Guizhou Province of China relies heavily on tourism, especially rural tourism. This study aims to develop and validate a structured framework for understanding tourists’ perceptions of Guizhou’s rural tourism destinations. The study selected three sites: Zhaoxing Dong Village, Qianhu Yi Village (Haiping, Liupanshui), and Xijiang Qianhu Miao Village. To accomplish this task, the netnography method provides realistic pictures of tourist experiences and feedback, which is theoretically supported by reviewing the extant literature. The four domains of factors that influence tourist satisfaction and loyalty are captured in a theoretical framework, which includes destination theme (attractions and destination identity), destination enabler (amenity services and rural interactions), experience-driven (sensory experience, intellectual experience, and emotional experience), and promotion target (induced versus organic image matching, and personality matching). These factors are shown to be structurally linked to influence the perceptions and experience states of the tourists, represented by the perceived sustainability ability of the destination, authenticity, attachment, and flow experience state. Collectively, these factors are treated as inputs using neural network (NN) simulation, which provides the optimized weights for TOPSIS computation and SEM (structural equation modeling) validation. TOPSIS ranks the performances of the destination (e.g., inferred as the perceived preference of the tourists) based on the ANN (artificial neural network)-simulated weights.