Dynamic pricing, also referred to as surge pricing, demand pricing, time-based pricing and variable pricing, is a revenue management pricing strategy in which businesses set flexible prices for products or services based on current market demands. It usually entails raising prices during periods of peak demand and lowering prices during periods of low demand.
As a pricing strategy, it encourages consumers to make purchases during periods of low demand (such as buying tickets well in advance of an event or buying meals outside of lunch and dinner rushes) and disincentivizes them during periods of high demand (such as using less electricity during peak electricity hours). In some sectors, economists have characterized dynamic pricing as having welfare improvements over uniform pricing and contributing to more optimal allocation of limited resources. Its usage often stirs public controversy, as people frequently think of it as price gouging.
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. Dynamic pricing is a common practice in several industries such as hospitality, tourism, entertainment, retail, electricity, and public transport. Each industry takes a slightly different approach to dynamic pricing based on its individual needs and the demand for the product.
Methods Cost-plus pricing Cost-plus pricing is the most basic method of pricing. A store will simply charge consumers the cost required to produce a product plus a predetermined amount of profit. Cost-plus pricing is simple to execute, but it only considers internal information when setting the price and does not factor in external influencers like market reactions, the weather, or changes in consumer value. A dynamic pricing tool can make it easier to update prices, but will not make the updates often if the user does not account for external information like competitor market prices. Due to its simplicity, this is the most widely used method of pricing with around 74% of companies in the United States employing this dynamic pricing strategy. Although widely used, the usage is skewed, with companies facing a high degree of competition using this strategy the most, on the other hand, companies that deal with manufacturing tend to use this strategy the least.
Pricing based on competitors Businesses that want to price competitively will monitor their competitors' prices and adjust accordingly. This is called competitor-based pricing. In retail, the competitor that many companies watch is Amazon, which changes prices frequently throughout the day. Amazon is a market leader in retail that changes prices often,Arie Shpanya (2013) "Do profits matter? The curious case of Amazon.com". Venturebeat. Retrieved April 18, 2014. which encourages other retailers to alter their prices to stay competitive. Such online retailers use price-matching mechanisms like price trackers.Amor Avhad (2021) "This is how product prices change in the market every day". GlassIt. Retrieved June 26, 2023. The retailers give the end-user an option for the same, and upon selecting the option to price match, an online bot searches for the lowest price across various websites and offers a price lower than the lowest.
Such pricing behavior depends on market conditions, as well as a firm's planning. Although a firm existing within a highly competitive market is compelled to cut prices, that is not always the case. In case of high competition, yet a stable market, and a long-term view, it was predicted that firms will tend to cooperate on a price basis rather than undercut each other.
Pricing based on value or elasticity Ideally, companies should ask the price for a product that 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, consumers' willingness to pay can be used as a proxy for the perceived value. 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. With the price elasticity of products, companies can calculate how many consumers are willing to pay for the product at each price point. The dynamic aspect of this pricing method is that elasticities change with respect to the product, category, time, location, and retailers. With the price elasticity of products and the margin of the product, retailers can use this method with their pricing strategy to aim for volume, revenue, or profit maximization strategies.Hidde Roeloffs Valk (2017) "Three dynamic pricing methods & how to implement them"
Bundle pricing There are two types of bundle pricing strategies: one from the consumer's point of view, and one from the seller's point of view. From the seller's point of view, an end product's price depends on whether it is bundled with something else; which bundle it belongs to; and sometimes on which customers it is offered to. This strategy is adopted by print-media houses and other subscription-based services. The Wall Street Journal, for example, offers a standalone price if an electronic mode of delivery is purchased, and a discount when it is bundled with print delivery.
Time-based Many industries, especially online retailers, change prices depending on the time of day. Most retail customers shop during weekly office hours (between 9 am and 5 pm), so many retailers will raise prices during the morning and afternoon, then lower prices during the evening.
Time-based pricing of services such as provision of electric power includes:Partially reworded from United States Energy Policy Act of 2005, sec. 1252. Smart metering 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 pre-established 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). Prices may be signaled to a 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. Peak fit pricing is best used for products that are inelastic in supply, where suppliers are fully able to anticipate demand growth and thus be able to charge differently for service during systematic periods of time.
A utility with regulated prices may develop a time-based pricing schedule on analysis of its long-run costs, such as operation and investment costs. A utility such as electricity (or another service), operating in a market environment, may be auctioned on a competitive market; time-based pricing will typically reflect price variations on the market. Such variations include both regular oscillations due to the demand patterns of users; supply issues (such as availability of intermittent natural resources like water flow or wind); and exceptional price peaks. Price peaks reflect strained conditions in the market (possibly augmented by market manipulation, as during the California electricity crisis), and convey a possible lack of investment. Extreme events include the default by Griddy after the 2021 Texas power crisis.
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 information 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. Automated technology applications for pricing differ among competitors which makes price discovery highly complex and dynamic in the general retail marketplace.Brown, Zach Y., and Alexander MacKay. “Competition in Pricing Algorithms.” American Economic Journal: Microeconomics, vol. 15, no. 2, 2023, pp. 109–56. JSTOR Accessed 5 May 2026.Skye Jacobs. (20 March 2026). "Walmart secures two AI pricing patents, raising dynamic pricing concerns." TechSpot website Accessed 5 May 2026. 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.Kevin Williams. (21 March 2026). "The Bottom Line: Walmart digital price labels are coming to every store shelf in U.S. by end of 2026." CNBC website Accessed 5 May 2026. 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. 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.
By industry 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 long-run marginal cost pricing: see also long run and short 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.Tucker Cummings (2013) "Everything You Need to Know About Dynamic Pricing". Hospitality Net. Retrieved April 1, 2014. 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.
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