Retail Analysis and Inventory Management

Retail Analysis and Inventory Management

Manyamala Sunaina1, Monisha A1 , Ballupet Prakash Monal 2, Prarthana R3 , Priyanka TR3

Rekha BS3  (Professor)

1 Department of Computer Science & Engineering, RV College of Engineering Bengaluru, India

2 Department of Artificial Intelligence & Machine Learning, RV College of Engineering Bengaluru, India

3 Department of Information Science & Engineering, RV College of Engineering Bengaluru, India

Abstract — Retail enterprises depend on effective inventory management and comprehensive sales analysis to improve their operational efficiency and profitability. This initiative presents a data-centric framework for retail analysis and inventory oversight, integrating association analysis to reveal connections between products and enhance cross-selling potential.

The project encompasses several critical elements, including the examination of sales trends, the identification of product associations through methodologies such as market basket analysis, and the categorization of inventory according to turnover rates and demand patterns. Predictive analytics and demand forecasting techniques are employed to fine-tune stock levels, thereby reducing the risks of overstocking and stockouts. Furthermore, advanced visualization methods empower retailers to extract actionable insights, supporting informed strategic decision-making.

By merging association analysis, inventory optimization, and predictive modeling, this initiative offers a practical and scalable approach to tackling contemporary retail challenges, ultimately fostering sustainable growth and profitability.

Keywords — Retail Analysis, Inventory Management, Association Analysis, Market Basket Analysis, Demand Forecasting, Sales Trends, Inventory Optimization, Data Analytics, Predictive Modeling.