Setting different prices for the same product is a practice as old as the retail trade: we see this everyday, whether through price reductions for youths, air ticket prices varying according to the dates they are booked, or prices differentiating depending on the store location. These practices of “price discrimination” have so far been accepted by consumers because they remain fairly simple to justify: young people pay less for certain services because they are on average less wealthy than adults; similarly, when buying an airline ticket, everyone knows that the consumer can benefit from a low price by booking early. Previously, the usual price discrimination did not concern the characteristics of individuals but rather broad statistical categories such as age or location. However, with the development of digital technology, price discrimination could take a decisive step forward tomorrow, by encouraging firms to charge personalised prices: thanks to Big Data, each customer will be offered a specific price depending on their individual willingness to pay. The era of uniform pricing, on which all retail trade has been based for more than a century, could gradually give way to a world of personalised prices. While this practice would be very profitable for businesses, it could nevertheless lead to customer distrust: customers often do not know which criteria were used by the algorithms to establish pricing. It is therefore with caution that companies should explore personalised pricing, through subtle and indirect practices, such as targeted discounts or a differentiated display of the results of an internet search (“price steering”).