<p>Live streaming of e-commerce platforms attracts consumers for their products/purchases and hence the familiarity is retained high amid different competitors. Fuzzy decision systems are incorporated to filter the streaming content of the platforms to improve consumer augmentations at different promotions. Therefore to support such augmentation and consumer building process, this article proposes a filtered sale streaming model to improve the circulation of new launches and to project the existing products through sustainable promotions. In this process, the comprehensive transition rule for product promotions and sale improvements is defined using fuzzy mining. The fuzzy process introduces the different performance members based on consumer access rate and sale count. The rule modifications are defined using the above factors’ decrease over filtered promotions to boost the augmentation. Using the highest possible member weights over a product, sale, and consumers, the linear improvements between the three factors are estimated over the closure observed at each sale interval. Thus, the streaming modifications and the product exposures are modeled using different mining rules adaptable for e-commerce platforms.</p>