Dynamic Pricing in Retail Trade: Algorithms, Effects, and Limitations of Application

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The article considers dynamic pricing as a management practice based on data, analytics, and algorithmic models. The relevance of the topic is driven by the digital transformation of retail, the growth of e-commerce, and the adoption of Big Data and artificial intelligence technologies, which turn pricing from a periodic operation into a continuously managed process. The paper reveals the essence of dynamic pricing and its place in the company management system, shows the role of Big Data and machine learning as the basis for forming pricing decisions, systematizes tools and pricing strategies, summarizes the experience of Russian retailers, and assesses the effects, risks, and limitations of application. It is substantiated that the effectiveness of dynamic pricing is determined not by the frequency of price revisions, but by the quality of data, analytics, and managerial coordination.