DATA ANALYTICS AND ACCOUNTING AND ANALYTICAL SUPPORT AS THE BASIS FOR INNOVATIVE DEVELOPMENT IN E-COMMERCE (Economic journal of Lesya Ukrainka Volyn National University, 2025)
Introduction. In the era of digital transformation, e-commerce is rapidly evolving, offering increasinglyconvenient opportunities for buying and selling goods and services. According to Statista, the global e-commercemarket is expected to reach USD 4.32 trillion by the end of 2025, while in Ukraine the figure may reach USD 3.32billion. In this context, data analytics has become a critical asset for enterprises to remain competitive and maximizereturns on their digital investments. However, despite numerous advances, businesses still face challenges in managingunstructured data and unlocking its strategic value, especially through the use of artificial intelligence.The purpose of the article. The purpose of the article is to study the role of data analytics in the field of ecommerce, analyze its main advantages, methods and application scenarios, as well as assess the impact of generativeartificial intelligence on improving business processes.Methods. The research employs a multidisciplinary approach combining theoretical analysis, comparativestudies, and empirical observations. The methodology includes content analysis of global analytical reports (fromGartner, Statista, McKinsey, etc.), review of scholarly publications, and evaluation of business case studies involvingreal-time data systems and generative AI applications in e-commerce. The study pays special attention to the synergybetween analytical platforms and AI-driven personalization, chatbots, content automation, and predictive modeling.Results. The study found that data analytics in e-commerce plays a pivotal role in optimizing demand forecasting,inventory management, customer retention, fraud detection, and marketing efficiency. Key analytics types - descriptive,diagnostic, predictive, and prescriptive - are widely used to extract insights from customer behavior, transactionpatterns, and social media feedback. It has been established that the combination of modern analytical methods with apowerful accounting and analytical support system creates a reliable foundation for strategic management of ecommerce, reducing risks, increasing efficiency, and contributing to the sustainable development of the enterprise inthe digital economy. The integration of generative AI with data analytics enables highly personalizedrecommendations, real-time content generation, dynamic pricing, and smarter decision-making across customertouchpoints. Moreover, the research outlines critical challenges such as data fragmentation, real-time processing,compliance with data protection regulations, and cost-effectiveness of analytics investments.Conclusions. Data analytics has become a cornerstone of innovation and competitiveness in e-commerce. Thecombination of analytical methods and generative AI allows businesses to make data-driven decisions, personalize thecustomer journey, and increase profitability. For companies operating in Ukraine and globally, strategic integration ofanalytics into business models, supported by scalable and secure data infrastructures, is essential for future growth.Further research should explore advanced AI-analytics convergence scenarios and address the implementationbarriers in small and medium-sized enterprises.
Keywords: data analytics, e-commerce, generative artificial intelligence, accounting and analytical support, user behavior analysis, content personalization, demand forecasting, inventory management, pricing analytics, usiness process automation.