Marketing Strategy Analysis Based on User Profiling of Unmanned Supermarket Consumers

Due to the limitations of traditional stores, the collection of user data is not comprehensive enough and the utilization of user data is not precise enough, which affects the accuracy of target audience positioning. Based on the application of intelligent technology, unmanned supermarkets can achieve comprehensive and accurate data collection through automated devices and smart monitoring systems. Therefore, by constructing user profiles, understanding the characteristics of different user types, and providing personalized services, user satisfaction and loyalty can be improved. This study is based on data from unmanned supermarkets to establish a user profile database, using statistical and clustering analysis to classify users and formulate corresponding marketing strategies. The research shows that commuting elderly users, leisure elderly users, and potential new users are the main user types. By providing marketing strategies based on different user needs, the long-term and healthy operation of unmanned supermarkets can be achieved.