基于外卖数据的社区团购选品系统研究与应用  

RESEARCH AND APPLICATION OF COMMUNITY GROUP BUYING SELECTION SYSTEM BASED ON TAKEOUT DATA

作　　者：李瑾[1] 刘云鹏[1] 邱虹 Li Jin;Liu Yunpeng;Qiu Hong(Zhejiang Wanli University,Ningbo 315100,Zhejiang,China)

机构地区：[1]浙江万里学院,浙江宁波315100

出　　处：《计算机应用与软件》2022年第11期43-48,118,共7页Computer Applications and Software

基　　金：国家自然科学基金项目(61906170);浙江省教育厅项目(Y201840695);宁波市自然科学基金项目(2018A610164)。

摘　　要：新零售时代下,社区团购开创了一种全新的团购模式,正确的选品能够帮助社区团购平台提升客户留存,并且通过商品的差异化特点裂变出更多客户。通过对不同社区外卖数据的分析,找出社区对商品需求的差异性,并将外卖菜品名与常见大众菜谱进行关联,同时围绕菜谱推荐,将菜谱主料与竞品单品进行关联,为不同社区的团购选品提供有价值的数据支撑。所提方法在宁波某团购平台试用一个月后,31个不同社区的平均销售额增长率为85.71%,平均有效订单数增长率为70.45%,平均总销售件数增长率为39.69%。In the new retail era,community group buying has created a new group buying mode.The right selection can help the community group buying platform to improve customer retention,and more customers can be split through the differentiation characteristics of commodities.Based on the analysis of the takeout data of different communities,this paper found out the differences of community demand for commodities,and associated the name of takeout dishes with common popular recipes.Around the recommendation of recipes,it associated the main ingredients of recipes with the competitive items,providing valuable data support for the group buying selection of different communities.After one month's trial on a group buying platform in Ningbo,the average sales growth rate of 31 different communities was 85.71%,the average effective orders growth rate was 70.45%,and the average total sales growth rate was 39.69%.

关 键 词：社区团购 短文本相似度 选品 推荐 数据分析 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]