Selecting Valuable Customers for Merchants in E-Commerce Platforms

An e-commerce website provides a platform for merchants to sell products to customers. While most existing research focuses on providing customers with personalized product suggestions by recommender systems, in this paper, we consider the role of merchants and introduce a parallel problem, i.e., how to select the most valuable customers for a merchant? Accurately answering this question can not only help merchants to gain more profits, but also benefit the ecosystem of e-commence platforms. To deal with this problem, we propose a general approach by taking into consideration the interest and profit of each customer to the merchant, i.e., select the customers who are not only interested in the merchant to ensure the visit of the merchant, but also capable of making good profits. Specifically, we first generate candidate customers for a given merchant by using traditional recommendation techniques. Then we select a set of the valuable customers from candidate customers, which has the balanced maximization between the interest and the profit metrics. Given the NP-hardness of the balanced maximization formulation, we further introduce efficient techniques to solve this maximization problem by exploiting the inherent submodularity property. Finally, extensive experimental results on a real-world dataset demonstrate the effectiveness of our proposed approach.