Dynamic pricing can be used on anything where supply and demand is in a constant state of flux. A hotel located in Dodge City, Kansas is constantly changing its prices to maximize the profit based on availability. When that rodeo rolls into town the prices automatically go up. The first market to really get good at dynamic pricing was airlines, whose goal is to maximize revenue for every single flight through a combination of not just more passengers but more revenue per passenger. The ultimate goal being total revenue per flight. A dynamic pricing system would automatically adjust the price downwards if there was excess capacity and bring it up if demand was high. These systems understand the relationship between supply and demand so they can better avoid cutting prices unnecessarily low in which you’re making almost no margin or the inverse of setting them so high that you lose out to all your competitors and end up with too much extra capacity to make any money.
Most national and global hotel chains are now using dynamic pricing (surge pricing) software which allows them to fill as many rooms as possible but without under charging based on the potential capacity. For online retailers, Amazon was the poster child of dynamic pricing with the occasional item jumping 300%+ when it becomes hard to get from any other suppliers. Amazon’s pricing includes advanced algorithms analyzing thousands of their competitors and adjusting their price to maximize total revenue.
Imagine for instance a plane with 100 seats that is flying to Las Vegas. A manager could decide to price each seat on the plane for $100 which gives you $10,000 in revenue. But a dynamic pricing system might forecast that at $200 you would fill 56 seats for a total of $11,200. It would also know when to drop that price even lower than $100 to fill those remaining 44 seats. A dynamic pricing system will always strive to maximize total margin. This is all done in real-time and changing as capacity and traffic changes. The goal is to avoid underpricing and leaving money on the table or overpricing which would keep customers away from even considering you. A dynamic pricing system can also assign value to bookings that are done far in advance, since it allows a company to better plan and reduce costs. In almost all instances you will get a significantly lower airline fare booked 3 months out then booked 3 hours out. Uber is another service that will adjust rates when demand becomes higher than capacity, called surge pricing. Some companies have taken it even farther and used data to alter the price based on what different segments may have been willing to pay. Many retailers have experienced a 5-10% increase by using a price optimization system which in a rather low margin commoditized market is large enough to give most Chief Revenue Officers a heart attack.
Dynamic pricing can also involve machine learning as companies like IBM have developed software that looks for behaviors of users: Mac vs PC, cart abandonment, past sales history and other rich tracking data can adjust the price to create the maximum effect by understanding what motivates each person and what price point would likely move them. This is the future of dynamic pricing where it involves not just calculations of capacity vs. demand but also intelligently learns about each customer segment. Based on these segments the price can be adjusted accordingly as part of a total strategy to get the most total gross profit. Some have already taken it to an extreme, Delta Airlines for instance went so far as to raise rates for frequent flyers by up to $300 since algorithms had determined they are willing to pay more. This practice of raising prices only for particular customers still presents some risk as the backlash can be quite severe so proceed with caution if you plan on using segmented technology to raise rates. If customers of your industry are already used to dynamic pricing (hotels, concert tickets, airlines or any other form of transport) then there should be no real issues to dynamic pricing.
If your company is involved in a service or creates a product that is subject to changing demand and wants to explore dynamic pricing here are some software services:
Offers several solutions that automatically measure all sales and make changes throughout the day to maximize total profit. Relies heavily on A/B testing but also has features for more slow moving or high-value products. Can strike a balance between profit and margin.
Makes it easy to adjust the price based on location which is helpful for those brands that want to charge a premium to certain cities or are selling internationally and need to adjust the price up or down. You can test to figure out which prices are the best for certain countries, states or cities.
Up to the moment re-pricing based on what margins you want and by analyzing all your competitors. Can react immediately to any pricing change or out of stock of competitors.
We all know that pricing has to be dynamic for any national or global company since when you travel to a different country the price of some of the same stuff you buy is different. This level of pricing reflects the ability of the local population to pay. If you visit a Walmart in Hastings, Nebraska and one in Palo Alto, California you will not see the exact same prices. They are adjusted based on data representing the local economy and median pay. Because of all the variables representing demand and location, price optimization software is well suited to help maximize profits as it can quickly experiment, analyze and provide the best price possible.
The old method of setting prices by intuition is going to be become increasingly obsolete as the marketplace becomes more competitive and continued competitive advantage comes from being able to innovate in product development, cost savings, marketing and through sales strategies like dynamic pricing.