数据驱动洞察：K-means算法下即时零售线上超市消费者画像的实证研究及策略启示

• 作者： 邱婷婷 ¹ 林莉 ¹
• 作者单位：
  1.  福建农业职业技术学院
• 通讯作者： 林莉 
• 发布时间：2024-09-18

摘要: 本文通过对即时零售线上超市平台消费者的行为数据进行分析，基于K-means聚类方法，将消费群体按照其行为特征进行细分，得到四类用户：补充购物者、猎奇购物者、敏感购物者、活跃购物者，并针对不同类型用户的特征构建了即时零售线上超市FAST营销策略模型，提出了让消费者买得到、想得到、有性价比和体验佳等策略 。这些策略的实施可以促进用户转化和提升用户体验，帮助即时零售线上超市平台更好地为用户进行精细化推荐和服务，有效地吸引和留住各类用户，实现即时零售线上超市平台的长期发展。

Abstract: This paper analyzes the behavioral data of consumers on the instant retail online supermarket platform. Based on the K-means clustering method, the consumer groups are segmented according to their behavioral characteristics, and four types of users are obtained: supplemental shoppers, curiosity shoppers, sensitive shoppers, and active shoppers. A FAST marketing strategy model for the instant retail online supermarket is constructed based on the characteristics of different types of users, and strategies such as making the product available, desirable, cost-effective, and providing an excellent experience are proposed. The implementation of these strategies can promote user conversion and improve user experience, helping the instant retail online supermarket platform to provide more refined recommendations and services for users, effectively attract and retain users of various types, and achieve long-term development of the instant retail online supermarket platform.

• 来自： 邱婷婷
• 分类： 工商管理学 >> 企业管理
• 稿件状态： 未投稿
• 引用： PSSXiv:202409.01239 (或此版本 PSSXiv:202409.01239V1)
  DOI:10.12451/202409.01239
  CSTR:32012.36.PSSXiv.202409.01239
• 推荐引用方式： 邱婷婷,林莉.数据驱动洞察：K-means算法下即时零售线上超市消费者画像的实证研究及策略启示.哲学社会科学预印本平台:https://zsyyb.cn/abs/202409.01239.[PSSXiv:202409.01239V1] (点此复制)