Publication:
Customer mobility signatures and financial indicators as predictors in product recommendation

dc.contributor.coauthorBozkaya, Burçin
dc.contributor.departmentDepartment of Industrial Engineering
dc.contributor.kuauthorÜrküp, Çağan
dc.contributor.kuauthorSalman, Fatma Sibel
dc.contributor.otherDepartment of Industrial Engineering
dc.contributor.schoolcollegeinstituteCollege of Engineering
dc.contributor.schoolcollegeinstituteGraduate School of Sciences and Engineering
dc.contributor.yokidN/A
dc.contributor.yokid178838
dc.date.accessioned2024-11-09T13:19:19Z
dc.date.issued2018
dc.description.abstractThe rapid growth of mobile payment and geo-aware systems as well as the resulting emergence of Big Data present opportunities to explore individual consuming patterns across space and time. Here we analyze a one-year transaction dataset of a leading commercial bank to understand to what extent customer mobility behavior and financial indicators can predict the use of a target product, namely the Individual Consumer Loan product. After data preprocessing, we generate 13 datasets covering different time intervals and feature groups, and test combinations of 3 feature selection methods and 10 classification algorithms to determine, for each dataset, the best feature selection method and the most influential features, and the best classification algorithm. We observe the importance of spatio-temporal mobility features and financial features, in addition to demography, in predicting the use of this exemplary product with high accuracy (AUC = 0.942). Finally, we analyze the classification results and report on most interesting customer characteristics and product usage implications. Our findings can be used to potentially increase the success rates of product recommendation systems.
dc.description.fulltextYES
dc.description.indexedbyWoS
dc.description.indexedbyScopus
dc.description.indexedbyPubMed
dc.description.issue7
dc.description.openaccessYES
dc.description.publisherscopeInternational
dc.description.sponsoredbyTubitakEuN/A
dc.description.sponsorshipN/A
dc.description.versionPublisher version
dc.description.volume13
dc.formatpdf
dc.identifier.doi10.1371/journal.pone.0201197
dc.identifier.eissn1932-6203
dc.identifier.embargoNO
dc.identifier.filenameinventorynoIR01452
dc.identifier.linkhttps://doi.org/10.1371/journal.pone.0201197
dc.identifier.quartileQ2
dc.identifier.scopus2-s2.0-85051706769
dc.identifier.urihttps://hdl.handle.net/20.500.14288/3106
dc.identifier.wos440006600028
dc.keywordsImputation
dc.keywordsBehavior
dc.keywordsValues
dc.languageEnglish
dc.publisherPublic Library of Science
dc.relation.urihttp://cdm21054.contentdm.oclc.org/cdm/ref/collection/IR/id/8046
dc.sourcePlos One
dc.subjectMultidisciplinary sciences
dc.titleCustomer mobility signatures and financial indicators as predictors in product recommendation
dc.typeJournal Article
dspace.entity.typePublication
local.contributor.authoridN/A
local.contributor.authorid0000-0001-6833-2552
local.contributor.kuauthorÜrküp, Çağan
local.contributor.kuauthorSalman, Fatma Sibel
relation.isOrgUnitOfPublicationd6d00f52-d22d-4653-99e7-863efcd47b4a
relation.isOrgUnitOfPublication.latestForDiscoveryd6d00f52-d22d-4653-99e7-863efcd47b4a

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