Research on the Influence of Digital Marketing on Consumers’ Purchase Intention Based on Machine Learning

In order to explore the influencing factors of consumers’ purchase intention in the era of digital marketing, machine learning theory is introduced to complete the research on the impact of digital marketing on consumers’ purchase intention. First of all, this paper constructs the consumer purchase intention influence model on the basis of the theory of planned behavior, and elaborates on the content regarding how digital marketing influences consumer purchase intention. Then, the data preprocessing and feature mining of consumer purchase intention are carried out. Finally, the CNN and LSTM neural networks in machine learning theory are integrated to complete the construction of the prediction model of consumer purchase intention. The empirical results show that the relative error of the proposed model is less than [Formula: see text], the equality coefficient is 0.9961, the average absolute error is 0.9624, and the root mean square error is 0.6172%. In the realm of digital marketing, when ranking the characteristics of consumers’ purchase intention by importance, it is evident that consumers prioritize personal and commodity-related factors during the purchasing process, including factors such as income level, commodity price and quality evaluation. In addition, some characteristics related to consumer behavior and context, such as historical purchase records, visit time, and browsing times, also have a significant impact on purchase intention.