Behavior-Based Pricing strategy of quality-differentiated products with imperfect customer recognition capability

The development of data technology has enabled firms to identify and analyze consumers’ purchase history and classify them into new and old customers for price discrimination. However, this type of price discrimination tends to cause customer dissatisfaction and lead to resistance against firms’ data-driven pricing practices. Consequently, it challenges firms’ customer recognition capability. This paper develops a two-period pricing model in which two firms, differing in product quality, investigate the impact of behavior-based pricing (BBP) on firms with varying quality levels when they possess imperfect customer recognition capability. We find, first, that imperfect customer recognition capability causes different effects on price in each period for firms of different quality, depending on the level of product quality differentiation. Second, quality advantages do not always lead to more markets for high-quality firms; low-quality firms are also in a position to gain more markets. Third, due to firms’ customer recognition capability and quality differentiation, when both firms adopt BBP, they will both achieve higher profits and reach a ”win–win” situation. Conversely, if only one firm adopts BBP, it will result in reduced profitability for both firms, leading to a ”lose–lose” scenario. Finally, we have examined consumer surplus and social welfare, and the findings provide a theoretical foundation and policy recommendations for governments to develop regulatory measures against price discrimination in the digital economy era.