Customer Segmentation with Hyperparameter Tuning Using Machine Learning

Customer segmentation has become a very popular method for dividing a company's customers in order to retain customers. Customers of various organizations are categorized based on behavioral characteristics like age, income, spending and purchasing amount by employing a machine learning technique called the K-means clustering algorithm. Clusters are created to assist the business in focusing on certain clients and promoting the products to them through social media platforms and marketing campaigns that truly interest them. Hyperparameter tuning is found to facilitate appropriate convergence of the number of clusters. The clusters produced through hyperparameter tuning are more accurate and capable of capturing the inherent structure of the data by minimizing the clustering error.