Text classification, business intelligence, and interactivity: Automating C-Sat analysis for services industry

Abstract

Text classification has matured as a research discipline over the last decade. Independently, business intelligence over structured databases has long been a source of insights for enterprises. In this work, we bring the two together for Customer Satisfaction(C-Sat) analysis in the services industry. We present ITACS, a solution combining text classification and business intelligence integrated with a novel interactive text labeling interface. ITACS has been deployed in multiple client accounts in contact centers. It can be extended to any services industry setting to analyze unstructured text data and derive operational and business insights. We highlight importance of interactivity in real-life text classification settings. We bring out some unique research challenges about label-sets, measuring accuracy, and interpretability that need serious attention in both academic and industrial research. We recount invaluable experiences and lessons learned as data mining researchers working toward seeing research technology deployed in the services industry. Copyright 2008 ACM.