Dynamic pricing refers to the practice of changing prices in real time in response to changes in market conditions or other factors. This is typically done using automation, such as algorithms or artificial intelligence, which can quickly and accurately adjust prices based on data inputs. Dynamic pricing allows businesses to respond quickly to changes in demand or competition, and can help them maximize their revenue and profits. However, it can also be complex and requires careful planning and monitoring in order to avoid potential pitfalls, such as alienating customers or setting prices that are too low or too high. The following are common types of dynamic pricing.

Revenue Management

Setting prices at a finely grained level based on data related to competition, demand and inventory levels. For example, airlines may set prices at the seat level and use a variety of sales channels and policies to optimize revenue using data such as demand forecasts.

Supply & Demand

Estimating supply and demand in real time to set prices. In some cases, this can be unpopular with customers or be prohibited by law. For example, raising prices during a natural disaster is typically considered price gouging.

Sustainability

Dynamic pricing may be used to manage cities to improve quality of life or the environment. For example, tolls for emitting air pollution that go up when air quality drops.

Competition

Adjusting prices in response to competition in real time. Common in highly competitive market places long before automation existed.

Inventory

Adjusting prices in response to low or high inventory levels. Common in industries where inventory occurs at a point in time such as an airline seat or a hotel room.

Price Sensitivity

Algorithms that detect price sensitivities in real time. This requires careful attention to laws, regulations, business ethics, reputational issues and customer experience. Generally speaking, customers want pricing to be equitable, transparent and predictable.