Bibliographic citations
Lopez, J., De, J. (2023). Software de clasificación de llamadas para automatizar procesos en el área de calidad de un contact center [Trabajo de Suficiencia Profesional, Universidad Peruana de Ciencias Aplicadas (UPC)]. http://hdl.handle.net/10757/670210
Lopez, J., De, J. Software de clasificación de llamadas para automatizar procesos en el área de calidad de un contact center [Trabajo de Suficiencia Profesional]. PE: Universidad Peruana de Ciencias Aplicadas (UPC); 2023. http://hdl.handle.net/10757/670210
@misc{renati/409563,
title = "Software de clasificación de llamadas para automatizar procesos en el área de calidad de un contact center",
author = "De Los Santos Almazan, Jose James",
publisher = "Universidad Peruana de Ciencias Aplicadas (UPC)",
year = "2023"
}
Currently, in contact centers, call management is vital for achieving operational efficiency and ensuring customer satisfaction. Contact centers serve as pivotal points where companies provide customer support, sales, and service. The quality of these interactions is crucial for maintaining a company's reputation and retaining customers in a highly competitive market. The constant growth in the volume of calls has created an urgent need for effective methods to manage and monitor these interactions to ensure they meet quality and productivity standards. Consequently, the quality assurance department in contact centers has faced a considerable workload to cope with the call volume. As a result, contact centers have encountered problems due to the lack of efficient tools to manage and evaluate this large volume of calls. Manual quality assessment is costly and error-prone, limiting the identification of areas for improvement. The absence of an automated call classification system hinders the timely identification of service quality issues, ultimately affecting customer satisfaction and operational efficiency. This work focuses on call classification software, a critical tool that utilizes machine learning to automate call categorization and enhance service quality. The implementation of call classification software presents a promising solution. This technology automates call evaluation, improves service quality, and empowers organizations to take proactive measures based on concrete data.
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