I am often asked about dynamic pricing – what it means and how it is implemented. The short answer is dynamic pricing is a process of maximizing profit by adjusting prices based on demand. Earlier this month it was reported that New York City is considering congestion pricing to ease traffic gridlock. Congestion pricing is just a variation of dynamic pricing, in which the city is attempting to increase revenue and reduce demand. Uber does something similar but calls it surge pricing. Some utilities call it peak-load pricing. The concepts in all these uses of dynamic pricing are similar and simple. The critical part is determining how to apply those concepts to the specific industry.
The most important concept in dynamic pricing is demand for a product or service can vary depending on the situation, and the amount customers will pay in those situations also varies. The challenge for any business to set prices dynamically is to determine:
- What are the situations that can cause demand to vary?
- Is the supply of the product or service limited, or can the supply easily be increased or decreased as needed?
- How much more can we charge in high-demand situations to increase overall profit?
- Recognizing that some high-demand customers will no longer buy at higher prices
- How much do we need to lower prices in low-demand situations to stimulate sales without lowering the total profit of those situations?
Let’s consider some possible situations and the demand implications:
- Seasonality – Some things are in higher demand during the summer, such as swimsuits, lodging at national parks, rides at theme parks, tee-times at golf courses, etc.
- There is also a sub-seasonality measure – Some of those same attractions have even higher demand on holidays within a specific season
- Demand for costumes and candy increases near Halloween
- Ski resorts are more popular on holiday weekends, and spring break
- Day of the week – Theaters, aquariums, museums, and sports venues are usually less popular during the week with greater demand on weekends
- Hotels in business districts have greater demand Monday through Thursday nights, while hotels in tourist areas have greater weekend demand
- Time of day – more people go to movie theaters between 6 and 10 pm; the most popular dinner reservation times are 6:30 to 9, depending on the city; fitness classes have more participants before and after work hours, and businesses use more electricity during the peak daytime hours
- Theaters, restaurants, gyms, and utilities are under-utilized at other times
- Weather – pools, theme parks, and outdoor sporting events are more popular when it is dry and warm
- Ancillary attractions – attendance at Pittsburgh Pirate baseball games always increases on Fireworks Night
- Some promotional give-away items are more attractive than others and increase demand for the corresponding events
- Amount of time between purchase and use – often customer price sensitivity is related to how far in advance he or she purchases a ticket for an event
- Customers who are price sensitive will shop early for deals
- Customers who decide to do something without much lead time often are less sensitive to the price
- With a large enough discount, price-sensitive customers can often be persuaded to buy unused capacity that would otherwise go to waste
- Market availability – when the supply of a commodity tightens, customers who need that commodity will pay more.
You get the idea, and no doubt you can come up with more examples. Once the situations that impact demand have been identified, the next step is to determine if capacity is limited or can easily be ramped up. Each restaurant, sporting event, hotel, etc. has a fixed capacity, which cannot be easily increased. When demand is greater than capacity, raising the price will capture more income and allocate the fixed capacity. Conversely, more candy can be made around Halloween, so raising the price might just drive customers to a different brand.
In a somewhat similar comparison, high demand for concerts would have different capacity ramifications than high demand for a specific movie. The number of customers who would like to see Beyonce and Jay-Z, or Taylor Swift or Elton John, is much higher than many other acts. Concert promoters should set the prices for those events high. However, although demand for A Star is Born, Bohemian Rhapsody, and Aquaman was high relative to other films in 2018, a theater would capture more revenue by allocating additional screens to those films on Friday and Saturday night instead of increasing the prices of those specific movies.
After determining when prices should be adjusted due to demand, the next questions are how much to increase them for high-demand periods and how much to decrease them for low-demand periods. There is no simple answer, but it is always important to do the math. By that I mean, if prices are increased 10%, what percent of current buyers could switch to a low-demand period without lowering profit? Similarly, if low-demand prices are decreased by 10%, how many additional buyers are needed to break even?
There will always be uncertainty in adjusting prices to match changes in demand. My advice is to start small and prove the concepts. For a multi-location entity, you could try dynamic pricing in some, but not all, locations. If that is not feasible, start with modest differences in peak-period prices versus off-peak, and adjust as you learn from your results.
Nothing in this blog post is complicated. The concepts of dynamic pricing are pretty simple. It is true that companies like Disney and the airlines have sophisticated computer models to calculate the optimal amounts to adjust prices for different demand situations, but they all started with simple adjustments. By starting with smaller price differences and learning from their results over time, they have been able to identify more granular situations with varying demand characteristics; and they have been able to fine-tune their pricing. If you start with the basics, your dynamic pricing capabilities will also improve over time.
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