Abstract
One of the most important business decisions is how to acquire customers. Indeed, whatever the size of the company, it is faced with the problem of limited resources. Therefore, it is necessary to know which customers are worthy of marketing activities and efforts and which are not. Knowing the journeys and characteristics of customers that lead to successful sales would allow businesses to optimize their spending by targeting those likely to make purchases. Customer prioritization involves assigning a score (i.e., a buying probability) to each possible lead generated for the business. An accurate scoring process can help marketing and sales teams prioritize and respond appropriately to selected leads in an optimal time frame, increasing their propensity to become customers. The purpose of this article is to develop a new automated method to prioritize customers. A complete process for implementing a prioritization solution is described. We present experiments that show positive results using a real-world dataset.
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Hadid, A.B., Kheddouci, H., Hadjadj, S. (2023). A New Automated Customer Prioritization Method. In: Dorronsoro, B., Chicano, F., Danoy, G., Talbi, EG. (eds) Optimization and Learning. OLA 2023. Communications in Computer and Information Science, vol 1824. Springer, Cham. https://doi.org/10.1007/978-3-031-34020-8_32
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DOI: https://doi.org/10.1007/978-3-031-34020-8_32
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