[BuyMore Sales Data Analysis Report]

This Power BI project provides a comprehensive analysis of sales transactions from BuyMore Supermarket, focusing on operations across three key Nigerian cities. The dataset includes attributes such as product categories, transaction dates, store locations, customer demographics, promotional campaigns, and payment methods. The data folder contains the cleaned-up dataset which was done in Excel, the data visualization which was done in Microsoft Power BI, and the Dashboard, on Microsoft Power Point. 

I designed a dynamic and interactive dashboard that allows users to explore sales performance at multiple levels — including time-based trends, category-level contributions, regional comparisons, and customer behavior. Key insights derived include:

• Identification of high-performing product categories and underperforming SKUs
  
  

• Analysis of peak sales periods by hour, day, and month, with seasonal spikes highlighted
  
  

• Segmentation of customer purchases by gender and age group to reveal behavioral patterns
  
  

• Evaluation of the impact of discount strategies and promotional campaigns on sales lift
  
  

• Comparison of store performance across different cities to uncover growth opportunities

The dashboard integrates slicers, KPIs, bar and line charts, and geospatial visuals to provide a clear, actionable overview of sales dynamics. This project demonstrates how data visualization can be used to inform better decision-making in retail — from inventory planning and targeted marketing to store-level performance management. 

 KEY INSIGHTS  & RECOMMENDATIONS

✅ Final Outcome

This sales data analysis project was executed independently, from data cleaning and exploration to insightful visualization. Through meticulous analysis, I transformed raw sales data into an engaging visual story, uncovering trends and performance patterns that drive smarter business decisions. This project highlights my ability to bring data to life—both analytically and visually.