Business clients´segmentation based on activity : a banking approach

Detalhes bibliográficos
Autor(a) principal: Marques, Pedro Afonso Bandeira Ferreira
Data de Publicação: 2019
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/93269
Resumo: Internship report presented as partial requirement for obtaining the Master’s degree in Information Management, with a specialization in knowledge Management and Business Intelligence
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spelling Business clients´segmentation based on activity : a banking approachB2B SegmentationBanking SegmentationCluster AnalysisHierarchical K-MeansInternship report presented as partial requirement for obtaining the Master’s degree in Information Management, with a specialization in knowledge Management and Business IntelligenceClustering algorithms are frequently used by companies to segment their customers in order to develop accurate marketing strategies. The K-means is one of the most popular algorithms, despite its drawbacks in terms of seeds’ generation. In this study, several clustering algorithms were tested but in the end the K-means initialized with random seeds was used to segment the data due to its better performance. This B2B segmentation resulted in four clusters based on the activity patterns of each business client, The Loyals, The Minglers, The Challengers and The Believers. Each one of these clusters shows a different type of relationship with the bank, being the bank the first choice for The Loyals and for the Believers but not for the others.Jesus, Frederico Miguel Campos Cruz Ribeiro deRUNMarques, Pedro Afonso Bandeira Ferreira2020-02-24T12:39:02Z2019-12-182019-12-18T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/93269TID:202447227enginfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-07-10T15:52:50ZPortal AgregadorONG
dc.title.none.fl_str_mv Business clients´segmentation based on activity : a banking approach
title Business clients´segmentation based on activity : a banking approach
spellingShingle Business clients´segmentation based on activity : a banking approach
Marques, Pedro Afonso Bandeira Ferreira
B2B Segmentation
Banking Segmentation
Cluster Analysis
Hierarchical K-Means
title_short Business clients´segmentation based on activity : a banking approach
title_full Business clients´segmentation based on activity : a banking approach
title_fullStr Business clients´segmentation based on activity : a banking approach
title_full_unstemmed Business clients´segmentation based on activity : a banking approach
title_sort Business clients´segmentation based on activity : a banking approach
author Marques, Pedro Afonso Bandeira Ferreira
author_facet Marques, Pedro Afonso Bandeira Ferreira
author_role author
dc.contributor.none.fl_str_mv Jesus, Frederico Miguel Campos Cruz Ribeiro de
RUN
dc.contributor.author.fl_str_mv Marques, Pedro Afonso Bandeira Ferreira
dc.subject.por.fl_str_mv B2B Segmentation
Banking Segmentation
Cluster Analysis
Hierarchical K-Means
topic B2B Segmentation
Banking Segmentation
Cluster Analysis
Hierarchical K-Means
description Internship report presented as partial requirement for obtaining the Master’s degree in Information Management, with a specialization in knowledge Management and Business Intelligence
publishDate 2019
dc.date.none.fl_str_mv 2019-12-18
2019-12-18T00:00:00Z
2020-02-24T12:39:02Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/93269
TID:202447227
url http://hdl.handle.net/10362/93269
identifier_str_mv TID:202447227
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv
repository.mail.fl_str_mv
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