Publication detail

Cost-benefit metrics in customer churn prediction: A review

FRIDRICH, M.

Original Title

Cost-benefit metrics in customer churn prediction: A review

Type

conference paper

Language

English

Original Abstract

In saturated markets, achieving business goals depends highly on organizational ability of managing relationships with customers. Thus, retention management and modelling customer loyalty have been topics of interest for many years, although even bleeding edge classification models are rarely adjusted to business objectives. Therefore, the aim of this paper is to examine body of work in the domains of cost-benefit metrics and customer churn prediction. As a result, present state of research is reviewed through proposed lens of conceptual perspective and machine learning pipeline perspective. Possible directions for future research are identified.

Keywords

customer relationship management, customer churn, machine learning, cost-sensitive classification

Authors

FRIDRICH, M.

Released

21. 12. 2018

Publisher

Magnanimitas

Location

Hradec Králové

ISBN

978-80-87952-27-6

Book

MMK 2018 International Masaryk Conference For Ph.D. Students and Young Researchers

Pages from

178

Pages to

185

Pages count

8

BibTex

@inproceedings{BUT152163,
  author="Martin {Fridrich}",
  title="Cost-benefit metrics in customer churn prediction: A review",
  booktitle="MMK 2018 International Masaryk Conference For Ph.D. Students and Young Researchers",
  year="2018",
  pages="178--185",
  publisher="Magnanimitas",
  address="Hradec Králové",
  isbn="978-80-87952-27-6"
}