Track and analyze key support quality metrics, customer satisfaction, and technical support team performance to ensure optimal service delivery and identify areas for improvement in hardware support operations.
Report Objective
Monitor and evaluate the effectiveness of technical support operations for computer hardware, focusing on response times, resolution rates, customer satisfaction, and support team efficiency to maintain service quality standards and drive continuous improvement.
Support Response and Resolution Metrics
Time series analysis of key support metrics
Questions to Consider:
How are average response and resolution times trending quarter over quarter?
What percentage of issues are resolved on first contact?
Are there specific hardware categories showing longer resolution times?
How does current performance compare to SLA targets?
Is the trend in response times sustainable while maintaining quality?
How do these metrics compare to industry standards?
What factors are driving improvements in response time?
Which categories should be prioritized for proactive support?
Are there seasonal patterns in issue categories?
How does issue distribution align with product lifecycle stages?
Customer Satisfaction and Issue Categories
Distribution of customer feedback and common issues
Questions to Consider:
What is the overall CSAT trend for hardware support?
Which hardware components generate the most support tickets?
How does satisfaction vary by issue complexity?
Are there recurring issues that need product improvements?
Which issues have the highest impact on customer satisfaction?
Are there specific categories requiring additional agent training?
How do satisfaction scores correlate with resolution time?
What characterizes the most efficient agents?
Is there a trade-off between speed and quality?
How can we improve consistency across the team?
Support Team Performance Analysis
Team efficiency and productivity metrics
Questions to Consider:
How does individual agent performance compare to team averages?
What is the distribution of ticket complexity across the team?
Are there knowledge gaps in specific hardware areas?