Approximating Purchase Propensities and Reservation Prices from Broad Consumer Tracking

Abstract

A consumer's web‐browsing history, now readily available, may be much more useful than demographics for both targeting advertisements and personalizing prices. Using a method that combines economic modeling and machine learning methods, I find a striking difference. Personalizing prices based on web‐browsing histories increases profits by 12.99%. Using demographics alone to personalize prices raises profits by only 0.25%, suggesting the percent profit gain from personalized pricing has increased 50‐fold. I then investigate whether regulations intended to prevent price gouging increase aggregate consumer surplus. Two feasible regulations considered offer at best modest improvements.