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Author Sicilia, Miguel-Ángel ♦ García, Elena
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Language English
Subject Domain (in DDC) Social sciences ♦ Economics ♦ Microeconomics & related topics
Subject Keyword Relationship marketing ♦ E-commerce personalization ♦ Customer segmentation ♦ Uncertainty ♦ Customer value ♦ Fuzzy set theory
Abstract Relationship marketing strategies focus on the construction and maintenance of tailored relationship with customers. Consequently, electronic commerce systems following the relationship approach may benefit from Web personalization techniques in tailoring the interaction with its users according to an evolving customer model. In this context, relationship-value market segmentation becomes a central customer modeling activity. But value segmentation categories are inherently vague due to the use of imprecise linguistic categories, combined with a degree of uncertainty about customer behavior, and the difficulty inherent to estimating intangible variables. In this paper, a fuzzy approach to value segmentation is described, allowing more flexible customer segments. Fuzzy models of value estimations are represented by fuzzy triangular numbers, and two segmentation approaches, directed and discovery-oriented are briefly described. The usefulness of the approach is then illustrated through concrete personalization techniques based on those fuzzy categories.
Description Affiliation: Computer Science Department, University of Alcalá, Ctra. Barcelona, Alcalá de Henares, Madrid, Spain (García, Elena) || Computer Science Department, Carlos III University, Avda. Universidad, Leganés, Madrid, Spain (Sicilia, Miguel-Ángel)
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2003-03-01
Publisher Place New York
Journal ACM SIGecom Exchanges (SECO)
Volume Number 4
Issue Number 2
Page Count 10
Starting Page 1
Ending Page 10

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Source: ACM Digital Library