Why do firms collect data on customers? A behavior-based price discrimination approach

Abstract

This thesis discusses the collection of customer data and its potential use in price discrimination. I survey the current literature on behavior-based price discrimination to understand its implications to firms’ profitability. Focus is given to homogenous, non-durable good duopolies to investigate the competitive effects of customer recognition. As the objective is to understand why firms invest in the collection of customer data, welfare analysis is left outside the scope of the thesis.

The thesis also discusses two constraints that may have significant impact on the firms’ ability to discriminate. Firstly, customers’ view of fairness may provoke strong objection against behavior-based pricing. Secondly, the ability to anonymize or hide true identity creates arbitrage similar to second-hand markets.

Profitability of behavior-based price discrimination is strongly dependent on the assumptions of the models. With symmetric information about symmetric demands, firms are shown to be strictly worse off compared to uniform price regime. As both firms have unilateral incentive to implement behavior-based price discrimination, the model represents a classic prisoner’s dilemma.

However, less strict symmetry assumptions enable more diverse outcomes. This thesis discusses separately the importance of asymmetric demand and asymmetric information. The aforementioned appears to foster the ability to generate profitable discrimination, but results are ambiguous and leave still much to answer. The latter is the most recent field of research in behavior-based price discrimination. Again, the results are not conclusive and there is much to examine. I believe this direction to foster the most fruitful research in the coming years.