Customer Segmentation Based on E-Commerce using K-Mean Clustering

Due to the increasing growth of customers in market, there is fierce competition in business. Relationships between businesses and customer will be strengthened by understanding customer needs. The importance of giving users a comprehensive experience increases as a result of the digital market'...

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Bibliographic Details
Published in:	2023 International Conference on Recent Advances in Science and Engineering Technology (ICRASET) pp. 1 - 5
Main Authors:	Bhimarapu, Harshita, Bhelkar, Sakshi, Chavhan, Nekita, Dhule, Chetan, Agrawal, Rahul
Format:	Conference Proceeding
Language:	English
Published:	IEEE 23-11-2023
Subjects:	Behavioral sciences Business Businesses Customer Customer satisfaction Decision trees Electronic commerce K-Mean Clustering Machine learning Profitability Segmentation
Online Access:	Get full text
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Summary:	Due to the increasing growth of customers in market, there is fierce competition in business. Relationships between businesses and customer will be strengthened by understanding customer needs. The importance of giving users a comprehensive experience increases as a result of the digital market's rapid growth. The dataset from an ecommerce website is used in this study to identify all the factors for analysis, including date, customer id, and product; with the help of k-Mean clustering and decision tree. This research work will determine the most effective technique for Customer Segmentation. This facilitates the identification and resolution of distinct requirements and preferences among diverse customer segments. Customer Segmentation is a multifaceted strategy that can positively impact various aspects businesses, from revenue and profitability to customer satisfaction and long-term growth.
DOI:	10.1109/ICRASET59632.2023.10419925