Publication:
Retail Store Segmentation for Target Marketing

dc.contributor.authorÇAKIR, ÖZGÜR
dc.contributor.authorsBilgic, Emrah; Kantardzic, Mehmed; Cakir, Ozgur
dc.contributor.editorPerner, P
dc.date.accessioned2022-03-12T16:15:23Z
dc.date.accessioned2026-01-10T19:32:05Z
dc.date.available2022-03-12T16:15:23Z
dc.date.issued2015
dc.description.abstractIn this paper, we use Data Mining techniques such as clustering and association rules, for the purpose of target marketing strategy. Our goal is to develop a methodology for retailers on how to segment their stores based on multiple data sources and how to create marketing strategies for each segment rather than mass marketing. We have analyzed a supermarket chain company, which has 73 stores located in the Istanbul area in Turkey. First, stores are segmented in 5 clusters using a hierarchical clustering method and then association rules are applied for each cluster.
dc.identifier.doi10.1007/978-3-319-20910-4_3
dc.identifier.isbn978-3-319-20910-4; 978-3-319-20909-8
dc.identifier.issn0302-9743
dc.identifier.urihttps://hdl.handle.net/11424/225590
dc.identifier.wosWOS:000364842200003
dc.language.isoeng
dc.publisherSPRINGER-VERLAG BERLIN
dc.relation.ispartofADVANCES IN DATA MINING: APPLICATIONS AND THEORETICAL ASPECTS, ICDM 2015
dc.relation.ispartofseriesLecture Notes in Artificial Intelligence
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectClustering
dc.subjectAssociation rules
dc.subjectMarket basket analysis
dc.subjectSegmentation
dc.subjectSTRATEGIES
dc.titleRetail Store Segmentation for Target Marketing
dc.typeconferenceObject
dspace.entity.typePublication
oaire.citation.endPage44
oaire.citation.startPage32
oaire.citation.titleADVANCES IN DATA MINING: APPLICATIONS AND THEORETICAL ASPECTS, ICDM 2015
oaire.citation.volume9165

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