The Role of Big Data in the Digital Transformation of Marketing Systems in Turbulence Conditions

Анотація

Purpose. The study aims to substantiate the role of Big Data-based marketing as a strategic foundation for ensuring business viability in conditions of global turbulence. The paper analyzes the transformation of the traditional “intuitive” management model into an exact science based on evidence and real-time hyper-personalization. Methods. The article uses the method of system analysis to form a functional marketing architecture. Comparative analysis is used to describe the characteristics of data sources and compare the characteristics of digital marketing in periods of stability and turbulence. The generalization method allowed us to move from technology analysis to strategic conclusions, and the comprehensive approach combined different models and tools. Results. A conceptual marketing architecture has been developed, which includes Data-Driven Decision Making, Omnichannel, Predictive Analytics, 360-degree customer view, and Artificial Intelligence. It has been determined that Artificial Intelligence acts as an intellectual engine at all stages of the Big Data life cycle. It has been determined that the transition from intuitive marketing to scientifically based analysis allows for the implementation of hyper-personalization and objective decision-making in real time. The transition to a 360-degree customer view model, which combines online and offline consumer experiences, has been explored. Key data sources have been identified, among which first-party data is becoming critically important in turbulent conditions. Critical challenges have been identified, such as ethical and legal restrictions, the problem of data quality and relevance, technological challenges and cost, algorithmic bias, and Black Box AI. The impact of GDPR, CCPA, and Privacy First regulatory restrictions on the transformation of data collection methods has been outlined. Conclusions. The success of modern marketing strategies is determined not by the volume of accumulated data, but by the speed of extracting predictive insights and the system's ability to adapt. In turbulent conditions, businesses must move from extensive information accumulation to a model of pragmatic selection of highly liquid data that ensures transparency, cybersecurity, and emotional loyalty of consumers.

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