Abstract

The problem of managing the assortment of goods in retail is considered, a solution to this problem is proposed through digital transformation. It is emphasized that changes in consumer preferences can have a negative impact on business if companies are not ready to respond quickly to them. Goods assortment managing becomes a criti-cal factor for ensuring profitability. The formalization of the economic and mathematical characteristics of the commodity matrix and its impact on the trade policy of the enterprise is discussed. The importance of building an assortment matrix for each retail facility is emphasized, which contributes to more effective analysis and management of the assortment. It is noted that successful product policy management includes not only the assortment, but also pricing, quality of goods, product promotion and sales promotion. To achieve maximum efficiency, it is recommended to use information and analytical systems. A Data Mining methodology is proposed for analyzing the commodity matrix and forecasting demand. The analysis of the product matrix helps to automate the calculation of the sales forecast for a certain period of time, which contributes to more accurate inventory planning and timely formation of orders. The importance of the company's assortment policy is emphasized, which can increase customer demand, reduce costs and increase the marginality of retail activities. The development and implementation of an information and analytical product matrix management system can automate many processes in retail and simplify the management of retail business processes, which contributes to the optimization of the product range and customer satisfaction. In practice, this approach can significantly simplify the management of retail business processes and increase the competitiveness of the enterprise in a dynamic trading environment.

Full Text
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