Sentiment Analysis-Based Chatbot System to Enhance Customer Satisfaction in Technical Support Complaints Service for Telecommunications Companies

• Autores: Juipa, Anghelo, Guzman, Luis, Diaz, Edgar
• Formato: artículo
• Fecha de Publicación: 2024
• Institución: Universidad Peruana de Ciencias Aplicadas
• Repositorio: UPC-Institucional
• Lenguaje: inglés
• OAI Identifier: oai:repositorioacademico.upc.edu.pe:10757/676074
• Enlace del recurso: http://hdl.handle.net/10757/676074
• Nivel de acceso: acceso embargado
• Materia: Chatbot; Customer Service; Emotions; GPT 3.5; Natural Language Processing; Satisfaction; Sentiment Analysis; Technical Support Complaints

In the competitive world of telecommunications, a good customer technical support complaint service can make a difference. However, this business process still presents deficiencies in its quality. In the capital of Peru, there were 102, 665 internet complaints and 38, 621 cable television complaints. 9.27% and 9.97% of these, respectively, weren't resolved. In this sense, this research proposes the implementation of a chatbot, which incorporates GPT 3.5 as a sentiment analysis component, to reduce user dissatisfaction in this service process. To validate the proposal, experiments were conducted with 50 internet and cable television service owners to evaluate satisfaction and accuracy in recognizing their emotions. The results indicated that 86% of the respondents were satisfied with the chatbot service, and the satisfaction index reached 77.9, surpassing the minimum threshold of 75 points for providing quality customer service established by the industry. The methodology behind these results is detailed in the following research.