Abstract
This article presents a novel approach to handle customer attrition problem with knowledge discovery methods. The data mining is performed on the customer feedback data, which was labelled by means of temporal transactional invoice data in terms of customer activity. The problem was raised within industry-academia collaboration project at University of North Carolina at Charlotte by one of the companies from the heavy equipment repair industry. They expressed interest in gaining better insight into this problem, already having their own active CRM program implemented. The goal and motivation within this topic is to determine whether there are markers in the sales trends that might suggest a customer is getting ready to defect. Observing the behavior of customers who left a company, one might be able to identify customers who may leave as well.
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Tarnowska, K., Ras, Z. (2018). From Knowledge Discovery to Customer Attrition. In: Ceci, M., Japkowicz, N., Liu, J., Papadopoulos, G., Raś, Z. (eds) Foundations of Intelligent Systems. ISMIS 2018. Lecture Notes in Computer Science(), vol 11177. Springer, Cham. https://doi.org/10.1007/978-3-030-01851-1_40
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DOI: https://doi.org/10.1007/978-3-030-01851-1_40
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