客户细分利用差异化方法

J. Panus, Hana Jonášová, Kateřina Kantorová, M. Doležalová, Katerina Horackova
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引用次数: 9

摘要

客户细分和客户关系管理通常是值得探索的有趣课题。我们应该专注于探索这类研究的主要原因之一是客户忠诚度和盈利能力的概念,以增加市场份额。顾客价值可以为更有针对性和个性化的营销提供基础信息。本文将ABC和RFM (current, Frequency, Monetary)相结合用于客户细分。其独特之处在于随后使用数据挖掘分割方法将客户划分为四个部分。我们使用了众所周知的两步法、Kohononen图和K-means方法。结果显示可能使用这些组合的客户细分和结果为不同的细分可以用来解释公司的营销策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Customer segmentation utilization for differentiated approach
Customer segmentation and customer relationship management generally is interesting subject to explore. One of the main reasons why we should focus on exploring this type of research is to notion of customer loyalty and profitability to increasing market share. Customer value can provide basic information for more targeted and personalized marketing. In this paper, combination of ABC and RFM (Recency, Frequency, and Monetary) is used to customer segmentation. What is unique is using data mining segmentation method later on to dividing customers to four segments. We used well known Two Step, Kohononen - maps and K-means methods. Results show possibility to use these combinations for customer segmentation and results for different segments can be used to explain marketing strategies of company.
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