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Revenue Strategies and Pricing Analytics

This course is the second course offered in the Sports Analytics Certificate, and will constitute part of the ‘core’ offerings that all Certificate students will take. This course builds on other Certificate courses. It highlights the importance of analytics and data modeling to revenue management in the sports industry. This includes demand forecasting, pricing, inventory management, and consumer relationship management (CRM), among other topics.
Students will also learn about the technology infrastructures required to support these functions. This includes an overview of the technologies that capture, store, manage, and distill data. The course will also provide an overview of the communication structures and best practices required across a sport organization’s hierarchy in order to optimize the use of these technologies. The course will also delve into ‘next-gen’ sources of revenue, such as Non-fungible tokens (NFTs) and blockchain, sponsorship analytics, and spatial computing such as AR and VR.
Students pursuing the Certificate in Sports Analytics are required to complete Foundations in Sports Analytics/TGSC1-CE1000 before enrolling in this course. Flexibility  on the order of course completions may be granted, pending review of professional background/expertise.
For questions on the Certificate in Sports Analytics, please contact tischinstitute.ce@nyu.edu.  For assistance with registration, please call 212-998-7150.
 

More details

You'll Walk Away with

  • Identify the current and future sources of revenue for sport organizations
  • Apply data analysis methods to revenue management problems
  • Construct a ‘mental map’ of the data aggregation and management technology architectures
  • Identify the organizational and structural components of sport organizations that are essential for effective revenue optimization

1 section

  • Spring 2024

    • Section

      001
    • Semester

      Spring 2024
    • Date

      Jan 29 - May 14
    • Day

      Self-Paced
    • Time

      Self-Paced
      • Online
    • Format

      Online
      • Online
    • Sessions

      N/A
    • Location

      Self-Paced