Algorithmic pricing

Algorithmic pricing is the practice of automatically setting the requested price for items for sale, in order to maximize the seller's profits.

Dynamic pricing algorithms usually rely on one or more of the following data.

• Probabilistic and statistical information¹ on potential buyers; see Bayesian-optimal pricing.
• Prices of competitors. E.g., a seller of an item may automatically detect the lowest price currently offered for that item, and suggest a price within $1 of that price.²³ Automated technology applications for pricing differ among competitors which makes price discovery highly complex and dynamic in the general retail marketplace.⁴⁵ Retailers and technology vendors claim the adoption of new pricing tools continues to be dependent on their consumer's price sensitivity and trust that it will not be working against them.⁶

Personal information of the currently active buyer, such as her or his demographics and her or his interest in the product. If the seller detects that you are about to buy, your price goes up.⁷

• Business information of the seller, such as the expected date in which he or she is going to receive new stocks, or her or his target selling velocity in units per day.⁸