Publication:
Location-based performance management of sales teams

dc.contributor.coauthorKastan, Hande
dc.contributor.coauthorKasikci, Kerem
dc.contributor.coauthorGunes, Remziye
dc.contributor.coauthorGuven, Melih
dc.contributor.coauthorKoras, Murat
dc.contributor.departmentDepartment of Electrical and Electronics Engineering
dc.contributor.departmentDepartment of Industrial Engineering
dc.contributor.schoolcollegeinstituteCollege of Engineering
dc.date.accessioned2025-03-06T20:57:14Z
dc.date.issued2024
dc.description.abstractDirect sales are among the most valuable channels that bring banks together with customers in product and cross-product sales. Direct sales representatives, who communicate one-on-one with the customer, use tablet computers to process customer information that banks must receive or to sell products. Sales information flowing through these tablets constitute the target of the project. This project aims to identify regions with high potential for credit card sales carried out by direct sales personnel;it aims to move the workforce from regions with low potential to regions with high potential. Location optimization will be achieved using machine learning methods. In order for the algorithm to be used to learn the characteristics of each region and the factors affecting its performance, Turkey was placed in a grid view consisting of lines passing through hundredths of the latitude and longitude degrees. For each quadrangle, the characteristics of the customers living or travelling there, the area and the points of interest around it were taken into account. The value of each grid was calculated to decide on areas with high potential. A heat map is projected onto Turkey in order to visualize the study's results.
dc.description.indexedbyWOS
dc.description.indexedbyScopus
dc.description.publisherscopeInternational
dc.description.sponsoredbyTubitakEuN/A
dc.identifier.doi10.1109/SIU61531.2024.10601033
dc.identifier.isbn9798350388978
dc.identifier.isbn9798350388961
dc.identifier.issn2165-0608
dc.identifier.quartileN/A
dc.identifier.scopus2-s2.0-85200904333
dc.identifier.urihttps://doi.org/10.1109/SIU61531.2024.10601033
dc.identifier.urihttps://hdl.handle.net/20.500.14288/27167
dc.identifier.wos1297894700247
dc.keywordsSales prediction
dc.keywordsMachine learning
dc.keywordsGeographical information systems
dc.keywordsSpatial modelling
dc.language.isotur
dc.publisherIEEE
dc.relation.ispartof32ND IEEE SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE, SIU 2024
dc.subjectComputer science
dc.subjectElectrical and electronic
dc.subjectTelecommunications
dc.titleLocation-based performance management of sales teams
dc.title.alternativeSatış ekiplerinin konum bazlı performans yönetimi
dc.typeConference Proceeding
dspace.entity.typePublication
local.contributor.kuauthorAkgün,Barış
local.contributor.kuauthorGönen Mehmet
local.publication.orgunit1College of Engineering
local.publication.orgunit2Department of Electrical and Electronics Engineering
local.publication.orgunit2Department of Industrial Engineering
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relation.isOrgUnitOfPublicationd6d00f52-d22d-4653-99e7-863efcd47b4a
relation.isOrgUnitOfPublication.latestForDiscovery21598063-a7c5-420d-91ba-0cc9b2db0ea0
relation.isParentOrgUnitOfPublication8e756b23-2d4a-4ce8-b1b3-62c794a8c164
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