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Improving Customer Complaint Management by Automatic Email Classification Using Linguistic Style Features as Predictors

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Author Info
K. COUSSEMENT ()
D. VAN DEN POEL ()

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Abstract

Customer complaint management is becoming a critical key success factor in today’s business environment. This study introduces a methodology to improve complaint handling strategies through an automatic email classification system that distinguishes complaints from non-complaints. As such, complaint handling becomes less time-consuming and more successful. The classification system combines traditional text information with new information about the linguistic style of an email. The empirical results show that adding linguistic style information into a classification model with conventional text-classification variables results in a significant increase in predictive performance. In addition, this study reveals linguistic style differences between complaint emails and others.

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File URL: http://www.FEB.UGent.be/fac/research/WP/Papers/wp_07_481.pdf
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Publisher Info
Paper provided by Ghent University, Faculty of Economics and Business Administration in its series Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium with number 07/481.

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Length: 35 pages
Date of creation: Sep 2007
Date of revision:
Handle: RePEc:rug:rugwps:07/481

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Related research
Keywords: Customer Complaint Handling Call Center Email Voice of Customers (VOC) Singular Value Decomposition (SVD) Latent Semantic Indexing (LSI) Automatic Email Classification

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