Algorithmic pricing involves using automation to set prices dynamically based on a variety of factors, such as customer behavior, market conditions, and competition. This practice has been used extensively in the airline industry, where it is known as yield management, and is also common in other highly competitive industries such as travel and software. Algorithmic pricing can be implemented using a wide range of algorithms, from simple rules-based systems to complex machine learning models that are continually optimized through a/b testing. By using automation to adjust prices in real time, businesses can more effectively respond to changes in demand and competition, and can potentially improve their revenue and profits.

Some examples of algorithmic pricing in action include:

• Airlines using yield management systems to adjust ticket prices based on factors such as the number of seats available on a particular flight, the time until the flight departs, and the historical demand for that route
• Online retailers using pricing algorithms to adjust the prices of products in their catalogs based on factors such as the competition, the availability of the product, and the customer’s purchase history
• Ride-hailing companies using algorithms to adjust the prices of their services based on factors such as the demand for rides in a particular area, the availability of drivers, and the time of day

In each of these cases, the pricing algorithms are able to automatically adjust prices in real time based on data inputs, allowing the businesses to more effectively respond to changes in the market and maximize their revenue.

Algorithmic pricing may be unpopular with customers as people tend to value stability and fairness. Price changes based on everything a customer clicks tends to result in a schizophrenic customer experience. As such, brands that ambitiously optimize metrics such as conversion rate using pricing algorithms may miss big picture issues related to reputation, experience and loyalty. Aggressive price changes may also attract regulatory attention as an unfair business practice depending on the factors that are used in pricing. For example, changing the price could potentially be viewed as false advertising.