Dynamic pricing in marketing

Forming effective marketing communications with the target audience in the digital environment involves implementing a modern and flexible pricing system that considers the dynamics of changes in a set of factors. A hypothesis has been formulated that dynamic pricing based on machine learning algorithms allows businesses to achieve optimal demand for goods and services of companies, and also helps to ensure the loyalty of consumers to the brands in the long term. Conducting the research, general scientific methods of analysis and synthesis were used to characterize the main strategies of dynamic pricing used in marketing; empirical methods, graphical representation, and system-structural analysis. The main pricing strategies used by companies to stimulate demand for goods and services are presented. The effectiveness of using dynamic pricing in various areas of economic activity is proven, and international companies that successfully use the presented approaches are also presented. The main strategies of dynamic pricing are disclo­sed, which are used following the specifics of the companyʼs activities, the characteristics of the target audience, and product characteristics. The main advantages of using dynamic pricing in e-commerce are presented. The prospects for the development of the consumer electronics market are proven, and the dynamics of the growth of this market capacity during 2023–2034 are presented. Basic machine learning algorithms are used to build dynamic pricing models for popular smartphone models in three price segments in Ukraine in 2025