LEVERAGING PREDICTIVE ANALYTICS AND MATLAB APPROACH TO ENHANCE CUSTOMER RETENTION THROUGH EMPLOYEE-CUSTOMER INTERACTION METRICS IN IT COMPANIES

Abstract

In the competitive landscape of the IT industry, maintaining high levels of customer satisfaction and retention is critical for long-term success. The role of employee engagement and service quality in achieving these goals has been widely acknowledged, but the use of advanced analytical tools to predict customer behavior remains underexplored. This study seeks to address this gap by employing a MATLAB-based predictive model to analyze customer responses regarding IT service interactions. By leveraging employee-customer interaction data and customer feedback, the research aims to identify the key factors influencing customer retention and to predict potential churn scenarios. The fuzzy logic approach, which accounts for the inherent uncertainty and subjectivity in customer experiences, provides a more nuanced understanding of customer satisfaction. This model will allow IT companies to take proactive steps in optimizing service quality and engagement strategies, thus fostering higher customer loyalty. The research findings will offer valuable insights for IT companies to develop targeted interventions that enhance customer retention and strengthen their.