Customer support Ticket Analysis 

Domain 

Customer support is a core business function focused on resolving customer issues, handling service requests, and ensuring a positive overall experience with a product or service. It involves managing customer interactions across multiple channels such as email, chat, calls, and support portals, while addressing a wide range of concerns including technical issues, billing queries, and service feedback. As organizations grow and customer expectations rise, the volume and complexity of support tickets increase, making it essential to maintain efficient workflows, timely responses, and consistent service quality to retain customers, build trust, and protect brand reputation. 

 

The Challenges  

• Limited understanding of ticket trends and customer pain points, Difficulty in identifying peak ticket days, recurring issues, channel-wise volume, and negative customer feedback, which limits proactive improvements to support processes and customer experience. 
• Uneven agent workload and priority handling, Lack of clear visibility into ticket pressure by priority and by support agent, leading to imbalanced workloads and delayed resolution of critical issues. 
• Lack of visibility into ticket status and overall workload, Challenges in tracking open, closed, and pending customer response tickets in real time, resulting in reactive support management. 
• Unclear SLA adherence and response-time performance, Difficulty in monitoring first response time, resolution time, and SLA compliance, making it harder to detect delays and service inefficiencies. 

Objective 

The objective of this report is to provide a centralized and data-driven view of customer support operations by tracking ticket volume, status, priority, and resolution performance. It aims to identify ticket trends, recurring issues, and agent workload distribution while monitoring response times and SLA adherence. By delivering clear and actionable insights, the report supports timely decision-making, improves support efficiency, and enhances overall customer experience. 

The Solution 

We developed an interactive Power BI report that transforms raw customer support ticket data into meaningful, actionable insights. The report is designed to provide both high-level visibility and detailed, agent-level analysis through intuitive visuals and drill-through capabilities. 

Overview 
The Overview page delivers a consolidated snapshot of overall support performance. It highlights key metrics such as total tickets, open and closed tickets, average response and resolution times, and SLA compliance. The page also provides breakdowns by ticket status, channel, issue type, priority, and time of day, enabling stakeholders to quickly identify workload distribution, operational bottlenecks, and areas impacting customer satisfaction. 

Calendar View 
The Calendar View offers a day-by-day visualization of ticket volumes across weeks and months. Using color intensity, it compares daily ticket counts with the previous day, making it easy to identify spikes, drops, and recurring peak patterns. This view helps teams understand demand fluctuations over time, plan staffing effectively, and anticipate high-pressure support periods. 

Detailed View 
The Details View allows users to drill through from summary visuals to analyze tickets for a specific support agent. It provides detailed ticket-level information, including priority, issue type, raised time, first response time, and resolution time. This page enables deeper evaluation of individual performance, workload distribution, and SLA adherence, supporting fair performance assessment and targeted improvement actions. 

The Extra Mile 

• Implemented table pagination to improve readability and usability when analyzing employee performance, ensuring a clear and focused view even with large volumes of ticket data. 
• Designed a dedicated drill-through experience that activates on employee selection, allowing users to seamlessly navigate from summary insights to detailed, agent-specific ticket analysis. 
• Built a custom calendar view using a matrix visual to enable day-by-day ticket comparison, making it easy to identify workload patterns, spikes, and operational trends at a granular level.