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Listening to the Voice of the Customers: An Early Warning System Based on Sentiment

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Computational Intelligence in Intelligent Data Analysis

Part of the book series: Studies in Computational Intelligence ((SCI,volume 445))

Abstract

In a global economy, enterprises have to intelligently analyze their data asset in order to stay competitive. With the advent of the Web 2.0, there is a wealth of user generated content which contains valuable information on what customers think about available products and services: the voice of the customers is readily accessible. Listing to and understanding these data can reveal valuable customer insights especially for product quality assessment, improvement and innovation as well as marketing. This report focuses on the use of state-of-the-art text mining techniques for identifying and monitoring the sentiment of customer feedback on Web 2.0 channels over time such as to alert enterprise users to significant increases in negative sentiment as an early indicator of inferior or degrading product quality.

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Author information

Authors and Affiliations

  1. Heilbronn University, 74081, Heilbronn, Germany

    Carsten Lanquillon

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  1. Carsten Lanquillon
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Correspondence to Carsten Lanquillon .

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Editors and Affiliations

  1. Faculty of Computer Science, Otto-von-Guericke-University Magdeburg, Universitätsplatz 2, Magdeburg, 39106, Germany

    Christian Moewes

  2. , Faculty of Computer Science, Otto-von-Guericke University Magdeburg, Universitätsplatz 2, Magdeburg, 39106, Germany

    Andreas Nürnberger

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Lanquillon, C. (2013). Listening to the Voice of the Customers: An Early Warning System Based on Sentiment. In: Moewes, C., Nürnberger, A. (eds) Computational Intelligence in Intelligent Data Analysis. Studies in Computational Intelligence, vol 445. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32378-2_15

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  • DOI: https://doi.org/10.1007/978-3-642-32378-2_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32377-5

  • Online ISBN: 978-3-642-32378-2

  • eBook Packages: EngineeringEngineering (R0)

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