Dynamic pricing refers to AI dynamically changing prices according to supply and demand.
It is possible to realize the consumer’s desire to “cheap even 1 yen”, or to set the price higher according to the growing consumer needs.
“Pricing”, which used to be largely based on experience and intuition, has become a competition to derive the optimal price from a huge amount of data with the advent of AI. With the ease of price comparisons available on the Internet, dynamic pricing is a subject for all businesses, whether they like it or not.
In this article, we will introduce the overview and current situation of dynamic pricing through corporate case studies as of August 2019.
What is dynamic pricing?
Dynamic pricing, in which product prices fluctuate according to the balance between supply and demand. The variable price system itself is a system that has been introduced for a long time in the hotel industry and the airline industry, such as when prices rise during Golden Week and Obon.
So why is dynamic pricing attracting attention now? This is because big data is analyzed with AI, and real-time and accurate pricing that maximizes corporate profits is now possible.
Six years after its establishment, the hotel venture “OYO”, which has the second largest number of rooms in the world, offers 50 million room rates per day, depending on the location and destination of users searching for hotels. It changes 730 times per second. By always setting the optimal price, we can achieve a stable high occupancy rate and maximize profits.
How dynamic pricing works
Dynamic pricing consists of three processes: data collection, demand forecasting, and price proposal.
The data necessary for optimal price determination varies depending on the industry and company, but for example, “market conditions”, “product inventory”, “social media (trends)”, “weather”, “events”, “competitive trends”, and “site log (personal preferences)”. Collect data such as, and use AI to predict demand. It is also possible to gradually improve the accuracy of price proposals through AI machine learning.
Dynamic pricing has become a trend as companies have more access to big data. However, the flip side of this is that companies with accessible, unique big data also have an advantage in dynamic pricing.
Advantages and disadvantages of dynamic pricing
The greatest advantage of introducing dynamic pricing for companies is maximizing profits. When demand is high, prices can be raised and profits can be enjoyed, and when demand is low, prices can be lowered and surplus inventory can be disposed of, and profits can be enjoyed.
In addition, it is possible to reduce the large number of human resources that were previously required to determine and change prices, and to allocate them to other tasks. If dynamic pricing works well, it will be possible to set more optimal prices than those based on experience and intuition.
Disadvantages for companies
While it is possible to reduce the cost of human resources, new system development and operation costs for dynamic pricing will inevitably be incurred. If dynamic pricing doesn’t work well, the cost will be high.
We should also consider the risk that consumers will refrain from buying if they become distrustful of dynamic pricing price fluctuations. In Japan, manufacturers and retailers have fixed prices, and consumers have accepted them.
Products and services that were in high demand and difficult to obtain can now be obtained by paying a high price. For example, you can get tickets for artists’ live performances and popular brand items that sell out immediately, depending on the amount. In addition, it will be possible to prevent situations in which these products, which tend to rise in price, are purchased for resale.
Not only will the price of the product increase, but conversely, if the demand is not high, there is a possibility that the product can be obtained at a lower price than before.
Disadvantages for consumers
As a flip side of the merit, there is a great possibility that the products you want will be more expensive than before. It may lead to a situation where only the wealthy can buy popular products.
Also, when AI changes prices, the pricing algorithm becomes a black box for consumers, and there is a possibility that information transparency will be lost. We may not be able to shake off the suspicion that companies are unfairly manipulating prices to make a profit.
Conditions for introducing dynamic pricing
Not all business types are suitable for the introduction of dynamic pricing. There are operational issues with price changes and problems with consumer sentiment.
The following two points are the conditions for introducing dynamic pricing.
Easy price change
Items sold in stores have price tags. It is possible to change the price by replacing the price tag or sticking a discount sticker, but it is physically impossible to change the price 730 times per second like the above-mentioned OYO. In addition, catalog mail-order also require a great deal of cost to revise product prices.
Dynamic pricing is suitable for business formats where prices are easy to change, such as online shopping. However, recently, even in stores, electronic shelf labels (ELS) can be used to instantly change prices through the network. In that case, it will be operationally possible to introduce dynamic pricing at physical stores.
Products whose price fluctuations are accepted by consumers
Whether or not price fluctuations are accepted by consumers determines the success or failure of the introduction of dynamic pricing. For example, there is little consumer resistance to hotel room rates and airline tickets, which have been changing prices for a long time.
In addition, commodities such as tickets for live concerts and sports games, whose prices are likely to fluctuate in secondary distribution. Consumers have already accepted price fluctuations to some extent, even for items such as vegetables and fish whose prices change due to natural phenomena such as the weather.
However, there is no clear standard for consumer acceptance. Uber Eats has a fixed price for food, but a variable price for delivery based on the balance between the delivery person (supply) and the order (demand). In the future, as dynamic pricing spreads, the degree of consumer acceptance may change.
How to introduce dynamic pricing
In addition to cases where dynamic pricing mechanisms are developed and operated in-house, such as Amazon, Uber, and OYO, there are also cases where development is outsourced to external vendors.
In addition to requesting development from scratch to major IT consulting companies and SI companies, recently some companies provide SaaS-type dynamic pricing systems called PaaS (Pricing as a Service).
Overseas, UK-based Black Curve provides a comprehensive range of services, from pricing engines for price determination to pricing and management know-how.
In Japan, companies that provide SaaS-type automatic pricing tools, such as “Metro Engine,” which provides dynamic pricing services, “MagicPrice,” which specializes in hotels, and “through,” for e-commerce, are beginning to emerge.