Intelligent assistants are becoming increasingly important for controlling devices, providing social companionship, and assisting people with everyday life. Despite their increasing use, the user experience of intelligent assistants still needs to be improved. This research investigates users’ experience and satisfaction with intelligent assistants, using topic analysis, sentiment analysis, regression analysis, and the KANO model to analyze online reviews. The results show that, in terms of users’ experience, users pay attention to the device attributes (hardware features, functions, and connectivity), and the experience attribute (shopping experience) of the intelligent assistants. Comments related to device attributes contain more user sentiment than comments related to experience attribute. Emotions expressed in reviews related to hardware features and functions are more positive, while emotions expressed in reviews related to connectivity are more negative. In terms of satisfaction, emotional expressions related to hardware features and shopping experience had the greatest impact on users’ satisfaction. Improvements in hardware features and functions are prioritized the highest. The results of this study have implications for the design of intelligent assistants.