Dynamic video content planning: an adaptive model based on niche analysis

The article analyzes the features inherent in dynamic planning of video content, considers the possibilities of using an adaptive model based on niche analysis. The aim of the work is to describe the methods of niche selection and content planning based on data analysis, including behavioral metrics of the audience, competitive environment and algorithmic features of the platform. The methodology includes a systematic review of publications on media analytics and algorithmic strategies, a comparative analysis of existing approaches and the construction of a conceptual scheme for the interaction of key parameters. Practical cases analyzed within the framework of the work demonstrate that the implementation of the proposed model can increase the average viewing time, increase the conversion in subscribers and accelerate the start of monetization compared to a static plan. The results emphasize the need to switch to data-driven strategies. The information reflected in the article will be useful to specialists in the field of media management and marketing who are engaged in the personalization and optimization of video content to increase audience engagement and distribution efficiency. The material will also be of interest to other researchers studying the use of adaptive models and niche analysis for dynamic forecasting of trends and preferences of users of digital platforms.