(untitled) (Collection of research papers «ECONOMIC STRATEGY AND PROSPECTS OF TRADE AND SERVICES SECTOR DEVELOPMENT», 2026)
Natural language processing reshapes data analytics, revealing new avenues for comprehending customers and refining strategies, along with easing tasks like sentiment analysis, market segmentation, and targeting. It is crucial to regard data accuracy, data protection, and query handling capability for effective technology deployment. A main challenge is transforming raw data into clear and helpful insights. The solution rests in natural language processing systems and generative artificial intelligence, which allow converting complex data into accessible and relevant insights for implementation. Traditional manual review has long failed to satisfy present enterprise requirements, as it requires significant human resources, rendering the operation notably expensive. Natural language processing presents an answer to this problem by deploying algorithms able to automatically analyse text meanings, identifying the sentiment of statements, and extracting main entities from large data sets. The focus of the study is to build a framework for automatic user feedback analysis grounded on proven methods and models for automatic review assessment using natural language processing tools. The study outcomes can be utilized to construct software solutions that will assist businesses in better understanding customer needs, promptly resolving problems, and improving the quality of their products and services.