Big Data as a Tool for Assessing Consumer Practices and Efficiency of Consumer Problem Solving

The article examines Big Data in the context of its impact on the consumption segment: the advantages of this technology and the limiting factors are considered. A consolidated classifier of methods and technologies applicable to Big Data, which today open up breakthrough opportunities for the sustainable development of an organisation, is proposed. Using the example of the use of the analytical service for the automated analysis and processing of virtual community data in a social network, some possibilities of processing large amounts of data are demonstrated with the assignment of audience characteristics and the identification of regularities. It is shown that metrics of users’ involvement, their interactions and indicators of common interests become the basis for identifying the characteristics of the consumer and constructing his social portrait. The research is aimed at identifying the possibilities of using Big Data tools to help solve current consumer-related problems. The problematic issue is the insufficient introduction of basic technologies in the process of researching consumer practices. The paper uses the method of comparative analysis and parsing of data from social networks. The research can be interesting and useful for understanding consumer practices of different segments of the population and practical sphere of product promotion with maximisation of demanded characteristics.