Unleashing Customer Insights: Segmentation Through Machine Learning

The Customer Segmentation Analysis project is a machine learning based approach to segmenting customer based on their characteristics and behaviors. The project aims to help businesses to identify their most valuable customers and develop targeted marketing strategy for each segment. The project utilizes various data preprocessing techniques and machine learning algorithms such K-means clustering, Principal Component Analysis (PCA) and hierarchical clustering to segment customers based on the transactional credit card data. The data set used for the analysis is the Online Retail II dataset, which contains customer transaction from an online retailer. The results of the analysis are presented in the form visualization, insights and tabular columns containing the respective silhouette scores obtained against the respective algorithms, these results can be used to develop an effective marketing strategy targeting each customer segment.