Solution for prediction of customer behavior in call center systems

Traditional methods for gauging customer satisfaction in call centers, such as surveys, are often time-consuming and susceptible to bias. This paper proposes a software solution that uses speech analytics to predict real-time customer behavior during call interactions. By analyzing speech patterns, vocabulary choices, and intonation, the system identifies customer emotions and potential issues, empowering agents to proactively address concerns, tailor their communication for improved customer satisfaction, and prepare their voice and emotional state before answering the call.