大数据时代下越南中小企业客户细分研究

P. Tam, Duong Minh Son, Trinh Le Tan, H. Ha
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引用次数: 1

摘要

几乎越南的大企业经常使用外包服务进行营销研究,如分析和评估消费者的意图和行为,客户满意度,客户忠诚度,市场份额,市场细分和一些类似的营销研究。在越南最受欢迎的市场研究业务之一是ACNielsen,越南的大企业通常根据ACNielsen的报告计划和调整营销活动。由于预算的限制,越南中小企业往往自己做市场调研。在中小企业的营销研究活动中,客户细分是通过Excel, Facebook分析等工具进行的,或者只是通过简单的设计思维方法来帮助节省成本。然而,这些工具已经不再适合今天这个数据信息爆炸的时代。本文采用基于R包的聚类算法对英国在线零售商进行案例分析。结果证明,与越南中小企业使用的传统方法(SPSS, Excel, Facebook分析,设计思维)相比,聚类方法在客户细分方面具有优势。更重要的是,本文帮助越南中小企业在给定的数据集上有效地理解和应用R在客户细分中的聚类算法。在此基础上,越南中小企业可以计划营销计划,并推动他们的行动,将他们的信息适当地融入到客户的环境和/或个性化信息中
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data Driven Customer Segmentation for Vietnamese SMEs in Big Data Era
Almost Vietnamese big businesses often use outsourcing services to do marketing researches such as analysing and evaluating consumer intention and behaviour, customers’ satisfaction, customers’ loyalty, market share, market segmentation and some similar marketing studies. One of the most favourite marketing research business in Vietnam is ACNielsen and Vietnam big businesses usually plan and adjust marketing activities based on ACNielsen’s report. Belong to the limitation of budget, Vietnamese small and medium enterprises (SMEs) often do marketing researches by themselves. Among the marketing researches activities in SMEs, customer segmentation is conducted by tools such as Excel, Facebook analytics or only by simple design thinking approach to help save costs. However, these tools are no longer suitable for the age of data information explosion today. This article uses case analysing of the United Kingdom online retailer through clustering algorithm on R package. The result proves clustering method’s superiority in customer segmentation compared to the traditional method (SPSS, Excel, Facebook analytics, design thinking) which Vietnamese SMEs are using. More important, this article helps Vietnamese SMEs understand and apply clustering algorithm on R in customer segmenting on their given data set efficiently. On that basis, Vietnamese SMEs can plan marketing programs and drive their actions as contextualizing and/or personalizing their message to their customers suitably
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