In this , customer segmentation problem from a behavioural aspect with the customer groups, Annual income, Spending scores. Use of 3 features helped us with the understandability and visualization of the model.

All in all, the dataset was apt to perform an unsupervised machine learning problem. At first, we only had customers data with order information and did not know if they belonged to any group. With the K-means clustering, patterns in the data were found and extended further into groups. We carved out strategies for the formed groups, making meaning out of a dataset that is a dust cloud initially.