Abstract
In today's highly competitive business environment, companies are increasingly focusing on enhancing customer satisfaction to improve customer loyalty and drive business growth. In this context, the use of data-driven approaches can provide valuable insights for companies to improve their service quality and customer experience. This paper presents a case study in service operations management, where a data-driven approach is used to enhance customer satisfaction. We employ a dataset of customer feedback from a service company and proposes a deep learning (DL) algorithm learn to identify the factors that affect customer satisfaction. The results show that the proposed data-driven approach is effective in identifying the key drivers of customer satisfaction and in providing actionable insights for service improvement. We highlight the potential of our DL approach for enhancing customer satisfaction and provides insights for service companies to improve their customer experience based on the analysis of customer feedback.
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