Analytical CRM in a management consulting firm : an application of data driven techniques
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/10400.14/34745 |
Resumo: | Considering the competitive environment in which companies operate nowadays and the importance of customer relationship management (CRM), it is crucial to analyse customer-related data to gain knowledge and insights about them in order to increase their retention and company’s performance. The presented investigation resulted from a curricular internship carried out at Inova+, a management consulting firm specialised in supporting the growth of organizations. In this sense, the aim of this investigation is to support the CRM system and the customer’s management strategies of Inova+, contributing to the improvement and strengthening of relations between the company and its customers. For this purpose, a quantitative methodology using analytical tools, namely data mining tools, was adopted to study various dimensions of CRM. In this context, this investigation focused on four main aspects under analysis, which allowed to obtain a more detailed knowledge about the company's customers. Initially, the observation of KPIs regarding the CRM and the company's performance through the construction of dashboards. Secondly, a time-series forecasting model for prospective revenues was applied. Additionally, an identification of customer segments according to their purchasing behaviour through the application of a RFM model and a clustering analysis was carried out. Finally, significant factors that influence the probability of adjudication of a commercial proposal were identified, such as the country, type of organisation and economic sector of the client company, as well as the service associated. |
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Analytical CRM in a management consulting firm : an application of data driven techniquesB2BCustomer relationship managementData miningForecastingManagement consultingConsultoriaPrevisãoDomínio/Área Científica::Ciências Sociais::Economia e GestãoConsidering the competitive environment in which companies operate nowadays and the importance of customer relationship management (CRM), it is crucial to analyse customer-related data to gain knowledge and insights about them in order to increase their retention and company’s performance. The presented investigation resulted from a curricular internship carried out at Inova+, a management consulting firm specialised in supporting the growth of organizations. In this sense, the aim of this investigation is to support the CRM system and the customer’s management strategies of Inova+, contributing to the improvement and strengthening of relations between the company and its customers. For this purpose, a quantitative methodology using analytical tools, namely data mining tools, was adopted to study various dimensions of CRM. In this context, this investigation focused on four main aspects under analysis, which allowed to obtain a more detailed knowledge about the company's customers. Initially, the observation of KPIs regarding the CRM and the company's performance through the construction of dashboards. Secondly, a time-series forecasting model for prospective revenues was applied. Additionally, an identification of customer segments according to their purchasing behaviour through the application of a RFM model and a clustering analysis was carried out. Finally, significant factors that influence the probability of adjudication of a commercial proposal were identified, such as the country, type of organisation and economic sector of the client company, as well as the service associated.Considerando o ambiente competitivo em que as empresas operam atualmente e a importância do customer relationship management (CRM), é crucial analisar os dados relacionados com clientes para adquirir mais conhecimento e obter importantes insights sobre os mesmos, a fim de aumentar a sua retenção e o desempenho da empresa. A investigação apresentada resultou de um estágio curricular realizado na empresa Inova+, uma consultora especializada no apoio ao crescimento de organizações. Neste sentido, o objetivo desta investigação visa apoiar o sistema CRM e as estratégias de gestão de clientes da Inova+, contribuindo para a melhoria e fortalecimento das relações entre a empresa e os seus clientes. Para esse efeito, uma metodologia quantitativa utilizando ferramentas analíticas, nomeadamente ferramentas de data mining, foi adotada para estudar várias dimensões do CRM. Neste contexto, esta investigação focou-se em quatro aspetos principais em análise, que permitiram obter um conhecimento mais detalhado sobre os clientes da empresa. Inicialmente, a observação de KPIs relativos ao CRM e ao desempenho da empresa através da construção de dashboards. Em segundo lugar, foi aplicado um modelo de previsão de séries temporais relativo ao volume de negócios potencial. Adicionalmente, foram identificados segmentos de clientes de acordo com o seu comportamento de compra através da aplicação de um modelo RFM e foi desenvolvida uma análise de clustering. Por fim, foram identificados fatores significativos que influenciam a probabilidade de adjudicação de uma proposta comercial, tais como o país, tipo de organização e setor económico da empresa cliente, bem como o serviço associado.Silva, Vera Lúcia Miguéis Oliveira eVeritati - Repositório Institucional da Universidade Católica PortuguesaAmorim, Inês Oliveira2022-09-10T00:30:30Z2021-07-202021-052021-07-20T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10400.14/34745TID:202749339enginfo: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:RCAAP2023-07-12T17:40:15Zoai:repositorio.ucp.pt:10400.14/34745Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T18:28:10.303823Repositório 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 |
Analytical CRM in a management consulting firm : an application of data driven techniques |
title |
Analytical CRM in a management consulting firm : an application of data driven techniques |
spellingShingle |
Analytical CRM in a management consulting firm : an application of data driven techniques Amorim, Inês Oliveira B2B Customer relationship management Data mining Forecasting Management consulting Consultoria Previsão Domínio/Área Científica::Ciências Sociais::Economia e Gestão |
title_short |
Analytical CRM in a management consulting firm : an application of data driven techniques |
title_full |
Analytical CRM in a management consulting firm : an application of data driven techniques |
title_fullStr |
Analytical CRM in a management consulting firm : an application of data driven techniques |
title_full_unstemmed |
Analytical CRM in a management consulting firm : an application of data driven techniques |
title_sort |
Analytical CRM in a management consulting firm : an application of data driven techniques |
author |
Amorim, Inês Oliveira |
author_facet |
Amorim, Inês Oliveira |
author_role |
author |
dc.contributor.none.fl_str_mv |
Silva, Vera Lúcia Miguéis Oliveira e Veritati - Repositório Institucional da Universidade Católica Portuguesa |
dc.contributor.author.fl_str_mv |
Amorim, Inês Oliveira |
dc.subject.por.fl_str_mv |
B2B Customer relationship management Data mining Forecasting Management consulting Consultoria Previsão Domínio/Área Científica::Ciências Sociais::Economia e Gestão |
topic |
B2B Customer relationship management Data mining Forecasting Management consulting Consultoria Previsão Domínio/Área Científica::Ciências Sociais::Economia e Gestão |
description |
Considering the competitive environment in which companies operate nowadays and the importance of customer relationship management (CRM), it is crucial to analyse customer-related data to gain knowledge and insights about them in order to increase their retention and company’s performance. The presented investigation resulted from a curricular internship carried out at Inova+, a management consulting firm specialised in supporting the growth of organizations. In this sense, the aim of this investigation is to support the CRM system and the customer’s management strategies of Inova+, contributing to the improvement and strengthening of relations between the company and its customers. For this purpose, a quantitative methodology using analytical tools, namely data mining tools, was adopted to study various dimensions of CRM. In this context, this investigation focused on four main aspects under analysis, which allowed to obtain a more detailed knowledge about the company's customers. Initially, the observation of KPIs regarding the CRM and the company's performance through the construction of dashboards. Secondly, a time-series forecasting model for prospective revenues was applied. Additionally, an identification of customer segments according to their purchasing behaviour through the application of a RFM model and a clustering analysis was carried out. Finally, significant factors that influence the probability of adjudication of a commercial proposal were identified, such as the country, type of organisation and economic sector of the client company, as well as the service associated. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-07-20 2021-05 2021-07-20T00:00:00Z 2022-09-10T00:30:30Z |
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/10400.14/34745 TID:202749339 |
url |
http://hdl.handle.net/10400.14/34745 |
identifier_str_mv |
TID:202749339 |
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:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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