One of the biggest challenges in producing theater on any scale is to fill a house with people paying the "right" price. Producers want to maximize revenue. Audiences want to be entertained for a price that keeps the entertainment enjoyable.
Over the summer, I aim on developing the skillset to determine the perfect price point for shows so that houses are at 100% capacity with audiences that are paying prices they are most comfortable with. Revenue is maximized, producers can make more shows, actors + creative team have more jobs, and the industry grows!
Financial services already use these technologies. So do airlines, hotels, Facebook, Google, and Amazon. Let's use data science in Broadway!
I am most enthused by Kevin R. Williams's study from Yale: "Dynamic Airline Pricing and Seat Availability." Similarly Ian Boneysteele, Konstantine Buhler, James Kernochan, Mike Mester, and Soren Sudhof study at Stanford: "Forecasting Broadway Show Gross Revenue."
Wish me luck as I begin this next stage of my journey!
Boneysteele I., Buhler K., Kernochan, J., Mester M., Sudhof S. (2016). Forecasting Broadway Show Gross Revenue. [online] Stanford School of Business. Available at http://zoo.cs.yale.edu/classes/cs458/lectures/old/Broadway/Final%20report%20vF.pdf [Accessed 18 Jun. 2018].
Steinmetz, J. (2016). Exploring Broadway Data in Tableau | InterWorks. [online] InterWorks. Available at: https://interworks.com/blog/jsteinmetz/2016/08/03/exploring-broadway-data-tableau/ [Accessed 18 Jun. 2018].
Williams, K. R. (2017). Dynamic airline pricing and seat availability. Yale School of Management; Yale University - Cowles Foundation
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