Leveraging AI Methodologies for Automated Audit of Sales Agents in Call Centers

Durga Prasad Amballa

Abstract: The call center industry plays a crucial role in customer service and sales, making it essential to maintain high standards of performance among sales agents. Traditional manual audit processes are time-consuming and prone to human error. This article explores the potential of leveraging AI methodologies to automate the audit process of sales agents in call centers. The proposed system includes a comprehensive hygiene audit that identifies 20 key attributes and an open audit module that allows for querying analyzed data. The process involves converting calls to transcripts and utilizing Natural Language Processing (NLP) techniques to analyze sentiment and other aspects of the conversations. The automated audit tool aims to identify top and bottom-performing agents for rewards and retraining purposes. The article discusses the necessity and benefits of automated audits in call centers and provides an overview of the technical implementation.

Keywords: call center audit, quality assurance, agent performance evaluation, customer satisfaction, key performance indicators (KPIs), automated audit, artificial intelligence (AI), natural language processing (NLP), speech analytics, sentiment analysis, conversation analytics, agent training and development, compliance monitoring, operational efficiency, customer experience, quality management, performance metrics, benchmarking, continuous improvement, data-driven insights