Following the recent introduction of DynamO’s unique simulation tool, now we also share some of the results yielded by our deep analysis on a large set of data that we obtained via systematically screening the whole parameter space.
As we recently reported, DynamO’s one-of-a-kind simulation tool models the demand for dynamically priced movie tickets in different scenarios, and also showcases what benefits our dynamic pricing engine offers. We used this toolkit and screened the whole parameter space to produce a large set of data that helps the further development and fine-tuning of our pricing engine.
During the deep analysis of the obtained data set, this time we were primarily interested in how the Extra revenue (generated via dynamic pricing as compared to the revenue generated via static pricing) depended on the boundary conditions set for dynamic pricing (Initial, Minimum, and Maximum prices). Fig. 1 is a case study for low-popularity movies screened at unpopular times (before 2 p.m. during weekdays), while Fig. 1 is a case study for movies with higher than average popularity that are screened at highly popular times (Friday or weekend evenings).
As it can be observed on the left-hand side of Fig. 1, the Extra revenue from a low-popularity movie at an unpopular time is practically independent of the Minimum price, but highly depends on the Maximum price if the Initial price is relatively low (1000 HUF). In contrast, when the Initial price is comparable to the current static prices (1750 HUF), the Extra revenue from the same kind of screening is independent on the Maximum price but heavily depends on the Minimum price (the lower the Minimum price the higher the Extra revenue), as the graph on the right-hand side of Fig. 1 shows. This suggests that offering cheaper tickets for unpopular movies screened at unpopular times actually would pay off for cinemas.
The left-hand side of Fig. 2 makes it apparent that the Extra revenue from a popular movie at a highly popular time is also independent of the Minimum price, and has a nontrivial, non-monotonous dependence on the Maximum price if the Initial price is relatively low (1000 HUF). In contrast, when the Initial price is comparable to the current static prices (1750 HUF), the Extra revenue from the same kind of screening does have a slight dependence on the Minimum price, and heavy dependence on the Maximum price, as Fig. 2 shows. Hence, we argue that putting a higher price tag on some seats at appropriate times would also be beneficial for movie theaters.
Analyses such as this help us with the further development and tuning of our pricing engine. Remarkably, our findings already support previous trials and reports that pointed out the transformative potential of dynamic pricing on the cinema sector – and, on the ticketing industry in general. We at DynamO believe that dynamic pricing benefits not only operators but all parties: it brings more balanced demand, increased ticket sales and more revenue for cinemas; larger revenue for the distributors; and better, fairer value for money. All this together benefits the film industry itself.
DynamO’s team of experts can help you to get the most out of dynamic pricing. DynamO has been established in the recognition that the service sector’s increasing interest in dynamic pricing in now coupled with an increasing acceptance among end customers. Our vision is to make dynamic pricing as widespread and common in the service sector as credit cards and online shopping in everyday life.
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