This thesis explores a data-driven strategy approach to curtailing HVAC energy consumption in a large retail portfolio. Energy building simulation software was utilized to predict setpoint related energy savings potential across all United States climate zones. An extensive field study was conducted using building automation data of current setpoints, setpoint scheduling, various programmable features, and general building operations during the cooling season in Phoenix, Arizona. Experiments were conducted during the cooling season in Phoenix, Arizona, in order to verify suggested simulated cooling savings. Extrapolation models were created with building automation data to predict annual site energy reduction to further verify the savings opportunities suggested with simulation models.