{"title":"Analyze the trends of customer purchase data and visualize by the Shiny application","authors":"Kazuki Konda, Yoshiro Yamamoto","doi":"10.1109/ICTKE.2018.8612310","DOIUrl":null,"url":null,"abstract":"In this study, we analyze customer classification by the transition of the time series. We use customer information in the hair salon chain stores of two years, received the offer of POS input data. We watched habits of customers with the aim of analysis and classification. Furthermore, we propose regarding marketing for the benefit of the store. We use the programming language R to analysis. And we use the RFM analysis based on decyl analysis. As an analytical technique, performed from the purchase information the customer classification of every certain period of time. We can see how change the buying habits that the time from the period in which there is a them to the next period of time to transition, from use store, age, gender, the purchase content and so on. Further, by using the shiny packages and visNetwork package in R, we create the application to visualize them interactively.","PeriodicalId":342802,"journal":{"name":"2018 16th International Conference on ICT and Knowledge Engineering (ICT&KE)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 16th International Conference on ICT and Knowledge Engineering (ICT&KE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICTKE.2018.8612310","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this study, we analyze customer classification by the transition of the time series. We use customer information in the hair salon chain stores of two years, received the offer of POS input data. We watched habits of customers with the aim of analysis and classification. Furthermore, we propose regarding marketing for the benefit of the store. We use the programming language R to analysis. And we use the RFM analysis based on decyl analysis. As an analytical technique, performed from the purchase information the customer classification of every certain period of time. We can see how change the buying habits that the time from the period in which there is a them to the next period of time to transition, from use store, age, gender, the purchase content and so on. Further, by using the shiny packages and visNetwork package in R, we create the application to visualize them interactively.