Global Market Consumer Behavior Analysis for Traditional Chinese Medicine Products Using Neural Networks

This study constructs a model based on convolutional neural network (CNN) to predict consumer demand in the global TCM product market. By analyzing historical sales data, consumer feedback, and social media data, the model can automatically extract complex features and accurately capture the changing trends of consumer behavior in the global market. The study shows that the CNN model has better predictive ability than traditional machine learning models (such as logistic regression and decision trees) when processing large-scale, multi-dimensional market data. The experimental results show the high accuracy of the CNN model in different regional markets, proving its wide applicability in TCM product market forecasting. This paper provides a powerful decision-making support tool for the global market strategy of TCM companies.