Dynamic pricing

Dynamic pricing, also referred to as surge pricing, demand pricing, or time-based pricing is a pricing strategy in which businesses set flexible prices for products or service based on current market demands.^[1] Businesses are able to change prices based on algorithms that take into account competitor pricing, supply and demand, and other external factors in the market.^[2] Dynamic pricing is a common practice in several industries such as hospitality, travel, entertainment, retail, electricity, and public transport. Each industry takes a slightly different approach to repricing based on its needs and the demand for the product.

Hospitality

Time-based pricing is the standard method of pricing in the tourism industry. Higher prices are charged during the peak season, or during special-event periods. In the off-season, hotels may charge only the operating costs of the establishment, whereas investments and any profit are gained during the high season. (This is the basic principle of the long run marginal cost (LRMC) pricing, see also Long run).

Hotels and other players in the hospitality industry use dynamic pricing to adjust the cost of rooms and packages based on the supply and demand needs at a particular moment.^[3] The goal of dynamic pricing in this industry is to find the highest price that consumers are willing to pay. Another name for dynamic pricing in the industry is demand pricing. This form of price discrimination is used to try to maximize revenue based on the willingness to pay of different market segments. It features price increases when demand is high and decreases to stimulate demand when it is low. Having a variety of prices based on the demand at each point in the day makes it possible for hotels to generate more revenue by bringing in customers at the different price points they are willing to pay.

Transportation

Airlines change prices often depending on the day of the week, time of day, and number of days before the flight.^[4] For airlines, dynamic pricing factors in different components such as: how many seats a flight has, departure time, and average cancellations on similar flights.^[5]

Congestion pricing is often used in public transportation and roadways, where a higher price at peak periods is used to encourage more efficient use of the service or time-shifting to cheaper or free off-peak travel. For example, the San Francisco Bay Bridge charges a higher toll during rush hour and on the weekend, when drivers are more likely to be travelling.^[6] This is an effective way to boost revenue when demand is high, while also managing demand since drivers unwilling to pay the premium will avoid those times. The London congestion charge discourages automobile travel to Central London during peak periods. The Washington Metro and Long Island Rail Road charge higher fares at peak times.

Dynamic pricing is also practiced by on-demand transportation network companies such as Uber and Lyft.^[7] Uber's system for "dynamically adjusting prices for service" measures supply (Uber drivers) and demand (passengers hailing rides by use of smartphones), and prices fares accordingly.^[8]

Professional sports

Some professional sports teams use dynamic pricing structures to boost revenue. Dynamic pricing is particularly important in baseball because MLB teams play around twice as many games as some other sports and in much larger venues.^[9]

Sports that are outdoors have to factor weather into pricing strategy, in addition to date of the game, date of purchase, and opponent.^[10] Tickets for a game during inclement weather will sell better at a lower price; conversely, when a team is on a winning streak, fans will be willing to pay more.

Dynamic pricing was first introduced to sports by a start-up software company from Austin, Texas, Qcue and Major League Baseball club San Francisco Giants. The San Francisco Giants implemented a pilot of 2,000 seats in the View Reserved and Bleachers and moved on to dynamically pricing the entire venue for the 2010 season. Qcue currently works with two-thirds of Major League Baseball franchises, not all of which have implemented a full dynamic pricing structure, and for the 2012 postseason, the San Francisco Giants, Oakland Athletics, and St. Louis Cardinals became the first teams to dynamically price postseason tickets. While behind baseball in terms of adoption, the National Basketball Association, National Hockey League, and NCAA have also seen teams implement dynamic pricing. Outside of the U.S., it has since been adopted on a trial basis by some clubs in the Football League.^[11] Scottish Premier League club Heart of Midlothian introduced dynamic pricing for the sale of their season tickets in 2012, but supporters complained that they were being charged significantly more than the advertised price.^[12]

Retail

Retailers, and online retailers in particular, adjust the price of their products according to competitors, time, traffic, conversion rates, and sales goals.^[13] The aim of dynamic pricing is to increase revenue and profit. There are three basic ways to do this.

• First, retailers can use price intelligence to reprice based on the prices of their competitors.
• Second, retailers can drop prices when demand is low.
• Third, retailers can increase prices while demand is high.

Amazon.com

Amazon.com engaged in price discrimination for some customers in the year 2000, showing different prices at the same time for the same item to different customers, potentially violating the Robinson–Patman Act.^[14] The company stopped and apologised after it was discovered.

Some third-party sellers in the Amazon Marketplace use software to change prices more frequently than would be feasible for people to do, in order to compete for business on price.^[15][16]

Pricing based on value or elasticity

Ideally, companies should ask the price for a product which is equal to the value a consumer attaches to a product. This is called value-based pricing. As this value can differ from person to person, it is difficult to uncover the perfect value and have a differentiated price for every person. However, consumer's willingness-to-pay can be used as a proxy for the perceived value. With the price elasticity of products, companies can calculate how many consumers are willing to pay for the product at each price point. Products with high elasticities are highly sensitive to changes in price, while products with low elasticities are less sensitive to price changes (ceteris paribus). Subsequently, products with low elasticity are typically valued more by consumers if everything else is equal. The dynamic aspect of this pricing method is that elasticities change with respect to product, category, time, location and retailers. With the price elasticity of products the margin of the product, retailers can use this method with their pricing strategy to aim for volume, revenue or profit maximization strategies. ^[17]

Pricing based on competitors

Businesses that want to price competitively will monitor their competitors’ prices and adjust accordingly. Amazon is a market leader in retail that changes prices often,^[18] which encourages other retailers to alter their prices to stay competitive. Competitor-based dynamic pricing can increase sales, especially if they take advantage when other retailers run out of stock.

Time-based retail pricing

Many industries change prices depending on the time of day, especially online retailers, whose customers usually shop the most in during weekly office hours between 9AM-5PM.^[19] Raising prices during the morning and afternoon and lowering prices during the evening is a common practice with dynamic pricing.

Time-based utility pricing

Time-based pricing of services such as provision of electric power includes, but is not limited to:^[20]

• Time-of-use pricing (TOU pricing), whereby electricity prices are set for a specific time period on an advance or forward basis, typically not changing more often than twice a year. Prices paid for energy consumed during these periods are preestablished and known to consumers in advance, allowing them to vary their usage in response to such prices and manage their energy costs by shifting usage to a lower cost period or reducing their consumption overall (demand response)
• Critical peak pricing whereby time-of-use prices are in effect except for certain peak days, when prices may reflect the costs of generating and/or purchasing electricity at the wholesale level
• Real-time pricing whereby electricity prices may change as often as hourly (exceptionally more often). Price signal is provided to the user on an advanced or forward basis, reflecting the utility's cost of generating and/or purchasing electricity at the wholesale level; and
• Peak load reduction credits for consumers with large loads who enter into pre-established peak load reduction agreements that reduce a utility's planned capacity obligations.

A utility with regulated prices may develop a time-based pricing schedule on analysis of its cost on a long-run basis, including both operation and investment costs. A utility operating in a market environment, where electricity (or other service) is auctioned on a competitive market, time-based pricing will typically reflect the price variations on the market. Such variations include both regular oscillations due to the demand pattern of users, supply issues (such as availability of intermittent natural resources: water flow, wind), and occasional exceptional price peaks.

Price peaks reflect strained conditions on the market (possibly augmented by market manipulation, as during the California electricity crisis) and convey possible lack of investment.

Conversion rate pricing

Conversion rates measure how many browsers on a website turn into buyers. When conversion rates of viewers to buyers is low, dropping the price to increase conversions is standard with a dynamic pricing strategy.

References

See also

• Price discrimination
• Hedonic regression
• Pay what you want
• Variable pricing
• Futures contract

External links

• Dynamic Pricing software for retail
• In Praise of Efficient Price Gouging (2014-08-19), MIT Technology Review