• Samreen Siddiqui
• Dr. Sunita Soni
• Dr. Sumit Sar

A tremendous amount of data is gathered every day in the world in which we live. It is imperative that such data be analyzed. In this highly innovative era of fierce competition to surpass everyone, the company plan needs to consider the present environment. Modern businesses are built on innovative ideas because there are so many prospective customers who aren't sure what to buy or not buy. Divide consumers who may be relevant for advertising according to factors like gender, age, interests, and other purchasing patterns is known as customer segmentation. Any organization's primary goal is to identify its core customers and understand how their buyers behave and utilize its products. Additionally, each consumer may utilize an organization's goods in a unique way. We're trying to solve the issue of listing this organization's buyers to describe the constructive actions and methods such customers use the company's products for. In addition, companies who work in this industry are unable to pinpoint the possible customers in the target market. In order to find the hidden patterns in the data and make better decisions, machine learning is used in this work. The customer segmentation process employing the clustering technique determines which consumer segment to target. One common method in unsupervised machine learning is customer segmentation. We have suggested a solution in this research that makes use of K-Means clustering, a powerful method for dataset clustering. With the elbow method, the ideal clusters are found. After visualizing the data, the strategy is to identify the important characteristics that may be used to categorize the clients and derive some conclusions. Created clusters assist the business in focusing on certain clients and promoting material to them on social media platforms and marketing campaigns that truly interest them.

Machine learning, Customer segmentation, K-means algorithm, Elbow Method

"Customer Segmentation Using Machine Learning for a Shopping Mall Customers", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 9, page no.d750-d756, September-2024, Available :http://www.jetir.org/papers/JETIR2409386.pdf

"Customer Segmentation Using Machine Learning for a Shopping Mall Customers", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 9, page no. ppd750-d756, September-2024, Available at : http://www.jetir.org/papers/JETIR2409386.pdf