IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-3-8349-9777-7_14.html
   My bibliography  Save this book chapter

Supervised Classification for Decision Support in Customer Relationship Management

In: Intelligent Decision Support

Author

Listed:
  • Stefan Lessmann

    (University of Hamburg)

  • Stefan Voß

    (University of Hamburg)

Abstract

Supervised classification embraces theories and algorithms for disclosing patterns within large, heterogeneous data streams. Several empirical experiments in various domains including medical diagnosis, drug design, document and image classification as well as text recognition have proven its effectiveness to solve complex forecasting and identification tasks. This paper considers applications of classification within the scope of customer relationship management (CRM). Representative operational planning tasks are reviewed to describe the potential and limitations of classification analysis. To that end, a survey of the relevant literature is given to summarize the body of knowledge in each field and identify similarities across applications. The discussion provides a general understanding of technical and managerial challenges encountered in typical CRM applications and indicates promising areas for future research.

Suggested Citation

  • Stefan Lessmann & Stefan Voß, 2008. "Supervised Classification for Decision Support in Customer Relationship Management," Springer Books, in: Andreas Bortfeldt & Jörg Homberger & Herbert Kopfer & Giselher Pankratz & Reinhard Strangmeier (ed.), Intelligent Decision Support, pages 231-253, Springer.
    • Handle: RePEc:spr:sprchp:978-3-8349-9777-7_14
    DOI: 10.1007/978-3-8349-9777-7_14
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:sprchp:978-3-8349-9777-7_14. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.