Customer Segmentation Using Machine Learning

N. Patankar, Soham Dixit, Akshay Bhamare, Ashutosh Darpel, Ritik Raina
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引用次数: 1

Abstract

Nowadays Customer segmentation became very popular method for dividing company’s customers for retaining customers and making profit out of them, in the following study customers of different of organizations are classified on the basis of their behavioral characteristics such as spending and income, by taking behavioral aspects into consideration makes these methods an efficient one as compares to others. For this classification a machine algorithm named as k-means clustering algorithm is used and based on the behavioral characteristic’s customers are classified. Formed clusters help the company to target individual customer and advertise the content to them through marketing campaign and social media sites which they are really interested in.
使用机器学习进行客户细分
如今,客户细分成为划分公司客户以保留客户并从中获利的非常流行的方法,在接下来的研究中,不同组织的客户是根据他们的行为特征如支出和收入进行分类的,通过考虑行为方面使这些方法与其他方法相比是有效的。对于这种分类,使用了一种称为k-means聚类算法的机器算法,并根据行为特征对客户进行分类。形成的集群帮助公司瞄准个人客户,并通过营销活动和他们真正感兴趣的社交媒体网站向他们宣传内容。
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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