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Reseach Article

Segmenting the Banking Market Strategy by Clustering

by Varun Kumar. M, Vishnu Chaitanya. M, Madhavan. M
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 45 - Number 17
Year of Publication: 2012
Authors: Varun Kumar. M, Vishnu Chaitanya. M, Madhavan. M
10.5120/7000-9473

Varun Kumar. M, Vishnu Chaitanya. M, Madhavan. M . Segmenting the Banking Market Strategy by Clustering. International Journal of Computer Applications. 45, 17 ( May 2012), 10-15. DOI=10.5120/7000-9473

@article{ 10.5120/7000-9473,
author = { Varun Kumar. M, Vishnu Chaitanya. M, Madhavan. M },
title = { Segmenting the Banking Market Strategy by Clustering },
journal = { International Journal of Computer Applications },
issue_date = { May 2012 },
volume = { 45 },
number = { 17 },
month = { May },
year = { 2012 },
issn = { 0975-8887 },
pages = { 10-15 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume45/number17/7000-9473/ },
doi = { 10.5120/7000-9473 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:37:50.301410+05:30
%A Varun Kumar. M
%A Vishnu Chaitanya. M
%A Madhavan. M
%T Segmenting the Banking Market Strategy by Clustering
%J International Journal of Computer Applications
%@ 0975-8887
%V 45
%N 17
%P 10-15
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Customer segmentation is the practice of dividing a customer base into groups of individuals that are similar in specific ways relevant to marketing such as age, gender, interests, spending habits, and so on. One of the easiest definitions is "a group of customers with shared needs". From this definition, it's clear what we need to identify customers with shared needs. The customer segmentation consists of two phases. First phase includes K-Means clustering, where the customers are clustered according to their RFM (Recency Frequency Monetary). In the Second phase, with demographic data, each cluster is again partitioned into new clusters. Finally LTV (Life Time Value of the customers) are used to generate customer's profile.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Rfm - Recency Frequency Monetary Som - Self Organizing Map Ltv - Life Time Value Of A Customer Marc - Mining Association Rule Using Clustering Crm - Customer Relationship Management Osi-iso - Open Systems Interconnection – International Standards Organization