Adapted Decision Support Service Based on the Prediction of Offline Consumers' Real-Time Intention and Devices Interactions

摘要

Due to the specificity of the omni-channel retailing scenario, consumers in a brick and mortar store have a merging need for various decision support services to enhance their shopping experience. To survive the fierce competition in the retail world, firms need to predict which services are relevant to their customers and when to offer these services. To address this challenge, we propose a context-aware approach to collect, analyze, and interpret real-time consumer behavioral data from portable devices. Experiment results confirm that context-aware interaction can greatly enhance consumers' shopping experience in the offline scenario.