Jeff Zheng

Newsbreak’s programmatic merchandising platform automates the scheduling and content distribution process through sales data and predictive analytics. NewsBreak schedules and distributes content to display screens using two filters:1) Playlists vary by location and by screen and are based on key consumer variables that impact buyingbehavior — These include elastic variables such as time of day, temperature and precipitation, as well as static variables specific to the convenience store location, like average household income, gender or age distributions in the designated location.2) Predictive data analytics component — The analytics platform gathers data from the C-Store’s data warehouse and automatically pulls location-by-location sales data and key consumer buying data while simultaneously collecting playback data from the content management system. Means variance analyses and predictive selling models are then run assessing the impact of the merchandising playlist against changes in sales volume and market basket. If sales are not being effected, then the platform will replace that message with a promotional message for another product. This virtual feedback loop will ensure that the platform is always optimizing the most effective series of promotional messages.