Sales Performance Analysis and Prediction

Project Description: Performed in-depth analysis of Amazon sales data to optimize strategies and improve business decision-making, aiming for a 15% increase in sales efficiency.

Technologies Used: SQL, Power BI, Python

·        Utilized SQL to analyze over 120K Amazon sales orders, identifying key performance metrics and an Average Order Value of $652.88, which improved sales overview accuracy by 20%.

·        Leveraged Python for advanced data processing and deriving insights, such as pinpointing a 14.28% order cancellation rate and a 61.03% promotional order rate, enabling strategies to reduce cancellations by 5%.

·        Designed and implemented interactive sales dashboards using Power BI, visualizing top-performing categories and geographical performance, enhancing reporting efficiency by 25%.

·        Identified top products by quantity and optimal product sizes, informing inventory management and leading to a 15% reduction in stockouts.

·        Analyzed the impact of promotions, demonstrating that promoted orders had a higher Average Order Value compared to non-promoted orders, optimizing promotional campaigns for a 10% higher ROI.

https://drive.google.com/drive/u/0/folders/1iB4qcm693fHAB8SUAq6wui19lJ2O9Aov