Supervised Classification for Decision Support in Customer Relationship Management

Stefan Lessmann () and Stefan Voß ()
Additional contact information
Stefan Lessmann: University of Hamburg
Stefan Voß: University of Hamburg

A chapter in Intelligent Decision Support, 2008, pp 231-253 from Springer

Abstract: 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.

Keywords: Data Mining; Customer Relationship Management; Classification; Literature Survey (search for similar items in EconPapers)
Date: 2008
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-8349-9777-7_14

Ordering information: This item can be ordered from
http://www.springer.com/9783834997777

DOI: 10.1007/978-3-8349-9777-7_14

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().