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Business clients´segmentation based on activity : a banking approach

Bibliographic Details
Main Author: Marques, Pedro Afonso Bandeira Ferreira
Publication Date: 2019
Format: Master thesis
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10362/93269
Summary: 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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network_name_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
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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:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-22T17:43:41Zoai:run.unl.pt:10362/93269Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T17:14:57.139377Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
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:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron:RCAAP
instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
_version_ 1833596549954797568

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