tutors are experiencing longer response times. Impact on approach: We'd focus on subject-specific issues and onboarding processes for new tutors.
Why it matters: Technical problems could directly impact response times. Expected answer: There was a server outage for 2 hours last week, but no other reported issues. Impact on approach: We'd investigate the impact of the outage and overall system stability.
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