If you were grown up enough to fly away on your own in the nineties, you know that back then, airlines had printed time tables with ticked fares. If you were lucky, you could get a heavy discount by booking late. Since then, airlines have made a full 180-degree turn and the price of a flight is dynamic and depends on demand, increasing as you come closer to departure. And we, the customers, have come to accept a fully reversed, dynamic pricing model. Is it time for your business to break old habits and start a new journey using the principles of revenue management?
The 1979 deregulation of the US airline industry brought intensified competition, and revenue management was originally developed as a tool to manage discounting of seats while avoiding destructive price wars. The practice of dynamic pricing has developed and spread and is today crucial for survival if you are in the transportation or hotel industry, or in any industry where your offering is of a perishable nature or where capacity is limited.
The power of revenue management lies in disciplined analysis of historical data to forecast future demand. It begins with collecting and storing customer transactions and information on inventory, variable costs, own and competitor pricing to allow for modeling and accurately predicting customer behavior. And it is far from limited to travel and hospitality. An increasing number of clients from diverse industries are using these techniques to create a more differentiated and dynamic pricing, that allows for capturing volume at times of low demand and profits when it is high. Retailers, manufacturers and service providers report 3-7 percent increases in revenue, or a 40-50 percent increase in profits when a pricing based on these techniques is introduced.
 Yeoman, I. & McMahon-Beattie, U., 2011, Palgrave MacMillan.
Pontus Frithiof, Swedish chef and entrepreneur is breaking new ground, swearing by revenue management as a key factor in running his successful restaurants. “I am extremely interested in how companies in other industries do things, and what I can learn from them”, Mr. Frithiof says. With capacity limitations and highly perishable inventory, restaurants seem as a perfect school book example, but customer acceptance for dynamic pricing of meals is still perceived as low. However, using data-driven insight about the purpose, needs, and willingness-to-pay of the customer, Mr. Frithiof creates differentiated offerings and price levels to serve customers at different times of the day or week, customers who are in a hurry or who have time on their hands, customers who are doing business or dining with a friend or loved one, and customers who have different dietary preferences. The objectives are clear: serving the customers well, filling up capacity, and maximizing the number of paying customers.
The retail industry is undergoing fundamental changes, with a pandemic-driven, dramatic increase in e-commerce changing the competitive arena and mass death of physical stores a reality in several retail sectors. Fashion and design retail are furthermore characterized by long lead times, perishability due to trends, and even the weather is known to affect demand, making narrow sales windows difficult to match. The traditional retailer starts a season with high inventory levels, monitors sales daily and incentivizes personnel and customers with competitions and campaigns to drive sales. Once or twice per season, a sale is launched with discounts that can run as deep as 70%, with little or no margin left. It is easy to see how retailers who are using the vast amount of data at hand, either supported by machine learning algorithms or not, will make more informed and therefore profitable decisions regarding pricing, promotion, and discounting. Considering a 2-5 % point reduction of discounts can be the difference between red or black numbers if you are in retail, the outcome is certainly worth the effort.
Thinking about other industries, the same principles and techniques can be used to optimize revenue when demand is volatile. At Nets, the Danish payment provider, large volumes of card transactions are received from merchants daily, typically towards the end of the business day. In order to even out demand and match it to the company’s capacity, cut-off times have been priced differently, offering a discount for the merchants who sent their transactions at a quieter time and charging a premium if the merchant wanted to send them in at peak hours. Price differentiation by the number of settlement days is another example from the fintech industry.
In the consulting practice, we work in a wide range of industries and have the privilege to get to know the unique conditions of each one, explore the similarities, and figure out which practices of one industry would be beneficial for another. Whether you are in manufacturing, trade, software or professional services, over time you are certain to experience variations in demand and customer needs, aggressive competitor pricing and limitations in your own capacity. Therefore, exploring the opportunities of working with a more dynamic or demand-driven pricing would likely be a good investment in the future. Think about it, how would your business benefit from a more even demand, from filling up capacity, from capturing the value provided to customers with high willingness to pay, while still serving the customers looking for a low price. How would this affect your P&L statement, and what would you need to do to get there?
Lotte Kylberg is Senior Manager and Pricing Lead at Capacent_x in Sweden. Lotte has 15 years of experience from developing and implementing strategic and tactical pricing with clients in a wide range of industries, such as industrial manufacturing and trade, business services, rental, retail and MedTech.
Nora Härme is a pricing & revenue management professional and former Capacentian who played a key role in setting up the Pricing practice at our Helsinki office during 2019-2020. She currently works for Terveystalo.