Telecom customer segmentation and precise package design by using data mining

Detalhes bibliográficos
Autor(a) principal: Zhang Tianyuan
Data de Publicação: 2018
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10071/17567
Resumo: Changes in the form of communication have prompted the telecommunications industry to flourish. In the "big data era" of information explosion, as one of the leading industries in the information age, the development of the telecommunications industry depends not only on communication technology, but also on the ability of enterprises to optimize resource allocation. At present, the information resources owned by telecom companies mainly come from customers. During the development process, they have accumulated a large amount of customer data, which truly and objectively reflects the behavior of consumers. This paper is dedicated to combining data mining technology with the rich data resources of the telecom industry and the latest marketing theories, not only effectively helping subdivide the telecommunications customer market, but also supporting telecommunications companies in developing more accurate and efficient marketing strategies. In addition, data analysis method such as factor analysis, regression analysis and discriminant analysis are used to analyze the demographic, business, SMS messages and expense characteristics of telecom customers, providing a new vision and reference for the telecom industry to achieve accurate packaging design. Based on the above research results, a discriminant model for the loss of telecom customers is constructed, which will help telecommunications companies to obtain a control method for telecom customer management risk. At last, data mining technology is used to optimize the combination design of telecommunication services, which offer effective advice on precise telecom package design to telecommunications companies.
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spelling Telecom customer segmentation and precise package design by using data miningTelecomCustomer segmentationData miningTargeted marketingPackage designMarketingTelecomunicaçãoAnálise de regressãoChanges in the form of communication have prompted the telecommunications industry to flourish. In the "big data era" of information explosion, as one of the leading industries in the information age, the development of the telecommunications industry depends not only on communication technology, but also on the ability of enterprises to optimize resource allocation. At present, the information resources owned by telecom companies mainly come from customers. During the development process, they have accumulated a large amount of customer data, which truly and objectively reflects the behavior of consumers. This paper is dedicated to combining data mining technology with the rich data resources of the telecom industry and the latest marketing theories, not only effectively helping subdivide the telecommunications customer market, but also supporting telecommunications companies in developing more accurate and efficient marketing strategies. In addition, data analysis method such as factor analysis, regression analysis and discriminant analysis are used to analyze the demographic, business, SMS messages and expense characteristics of telecom customers, providing a new vision and reference for the telecom industry to achieve accurate packaging design. Based on the above research results, a discriminant model for the loss of telecom customers is constructed, which will help telecommunications companies to obtain a control method for telecom customer management risk. At last, data mining technology is used to optimize the combination design of telecommunication services, which offer effective advice on precise telecom package design to telecommunications companies.2019-03-12T11:57:07Z2018-11-16T00:00:00Z2018-11-162018-10info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfapplication/octet-streamhttp://hdl.handle.net/10071/17567TID:202041174engZhang Tianyuaninfo: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:RCAAP2023-11-09T17:28:05Zoai:repositorio.iscte-iul.pt:10071/17567Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T22:12:34.439585Repositório 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 Telecom customer segmentation and precise package design by using data mining
title Telecom customer segmentation and precise package design by using data mining
spellingShingle Telecom customer segmentation and precise package design by using data mining
Zhang Tianyuan
Telecom
Customer segmentation
Data mining
Targeted marketing
Package design
Marketing
Telecomunicação
Análise de regressão
title_short Telecom customer segmentation and precise package design by using data mining
title_full Telecom customer segmentation and precise package design by using data mining
title_fullStr Telecom customer segmentation and precise package design by using data mining
title_full_unstemmed Telecom customer segmentation and precise package design by using data mining
title_sort Telecom customer segmentation and precise package design by using data mining
author Zhang Tianyuan
author_facet Zhang Tianyuan
author_role author
dc.contributor.author.fl_str_mv Zhang Tianyuan
dc.subject.por.fl_str_mv Telecom
Customer segmentation
Data mining
Targeted marketing
Package design
Marketing
Telecomunicação
Análise de regressão
topic Telecom
Customer segmentation
Data mining
Targeted marketing
Package design
Marketing
Telecomunicação
Análise de regressão
description Changes in the form of communication have prompted the telecommunications industry to flourish. In the "big data era" of information explosion, as one of the leading industries in the information age, the development of the telecommunications industry depends not only on communication technology, but also on the ability of enterprises to optimize resource allocation. At present, the information resources owned by telecom companies mainly come from customers. During the development process, they have accumulated a large amount of customer data, which truly and objectively reflects the behavior of consumers. This paper is dedicated to combining data mining technology with the rich data resources of the telecom industry and the latest marketing theories, not only effectively helping subdivide the telecommunications customer market, but also supporting telecommunications companies in developing more accurate and efficient marketing strategies. In addition, data analysis method such as factor analysis, regression analysis and discriminant analysis are used to analyze the demographic, business, SMS messages and expense characteristics of telecom customers, providing a new vision and reference for the telecom industry to achieve accurate packaging design. Based on the above research results, a discriminant model for the loss of telecom customers is constructed, which will help telecommunications companies to obtain a control method for telecom customer management risk. At last, data mining technology is used to optimize the combination design of telecommunication services, which offer effective advice on precise telecom package design to telecommunications companies.
publishDate 2018
dc.date.none.fl_str_mv 2018-11-16T00:00:00Z
2018-11-16
2018-10
2019-03-12T11:57:07Z
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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
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reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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