Discreet Personalized Pricing
Benjamin R. Shiller
No 10025, CESifo Working Paper Series from CESifo
Abstract:
Emerging tracking data allow precise predictions of individuals’ reservation values. However, firms are reluctant to conspicuously implement personalized pricing because of concerns about consumer and regulatory reprisals. This paper proposes and applies a method which disguises personalized pricing as dynamic pricing. Specifically, a firm can sometimes tailor the “posted” price for the arriving consumer but privately commits to change price infrequently. Note such pricing may unintentionally arise through algorithmic pricing. I examine outcomes in four contexts: one empirical and three hypothetical distributions of consumer valuations. I find that this strategy is most intense and raises profits most for medium popularity products. Furthermore, improvements in the precision of individual-level demand estimates raise the range of popularities this strategy can be profitably applied to. I conclude that this is an auspicious strategy for online platforms, if not already secretly in use.
Keywords: personalized pricing; algorithmic pricing; price discrimination; targeted pricing; behavioural pricing; dynamic pricing; sticky pricing (search for similar items in EconPapers)
JEL-codes: D40 L10 L81 (search for similar items in EconPapers)
Date: 2022
New Economics Papers: this item is included in nep-com, nep-ind, nep-pay and nep-reg
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Citations: View citations in EconPapers (1)
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Persistent link: https://EconPapers.repec.org/RePEc:ces:ceswps:_10025
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