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Generating Customer Profiles for Retail Stores Using Clustering Tech

机译:使用集群技术生成零售商店的客户资料

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The retail industry collects huge amounts of data on sales, customer buying history, goods transportation, consumption, and service. With increased availability and ease of use of modern computing technology and e-commerce, the availability and popularity of such businesses has grown rapidly. Many retail stores have websites where customers can make online purchases. These factors have resulted in increase in the quantity of the data collected. For this reason, the retail industry is a major application area for data mining. This paper elaborates upon the use of the data mining technique of clustering to segment customer profiles for a retail store. Retail data mining can help identify customer buying patterns and behaviours, improve customer service for better customer satisfaction and hence retention.
机译:零售行业收集了大量有关销售,客户购买历史,货物运输,消费和服务的数据。随着现代计算技术和电子商务的可用性和易用性的提高,此类业务的可用性和受欢迎度迅速增长。许多零售商店都有网站供客户在线购买。这些因素导致收集的数据量增加。因此,零售业是数据挖掘的主要应用领域。本文详细介绍了使用群集的数据挖掘技术对零售商店的客户资料进行细分。零售数据挖掘可以帮助识别客户的购买模式和行为,改善客户服务,从而提高客户满意度,从而保留客户。

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