Abstract. The designing and marketing models of general catering customer service APP are made from business owners needs or from commissioned design company's thoughts. The ZMET and MEC technique are used to understand the consumers more properly. Consumers usually will not purchase a product for just the physical content or functionality of the product but will do so because of other reasons, such as what the product presents socially, how it affects their emotions and more In this context, it is necessary to identify the meaning better. This research attempts to understand how customer satisfaction in the context of the catering industry could be understood better by identifying product and company attributes. The catering company can then develop a unique style of their own, so consumers can better understand the ethos of the company, their culture and style. According to consumers' experience, we conclude 5 user expectations of catering customer service APP, including Fans Evaluation, Online-to-Offline Consistency, Timeliness, Smart Order, and Customized Logistics. In this paper, the results of these information show that the user expectations of catering customer services APP will become the effective scientific reference and different patterns of cognitive communities.

Despite extensively investigating the impact of social media on fashion products’ marketing, little evidence is available on how the platforms influence sales prediction. Focusing on Lolita fashion, this study investigates the impact of social media marketing on the sales volume prediction of fashion products. Essentially, we analyzed marketing data, including comments, likes, and shares from the Weibo social platform, to forecast future sales, examine how to enhance profit performance, and make production decisions. Using a quantitative approach, we tested three different prediction models, including multiple regression, decision tree, and XGBoost. The results revealed that increasing comments and decreasing the number of likes could significantly improve the sales volumes of Lolita products. In contrast, shares exerted a less significant impact on sales. Regarding prediction models, XGBoost was found to be the best method. In the fashion industry, social media is a useful tool for forecasting market trend. A limitation of this study is that only one social media platform was used to extract data, which might limit the generalization of the findings.