With the development of community economy and the arrival of the new retail era, many traditional convenience stores have gradually transformed into online and offline convenience stores, which mainly used Internet/Internet of Things technology, big data to analyze consumer behavior, predict consumption trends, and provide consumers with diversified and personalized products and services. Based on the industry environment of convenience stores, a new retail model for chain convenience stores has been proposed, including community convenience stores, community preferred apps or mini programs, e-commerce platforms, and upgrading of online and offline retail scenarios. It is recommended to continuously develop independent e-commerce platforms online, utilizing computer technologies such as virtual machines, intelligent shopping guides, AI recommendations, and machine learning to continuously analyze, mine, and refine consumer behavior data, and establish a rich big data database to achieve precise marketing. It is also recommended to actively guide consumers to experience and optimize the environmental atmosphere of convenience stores according to local conditions offline, in order to improve the influence of community chain convenience stores in the regional market, leverage convenience and convenience characteristics, meet people’s needs for high-quality, heterogeneous, and experiential consumption, and provide fast, convenient, and safe community convenience services.