RESEARCH OF THE ORGANIC TRAFFIC OPTIMIZATION SYSTEM FOR E-COMMERCE PLATFORMS USING LARGE LANGUAGE MODELS
The paper explores the use of large language models (LLM) to optimize SEO processes to increase organic traffic for e-commerce platforms. The possibilities of scalable adaptation of large content volumes to the requirements of search algorithms using tools built on the basis of LLM are considered. A comparative analysis of the effectiveness of new automated SEO optimization methods and traditional manual tuning approaches is conducted using the example of an e-commerce platform with a wide range of products and a high level of traffic.