• Dr. D. Veerabhadra Babu
• C. Pravallika Devi
• D. Sadhaf
• B. Sai Keerthana
• M. Shameemunnisa

Making wise selections is essential for every business to turn a profit. These days, there is intense competition, and every company is advancing using a unique set of techniques. We ought to make an informed choice based on data. Since each client is unique, we have no idea what they enjoy or what they purchase. But by using a variety of algorithms on the dataset, one can use machine learning techniques to sort through the data and identify the target group. In the absence of this, identifying a group of individuals with like interests and personalities within a sizable dataset will be exceedingly challenging and no better methods exist. In this case, K-Means clustering is utilized for client segmentation aids in grouping data according to similar characteristics, which is just what the business needs. The elbow approach will be used to determine the number of clusters before the data is finally shown. The project's results include enhanced personalization, efficient use of resources, and a competitive advantage, all derived from K-Means Clustering's strong points. This innovative method represents a major breakthrough in the field of customer segmentation and gives companies the resources they need to thrive in an increasingly complex and customer-driven business landscape.

Clustering, Elbow method, K-Means Algorithm, Customer Segmentation, Visualization

"A NOVEL APPROACH TO PERSONALIZED USER SEGMENTATION USING K-MEANS CLUSTERING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 12, page no.369-374, December-2023, Available :http://www.jetir.org/papers/JETIRGA06041.pdf

"A NOVEL APPROACH TO PERSONALIZED USER SEGMENTATION USING K-MEANS CLUSTERING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 12, page no. pp369-374, December-2023, Available at : http://www.jetir.org/papers/JETIRGA06041.pdf