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This article presents a comprehensive analysis of the application of big data technologies in modern marketing. The research covers key aspects of using big data for personalizing customer experience, predicting consumer behavior, and optimizing marketing strategies. The work examines data processing architectures, analysis methods, and machine learning techniques used in marketing, as well as presents practical cases of successful implementation of big data solutions in various industries. The purpose of this study is to identify the main directions of applying big data in marketing and assess their impact on the effectiveness of marketing campaigns. To achieve this goal, 50 case studies of companies that have implemented big data solutions were analyzed, interviews with 15 experts in marketing and data were conducted, and key performance metrics were evaluated. The results show that companies actively using big data in marketing demonstrate on average 35% higher ROI compared to companies not using big data analytics. Significant improvements are observed in offer personalization (conversion rate increase by 42%) and customer churn prediction (reduction by 28%). The study also identified key barriers to implementing big data in marketing: lack of qualified specialists, data integration problems from various sources, and privacy issues. The results and conclusions provide a solid foundation for decision-making regarding the implementation of big data solutions in corporate marketing strategies.
big data, marketing, analytics, personalization, machine learning, forecasting, ROI, customer experience
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