Conjoint analysis is an ubiquitous market research tool. As normally implemented, each time you wish to understand consumer utilities for a product category, you run a conjoint study for that category. For example, if you require consumer preferences for yogurt features, you run a (choice-based)...

Marketing researchers have become increasingly interested in spatial datasets. A main challenge of analyzing spatial data is that researchers must a priori choose the size and make-up of the areal units, hence the resolution of the analysis. Analyzing the data at a resolution that is too high...

Car purchases are among the largest and most expensive purchases consumers ever make. While functional and economic concerns are obviously important, we examine whether social influence also plays a role. Using a Bayesian probability model along with data on over 1.6 million cars sold over a...

We utilize household production theory to address the problem of micro-level demand estimation across complementary goods. According to this theory, consumers buy inputs and combine them to produce final goods from which they derive utility. We use this idea to build a structural model of demand...

While single-brand reward programs encourage customers to remain loyal to that one brand, coalition programs encourage customers to be “promiscuous” by offering points redeemable across partner stores. Despite the benefits of this “open relationship” with customers, store managers face...

A sequence of bids in Internet auctions can be viewed as record breaking events in which only those data points that break the current record are observed. We investigate stochastic versions of the classical record breaking problem for which we apply Bayesian estimation to predict observed bids...

Targeting individual consumers has become a hallmark of direct and digital marketing, particularly as it has become easier to identify customers as they interact repeatedly with a company. However, across a wide variety of contexts and tracking technologies, companies find that customers can not...

Modern businesses routinely capture data on millions of observations across subjects, brand SKUs, time periods, predictor variables, and store locations, thereby generating massive high-dimensional datasets. For example, Netflix has choice data on billions of movies selected, user ratings, and...