Dynamic prediction and intervention system for brand loyalty based on multimodal analysis

Abstract

The present invention relates to the technical field of marketing analysis and discloses a dynamic prediction and intervention system for brand loyalty based on multimodal analysis. The system comprises a multimodal data acquisition module, a dynamic prediction module, and an intelligent intervention module. The invention collects various transaction data between customers and the brand, evaluates and predicts the behavioral loyalty prediction coefficient, attitude loyalty prediction coefficient, and emotional loyalty prediction coefficient, and obtains the comprehensive loyalty prediction coefficient through weighted summation. This enables multidimensional analysis and effective integration of brand loyalty, improving the accuracy of brand loyalty prediction. Whether to intervene with customers is determined based on the comprehensive loyalty prediction coefficient, and personalized intervention measures are generated based on the customer's behavioral loyalty prediction coefficient, attitude loyalty prediction coefficient, and emotional loyalty prediction coefficient, thereby enhancing the humanization and quality of service.