The role of product art design based on a fuzzy decision support system in improving user interaction experience

User interaction for product selection relies on its design and technical support to improve the quality of the experience. Decision support systems are incorporated to leverage user experience through product interactions. This article introduces an interaction-based fuzzy decision support (FDS) system to meet user demands in product design through suggestions for user interaction. The proposed system models the maximum possible interaction features through previous user experiences and reviews. Based on these two factors, the fuzzy decisions for interaction improvement or product design modification are identified through likelihood. This likelihood is a variant between lower and higher fuzzy combinations for maximum interaction pursued by the user. The fuzzy process develops multiple higher-order recommendation variants from the interaction computed to improve the user experience. The lower-order variants recommend different product design features to increase the interaction rate. Thus, the decision process determines the need for adaptability through interactive platforms to achieve a better experience. This methodology aimed to improve the interaction rate of 97.4% with better impacts on product design and modification using likelihood variants. The user experience assessment is performed using the higher-order variants with a better user adaptability rate of 98.9%, maximizing the recommendations.