Identifying early buyers from purchase data

Market research has shown that consumers exhibit a variety of different purchasing behaviors; specifically, some tend to purchase products earlier than other consumers. Identifying such early buyers can help personalize marketing strategies, potentially improving their effectiveness. In this paper, we present a non-parametric approach to the problem of identifying early buyers from purchase data. Our formulation takes as inputs the detailed purchase information of each consumer, with which we construct a weighted directed graph whose nodes correspond to consumers and whose edges correspond to purchases consumers have in common; the edge weights indicate how frequently consumers purchase products earlier than other consumers. Identifying early buyers corresponds to the problem of finding a subset of nodes in the graph with maximum difference between the weights of the outgoing and incoming edges. This problem is a variation of the maximum cut problem in a directed graph. We provide an ...

• Type: Conference
• Year: 2004
• Where: KDD
• Authors: Paat Rusmevichientong, Shenghuo Zhu, David Selinger
• Keywords: Consumers Purchase Products, Data Mining, KDD 2004, Maximum Cut Problem, Weighted Directed Graph