Applications of Natural Language Processing in Customer Satisfaction in Telecommunication Industry

Abstract

Natural language processing (NLP) is a branch of artificial intelligence that focuses on teaching computers to understand, interpret, and generate human language. NLP can be used to improve customer satisfaction in a variety of ways in the telecommunication business. This study aims to assess the numerous applications of NLP in the telecommunication business in order to improve customer satisfaction. Chatbots driven by NLP can be used by telecommunications firms to provide speedy and personalized customer care. Chatbots can interpret and reply to consumer enquiries in real time, eliminating the need for customers to wait for a human representative to become available. Sentiment analysis: NLP can be used to evaluate customer feedback and reviews in order to find trends in customer sentiment. This can assist telecommunication firms in better understanding how their customers feel about their products and services, as well as identifying areas for improvement. Predictive maintenance: Some telecommunication businesses use NLP to evaluate machine-generated data from network equipment in order to identify potential issues before they arise. This can assist to increase network resilience and reduce downtime, resulting in a better customer experience. Automated call categorization: NLP can be used to classify and route incoming customer calls depending on the content of the call. This can assist telecommunication firms in properly allocating their resources and ensuring that consumers are connected with the appropriate representative as soon as feasible. The application of NLP in the telecommunications business can assist enhance customer satisfaction by offering faster and more personalized service, identifying and addressing issues before they occur, and optimizing the customer experience.