Please use this identifier to cite or link to this item: https://ir.iimcal.ac.in:8443/jspui/handle/123456789/1180
Full metadata record
DC FieldValueLanguage
dc.contributor.authorAeron, Harsha
dc.contributor.authorKumar, Ashwani.
dc.contributor.authorMoorthy, Janakiraman
dc.date.accessioned2021-08-26T06:04:05Z-
dc.date.available2021-08-26T06:04:05Z-
dc.date.issued2012
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84859143811&doi=10.1057%2fdbm.2012.1&partnerID=40&md5=35292df9b771ad08ff63f11472d91a09
dc.identifier.urihttps://ir.iimcal.ac.in:8443/jspui/handle/123456789/1180-
dc.descriptionAeron, Harsha, Latent View Analytics, India; Kumar, Ashwani, Indian Institute of Management, Lucknow, India; Moorthy, Janakiraman, Indian Institute of Management, Calcutta, India
dc.descriptionISSN/ISBN - 17412439
dc.descriptionpp.17-30
dc.descriptionDOI - 10.1057/dbm.2012.1
dc.description.abstractEstimating 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.
dc.publisherSCOPUS
dc.publisherJournal of Database Marketing and Customer Strategy Management
dc.relation.ispartofseries19(1)
dc.subjectCustomer lifetime value
dc.subjectDatabase marketing
dc.subjectGenetic algorithm
dc.subjectLustering
dc.subjectRecency-Frequency-Monetary Value (RFM)
dc.subjectSegmentation
dc.titleData mining framework for customer lifetime value-based segmentation
dc.typeArticle
Appears in Collections:Marketing

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.