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Using Text Mining for Automated Customer Inquiry Classification

Authors:
Raoul Jetley
Jinendra Gugaliya
Sana Javed

Keywords: text mining; information retrival; intention analysis; query classififcation; service center

Abstract:
Understanding the customer’s needs and issues is central to business survival and growth. Typically, customer inquiries are captured by a dedicated customer service center using unstructured narrative text. The number of such customer inquiries can vary from several thousands to millions depending on the business size and customer penetration. Analyzing such a huge number of customer inquiries manually is cumbersome, prone to errors and costly. More importantly, it is not possible to identify broad signals and trends among this data. In this paper, we describe an automated approach to analyze customer inquiries, and show how this approach can help classify customer inquiries. We illustrate the application of this approach through an example related to a leading multinational automation company.

Pages: 46 to 51

Copyright: Copyright (c) IARIA, 2015

Publication date: March 22, 2015

Published in: conference

ISSN: 2308-4391

ISBN: 978-1-61208-395-7

Location: Nice, France

Dates: from March 22, 2015 to March 27, 2015