Advanced Customer Query Analysis Using Machine Learning

Predicting customer turnover is important for firms in all industries since keeping current customers is less expensive than finding new ones. The goal of this research study is to offer insights into the most recent strategies and approaches by providing a thorough review of customer churn prediction tools. The first section of the essay defines customer churn and discusses its importance to business operations. Then, it examines different data sources and attributes that are frequently utilized for churn prediction. It then explores various machine learning algorithms and methods used for churn prediction, highlighting their advantages and disadvantages. The paper also provides validation methods and evaluation metrics for churn prediction model performance evaluation. It concludes by presenting a case study that illustrates the use of churn prediction in a practical situation.