Retail businesses often struggle to identify and target the right customers for their products and services. Customer segmentation allows businesses to divide their customers into distinct groups based on various characteristics such as buying behavior, demographics, and preferences. This segmentation enhances marketing strategies and improves customer engagement. Additionally, lead generation is crucial for acquiring new customers and driving sales growth. This project proposes a cloud-based solution that integrates customer segmentation with lead generation using cloud computing platforms.

The system will collect and process large volumes of retail customer data in the cloud, leveraging cloud computing's scalability, flexibility, and processing power. Advanced data analytics and machine learning algorithms will segment customers into meaningful groups. Based on these segments, the system will generate targeted leads to help retail businesses run focused marketing campaigns. This approach provides high availability, on-demand resource scalability, and cost-effectiveness, ensuring better performance than traditional on-premise solutions.

The project also aims to offer an easy-to-use interface for retail marketers to visualize segmented customer profiles and generated leads. The proposed system is expected to enhance marketing ROI, increase customer retention, and optimize lead conversion rates by delivering personalized marketing strategies powered by cloud technology.