Approximating Purchase Propensities and Reservation Prices from Broad Consumer Tracking

44 Pages Posted: 17 Jan 2020

See all articles by Benjamin Shiller

Benjamin Shiller

Brandeis University - Department of Economics

Multiple version iconThere are 2 versions of this paper

Date Written: November 5, 2018

Abstract

A consumer’s web-browsing history, now readily available, may be much more useful than demographics for both behaviorally targeting advertisements and personalizing prices. Using a method that combines economic modeling and powerful machine learning techniques, I find a striking difference. Using demographics yields purchase probabilities at observed prices ranging across individuals from about 8% to about 30%. Adding consumers’ web-browsing histories increases this range to about 5% to 90%, allowing more precise behavioral targeting. I further find that personalizing prices based on web browsing histories increases profits by 12.99% and results in some consumers paying substantially more than others for the same product. Using only demographics to personalize prices raises profits by only 0.25%, suggesting the percent profit gain from personalized pricing has increased 50-fold.

Keywords: First-Degree Price Discrimination, Price Discrimination, Big Data, Behavioral Targeting, Personalized Pricing, Algorithmic Pricing

JEL Classification: D42, L130

Suggested Citation

Shiller, Benjamin, Approximating Purchase Propensities and Reservation Prices from Broad Consumer Tracking (November 5, 2018). Available at SSRN: https://ssrn.com/abstract=3503079 or http://dx.doi.org/10.2139/ssrn.3503079

Benjamin Shiller (Contact Author)

Brandeis University - Department of Economics ( email )

Waltham, MA 02454-9110
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