Research on Prediction and Analysis of Consumer Behavior Management Based on Deep Learning

With the rapid development of deep learning technology and the arrival of the big data era, consumer behavior prediction has become a hot research topic in the field of e-commerce. This article conducts a comprehensive analysis and prediction of consumer purchasing behavior and feedback emotions based on a deep learning model. By constructing a convolutional neural network (CNN) and a long short-term memory network (LSTM), this study can effectively process and analyze image and text data on large-scale e-commerce platforms. Case studies show that the proposed model can accurately predict consumers' purchasing preferences and emotional tendencies, providing a scientific basis for personalized recommendations and product improvement. In addition, this article also explores the limitations of the research and proposes future research directions aimed at further improving the generalization ability and interpretability of the model to better serve e-commerce platforms and consumers.