Improving customer routing in contact centers: An automated triage design based on text analytics
提出一种基于文本分析和机器学习的自动分诊设计，用于智能路由客户至合适客服，通过真实数据实验证明其在服务水平、时间和成本上优于人工分诊和客户自选分诊。
Abstract We propose an automated triage design for intelligent customer routing in live‐chat contact centers and demonstrate its implementation using a real‐world data set from an S&P 500 firm. The proposed design emerges as a synthesis of text analytics and predictive machine learning methods. Using numerical experiments based on the simulation of the firm's contact center, we demonstrate the service level, time, and labor cost benefits of the automated design over two other triage designs (i.e., customer choice triage and human expert triage) that are commonly employed in the real world. Through additional analyses, we explore the generalizability of the automated design for creating solutions for different types of communication channels. Our work has implications for managing customer relations under emerging communication technologies (e.g., live‐chat, e‐mail, and social media) and more broadly for demonstrating the use of text analytics and machine learning to improve Operations Management practice.