Retail business analytics: Customer visit segmentation using market basket data
作者：
Highlights：
• Business analytics approach that mines customer visit segments from basket sales data.
• A semi-supervised feature selection approach to adjust product taxonomy tree.
• Clustering is used to identify customer shopping mission based on market basket data.
• Shoppers’ buying patterns in terms of product categories characterize customer visits.
• The approach is evaluated by applying it to 38M transactions provided by a retailer.
摘要
•Business analytics approach that mines customer visit segments from basket sales data.•A semi-supervised feature selection approach to adjust product taxonomy tree.•Clustering is used to identify customer shopping mission based on market basket data.•Shoppers’ buying patterns in terms of product categories characterize customer visits.•The approach is evaluated by applying it to 38M transactions provided by a retailer.
论文关键词：Customer visit segmentation,Retail business analytics,Shopper behavior,Clustering,Data mining
论文评审过程：Received 7 September 2017, Revised 15 December 2017, Accepted 20 January 2018, Available online 2 February 2018, Version of Record 5 February 2018.
论文官网地址：https://doi.org/10.1016/j.eswa.2018.01.029
