Effect of gender and call duration on customer satisfaction in call center big data

Abstract

Customer center call data is typically collected by organizations and corporations in order to improve customer experience through the analysis of such call data. In this paper, we report our findings when analysing more than 26 thousand calls to the call centers of a large corporation in a Latin American country. We focus on the impact of gender and call duration on selfreported customer satisfaction. Speech-based gender detection technology is employed to automatically detect the gender of the customer and the agent involved in the calls. A significant correlation is found between self-reported customer satisfaction at the end of the call and gender homophily between the customer and the call center’s agent. Interestingly, we do not find any significant effect of call duration on satisfaction.