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Leveraging customer segmentation on hotel loyalty programs with data mining

Bibliographic Details
Main Author: Caetano, Joana Maria Pereira Lupi
Publication Date: 2019
Format: Master thesis
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10362/104412
Summary: This study aims to provide a new customer segmentation solution for hotels’ loyalty programs using a data mining approach forclassifying the customers into segments through clustering processes.Mainfindings suggest somehigh tier members are not as valuable as lower tier ones, there are groups of clients with distinct brand preferences, stay duration anddestination patterns which are not being correctly grouped due to tier segmentation andthatloyalty programs are not equally suitable for all brands within a hotel group, therefore additional levels of segmentation would be appropriate to match the distinct guests’behaviorand value.
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spelling Leveraging customer segmentation on hotel loyalty programs with data miningLoyaltyHotel loyalty programsData miningCustomer segmentationClusteringK-meansDomínio/Área Científica::Ciências Sociais::Economia e GestãoThis study aims to provide a new customer segmentation solution for hotels’ loyalty programs using a data mining approach forclassifying the customers into segments through clustering processes.Mainfindings suggest somehigh tier members are not as valuable as lower tier ones, there are groups of clients with distinct brand preferences, stay duration anddestination patterns which are not being correctly grouped due to tier segmentation andthatloyalty programs are not equally suitable for all brands within a hotel group, therefore additional levels of segmentation would be appropriate to match the distinct guests’behaviorand value.Rita, PauloCardoso, ElizabeteRUNCaetano, Joana Maria Pereira Lupi2020-09-21T10:03:14Z2020-01-072019-11-282020-01-07T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/104412TID:202492460enginfo: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:RCAAP2024-05-22T17:47:39Zoai:run.unl.pt:10362/104412Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T17:18:48.573174Repositórios 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 Leveraging customer segmentation on hotel loyalty programs with data mining
title Leveraging customer segmentation on hotel loyalty programs with data mining
spellingShingle Leveraging customer segmentation on hotel loyalty programs with data mining
Caetano, Joana Maria Pereira Lupi
Loyalty
Hotel loyalty programs
Data mining
Customer segmentation
Clustering
K-means
Domínio/Área Científica::Ciências Sociais::Economia e Gestão
title_short Leveraging customer segmentation on hotel loyalty programs with data mining
title_full Leveraging customer segmentation on hotel loyalty programs with data mining
title_fullStr Leveraging customer segmentation on hotel loyalty programs with data mining
title_full_unstemmed Leveraging customer segmentation on hotel loyalty programs with data mining
title_sort Leveraging customer segmentation on hotel loyalty programs with data mining
author Caetano, Joana Maria Pereira Lupi
author_facet Caetano, Joana Maria Pereira Lupi
author_role author
dc.contributor.none.fl_str_mv Rita, Paulo
Cardoso, Elizabete
RUN
dc.contributor.author.fl_str_mv Caetano, Joana Maria Pereira Lupi
dc.subject.por.fl_str_mv Loyalty
Hotel loyalty programs
Data mining
Customer segmentation
Clustering
K-means
Domínio/Área Científica::Ciências Sociais::Economia e Gestão
topic Loyalty
Hotel loyalty programs
Data mining
Customer segmentation
Clustering
K-means
Domínio/Área Científica::Ciências Sociais::Economia e Gestão
description This study aims to provide a new customer segmentation solution for hotels’ loyalty programs using a data mining approach forclassifying the customers into segments through clustering processes.Mainfindings suggest somehigh tier members are not as valuable as lower tier ones, there are groups of clients with distinct brand preferences, stay duration anddestination patterns which are not being correctly grouped due to tier segmentation andthatloyalty programs are not equally suitable for all brands within a hotel group, therefore additional levels of segmentation would be appropriate to match the distinct guests’behaviorand value.
publishDate 2019
dc.date.none.fl_str_mv 2019-11-28
2020-09-21T10:03:14Z
2020-01-07
2020-01-07T00:00:00Z
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/10362/104412
TID:202492460
url http://hdl.handle.net/10362/104412
identifier_str_mv TID:202492460
dc.language.iso.fl_str_mv eng
language eng
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instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
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repository.mail.fl_str_mv info@rcaap.pt
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