Improving customer complaint management by automatic email classification using linguistic style features as predictors
作者:
摘要
Customer complaint management is becoming a critical key success factor in today's business environment. This study introduces a methodology to improve complaint-handling strategies through an automatic email-classification system that distinguishes complaints from non-complaints. As such, complaint handling becomes less time-consuming and more successful. The classification system combines traditional text information with new information about the linguistic style of an email. The empirical results show that adding linguistic style information into a classification model with conventional text-classification variables results in a significant increase in predictive performance. In addition, this study reveals linguistic style differences between complaint emails and others.
论文关键词:Customer Complaint Handling,Call-center email,Voice of customers (VOC),Singular Value Decomposition (SVD),Latent Semantic Indexing (LSI),Automatic email classification
论文评审过程:Received 12 January 2007, Revised 19 September 2007, Accepted 14 October 2007, Available online 24 October 2007.
论文官网地址:https://doi.org/10.1016/j.dss.2007.10.010