In addition to cost-oriented or competition-oriented pricing, demand-oriented pricing is also seen in the retail industry. It is a strategy based on known periods or high or low demand and the elasticity of price during those periods. We will explain this strategy using a few examples.

One of the simplest examples would be the pricing and selling dynamics at your local farmer’s market. Early in the morning when the market is first open, there is the best selection but at the highest prices of the day. As the day goes on and the market nears closing, the produce will normally see a reduction in price by the sellers who are trying to avoid having any product left unsold.

Another example of demand-oriented pricing comes from the airline industry. Flights from Minnesota to sunny Arizona in February will not be at the same price as the same flight in August . The aircraft would use the same amount of fuel, have the same number of employees on board, and pay the same airport costs, etc. The flight in August would only be partially full compared to the number of travelers in February. If there are more passengers in February sharing the costs of the airline operation, the ticket price should be less in a cost-based world. But it is the opposite. This is due to demand. Arizona is a much more desirable destination for snow birds in winter thus the price goes up.

The same demand-oriented pricing exists in the retail industry. When down parkas are offered by department stores at the beginning of the fall season, they will be at their highest-ticketed price. There may be off-price promotions during “pre-season” and heading into the holidays, but most retailers will continue to “own” the down parka at the original price throughout the prime selling season. Then, when it is time for swimwear and shorts to arrive for sale, the price of those down parkas will undoubtedly be greatly reduced. With falling demand for down parkas, the retailer lowers the price in efforts to reduce inventory.

These are simple examples to illustrate the concept. Imagine the complexity of a demand-oriented pricing strategy for a large supermarket retailer where there are tens of thousands of individual products to track. The same ebb and flow of demand certainly exists in grocery products, but adjusting pricing across all of the product categories to take advantage of the dynamics would be a huge challenge. Once again, software applications have been created to help retailers handle the analytics and automation of demand-based pricing.