Shopping Intent

Shopping intent research focuses on understanding and predicting consumer behavior to improve the online and in-person shopping experience. Current research emphasizes identifying shopping intent from various data sources, including voice queries, browsing history, and shopping basket contents, employing techniques like Mixture-of-Experts models and neural pattern associators to model complex user behaviors and multiple simultaneous intentions. This work has significant implications for personalized recommendations, targeted marketing, and the development of assistive technologies that cater to diverse shopper needs, ultimately leading to more efficient and satisfying shopping experiences.