Please use this identifier to cite or link to this item: https://ir.iimcal.ac.in:8443/jspui/handle/123456789/1180
Title: Data mining framework for customer lifetime value-based segmentation
Authors: Aeron, Harsha
Kumar, Ashwani.
Moorthy, Janakiraman
Keywords: Customer lifetime value
Database marketing
Genetic algorithm
Lustering
Recency-Frequency-Monetary Value (RFM)
Segmentation
Issue Date: 2012
Publisher: SCOPUS
Journal of Database Marketing and Customer Strategy Management
Series/Report no.: 19(1)
Abstract: Estimating Customer Lifetime Value (CLV) is essential for firms competing in data-rich environments. Segmentation on the basis of CLV is helpful in customization of products and services by justification of resource allocation. Model-based automated decision making is likely to penetrate various marketing decision-making environments. We are presenting a framework for customer lifetime value-based segmentation. The framework automates two decisions: first, selection of variables; and second creation of optimal segments on the basis of CLV. The framework uses clustering for segmentation and genetic algorithm for optimization.© 2012 Macmillan Publishers Ltd.
Description: Aeron, Harsha, Latent View Analytics, India; Kumar, Ashwani, Indian Institute of Management, Lucknow, India; Moorthy, Janakiraman, Indian Institute of Management, Calcutta, India
ISSN/ISBN - 17412439
pp.17-30
DOI - 10.1057/dbm.2012.1
URI: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84859143811&doi=10.1057%2fdbm.2012.1&partnerID=40&md5=35292df9b771ad08ff63f11472d91a09
https://ir.iimcal.ac.in:8443/jspui/handle/123456789/1180
Appears in Collections:Marketing

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