Improving customer experience via text mining

Abstract

Improving customer experience on company web sites is an important aspect of maintaining a competitive edge in the technology industry. To better understand customer behavior, e-commerce sites provide online surveys for individual web site visitors to record their feedback with site performance. This paper describes some areas where text mining appears to have useful applications. For comments from web site visitors, we implemented automated analysis to discover emerging problems on the web site using clustering methods and furthermore devised procedures to assign comments to pre-defined categories using statistical classification. Statistical clustering was based on a Gaussian mixture model and hierarchical clustering to uncover new issues related to customer care-abouts. Statistical classification of comments was studied extensively by applying a variety of popular algorithms. We benchmarked their performance and make some recommendations based on our evaluations. © Springer-Verlag Berlin Heidelberg 2005.