On fuzziness in relationship value segmentation: applications to personalized e-commerce

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.

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INDEX TERMS

Primary Classification:
  K. Computing Milieux
  K.4 COMPUTERS AND SOCIETY
      K.4.4 Electronic Commerce

Additional Classification:
  I. Computing Methodologies
  I.5 PATTERN RECOGNITION
      I.5.1 Models
          Subjects: Fuzzy set

  J. Computer Applications
  J.4 SOCIAL AND BEHAVIORAL SCIENCES
      Subjects: Economics

General Terms:
Economics, Human Factors, Performance, Theory

Keywords:
customer segmentation, customer value, e-commerce personalization, fuzzy set theory, relationship marketing, uncertainty