Pricing with Cookies: Behavior-Based Price Discrimination and Spatial Competition

Abstract

We study a two-period model of spatial competition with two symmetric firms where firms learn customers' preferences from the first-period purchase, which they use for personalized pricing in the second period. With product choice exogenously fixed with maximal differentiation, we show that there exist two asymmetric equilibria and customer switching is only from one firm to the other unless firms discount future too much. Firms are worse off with such personalized pricing than when they use pricing at higher levels of aggregation. When product choice is also made optimally, there continue to exist two asymmetric equilibria given sufficiently small discounting, none of which features maximal differentiation. More customer information hurts firms, and more so when they make both product choice and pricing decisions.

Mapping the Ethicality of Algorithmic Pricing: A Review of Dynamic and Personalized Pricing

“…Contrary to dynamic pricing, ethical issues of personalized pricing have triggered a broader public and scholarly debate (see, e.g., Amazon's experiments with personalized pricing as the most publicized negative example in the year 2000, Choe et al 2018). Personalized pricing goes beyond demand estimations of groups toward the demand of the individual (Obermiller et al 2012).…”

“…Customer information is a valuable revenue source, as it can help firms to identify individual preferences and personalize the price (Choe et al 2018;Cohen 2018). Equipped with such detailed profiles, firms can, for instance, manipulate customers via personalized emotional pitches to increase their consumption and willingness to accept a certain price (Amaldoss and He 2019;Townley et al 2017).…”

Behavior-Based Pricing of Organic and Conventional Agricultural Products Based on Green Subsidies

“…With the rapid development of information technology, enterprises can now track and store information about the purchase history of individual customers, such as location, preference, and so on, through information tracking tools. Acquiring such information makes it feasible for enterprises to set behavior-based pricing [6]; enterprises divide consumers into "loyal customers" and "poaching customers" [7]. For "loyal customers" and "poaching customers", the enterprise will implement different degrees of premium or discount as per their historical purchase information [8,9].…”

“…Substituting Equations (1), (2), (3), and (4) into equations (5) and (6), and solving the Nash equilibrium, it is clear that the Nash equilibrium price now is * = 2 As shown in Figures 1 and 2, the profits of Firm G and Firm L can be defined as follows:…”

Quality and Price Personalization under Customer Recognition: a Dynamic Monopoly Model

“…Mason, 2000; Laussel, Long, and Resende, 2015). 8 In the context of non-renewable resource markets, various authors have shown that the lack of ability to commit may reduce monopoly pro…t, or make monopoly power disadvantageous (Kemp and Long, 1980;Maskin and Newbery, 1990). Similarly, the macroeconomic literature is abound with the disadvantages of governmental "discretion" as compared to "rule" (Kydland and Prescott, 1977).…”