How Dynamic Pricing Is Revolutionizing Retail

The use of analytics to set prices in real time is becoming widespread


The concept of ’dynamic pricing’ - in which prices are adjusted in real time according to changes to supply and demand - is not a new one, but it has only really entered the public consciousness recently. It is now being adopted by companies across a variety of industries, in particular retail, and big players like Walt Disney are adopting it. Among retailers, 22% have chosen to implement pricing intelligence software, while an additional 7% plan to start using it within the next six months, and 36% in the next year.

In the 1980s, former American Airlines chairman Robert Crandall pioneered ‘super-saver’ fares - a ticket pricing strategy whereby costs went up and down according to seat availability, passenger demand, and how far in advance customers made reservations. More companies have started to use dynamic pricing in the last few years thanks largely to advances in pricing intelligence software driven by data analytics. It is now far easier for organizations of all sizes to match supply with demand in real time, because computers are far better equipped to deal the vast amount of data necessary, and the technology is so much cheaper than it was.

Dynamic pricing uses automation algorithms to enable retailers to increase their price responsiveness. Pricing intelligence software not only monitors supply and demand internally to set charges, it also trawls nearly a billion product prices on sites like Amazon, from tens of thousands of brands, analyze market shifts in near real time and keep ahead of competitors.

Uber’s ‘surge pricing’ policy is perhaps the most notorious example of dynamic pricing in action. The ride sharing app adjusts prices depending on demand, the time of day the trip is taken, whether it’s raining or snowing, and various other conditions. The popularity of Uber, and the clear advantages it has demonstrated can arise as a result of dynamic pricing for the consumer, has greatly helped to increase the general public’s comfort levels with the concept, giving other companies the confidence to implement it themselves.

The benefits for companies are also profound. Studies have shown that dynamic pricing boosts profits among retailers by 25% on average, and improves gross margins by 10%. This is likely why it is being introduced in every facet of day-to-day life. For example, California-based mobile app developer Atom Tickets has recently experimented with dynamic pricing in movie theaters, and raised $50 million in a funding round led by The Walt Disney Co., Lionsgate and 21st Century Fox. Walt Disney Co. has, incidentally, recently introduced dynamic pricing itself in its theme parks, making the move to lift prices at Disneyland on especially busy days.

There are several problems with the policy, however. For one, customers may not respond favorably to having paid more than someone else for the same product simply because of the time they bought it. Uber has also drawn criticism for the timing of some of its price surges. The issue with algorithms is that they do not distinguish between an increase in demand because of something palatable to the public, and an increase due to something that isn’t - like a natural disaster. So when Uber’s prices went up during Hurricane Sandy in 2014, for example, the public outcry and negative press was such that the app was forced to agree not to substantially increase prices during states of emergency.

There have also been examples of attempts to introduce the pricing policy backfiring in sports when not implemented correctly. In a recent paper examining the impact of dynamic pricing in the industry, Joseph Xu found that overall revenue actually fell 0.79% if prices were not allowed to freely decline even if circumstances — such as poor team performance — warranted it. However, according to their paper, if prices were allowed to move up and down freely, revenue would have gone up by 14.3%.

George Lawrie, vice president and principal analyst serving application development and delivery professionals at Forrester Research, notes that these problems are less pronounced in retail, noting that businesses with a high proportion of fixed costs and limited capacity are well suited for dynamic pricing. He argued that these conditions hold ‘true for seasonal retail or fashion, in which the merchant commits capital to buying a line of stock that must be cleared before the next season.’

Ultimately - as when any data analytics techniques is used in a consumer orientated industry - the key to implementing using it in a way the public reacts well to is transparency. Companies must keep customers informed of the methodology and reasoning behind how prices are being set, and ensure that their pricing is consistent and applied fairly. As people’s comfort with the policy grows, they are already accepting that there is a trade off and this acceptance is only going to increase.

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