Please use this identifier to cite or link to this item: http://hdl.handle.net/10362/89468
Title: Customer clustering in the health insurance industry by means of unsupervised machine learning
Author: Zaqueu, Jéssica Raquel
Advisor: Vanneschi, Leonardo
Rufino, André
El-Jawhari, Anwar
Keywords: Segmentation
Clustering
Customer Analytics
Customer Clustering
Customer Segmentation
Insurance
Unsupervised learning
KMeans
Decision Trees
Data Mining
Customer Behaviour
Health Insurance
Defense Date: 19-Nov-2019
Abstract: To ensure competitiveness and relevancy in today’s highly digitised world, companies need to ensure that their focus is continuously on the client and on the experience they provide – while not having a negative effect on the organisation’s bottom line. A crucial step to achieving this is to get to know one’s customer base. With the vast amount of data available in a health insurance company, they are able to leverage on unsupervised machine learning techniques to segment their customers. This enables organisations to have a more tailored approach to their customers, identify market growth opportunities and gain competitive advantage.
Description: Internship Report presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics
URI: http://hdl.handle.net/10362/89468
Designation: Mestrado em Métodos Analíticos Avançados
Appears in Collections:NIMS - Dissertações de Mestrado em Ciência de Dados e Métodos Analíticos Avançados (Data Science and Advanced Analytics)

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