Deep reinforcement learning (DRL) has opened up many unprecedented opportunities in revolutionizing the digital marketing field. In this study, we designed a DRL-based personalized targeting strategy. We show that it can address four important challenges in this area. 1) Sequential-decisions:...

Consumer location tracking is becoming omnipresent on mobile devices, producing massive volumes of behavior-rich location data and an elaborate multi-billion dollar ecosystem consisting of consumers providing data, third-party data collectors aggregating data, and advertisers using the data for...

The proliferation of cameras and their video data in retail marketing presents new opportunities for academics to study customer behavior with the newer video analytics tools. In collaboration with a large retail chain store in Asia, we obtained a unique video dataset collected from in-store...

Artificial intelligence (AI) presents opportunities to revolutionize financial services. In the current study, we focused on the microloan debt-collection context wherein collectors usually follow a strict sequence of “harsh” debt-collection actions, such as notifying borrowers' social...

In this paper, we explore how keyword ambiguity can affect search advertising performance. Consumers arrive at search engines with diverse interests, which are often unobserved and nontrivial to predict. The search interests of different consumers may vary even when they are searching using the...

Rapid improvements in the precision of mobile technologies make it possible for advertisers to go beyond using the real-time static location and contextual information about consumers. In this study, we propose a novel “trajectory-based” targeting strategy for mobile recommendation that...