Segmentation of retail consumers with soft clustering approach

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dc.authorscopusid57202924825
dc.authorscopusid55322301200
dc.authorscopusid55628294300
dc.contributor.authorDoğan, Onur
dc.contributor.authorHızıroğlu, Abdülkadir
dc.contributor.authorSeymen, Ömer Faruk
dc.date.accessioned2022-02-15T16:57:32Z
dc.date.available2022-02-15T16:57:32Z
dc.date.issued2021
dc.departmentBakırçay Üniversitesien_US
dc.descriptionInternational Conference on Intelligent and Fuzzy Systems, INFUS 2020 -- 21 July 2020 through 23 July 2020 -- -- 242349en_US
dc.description.abstractDefining customer requirements in a huge amount of data of the digital era is crucial for companies in a competitive business environment. Customer segmentation has been attracted to a great deal of attention and has widely been performed in marketing studies. However, boundary data which are close to more than one segment may be assigned incorrect classes, which affects to make the right decisions and evaluations. Therefore, segmentation analysis is still needed to develop efficient models using advanced techniques such as soft computing methods. In this study, an intuitionistic fuzzy clustering algorithm were applied to customer data in a supermarket according to the amount spent in some product groups. The data represent 33-month customer shopping data in a supermarket for eight product groups. The results indicate the intuitionistic fuzzy c-means based customer segmentation approach produces more reliable and applicable marketing campaigns than conditional fuzzy c-means and k-means segmentation method. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.en_US
dc.identifier.doi10.1007/978-3-030-51156-2_6
dc.identifier.endpage46en_US
dc.identifier.isbn9783030511555
dc.identifier.issn2194-5357
dc.identifier.scopus2-s2.0-85088749341en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage39en_US
dc.identifier.urihttps://doi.org/10.1007/978-3-030-51156-2_6
dc.identifier.urihttps://hdl.handle.net/20.500.14034/199
dc.identifier.volume1197 AISCen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.journalAdvances in Intelligent Systems and Computingen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectCustomer segmentationen_US
dc.subjectFuzzy clusteringen_US
dc.subjectIntuitionistic fuzzy c-meansen_US
dc.subjectMarketing perspectiveen_US
dc.subjectStatistical methodsen_US
dc.subjectFuzzy clusteringen_US
dc.subjectFuzzy setsen_US
dc.subjectRetail storesen_US
dc.subjectSalesen_US
dc.subjectSoft computingen_US
dc.subjectCompetitive businessen_US
dc.subjectCustomer requirementsen_US
dc.subjectCustomer segmentationen_US
dc.subjectIntuitionistic Fuzzy C-Meansen_US
dc.subjectIntuitionistic fuzzy clusteringen_US
dc.subjectK-means segmentationsen_US
dc.subjectSegmentation analysisen_US
dc.subjectSoft computing methodsen_US
dc.subjectClustering algorithmsen_US
dc.titleSegmentation of retail consumers with soft clustering approachen_US
dc.typeConference Objecten_US

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