Uplift Model-Based Targeting Methods for Enhancing Mobile Advertising Efficiency

Personalized advertising strategies are becoming increasingly important to enhance the effectiveness of mobile advertising, which has recently been used as a key marketing tool by companies. In this study, we propose an optimal targeting method by utilizing Uplift modeling based on consumer features and behavioral data. In particular, consumers are classified into four types to identify customer segments and suggest ways to maximize the actual impact of mobile advertising. By doing so, the study aims to establish the most effective advertising messages and delivery methods, ultimately contributing to improving companies' ROI through personalized advertising strategies.