摘要
为更好地描述会员消费者特征,在文献分析的基础上,对RFM模型中的M参数进行改进,新增单笔最大消费金额和高单价商品消费占比两个参数,并以服装品牌会员实际销售数据为例,应用因子分析模型,提取了价格容忍度和会员忠诚度两个因子;利用K-means聚类算法,将会员划分为4类;通过四象限矩阵法对会员进行了画像。最终提出了针对不同类别会员,基于产品价位和产品货龄的9种差异化产品组合策略。
In order to better describe the characteristics of member consumers,on the basis of literature analysis,the M parameter in RFM model was improved,and two parameters were added,namely the maximum consumption amount of a single transaction and the proportion of high unit price goods consumption.In this study the actual sales data of clothing brand members was taken as example,and the factor analysis model was used to extract price tolerance and member loyalty.K-means clustering algorithm was used to divide members into four categories,and four quadrant matrix method was applied to depict members.Furthermore,nine different product mix strategies were proposed based on product price and product age for different types of members.
作者
刘小红
郑茵妮
LIU Xiaohong;ZHENG Yinni(Glorious Sun Guangdong School of Fashion,Huizhou University,Huizhou516007,China)
出处
《服装学报》
CAS
2020年第4期372-376,共5页
Journal of Clothing Research
基金
广东省教育厅重点平台及科研项目(2017WTSCX111)
惠州学院重点项目(hzux1201629)。
作者简介
刘小红(1967-),男,教授,硕士。主要研究方向为服装营销与教育研究。Email:477809786@qq.com。
