Enhancing Retail Transactions: A Data-Driven Recommendation Using Modified RFM Analysis and Association Rules Mining

IF 2.5 4区综合性期刊 Q2 CHEMISTRY, MULTIDISCIPLINARY

Applied Sciences-Basel Pub Date : 2023-09-06 DOI:10.3390/app131810057

Angela Hsiang-Ling Chen, Sebastian Gunawan

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引用次数: 1

Abstract

Retail transactions have become an integral part of the economic cycle of every country and even on a global scale. Retail transactions are a trade sector that has the potential to be developed continuously in the future. This research focused on building a specified and data-driven recommendation system based on customer-purchasing and product-selling behavior. Modified RFM analysis was used by adding two variables, namely periodicity and customer engagement index; clustering algorithm such as K-means clustering and Ward’s method; and association rules to determine the pattern of the cause–effect relationship on each transaction and four types of classifiers to apply and to validate the recommendation system. The results showed that based on customer behavior, it should be split into two groups: loyal and potential customers. In contrast, for product behavior, it also comprised three groups: bestseller, profitable, and VIP product groups. Based on the result, K-nearest neighbor is the most suitable classifier with a low chance of overfitting and a higher performance index.

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增强零售交易：一种基于改进RFM分析和关联规则挖掘的数据驱动建议

零售交易已成为每个国家乃至全球经济周期中不可或缺的一部分。零售交易是一个在未来具有持续发展潜力的贸易部门。本研究的重点是建立一个基于客户购买和产品销售行为的指定和数据驱动的推荐系统。采用改进的RFM分析方法，加入周期和客户参与指数两个变量;聚类算法，如K-means聚类和Ward方法;关联规则用于确定每笔交易的因果关系模式，四种分类器用于应用和验证推荐系统。结果表明，根据顾客的行为，应将其分为两组:忠诚顾客和潜在顾客。相比之下，在产品行为方面，它也分为三组:畅销产品组、盈利产品组和VIP产品组。基于结果，k近邻是最合适的分类器，过拟合几率低，性能指标更高。

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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来源期刊

Applied Sciences-Basel CHEMISTRY, MULTIDISCIPLINARYMATERIALS SCIE-MATERIALS SCIENCE, MULTIDISCIPLINARY

CiteScore

5.30

自引率

11.10%

发文量

10882

期刊介绍： Applied Sciences (ISSN 2076-3417) provides an advanced forum on all aspects of applied natural sciences. It publishes reviews, research papers and communications. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. There is no restriction on the length of the papers. The full experimental details must be provided so that the results can be reproduced. Electronic files and software regarding the full details of the calculation or experimental procedure, if unable to be published in a normal way, can be deposited as supplementary electronic material.