  The online advertising management platform has become increasingly popular
among e-commerce vendors/advertisers, offering a streamlined approach to reach
target customers. Despite its advantages, configuring advertising strategies
correctly remains a challenge for online vendors, particularly those with
limited resources. Ineffective strategies often result in a surge of
unproductive ``just looking'' clicks, leading to disproportionately high
advertising expenses comparing to the growth of sales. In this paper, we
present a novel profit-maximing strategy for targeting options of online
advertising. The proposed model aims to find the optimal set of features to
maximize the probability of converting targeted audiences into actual buyers.
We address the optimization challenge by reformulating it as a multiple-choice
knapsack problem (MCKP). We conduct an empirical study featuring real-world
data from Tmall to show that our proposed method can effectively optimize the
advertising strategy with budgetary constraints.
