Web analytics as a tool for improving the effectiveness of digital marketing in Russia

Abstract

Introduction. The article analyzes the challenges facing modern digital marketing and the role of web analytics in ensuring informed management decisions at Russian small and medium-sized businesses. The paper examines the stages of web analytics development, with an emphasis on the transition from basic monitoring of positions in search engines to sales forecasting based on artificial intelligence methods. Special attention is paid to the use of Russian business intelligence systems to solve automation problems and optimize marketing efforts in order to achieve maximum efficiency in the field of planning and development of the company. Purpose. Research of the role of web analytics as a key tool for improving the effectiveness of digital marketing, analysis of its development and application possibilities for automating marketing processes. The relevance of the topic is due to the dynamic development of digital marketing in Russia and the growing competition in the online environment, which requires business to make prompt and informed decisions. In the context of rapidly changing user preferences, increased regulation of online advertising, and the need to increase the effectiveness of advertising budgets, traditional web analytics methods are becoming insufficient. Results. The results of the study indicate that web analytics plays a significant role in digital marketing, requiring not only the use of various tools and services, but also the ability to structure data, formulate hypotheses and predict user behavior on the site. Effective integration of web analytics into an enterprise's digital marketing system can significantly improve the quality and productivity of its Internet strategies, as well as optimize the overall operation of the marketing system by providing timely information about consumer behavior and brand perception. Conclusions. The use of end-to-end analytics and BI systems plays an important role in the development of digital marketing, contributing to in-depth data analysis, process automation, and personalized customer interaction. Further research should be focused on developing methods for assessing the impact of AI, optimizing the integration of analytical systems, and improving educational programs for training specialists in this field.