2023 Technical Support Analysis

Project Overview:

This project involves a comprehensive analysis of our technical support ticket system using data-driven insights to identify areas of improvement. By leveraging a three-page Power BI dashboard, we aim to optimize ticket handling processes, enhance customer satisfaction, and improve overall operational efficiency. The dataset encompasses critical information such as ticket creation date and time, processing time, source, assigned agent, ticket topic / product, and customer satisfaction rate.

Key Observations:

1. Ticket Creation Patterns:

   • Peak Ticket Creation Time: The highest volume of tickets is created at 15:00, indicating a potential need for increased staffing or resource allocation during this period.
   • Off-Peak Time: The lowest volume of tickets is created at 14:00, suggesting a window for potential staff breaks or training sessions.

2. Weekly Ticket Distribution:

   • Weekday Dominance: 76.4% of tickets are generated on weekdays, highlighting the importance of maintaining robust weekday support.

3. Service Level Agreement (SLA) Compliance:

   • Response Time Compliance: 13.3% of tickets receive the first response later than the SLA requirement, pointing to a need for process improvements.
   • Resolution Time Compliance: 33.6% of tickets are resolved later than the SLA requirement, indicating significant room for enhancing resolution efficiency.

4. Resolution Time Analysis:

   • Average Resolution Time: It takes an average of 33.2 hours to resolve a ticket.
   • Channel-Specific Resolution: Tickets from chat are resolved the fastest, while phone tickets take the longest to resolve, suggesting a need for process optimization in phone support.

5. Ticket Topic Distribution:

   • Product Setup Inquiries: 27% of tickets are related to product setup. Improving manuals and FAQs could reduce the volume of such tickets, leading to increased efficiency and customer satisfaction.

6. Source and Satisfaction Rates:

   • Email Dominance: 53% of tickets originate from emails.
   • Satisfaction Rates: Email and chat tickets have an average satisfaction rate of 3.5, while phone tickets average at 3.4, indicating a marginally lower satisfaction rate for phone support.