Abstract

The aim of this study is to present a new useful process of segmentation in large data, because organizing data into sensible groupings is now becoming the most fundamental modes of understanding and learning and enterprises have gathered a large amount of information over the last decades, the dilemma of managing such information by retrieving advantage in efficient way and less costing methods is becoming the key business success and takes top rows in strategy scale, different methods and techniques have been developed to reduce the data volumes to manageable structure and help enterprise to isolate the business value from the data sets. Clustering is one of those most important used data mining techniques. The algorithm that we will present can be helpful in CRM area. It can be potentially useful to better study customer profiles based on parameters called descriptor and may have a positive impact on customer retention and churn prevention, because the main aim of an ideal business is to optimise customer interactions by well remaining connected with customer.

Keywords:

Clustering, CRM, customer segmentation , similarity,

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Competing interests

The authors have no competing interests.

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Copyright

The authors have no competing interests.