The use of machine learning as a tool for digitalization of the economic activity of retailers

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The article describes the use of machine learning as a tool for digitalizing the economic activities of companies - players in the retail market of the Russian Federation. Currently, machine learning is one of the main tools for digitalization of the modern Russian economy, but due to the specifics of the retail market and the lack of such experience, a very small number of organizations implement this tool in their activities. The article proposes a set of indicators that helps to assess the efficiency and effectiveness of business processes, before and after the introduction of machine learning models, the calculation of which is unique for each retailer. Particular attention is paid to machine learning algorithms applied to the activities of retailers to improve the two main processes of their activities, namely the pricing process and the supplier selection process. The author proposes an algorithm for implementing machine learning models, which has already been tested in two large organizations and is in constant use. This algorithm is the basic algorithm for the retailer's transition to the use of machine learning, while the company itself must determine the learning features in accordance with the specifics of its economic activity.

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Retail, quality management, sale of goods & services to consumers, customer satisfaction, economic efficiency, performance, machine learning, linear regression, logistic regression, distribution channel

Короткий адрес: https://sciup.org/140300858

IDR: 140300858

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