Evaluation on interactive waiting experience design of mobile internet products based on machine learning

• Published in: Scientific reports Vol. 13; no. 1; pp. 16985 - 10
• Main Author: Yu, Yi
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 09.10.2023; Nature Publishing Group; Nature Portfolio
• Subjects: 631/1647; 631/553; Anxiety; Design; Humanities and Social Sciences; Learning algorithms; Machine learning; multidisciplinary; Optimization; Science; Science (multidisciplinary); User experience
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-023-43405-2

In today’s rapidly changing economy, efficient lifestyle has become the current situation of most mobile product users. With the development of performance tools and technologies, a fast lifestyle has brought more wealth and opportunities to users. The slow pace and fluctuating time are indirect income losses, which cause user anxiety to some extent. When the waiting time exceeds the user’s waiting threshold, users would experience negative emotions, such as boredom, anxiety and anger, and product satisfaction would drop significantly. Therefore, by analyzing the uniqueness of mobile Internet products and the characteristics of users, this paper studied the reasons and influencing factors of product interactive waiting, and then used machine learning algorithm to analyze the cost function of interactive waiting experience. Finally, the corresponding interactive waiting experience design strategy was proposed. By comparison, the user experience after product interaction optimization design was 8.4% higher than that before product interaction optimization design, and the user frequency was also 14.7% higher after optimization design. In short, user experience plays an important role in product interaction design.