Economic cybernetics in marketing budget management: optimization of digital advertising expenses - Zubova, V.; Nikolaeva, O.; Savchenko, Ye. (Bulletin of V. N. Karazin Kharkiv National University Economic Series, 2025)
The article highlights the role of economic cybernetics in the context of economic digitalization and substantiates its relevance in the field of marketing budget management. It is noted that effective planning of advertising expenditures requires the application of mathematical models capable of capturing complex interrelationships among consumers, promotion channels, and business strategic goals. The purpose of the study is to substantiate the feasibility of integrating economic cybernetics tools (logistic regression, Markov chains, game theory) and modern digital technologies (Big Data, machine learning) into the process of enterprise marketing budget planning. The article reveals the advantages of using logistic regression to forecast ad clicks, taking into account consumers’ demographic and behavioral characteristics. The Markov chain model is applied to analyze multichannel interactions and identify the most effective touchpoints. Game theory is used to describe strategic responses to competitors’ actions in the digital environment. The critical role of Big Data technologies is outlined in improving audience segmentation, personalizing advertising content, and enhancing predictive accuracy. It is shown that machine learning algorithms enable automated data analysis and allow for real-time strategy adaptation. Key digital marketing KPIs (CPM, CPC, CTR, CPA, ROMI, LTV) are systematized to evaluate campaign effectiveness. The application of the AIDA model to online marketing is demonstrated, and empirical examples are provided on audience segmentation, improving prediction accuracy over time, and budget optimization using integer programming. Trends in the global and national digital advertising markets are also considered. The study proves that the integration of economic cybernetics tools with the analytical capabilities of Big Data and machine learning significantly enhances the efficiency of marketing budget management. This is achieved through more accurate consumer behavior forecasting, adaptive strategies to environmental changes, and the formation of optimal, data-driven decisions. A systemic approach to digital campaign planning contributes to increased ROI, strategic flexibility, and a stronger competitive position in the dynamic digital marketplace.