Text to Intelligence: Building and Deploying a Text Mining Solution in the Services Industry for Customer Satisfaction Analysis

Authors:
Shantanu Godbole;Shourya Roy
Affiliations:
-;-
Venue:
SCC '08 Proceedings of the 2008 IEEE International Conference on Services Computing - Volume 2
Year:
2008

Citing 0
Cited 3

An Enhanced Swarm Intelligence Clustering-Based RBF Neural Network Web Text Classifier

ISNN 2009 Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II
Customer-focused service management for contact centers

IBM Journal of Research and Development
Knowledge discovery in inspection reports of marine structures

Expert Systems with Applications: An International Journal

Quantified Score

Hi-index	0.00

Visualization

Abstract

We present our experiences in building and deploying a text mining solution in services industry settings, specifically in contact centers. We describe the Voice of Customer (VoC) and Customer Satisfaction (C-Sat) analysis settings and outline several unique research challenges brought about by this confluence of text mining and industrial services research. We describe our system for integrated \tc{}, business intelligence and interactive text labeling for C-Sat analysis. We recount invaluable lessons learned as computer science researchers in services research engagements. The system has been deployed in multiple accounts in contact centers and can be extended to any industrial CRM service practice to analyze unstructured text data.