Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11779/1564
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dc.contributor.authorUcal Sarı, İrem-
dc.contributor.authorSergi, Duygu-
dc.contributor.authorOzkan, Burcu-
dc.date.accessioned2021-10-08T19:48:45Z
dc.date.available2021-10-08T19:48:45Z
dc.date.issued2020-
dc.identifier.citationSari, I.U., Sergi, D. and Ozkan, B. (2020), "Customer Segmentation Using RFM Analysis: Real Case Application on a Fuel Company", Kumari, S., Tripathy, K.K. and Kumbhar, V. (Ed.) Application of Big Data and Business Analytics, Emerald Publishing Limited, Bingley, pp. 139-158. https://doi.org/10.1108/978-1-80043-884-220211009en_US
dc.identifier.isbn9781800438859-
dc.identifier.isbn9781800438842-
dc.identifier.urihttps://hdl.handle.net/20.500.11779/1564-
dc.identifier.urihttps://doi.org/10.1108/978-1-80043-884-220211009-
dc.description.abstractCustomer segmentation is an important research area that helps organizations to improve their services according to customer needs. With the increased information that shows customer attitudes, it is much easier and also more necessary than before to analyze customer responses on different campaigns. Recency, frequency, and monetary (RFM) analysis allows us to segment customers according to their common features. In this chapter, customer segmentation and RFM analysis are explained first, then a real case application of RFM analysis on customer segmentation for a Fuel company is presented. At the end of the application part, possible strategies for the company are generated.en_US
dc.language.isoenen_US
dc.publisherEmerald Publishing Limited.en_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectRecency, frequency, and monetary analysisen_US
dc.subjectCustomer segmentationen_US
dc.subjectReal case studyen_US
dc.subjectB2Cen_US
dc.titleCustomer Segmentation Using Rfm Analysis: Real Case Application on a Fuel Companyen_US
dc.typeBook Parten_US
dc.identifier.doi10.1108/978-1-80043-884-220211009-
dc.authoridDuygu Sergi / 0000-0003-1636-0230-
dc.relation.publicationcategoryKitap Bölümü - Uluslararasıen_US
dc.identifier.startpage139-158en_US
dc.departmentMühendislik Fakültesi, Endüstri Mühendisliği Bölümüen_US
dc.relation.journalApplication of Big Data and Business Analyticsen_US
dc.institutionauthorSergi, Duygu-
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.languageiso639-1en-
item.openairetypeBook Part-
item.grantfulltextnone-
item.cerifentitytypePublications-
crisitem.author.dept02.01. Department of Industrial Engineering-
Appears in Collections:Endüstri Mühendisliği Bölümü Koleksiyonu
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