Advanced data capturing and networking technology in Grape Growing Marketing and Customer Behavior Modeling

In grape-growing marketing areas, data representation of consumer behavior objects do not correspond to the information available in existing databases. This problem is directly associated with the low level of implementation of advanced data capturing technologies in the processes of network-driven management of customer interactions, as well as with the lack of algorithmic support for promptly making changes to the network structure by the dynamic relations between influencers of the consumer ecosystem. As a solution to these challenges, the integrated use of sentiment analysis and network modeling technologies is proposed. The article examines the development of customer segmentation models based on computational analysis of interaction networks. It is proposed to use extended methodological frameworks and computational methods for processing "big data" in the sociological study of consumer clusters. The article provides an extended overview of the architecture of the network-based marketing system, the principles of maintaining a data-driven basis for consumer behavior prediction systems and the technological process of preparing structured data for decision-making on the market landscape. Using the example of sentiment-driven modeling of the grape-growing consumer market, the functioning of the technological infrastructure on the use of predictive analytics support in the management of marketing strategy objects is shown.