Comparative Analysis of Clustering Techniques for Customer Behaviour

Abstract

In real world, customer behaviour is changing and evolving over time. Business in each industry endeavours to expand client esteem and accomplish a high level state of consumer loyalty. Sells group concentrate on open doors for cross-sell and up-sell while client mind concentrates on certain key measurements, for example first call determination, snappy determination to client’s issues, best service levels and quality scores. Customer clustering is utilized to know about behavioural patterns of customers so that industry or organization can make their marketing strategies according to the customers’ preferences and retain them. This paper shows the performance review of clustering data mining techniques to know which technique is more suitable to identify customer profile and patterns for a retail store, to improve better customer satisfaction and retention.