Customer Support: A Machine Learning Approach to Smarter Task Allocation and Employee Performance Management

Anju L, Preethi Thomas

Abstract: The Support Ticket System is designed to enhance customer service by automating task allocation and evaluating employee performance using machine learning. It addresses the inefficiencies of manual ticket assignment and tracking by implementing the Random Forest Algorithm to assign tasks based on employee experience, workload, and expertise. The system also streamlines complaint management, product sales, and employee assessments. Key performance indicators such as resolution rate, experience, and satisfaction scores are used to train the model, ensuring accurate task distribution. The model?s evaluation provides an Employee Performance Score (EPS) to assess productivity and optimize workload distribution. Results demonstrate that the system significantly improves task assignment efficiency, reduces manual intervention, and enhances customer satisfaction through faster issue resolution. By integrating machine learning, this project contributes to better workflow automation, optimized resource allocation, and an improved support experience, making it a valuable solution for modern customer service management.

Keywords: Support ticket automation, Employee performance evaluation, Machine learning integration, Random forest task allocation