In today's turbulent business environment, customer retention presents a significant challenge for many service companies. Academics have generated a large body of research that addresses part of that challenge – with a particular focus on predicting customer churn. However, several other...

The goal of causal classification is to identify individuals whose outcome would be positively changed by a treatment. Examples include targeting advertisements and targeting retention incentives to reduce churn. Causal classification is challenging because we observe individuals under only one...

This position paper is about methods for effective, privacy-friendly mobile advertising. Specifically, we propose a new social-targeting design for using consumer location data from mobile devices (smartphones, smart pads, laptops, etc.) to target advertisements in a manner that is both...

The emergence of online paid crowdsourcing platforms, such as Amazon Mechanical Turk (AMT), presents us huge opportunities to distribute tasks to human workers around the world, on-demand and at scale. In such settings, online workers can come and complete tasks posted by a company, and work for...

The increasing availability of massive data on users' online behavior presents exciting opportunities for business analytics. In particular, if we could model the distributions of interests of visitors to webpages (or websites), we could apply the result to applications including site...

A main goal of online display advertising is to drive purchases (etc.) following ad engagement. However, there often are too few purchase conversions for campaign evaluation and optimization, due to low conversion rates, cold start periods, and long purchase cycles (e.g., with brand...

Recent studies show the remarkable power of information disclosed by users on social network sites to infer the users' personal characteristics via predictive modeling. In response, attention is turning increasingly to the transparency that sites provide to users as to what inferences are drawn...

TV viewership data available at the individual set-top box level has enabled new methods for estimating the demographics of shows' audiences, but it is impossible to tell with certainty which household members are watching TV in multi-person households. We address this problem through four main...

Dimensionality Reduction (DR) is frequently employed in the predictive modeling process with the goal of improving the generalization performance of models. This paper takes a design science perspective on DR.We treat it as an important business analytics artifact and investigate its utility in...