Quarterly Technical Support Service Level Review

Track and analyze technical support team performance across key service level metrics, customer satisfaction, and operational efficiency measures to ensure high-quality support delivery and identify areas for improvement in the communications and networking division.

Report Objective

Monitor technical support KPIs including resolution times, satisfaction scores, and ticket volume trends to maintain service excellence, identify training needs, and optimize resource allocation in our communications and networking support operations.

Ticket Resolution Performance

Line chart showing resolution times and compliance with SLA targets

Questions to Consider:

2025-01-012025-02-012025-03-01date5.56.06.57.07.58.0avg_resolution_time_hoursavg_resolution_time_hoursHow are Average Resolution Times Trending?Resolution times show quarterly variation with recent improvement trend
  • What is driving changes in resolution time?

  • Are there specific days or periods with consistently higher times?

  • How do these times compare to our target SLAs?

  • Which periods show the strongest/weakest SLA compliance?

  • What factors contribute to SLA misses?

  • How does compliance vary by ticket priority?

2025-01-012025-02-012025-03-01date91.0%92.0%93.0%sla_compliance_ratesla_compliance_rateSLA Compliance Rate TrendsSLA compliance maintains strong performance above 90% target

Customer Satisfaction and Support Quality

Bar charts comparing CSAT scores and first-contact resolution rates

Questions to Consider:

VoiceEmailChatPortalsupport_channel0.020.040.060.080.0100.0sum(csat_score)sum(csat_score)Customer Satisfaction by Support ChannelVoice support leads satisfaction scores across channels
  • Which channels are performing best/worst for customer satisfaction?

  • What drives satisfaction differences between channels?

  • How can we improve lower-performing channels?

  • Which channels excel at first contact resolution?

  • What prevents first contact resolution in lower-performing channels?

  • How does FCR correlate with satisfaction scores?

VoiceEmailChatPortalsupport_channel0.0%500.0%1000.0%1500.0%sum(first_contact_resolution_rate)sum(first_contact_resolution_rate)First Contact Resolution Rate by ChannelFirst contact resolution varies significantly by support channel

Support Volume and Resource Utilization

Line and bar charts showing ticket volumes and agent productivity metrics

Questions to Consider:

2025-01-012025-02-012025-03-01date230240250260270280total_ticketstotal_ticketsDaily Ticket Volume TrendsTicket volumes show consistent weekly patterns with occasional spikes
  • What drives peaks in ticket volume?

  • Are there predictable patterns in volume?

  • How does staffing align with volume patterns?

  • What factors influence agent productivity?

  • Is higher productivity impacting resolution quality?

  • How does productivity vary across teams?

2025-01-012025-02-012025-03-01date16.017.018.019.0tickets_per_agenttickets_per_agentAgent Productivity TrendsAverage tickets per agent showing steady improvement