An integrated system for automatic customer satisfaction analysis in the services industry

Abstract

Text classification has matured well as a research discipline over the years. At the same time, business intelligence over databases has long been a source of insights for enterprises. With the growing importance of the services industry, customer relationship management and contact center operations have become very important. Specifically, the voice of the customer and customer satisfaction (C-Sat) have emerged as invaluable sources of insights about how an enterprise's products and services are percieved by customers. In this demonstration, we present the IBM Technology to Automate Customer Satisfaction analysis (ITACS) system that combines text classification technology, and a business intelligence solution along with an interactive document labeling interface for automating C-Sat analysis. This system has been successfully deployed in client accounts in large contact centers and can be extended to any services industry setting for analyzing unstructured text data. This demonstration will highlight the importance of intervention and interactivity in real-world text classification settings. We will point out unique research challenges in this domain regarding label-sets, measuring accuracy, and interpretability of results and we will discuss solutions and open questions.