RFM analysis optimized
Autor(a) principal: | |
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Data de Publicação: | 2005 |
Outros Autores: | , , , , |
Tipo de documento: | Relatório |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFRJ |
Texto Completo: | http://hdl.handle.net/11422/1929 |
Resumo: | In the classic recency, frequency and monetary approach to market segmentation, i.e. RFM analysis, given a time frame, customers are clustered together into an arbitrary number of segments according to their most recent day of purchase, the number of purchases and the monetary value of their purchases. In this work we show how the choice of the number of segments and the time frame used in the RFM segmentation process can be optimized to maximize the result of direct marketing campaigns. We also indicate how RFM analysis can be extended to accommodate new dimensions of customer behavior and how the extended RFM analysis can be optimized. Furthermore, we discuss the implications of the optimized and extended RFM approach to market segmentation for direct marketing and business strategies. |
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Alencar, Antônio JuarezRibeiro, Eduardo MartinsFerreira, Armando LeiteSchmitz, Eber AssisLima, Priscila Machado VieiraManso, Fernando Silva Pereira2017-05-09T15:38:01Z2023-11-30T03:00:27Z2005-12-31ALENCAR, A. J. et al. RFM analysis optimized. Rio de Janeiro: NCE/UFRJ, 2005. 19 p. (Relatório Técnico, 01/05)http://hdl.handle.net/11422/1929In the classic recency, frequency and monetary approach to market segmentation, i.e. RFM analysis, given a time frame, customers are clustered together into an arbitrary number of segments according to their most recent day of purchase, the number of purchases and the monetary value of their purchases. In this work we show how the choice of the number of segments and the time frame used in the RFM segmentation process can be optimized to maximize the result of direct marketing campaigns. We also indicate how RFM analysis can be extended to accommodate new dimensions of customer behavior and how the extended RFM analysis can be optimized. Furthermore, we discuss the implications of the optimized and extended RFM approach to market segmentation for direct marketing and business strategies.Submitted by Elaine Almeida (elaine.almeida@nce.ufrj.br) on 2017-05-09T15:38:01Z No. of bitstreams: 1 01_05_000637947.pdf: 125517 bytes, checksum: e25818af0e30456a506ce44c642b4dd8 (MD5)Made available in DSpace on 2017-05-09T15:38:01Z (GMT). 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dc.title.en.fl_str_mv |
RFM analysis optimized |
title |
RFM analysis optimized |
spellingShingle |
RFM analysis optimized Alencar, Antônio Juarez CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO Análises RFM Marketing direto |
title_short |
RFM analysis optimized |
title_full |
RFM analysis optimized |
title_fullStr |
RFM analysis optimized |
title_full_unstemmed |
RFM analysis optimized |
title_sort |
RFM analysis optimized |
author |
Alencar, Antônio Juarez |
author_facet |
Alencar, Antônio Juarez Ribeiro, Eduardo Martins Ferreira, Armando Leite Schmitz, Eber Assis Lima, Priscila Machado Vieira Manso, Fernando Silva Pereira |
author_role |
author |
author2 |
Ribeiro, Eduardo Martins Ferreira, Armando Leite Schmitz, Eber Assis Lima, Priscila Machado Vieira Manso, Fernando Silva Pereira |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Alencar, Antônio Juarez Ribeiro, Eduardo Martins Ferreira, Armando Leite Schmitz, Eber Assis Lima, Priscila Machado Vieira Manso, Fernando Silva Pereira |
dc.subject.cnpq.fl_str_mv |
CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO |
topic |
CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO Análises RFM Marketing direto |
dc.subject.por.fl_str_mv |
Análises RFM Marketing direto |
description |
In the classic recency, frequency and monetary approach to market segmentation, i.e. RFM analysis, given a time frame, customers are clustered together into an arbitrary number of segments according to their most recent day of purchase, the number of purchases and the monetary value of their purchases. In this work we show how the choice of the number of segments and the time frame used in the RFM segmentation process can be optimized to maximize the result of direct marketing campaigns. We also indicate how RFM analysis can be extended to accommodate new dimensions of customer behavior and how the extended RFM analysis can be optimized. Furthermore, we discuss the implications of the optimized and extended RFM approach to market segmentation for direct marketing and business strategies. |
publishDate |
2005 |
dc.date.issued.fl_str_mv |
2005-12-31 |
dc.date.accessioned.fl_str_mv |
2017-05-09T15:38:01Z |
dc.date.available.fl_str_mv |
2023-11-30T03:00:27Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/report |
format |
report |
status_str |
publishedVersion |
dc.identifier.citation.fl_str_mv |
ALENCAR, A. J. et al. RFM analysis optimized. Rio de Janeiro: NCE/UFRJ, 2005. 19 p. (Relatório Técnico, 01/05) |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/11422/1929 |
identifier_str_mv |
ALENCAR, A. J. et al. RFM analysis optimized. Rio de Janeiro: NCE/UFRJ, 2005. 19 p. (Relatório Técnico, 01/05) |
url |
http://hdl.handle.net/11422/1929 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.ispartof.pt_BR.fl_str_mv |
Relatório Técnico NCE |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.publisher.country.fl_str_mv |
Brasil |
dc.publisher.department.fl_str_mv |
Instituto Tércio Pacitti de Aplicações e Pesquisas Computacionais |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da UFRJ instname:Universidade Federal do Rio de Janeiro (UFRJ) instacron:UFRJ |
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Universidade Federal do Rio de Janeiro (UFRJ) |
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UFRJ |
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UFRJ |
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Repositório Institucional da UFRJ |
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Repositório Institucional da UFRJ |
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