In the article, the author provides an analysis of the state of the digital economy, when the dynamics of processes in the economy are quite high and a quick analysis of multidimensional data is required, where the strategy for the production of goods and market promotion, as well as pricing, depends on consumers. The author determined that the activity of modern trading platforms is aimed at the formation of the product range and its product range with the most advantageous characteristics of the product. These requirements have a direct impact on marketing strategy and pricing at the Internet-market. The author proposed the concept of building a digital marketing system based on the theory and practice of market segmentation, which takes into account many factors: geographical, costs, time, and others. The formation of similarities in consumption and pricing in the Internet market is the unifying factor in marketing research. In this concept, the author applied the method of assessing consumer efficiency, which is based on the use of rating estimates obtained on the basis of the ranking of expert opinion. Thus, the proposed concept and method for assessing consumer demand in the target market is aimed at the perspective management of trading platforms using cloud technologies.

This article discusses the theoretical aspects of evaluating personnel performance indicators in the development of the digital economy. Eight procedures were identified for a comprehensive assessment of staff performance. A mathematical apparatus was built for assess normative or average values of performing job duties, determine many specialties, assess the level of education, evaluate the levels of enterprise management, describe many posts, describe the correspondence and interchangeability of posts, evaluate additional characteristics of employees and describe many additional tasks and their characteristics. Allocated linguistic variables characteristics of employees. The structural model of data mining in HR process management was built. Highlighted the membership function of the input linguistic variables of the staff and conducted a description of linguistic variables.

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In this article, a systematic methodology for analyzing and assessing the effectiveness of human resources based on fuzzy sets using big data technologies is used. Based on our research, we analyzed the big data construction method for our chosen approach using Industry 4.0. For the selected fuzzy sets, a set of sequence of procedures in the sequence of the method for assessing the effectiveness of human resources have been identified. Input and output membership functions for data mining have been developed. This article discusses process of building rules of fuzzy logic that allowed us to determine the degree of truth for each condition. The relevance achieved through the development of a methodology that includes eight procedures required for a comprehensive assessment of the economic efficiency of human resources. In this article, an approach to assessing the normative or average values of the performance of official duties by employees of an enterprise in many specialties, educational levels, levels of management, as well as taking into account the description of many positions, descriptions of compliance and interchangeability of positions, assessment of additional characteristics of employees and a description of many additional tasks and their characteristics is presented. The article presents a structural data-mining model for personnel assessment. The results of modeling the assessment of human resources is presented.