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 |
Files in This Item:
File | Description | Size | Format | |
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Dissertação_MariaCernaut.pdf | 2.1 MB | Adobe PDF | View/Open |
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