In this post, we discuss the impact of external shocks (e.g., changes in factors that are outside the control of the seller) on optimal ticket pricing. We use the case of the COVID-19 outbreak as an example to illustrate our points, focusing on ticket pricing in attractions and live entertainment, two industries in which Digonex has extensive experience. The basic principles apply to many other industries as well. If the reader wants to jump to the discussion of the impact of the coronavirus, she can skip the first few paragraphs and go right to the numbered points.
What are some common examples of external shocks that are particularly relevant for ticket pricing? Even a day-to-day change in weather conditions is an example. More major examples include earthquakes, weather-related disasters such as hurricanes, epidemics, changes in economic and market conditions such as recessions or macro shifts in tourism activity. Companies cannot control these factors and need to take them into account in their pricing decisions while these events unravel or in anticipation of them, to the extent such an event can be forecast. The impact of such events on optimal pricing is usually not trivial and data analysis is required to understand its direction and magnitude. The fact that any of these events do happen justifies the use of “dynamic pricing”.
What is dynamic pricing? It is the primary service we provide our clients at Digonex. Dynamic pricing can be defined as the method that involves prices changing at some frequency (e.g., weekly, daily or real-time) based on supply and demand conditions. At Digonex, we use automated algorithms that incorporate methods of econometrics, machine learning, and optimization for dynamically pricing our clients’ tickets. Our algorithms allow us to take into account external shocks in determining optimal prices.
What do we mean by “optimal”? It really depends on the objective of an organization. Some of our clients are interested in maximizing their long-term revenues subject to certain constraints, others want to maximize attendance while hitting their revenue goals. Other examples are increasing advance sales or shifting attendance from peak to off-peak periods to improve the guest experience. Prices that lead to our clients achieving their goals are what we refer to as optimal prices. Regardless of what the objectives are, external factors usually have an impact optimal pricing. However, in the rest of this note, we focus on the case of revenue maximization. One may question the social responsibility aspect of pricing decisions, especially in case of external shocks that negatively affect the general public. No organization would want to (nor should) give the impression of taking advantage of such an event. For this theoretical discussion of pricing, we set aside this aspect, though in practice, it should definitely be a constraining factor on pricing.
If the goal is revenue maximization, there are four main reasons for organizations to change their optimal prices. The first one is related to supply, the other three relate to demand.
COVID-19 billboard, San Jose, CA
Let’s apply these factors to the case of the coronavirus, starting with limited inventory. Consider a venue that would sell out without the outbreak. Since many potential customers will rather stay home to avoid public areas during the outbreak, sales will go down. As a result, availability in seating will increase. Everything else being the same, this justifies lower prices. For those organizations without limited capacity or no real sellout possibility, the coronavirus won’t necessarily justify lower prices. To the extent that better seats are left for purchase, higher prices may be warranted as well.
On the second factor, the COVID-19 outbreak will not directly influence product quality in most cases. However, people’s perception of the experience (i.e., their preference) may be affected to the extent that they may be hesitant to be in areas with other people. For those visitors, lower optimal prices will be justified. For other visitors, the impact on the quality of experience may be negligible or none. For them, optimal prices will stay the same. To the extent that these different groups can be distinguished based on their identifiable demographics, data can be used to capture the change in the mix of customers. This is related to the third factor listed above, customer composition.
It is important for an organization to understand the impact of the pandemic on the mix of their customers. If, say, the share of tourists who may be more price insensitive is down due to travel restrictions, lower optimal prices will be justified. If more price sensitive locals are more likely to stay at home, higher prices may be warranted. As mentioned in the previous paragraph, changes in the preferences of the overall population can be considered under the third bullet as well, as preferences are a dimension of customer characteristics.
Lastly, competitors may respond to the coronavirus rationally based on these factors or simply offer promotions without any rational justification. Any organization should keep an eye on their close competitors and maintain the price difference at a level that justifies the difference in the value of experience. If competitors start cutting prices, it will be the rational action to cut prices even if the first three factors do not together justify a price drop.
In many countries, only a couple of months after the first COVID-19 case was reported, social life came to a halt given the restrictions on public gatherings and advice on social distancing and self-isolation. Almost all live entertainment venues and attractions cancelled their events for the next few weeks. It is possible that closures will extend into late spring or summer. It is impossible to predict how and when life will get back to normal. Once venues and attractions start re-opening doors to their customers, there will likely be an initial surge in demand for a few weeks. Then, sales will probably level off to their new norm. All four of the aforementioned factors will come into play during the “aftermath” as well.
As discussed in the last few paragraphs, the impact of the coronavirus, or any external shock, on optimal price can be tricky. Cutting prices with the expectation that sales will go down may not be the optimal strategy. Similarly, increasing prices to mitigate the negative impact of lower attendance on the bottom line may not be the right move. It is important to look at various factors as explained above and measure the overall impact of the COVID-19 pandemic on optimal prices. To the extent that relevant data is available to quantify these factors, algorithmic dynamic pricing will allow live entertainment institutions or attractions to respond to the coronavirus in the best possible way.