Efficiency vs. Fairness: The Price of Personalization

What if the price you see online when you’re making a purchase isn’t the real price, just the one the algorithm thinks you will accept? Personalized pricing is present in our daily lives, from flight tickets and hotel rooms to food delivery and ride-sharing services. Every time we browse, click, or linger on a product, we create an online trail that businesses use to determine our willingness to pay. What used to be a simple purchase is becoming a private negotiation between you and a machine that knows you better than you think.

Personalization in pricing strategies offers a range of benefits for both businesses and consumers. We may get better deals that allow us to save money and time as well, and if done with transparency, it builds a relationship of trust and loyalty between the customer and the brand. For companies, they get increased revenue, a competitive advantage, and valuable data about customer behavior.

Online platforms collect data, such as your purchase history, location, device type and demographics. These are used to engage in price discrimination, meaning charging different prices to different consumers for the same product or service. Economically speaking, this can increase efficiency since prices are based on each customer's willingness to pay, generating higher revenue and also enhanced customer satisfaction. However, in practice, it often increases producer surplus at the expense of consumer surplus.

Imagine two friends buying tickets online for the same concert. One has been looking for similar events all week long, so the algorithm perceives interest and shows a price of €85. The other friend goes online for the first time through a discount link and gets the price of €70. Both make the purchase and are happy until they compare costs. Two friends paying different prices for the same thing feels wrong. Since customers will walk away if pricing feels unfair, this reseller could lose a loyal customer.

BCG conducted a global survey with 23,000 consumers, and two-thirds of them say that they’ve recently had a personalized experience with a brand which was invasive or inaccurate. In many of these cases, it caused the customers to unsubscribe and disengage with the brand.

Behavioral economics allows us to analyze why people react so strongly to personalized pricing. It is all about fairness perception. Consumers would rather pay a higher price than being tricked by an algorithm. For us, efficiency is not the main concern, but equality is.

Furthermore, personalized pricing can unintentionally reinforce inequality. People who live in wealthier areas may see higher prices because of the willingness to pay. As well as that, owning newer devices can raise your profile price. Meanwhile, low-income users may still receive higher prices if algorithms make mistakes and misread spending patterns.

Governments and regulatory bodies have started responding. In the European Union, the Omnibus Directive obliges companies to disclose to consumers when they are using personalized pricing or automated decision-making. Noncompliance to any of the obligations set may result in substantial fines.

Economics shows us that efficient markets don’t always mean fair markets. Next time you click shop now, remember that someone might be getting a better offer and not because they’re lucky, but because the algorithm thinks they should. As artificial intelligence becomes more advanced, it makes us wonder what are the future personalization techniques that companies will use. Could consumers even get the option to bargain back or will the market tilt toward those who control the algorithms?