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Enhancing Customer Relationship Management by Integrating Customer and Product Values based on Clustering and Indexing Techniques

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International Journal of Computer Applications
© 2015 by IJCA Journal
Volume 119 - Number 20
Year of Publication: 2015
Authors:
V. Jayaraj
M. Rajakumar
J. Lavanya
J. Jegathesh Amalraj
10.5120/21182-4238

V.jayaraj, M Rajakumar, J.lavanya and J.jegathesh Amalraj. Article: Enhancing Customer Relationship Management by Integrating Customer and Product Values based on Clustering and Indexing Techniques. International Journal of Computer Applications 119(20):10-13, June 2015. Full text available. BibTeX

@article{key:article,
	author = {V.jayaraj and M. Rajakumar and J.lavanya and J.jegathesh Amalraj},
	title = {Article: Enhancing Customer Relationship Management by Integrating Customer and Product Values based on Clustering and Indexing Techniques},
	journal = {International Journal of Computer Applications},
	year = {2015},
	volume = {119},
	number = {20},
	pages = {10-13},
	month = {June},
	note = {Full text available}
}

Abstract

Customer relationship management is not only pure business, but also indicates strong personal bonding within people. Development of this type of bonding drives the business to new levels of success. Once this personal and emotional linkage is built, it is very easy for any organization to identify the actual needs of the customer and to help and serve them in a better way. It is a belief that if more sophisticated strategies are involved in implementing the customer relationship management, the business becomes stronger and fruitful. The main objective of this paper is to provide an optimal solution which optimizes the process of Customer Relationship Management. The process is primarily executed by means of the Clustering technique . When a new customer arrives, that customer is classified into any one of the existing Clusters which automatically provides us the properties of the customer. This paper presents two phases of Clustering method which is not only the clusters on the base of an only attribute, but performs a secondary clustering operation for improved and precise results. Additionally all the Clustered information is indexed in such a manner that Clustering come to be faster.

References

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