Research on the Construction and Optimization Path of Digital Marketing Systems Driven by Deep Learning Algorithms

Abstract

With the networking and internationalization of commodity circulation and sales, the establishment of a digital marketing system is of great significance for maintaining the business environment and the operation of the business system. Deep learning algorithms have significant advantages in system construction and optimization. Based on this, this paper first introduces the definition, model classification, principles, and application advantages of deep learning algorithms. It analyzes the current situation of digital marketing, as well as the transformation achievements and existing dilemmas. Then, it proposes to use deep learning algorithms to construct a digital marketing system, covering the design ideas of the system architecture, data processing, and the selection of algorithm models. Finally, optimization paths such as data feedback and multi - algorithm fusion strategies are proposed. Building a marketing system with deep learning algorithms can help enterprises accurately grasp consumer demands, timely adjust marketing methods and directions, and promote the efficient circulation of commodities. Each link in its construction and optimization is closely connected, jointly constructing an efficient digital marketing system. It also indicates that deep learning algorithms have broad development prospects and potential in the marketing field in the big - data era.