Please use this identifier to cite or link to this item: http://hdl.handle.net/10773/30010
Title: Customer targeting models using data mining techniques
Author: Cernaut, Oana-Maria
Advisor: Albergaria, José Manuel Almeida Lima Soares de
Keywords: B2B segmentation
Data-driven marketing
K-means clustering
Artificial neural networks
Defense Date: 23-May-2019
Abstract: 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.
URI: http://hdl.handle.net/10773/30010
Appears in Collections:UA - Dissertações de mestrado
ISCA-UA - Dissertações de mestrado

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