Customer segmentation using unsupervised clustering algorithm Sharma Sheelesh Kumar1,*, Professor, Pathak Garvit2, MCA Student, Chandralok3, MCA Student, Kumari Sweta4, MCA Student 1Department of IT, Institute of Management Studies, Ghaziabad, Uttar Pradesh, India 2Institute of Management Studies, Ghaziabad, Uttar Pradesh, Indiagarvitraj1@gmail.com 3Institute of Management Studies, Ghaziabad, Uttar Pradesh, Indiapandeychandralok@gmail.com 4Institute of Management Studies, Ghaziabad, Uttar Pradesh, Indiakumarisweta9801@gmail.com *(Corresponding author) email id: sheelesh.sharma@imsgzb.com
ABSTRACT The power of artificial intelligence (AI) is being harnessed by all businesses to expand business and earning maximum profit out of least expenditure. The sales data captured by businesses carries huge value from this point of view. It can reveal useful and interesting insights for making better strategic decisions. The metrics like frequency of purchase, last purchase and monetary value of the customer entering an outlet may be of vital importance for attracting them to specific offers. The paper proposes a variant of clustering approach for segmenting the data of customers based on their various attributes. Experimental results show that the proposed technique is good enough for forming clusters on customer data and quantitative parameters establish the accuracy of clusters formed. Top Keywords: Business intelligence, Customer segmentation, K-means clustering, Strategic analytics, Unsupervised learning. Top |