Online Shopping Service Optimization Based on Topic Mining and Process Chain Network

ABSTRACT With the wide spread of Internet and e‐commerce, the online shopping market has attracted more and more customers. Under this background, the service quality of online shopping platforms has become more and more important. A high level of service quality leads to higher customer loyalty and increases sale profits. In this paper, we focus on the service quality management of online shopping platforms. Firstly, we analyze the service problems of online shopping platforms by topic mining, according to the customer complaint text. Secondly, we analyze the general purchase processes of online shopping platforms by using process chain network (PCN), a tool for service analysis. Finally, we optimize the purchase processes of online shopping platforms based on the discovered service problems and PCN. Our paper contributes to the area of service management by presenting a data‐driven methodology for service quality management of online shopping platforms. Furthermore, our methodology can be generalized for the service quality management of various domains.