Customer Segmentation Using Machine Learning
DOI:
https://doi.org/10.32628/CSEIT217654Keywords:
Customer, Segmentation, Data, Product, K-means.Abstract
Customer Segmentation is the process of division of customer base into several groups called as customer segments such that each customer segment consists of customers who have similar characteristics. Segmentation is based on the similarity in different ways that are relevant to marketing such as gender, age, interests, and miscellaneous spending habits.The customer segmentation has the importance as it includes, the ability to modify the programs of market so that it is suitable to each of the customer segment, support in business decisions; identification of products associated with each customer segment and to mange the demand and supply of that product; identifying and targeting the potential customer base, and predicting customer defection, providing directions in finding the solutions.
References
- Azad Abdulhafedh, “Incorporating K-means, Hierarchical Clustering and PCA in Customer Segmentation”.
- Yash Kushwaha, Deepak Prajapati, “Customer Segmentation using K-Means Algorithm”.
- Kishana R. Kashwan, Member, IACSIT, and C. M. Velu, “Customer Segmentation Using Clustering and Data Mining Techniques”.
- Shreya Tripathi, Aditya Bhardwaj and Poovammal E, “Approaches to Clustering Customer Segmentation”.
- Chinedu Pascal Ezenkwu, Simeon Ozuomba, Constance
- kalu, “Application of K-Means Algorithm for Efficient Customer Segmentation”.
- V.Vijilesh, A. Harini, M. Hari Dharshini, R. Priyadharshini, “Customer Segmentation using Machine Learning”.
- Balmeet Kaur, Pankaj Kumar Sharma, “Implementation of Customer Segmentation using Integrated Approach”.
- https://www.infoworld.com/article/3347406/what-is-jupyter-notebook-data-analysis-made-easier.h
Downloads
Published
Issue
Section
License
Copyright (c) IJSRCSEIT

This work is licensed under a Creative Commons Attribution 4.0 International License.