Learning about the customer for improving customer retention proposal of an analytical framework

• Autor(a) principal: Simões, Dora
• Data de Publicação: 2022
• Outros Autores: Nogueira, Joana
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10773/39159
• topic: Customer relationship management; Customer segmentation; Business-to-business; RFM metric; Data mining analysis; ABC curve

The market faces new challenges in retaining customers, since they have very high expectations, which translate into the demand for a swift response and intransigence to empty promises on the part of brands. These requirements result from the ability to disseminate and infuse information, which in turn makes customers more informed, more participative, and more uncompromising. This change in behavior implies redesigning the strategic management of the brands, in terms of the relationship with the customer. In view of this challenge, the relevance of developing an adequate diferentiation model for customer retention prevails. Based on this premise, this paper presents a proposal based on RFM and ABC analytical methods applied to customer relationship management and contextualized in a particular case of the printing industry. The proposed model deines a set of metrics aimed at customer segmentation, which improves the customers knowledge. The outcomes will allow to deine more assertive marketing strategies for customer loyalty and to increase the volume of a brand’s revenue.