The Rise of Personalized Pricing: Are Companies Charging You More Based on Your Data?

The expectation that prices should be fixed is increasingly challenged. While fluctuations are accepted for time-sensitive items like flights or concert tickets based on demand, the idea that the price tag should represent the final cost for most goods is eroding. Businesses are leveraging technology to dynamically adjust prices, aiming to extract more revenue from consumers. A growing frontier in this practice involves using “black box” software and personalized data to set individual prices, often without consumers realizing it’s happening.

The McDonald’s Experiment

To investigate this trend, a team at Business Insider conducted an experiment in Manhattan. Six colleagues ordered the same Substantial Mac meal (Big Mac, medium fries and a drink) simultaneously from the same McDonald’s location. New York state recently enacted a law requiring companies to disclose the use of personalized algorithmic pricing, or “surveillance pricing,” but the implementation and clarity of these disclosures remain questionable.

The results were revealing: despite ordering the same items, each person was charged a slightly different amount. The base price of the Big Mac meal remained consistent, but the service fees varied between $3.25 and $3.45. Even two colleagues who had the same delivery driver paid different amounts. There was no discernible pattern based on demographics like age, income, or gender. The price difference, while small (15 to 20 cents), raised concerns about the transparency of pricing practices.

What Companies Say (and Don’t Say)

Uber, the delivery platform used in the experiment, stated via email that fee variations do not stem from a user’s personal characteristics. However, the company acknowledged that its app includes a disclaimer mandated by New York’s law, stating that the price is determined by an algorithm using personalized data, including location. This contradiction highlights the ambiguity surrounding algorithmic pricing.

Other companies, like Instacart, have also faced scrutiny. Consumer Reports and Groundwork Collaborative reported evidence of Instacart charging different customers varying prices for the same groceries. Instacart initially attributed these differences to testing but later pledged to discontinue the practice.¹

The Technology Behind Personalized Pricing

Oren Bar-Gill, a professor of law and economics at New York University, notes that companies are investing heavily in data collection and personalized information about consumers. A 2025 report from the Federal Trade Commission (FTC) mapped the technological ecosystem enabling algorithmic pricing, revealing the extent of experimentation with dynamic pricing models.²

Why It Matters – and Why It Might Not

While the price differences observed in the McDonald’s experiment were minimal, the potential for larger discrepancies raises concerns about a regressive redistribution of wealth, where those less aware of these practices end up paying more. The lack of transparency and the inability to understand *why* prices vary can also erode consumer trust.

However, some argue that dynamic pricing isn’t inherently negative. The law of supply and demand dictates that sellers will attempt to maximize revenue. Practices like happy hour and last-minute discounts can benefit consumers. The key issue is fairness and transparency.

The Risk of Backlash

Companies are aware of the potential for negative public reaction. Incidents involving Wendy’s and Delta, where discussions of dynamic pricing sparked customer outrage, demonstrate the sensitivity surrounding this issue. Arnab Sinha, head of Boston Consulting Group’s pricing practice, emphasizes the need for caution, warning that perceived unfairness can lead to reputational damage.

Looking Ahead

The trend toward personalized pricing is likely to continue as technology advances and data collection becomes more sophisticated. The challenge lies in finding a balance between leveraging data to optimize revenue and maintaining transparency and fairness for consumers. The question isn’t just “Why is your Big Mac more expensive than mine?” but “Why is your coat, hotel, apartment, and everything else priced specially for you and differently for me?”