Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Retail analytics: store segmentation using Rule-Based Purchasing behavior analysis
The International Review of Retail, Distribution and Consumer Research ( IF 2.9 ) Pub Date : 2021-04-29 , DOI: 10.1080/09593969.2021.1915847
Emrah Bilgic 1 , Ozgur Cakir 2 , Mehmed Kantardzic 3 , Yanqing Duan 4 , Guangming Cao 5
Affiliation  

ABSTRACT

Retailers are facing challenges in making sense of the significant amount of data available for a better understanding of their customers. While retail analytics plays an increasingly important role in successful retailing management, comprehensive store segmentation based on Data Mining-based Retail Analytics is still an under-researched area. This study seeks to address this gap by developing a novel approach to segment the stores of retail chains based on ‘purchasing behavior of customers’ and applying it in a case study. The applicability and benefits of using Data Mining techniques to examine purchasing behavior and identify store segments are demonstrated in a case study of a global retail chain in Istanbul, Turkey. Over 600 K transaction data of a global grocery retailer are analyzed and 175 stores in Istanbul are successfully segmented into five segments. The results suggest that the proposed new retail analytics approach enables the retail chain to identify clusters of stores in different regions using all transaction data and advances our understanding of store segmentation at the store level. The proposed approach will provide the retail chain the opportunity to manage store clusters by making data-driven decisions in marketing, customer relationship management, supply chain management, inventory management and demand forecasting.



中文翻译:

零售分析:使用基于规则的采购行为分析进行商店细分

摘要

零售商在理解大量可用数据以更好地了解客户方面面临挑战。虽然零售分析在成功的零售管理中发挥着越来越重要的作用,但基于数据挖掘的零售分析的综合商店细分仍然是一个研究不足的领域。本研究旨在通过开发一种新颖的方法来解决这一差距,以根据“客户的购买行为”对零售连锁店进行细分,并将其应用于案例研究。在土耳其伊斯坦布尔的一家全球零售连锁店的案例研究中,展示了使用数据挖掘技术检查购买行为和识别商店细分的适用性和好处。分析了一家全球杂货零售商超过 60 万的交易数据,成功将伊斯坦布尔的 175 家商店划分为五个部分。结果表明,所提出的新零售分析方法使零售连锁店能够使用所有交易数据识别不同地区的商店集群,并增进我们对商店级别商店细分的理解。提议的方法将通过在营销、客户关系管理、供应链管理、库存管理和需求预测方面做出数据驱动的决策,为零售连锁店提供管理商店集群的机会。结果表明,所提出的新零售分析方法使零售连锁店能够使用所有交易数据识别不同地区的商店集群,并增进我们对商店级别商店细分的理解。提议的方法将通过在营销、客户关系管理、供应链管理、库存管理和需求预测方面做出数据驱动的决策,为零售连锁店提供管理商店集群的机会。结果表明,所提出的新零售分析方法使零售连锁店能够使用所有交易数据识别不同地区的商店集群,并增进我们对商店级别商店细分的理解。提议的方法将通过在营销、客户关系管理、供应链管理、库存管理和需求预测方面做出数据驱动的决策,为零售连锁店提供管理商店集群的机会。

更新日期:2021-04-29
down
wechat
bug