• S P Chandana
• P Karthik Reddy

Consumer Network Traffic has become a major hurdle in Banking and Financial organizations because a huge number of customers try to access the network at the same time. In order to solve this problem the banks, banking and financial sectors have tried Customer Segmentation as a core function and to provide better customer services. Customer Segmentation is an integrated novel approach that helps to understand the customers based on their similarities and allows marketers to address customers in the most effective way. This approach is very much needed in order to lay successful organizations. The accessible clustering models for customer segmentation, as a general rule, and the significant models are Hierarchical and K-Means Clustering. We have used the K-means clustering algorithm which has high computational speed as a hybrid solution to reduce the consumer network traffic.

Network Traffic, Customer Relationship Management, Quality of Service, Customer Segmentation, Hierarchical Clustering, K-Means Clustering, Cluster Analysis.

"Reduction of Network Traffic by Customer Segmentation in Banking Sector", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 8, page no.b117-b124, August-2021, Available :http://www.jetir.org/papers/JETIR2108143.pdf

"Reduction of Network Traffic by Customer Segmentation in Banking Sector", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 8, page no. ppb117-b124, August-2021, Available at : http://www.jetir.org/papers/JETIR2108143.pdf