Publicação
Customer clustering in the health insurance industry by means of unsupervised machine learning
| Resumo: | 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. |
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| Autores principais: | Zaqueu, Jéssica Raquel |
| Assunto: | Segmentation Clustering Customer Analytics Customer Clustering Customer Segmentation Insurance Unsupervised learning KMeans Decision Trees Data Mining Customer Behaviour Health Insurance |
| Ano: | 2019 |
| País: | Portugal |
| Tipo de documento: | dissertação de mestrado |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade Nova de Lisboa |
| Idioma: | inglês |
| Origem: | Repositório Institucional da UNL |
| Resumo: | 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. |
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