Analyze the trends of customer purchase data and visualize by the Shiny application

Kazuki Konda, Yoshiro Yamamoto
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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.
分析客户购买数据的趋势,并通过Shiny应用程序可视化
在本研究中,我们通过时间序列的转换来分析客户分类。我们利用客户信息在美发连锁店工作了两年,收到报价后输入POS数据。我们观察顾客的习惯,目的是分析和分类。此外,我们提出了关于营销的建议,以使商店受益。我们使用编程语言R进行分析。我们使用基于癸基分析的RFM分析。作为一种分析技术,从购买信息中对每一特定时期的顾客进行分类。我们可以看到购买习惯是如何改变的,从上一段时间他们到下一段时间的过渡,从使用商店,年龄,性别,购买内容等等。此外,通过使用R中的shiny包和visNetwork包,我们创建了应用程序来交互式地可视化它们。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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