Early Anomaly Detection in Marketing Data

Rockerbox Computer Science, 2021–22

Liaison(s): Kevin Hsu ’10, Mike Cen, Rick O’Toole ’10
Advisor(s): George Montañez
Students(s): Bettina Benitez, David Webber, Jacqueline Choe, Nicolas Espinosa Dice (PM), Noah Smith

Rockerbox provides a software as a service platform that centralizes marketing data and provides insights for e-commerce companies, allowing them to optimize their marketing strategies. This project’s goal is to research and develop anomaly detection methods that Rockerbox will use to ensure the reliability of their customers’ data. Identifying and correcting potential issues quickly and proactively will enable Rockerbox’s customers to make more accurate marketing decisions.