Description:
Amazon UK stands as a giant in the world of online shopping, offering a wide array of products ranging from electronics and clothing to books and household items. The Amazon UK Dataset serves as a treasure trove of information, providing valuable insights into product sales, trends, customer preferences, and more.

Our project revolves around delving deep into this dataset to uncover meaningful insights that can boost sales performance and enhance customer satisfaction on the Amazon platform. By analyzing sales data, customer ratings, and product categories, we aim to identify top-selling products, trending categories, and niche markets with high sales potential.

Data mining techniques play a crucial role in understanding customer behavior, preferences, and purchasing patterns. By studying these insights, we can tailor personalized marketing strategies and product recommendations to cater to individual customer needs effectively.

Moreover, data mining aids in forecasting customer demand, optimizing inventory management, and devising pricing strategies based on historical sales trends. It empowers us to target specific audience segments and improve conversion rates, thereby enhancing overall sales performance.

In summary, our project aims to leverage data-driven strategies to optimize marketing approaches, streamline inventory management, and maximize sales performance within the Amazon UK e-commerce platform.

Team Members:
Dinesh Thapa, Arun Rajput & Ashwani Kumar

This project was completed as part of our academic coursework at Birmingham City University.