Abstract
Providing excellent customer service is always important for an organisation, and one of the biggest demands from customers is the speed of resolution. Customers anticipate a prompt, simple, and efficient response when they submit a service ticket to request service. While the customer service representatives attempt to resolve problems assigned to them while simultaneously giving clients a nice experience and upholding the company's excellent reputation, they receive several tickets each day. On-time services may boost customer satisfaction, foster client loyalty, and grow the number of prospective loyal consumers. The best option for speeding up ticket resolution in this case will be a prediction model that makes use of Machine Learning techniques. Experimental evaluations revealed that eXtreme Gradient Boosting works better than other strategies by achieving a low Root Mean Squared Error (RMSE), Mean Squared Error (MSE), and MAE (Mean Absolute Error) scores with good model accuracy.