Quarterly Technical Support Service Level Review - Household Electronics
Track and analyze key service level metrics for household electronics technical support operations, focusing on customer satisfaction, resolution times, and support team performance to ensure high-quality customer service delivery and identify areas for operational improvement.
Report Objective
Monitor and evaluate quarterly technical support performance for household electronics, analyzing customer satisfaction metrics, response times, and support efficiency to maintain service quality standards and drive continuous improvement.
Response Time and Resolution Efficiency
Line chart showing average response and resolution times
Questions to Consider:
How do current response times compare to SLA targets?
Which product categories have the longest resolution times?
What is the first-contact resolution rate trend?
Are there specific times or days with notably different performance?
Are there any consistent patterns in response time variations?
How do resolution times correlate with ticket complexity?
What factors contribute to longer resolution times?
What drives variations in first contact resolution rates?
Which types of issues are most likely to be resolved on first contact?
How does FCR impact overall customer satisfaction?
Customer Satisfaction and Issue Categories
Bar charts displaying CSAT scores and issue distribution
Questions to Consider:
What are the most common technical issues reported?
How does satisfaction vary by product category?
Which issues have the lowest satisfaction scores?
What is the correlation between resolution time and satisfaction?
Which issues are showing increasing or decreasing trends?
Are there seasonal patterns in certain issue types?
How does issue volume correlate with product launches or updates?
Which issues consistently receive lower satisfaction scores?
How does issue complexity affect satisfaction ratings?
What best practices from high-scoring categories can be applied to others?
Support Team Performance
Table showing key agent performance metrics
Questions to Consider:
How does agent productivity compare across teams?
What is the average handle time by issue type?
Are there specific agents excelling at particular issue types?
What is the escalation rate and pattern?
agent_name
tickets_resolved
avg_handle_time_minutes
customer_satisfaction
John Davis
151
37.1
4.1
Sarah Wilson
245
24.1
4.8
Mike Thompson
109
27.3
4.6
Lisa Garcia
192
23.8
4.7
John Davis
242
42.7
4.7
Sarah Wilson
240
26.3
3.8
Mike Thompson
147
16.0
4.7
Lisa Garcia
166
15.3
4.0
John Davis
258
30.0
3.9
Sarah Wilson
234
20.2
3.9
How does experience level correlate with performance metrics?
What characteristics define top-performing agents?
Are there specific training needs indicated by the data?
Areas for Additional Focus
Analyze patterns in escalated tickets to identify training opportunities
Review knowledge base effectiveness for most common issues
Evaluate self-service portal usage and success rates
Assess impact of recent technical support tool implementations
Review staffing levels against peak support times
Investigate correlation between product categories and support needs
Analyze customer feedback themes for product improvement opportunities
Evaluate effectiveness of remote troubleshooting procedures