Customer targeting models using data mining techniques

• Autor(a) principal: Cernaut, Oana-Maria
• Data de Publicação: 2019
• Tipo de documento: Dissertação
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10773/30010
• topic: B2B segmentation; Data-driven marketing; K-means clustering; Artificial neural networks

In recent years, the segmentation process has undergone numerous changes, once with the advances in data mining. Knowledge discovery can automatize and provide better insights into customer trends and dynamics. The objective of the paper is to improve the quality of the marketing segmentation for company T. More specifically, the research question it plans to answer is whether data mining techniques deliver a better segmentation model than intuitive approaches. The segmentation steps comprise the identification of the necessary variables, the selection of the relevant ones to conduct the segmentation and the usage of artificial neural networks to predict future outcomes. To this end, the work makes use of web scraping (based on Google searches), K-means clustering and artificial neural networks.