Track and analyze key technical support performance metrics including case volume, resolution times, customer satisfaction, and first contact resolution rates to ensure effective support delivery and identify areas for improvement.
Report Objective
Monitor and evaluate technical support team performance for phones and handheld devices on a weekly basis, focusing on case volumes, resolution efficiency, customer satisfaction, and support quality metrics to maintain service excellence and identify operational improvements.
Case Volume and Resolution Times
Analyze weekly support case volumes and average resolution times
Questions to Consider:
How has the case volume trended over the past weeks?
Are there specific issue categories driving higher volumes?
How do resolution times vary by issue type?
Are we meeting our target resolution time SLAs?
What is the week-over-week change in case volume?
Are there any seasonal patterns in support volume?
How does current volume compare to our support capacity?
Which categories consistently require more resolution time?
How do resolution times compare to our SLA targets?
Are there opportunities to optimize resolution processes?
Customer Satisfaction and First Contact Resolution
Track customer satisfaction scores and first contact resolution rates
Questions to Consider:
How are satisfaction scores trending week over week?
What is the correlation between FCR rates and satisfaction?
Which issue types have the highest escalation rates?
Are there patterns in customer feedback that suggest areas for improvement?
What is the week-over-week trend in satisfaction scores?
Are there correlations with other support metrics?
How do scores compare to our target benchmarks?
How has FCR rate changed over recent weeks?
What is the relationship between FCR and escalation rates?
Are we meeting our FCR targets?
Support Categories Analysis
Review distribution of cases across different issue categories
Questions to Consider:
Which issue categories are most common?
How do resolution times vary by category?
Are there recurring issues that could be addressed through knowledge base updates?
What training opportunities can be identified from case patterns?
Which categories generate the highest volume of cases?
How has the distribution changed over time?
Are there opportunities for proactive support in high-volume categories?
Areas for Additional Focus
Analyze trends in specific device models or OS versions generating higher support volumes
Review knowledge base article effectiveness and identify gaps
Evaluate tech support team capacity and scheduling based on volume patterns
Assess impact of recent product updates on support metrics
Investigate opportunities for proactive support measures
Review escalation patterns and root causes
Evaluate self-service tool effectiveness
Analyze correlation between support metrics and recent product launches