A Data-Driven Approach to Understanding Customer Satisfaction

Abstract

The study of customer satisfaction has become a pivotal aspect of business for companies nowadays, particularly in the realm of new product development. As businesses strive to innovate and introduce new products to market, understanding and anticipating customer satisfaction has gained heightened significance. To achieve this, companies must be able to harness customer data and employ effective data analytics. With this in mind, this study proposes a machine learning-based approach to identify drivers of satisfaction and predict the effect of successful improvement of specific features of a product on customer satisfaction. A case study is conducted to better illustrate the proposed procedure.