How Researchers Built a Model to Predict In-Person Ticket Sales

 
When the COVID-19 virus began spreading across the U.S., researchers at SMU DataArts responded by integrating datasets and building a framework for predicting ticket purchasing demand. Continually refined for over a year, this framework takes into account ticketing purchases, census data, COVID cases, vaccine rates, restaurant employment, and arts ticket prices to help organizations across the nation predict demand for in-person ticket purchases. Join our leading researchers for a behind-the-scenes look at how the model was developed and how early actual results compare with predictions. Participants will also receive a first look at a new tool that will allow cohort groups of organizations to submit their data for analysis within the model.

Presenters: Karthik Kannan, Glenn Voss
Host: Katie Ingersoll, Director of Programs at SMU DataArts

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