This study presents a comprehensive investigation into the development of a robust customer segregation infrastructure using advanced data mining techniques. In an era of ever-expanding data, understanding and categorizing customers based on their preferences and behaviors are paramount for businesses. Leveraging data mining, this research unveils insights into the creation of a feasible and efficient infrastructure for customer segregation. By analyzing vast datasets, we identify patterns, preferences, and clusters among customers, enabling businesses to tailor their strategies, improve customer experiences, and optimize resource allocation.