An evaluation of predictive customer segmentation for a German grocery retailer
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10362/142644 |
Resumo: | This work project reports about an applied project in partnership with a German grocer that wanted to substitute its RFM model with a predictive customer lifetime segmentation model. A dataset for model development and evaluation was made available. The overarching question: "Can a predictive customer life time value segmentation model have better performance than the existing Recency, Frequency, and Monetary Value segmentation model? "will be answered by using a segmentation model evaluation framework. Finally, this master thesis’ findings show that a predictive customer lifetime value model has superior qualities to an RFM model but lacks reliability and cannot fully replace the old model. |
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An evaluation of predictive customer segmentation for a German grocery retailerMachine learningGermanyCustomer lifetime valuePredictive customer segmentationE-groceryDomínio/Área Científica::Ciências Sociais::Economia e GestãoThis work project reports about an applied project in partnership with a German grocer that wanted to substitute its RFM model with a predictive customer lifetime segmentation model. A dataset for model development and evaluation was made available. The overarching question: "Can a predictive customer life time value segmentation model have better performance than the existing Recency, Frequency, and Monetary Value segmentation model? "will be answered by using a segmentation model evaluation framework. Finally, this master thesis’ findings show that a predictive customer lifetime value model has superior qualities to an RFM model but lacks reliability and cannot fully replace the old model.Zejnilovic, LeidRUNBohrer, Adrian2022-01-272021-12-162025-12-16T00:00:00Z2022-01-27T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/142644TID:203022165enginfo:eu-repo/semantics/embargoedAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T05:20:30Zoai:run.unl.pt:10362/142644Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:50:27.108869Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
An evaluation of predictive customer segmentation for a German grocery retailer |
title |
An evaluation of predictive customer segmentation for a German grocery retailer |
spellingShingle |
An evaluation of predictive customer segmentation for a German grocery retailer Bohrer, Adrian Machine learning Germany Customer lifetime value Predictive customer segmentation E-grocery Domínio/Área Científica::Ciências Sociais::Economia e Gestão |
title_short |
An evaluation of predictive customer segmentation for a German grocery retailer |
title_full |
An evaluation of predictive customer segmentation for a German grocery retailer |
title_fullStr |
An evaluation of predictive customer segmentation for a German grocery retailer |
title_full_unstemmed |
An evaluation of predictive customer segmentation for a German grocery retailer |
title_sort |
An evaluation of predictive customer segmentation for a German grocery retailer |
author |
Bohrer, Adrian |
author_facet |
Bohrer, Adrian |
author_role |
author |
dc.contributor.none.fl_str_mv |
Zejnilovic, Leid RUN |
dc.contributor.author.fl_str_mv |
Bohrer, Adrian |
dc.subject.por.fl_str_mv |
Machine learning Germany Customer lifetime value Predictive customer segmentation E-grocery Domínio/Área Científica::Ciências Sociais::Economia e Gestão |
topic |
Machine learning Germany Customer lifetime value Predictive customer segmentation E-grocery Domínio/Área Científica::Ciências Sociais::Economia e Gestão |
description |
This work project reports about an applied project in partnership with a German grocer that wanted to substitute its RFM model with a predictive customer lifetime segmentation model. A dataset for model development and evaluation was made available. The overarching question: "Can a predictive customer life time value segmentation model have better performance than the existing Recency, Frequency, and Monetary Value segmentation model? "will be answered by using a segmentation model evaluation framework. Finally, this master thesis’ findings show that a predictive customer lifetime value model has superior qualities to an RFM model but lacks reliability and cannot fully replace the old model. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-12-16 2022-01-27 2022-01-27T00:00:00Z 2025-12-16T00:00:00Z |
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/10362/142644 TID:203022165 |
url |
http://hdl.handle.net/10362/142644 |
identifier_str_mv |
TID:203022165 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
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info:eu-repo/semantics/embargoedAccess |
eu_rights_str_mv |
embargoedAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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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 |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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1799138101255208960 |