Abstract
Identifying customers with a higher probability to leave a merchant (churn customers) is a challenging task for sellers. In this paper, we propose a system able to detect churner behavior and to assist merchants in delivering special offers to their churn customers. Two main goals lead our work: on the one hand, the definition of a classifier in order to perform churn analysis and, on the other hand, the definition of a framework that can be enriched with social information supporting the merchant in performing marketing actions which can reduce the probability of losing those customers. Experimental results of an artificial and a real datasets show an increased value of accuracy of the classification when random forest or decision tree are considered.
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Birtolo, C., Diessa, V., De Chiara, D., Ritrovato, P. (2013). Customer Churn Detection System: Identifying Customers Who Wish to Leave a Merchant. In: Ali, M., Bosse, T., Hindriks, K.V., Hoogendoorn, M., Jonker, C.M., Treur, J. (eds) Recent Trends in Applied Artificial Intelligence. IEA/AIE 2013. Lecture Notes in Computer Science(), vol 7906. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38577-3_42
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DOI: https://doi.org/10.1007/978-3-642-38577-3_42
Publisher Name: Springer, Berlin, Heidelberg
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