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INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
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Om Narayan Gupta
, Ragini Sinha , Akanksha Toppo , Sana Danwani
Unique Id:
IJSDR2305263
Published In:
Volume 8 Issue 5, May-2023
Abstract:
The emergence of numerous competitors and entrepreneurs has created a great deal of tension among competing businesses as they seek new buyers while retaining existing ones. As a result of the preceding, the requirement for exceptional customer service becomes appropriate regardless of the size of the business. Furthermore, the ability of any business to understand the needs of each of its customers will provide greater customer support in the provision of targeted customer services and the development of customised customer service plans. This comprehension is attainable through structured customer service. Customers in each segment share similar market characteristics. Traditional market analytics always fail when the customer base is very large, so k-means clustering algorithm and DBSCAN clustering algorithm are used for this purpose. Additionally, t-SNE and PCA are applied for dimensionality reduction. Finally, a variance technique and feature importance are applied to select variables that specifically represent the customer base.
"Customer Segmentation Using Machine Learning", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.8, Issue 5, page no.1672 - 1676, May-2023, Available :http://www.ijsdr.org/papers/IJSDR2305263.pdf
Downloads:
000222061
Publication Details:
Published Paper ID: IJSDR2305263
Registration ID:205939
Published In: Volume 8 Issue 5, May-2023
DOI (Digital Object Identifier):
Page No: 1672 - 1676
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631
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