Your Browsing History May Cost You: A Framework for Discovering Differential Pricing in Non-Transparent Markets

In many online markets we “shop alone” — there is no way for us to know the prices other consumers paid for the same goods. Could this lack of price transparency lead to differential pricing? To answer this question, we present a generalized framework to audit online markets for differential pricing using automated agents. Consensus is a key idea in our work: for a successful black-box audit, both the experimenter and seller must agree on the agents’ attributes. We audit two competitive online travel markets on kayak. com (flight and hotel markets) and construct queries representative of the demand for goods. Crucially, we assume ignorance of the sellers’ pricing mechanisms while conducting these audits. We conservatively implement consensus with nine distinct profles based on behavior, not demographics. We use a structural causal model for price differences and estimate model parameters using Bayesian inference. We can unambiguously show that many sellers (but not all) demonstrate behavior-driven differential pricing. In the flight market, some profles are nearly 90% more likely to see a worse price than the best performing profle, and nearly 60% more likely in the hotel market. While the control profle (with no browsing history) was on average offered the best prices in the flight market, surprisingly, other profles outperformed the control in the hotel market. The price difference between any pair of profles occurring by chance is $ 0.44 in the flight market and $ 0.09 for hotels. However, the expected loss of welfare for any profle when compared to the best profle can be as much as $ 6.00 for flights and $ 3.00 for hotels (i.e., 15× and 33× the price difference by chance respectively). This illustrates the need for new market designs or policies that encourage more transparent market design to overcome differential pricing practice

Recommended citation: Karan, A., Balepur, N., & Sundaram, H. (2023, June). Your Browsing History May Cost You: A Framework for Discovering Differential Pricing in Non-Transparent Markets. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (pp. 717-735).
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