An Analysis of Community Group Buying Behavior of Urban Residents Based on Big Data

By using keywords crawled by big data as a survey reference, this research applied latent category clustering method and binary logistic regression model analysis method to analyze the differences in community group buying behaviors of residents from different city scale and summarize the shopping behavior and features of different types of residents, for the purpose of offering advice on different marketing methods for different types of urban residents, so as to realize the precise marketing of community e-commerce and promote the further development of the industry.