This project showcases an interactive Power BI dashboard built to analyze FMCG retail sales performance for comapny with a distributed outlet network. The dashboard helps understand sales trends, outlet performance, and product-level insights to support data-driven decision-making.
- Analyze overall and average sales performance
- Compare sales across outlet sizes and location tiers
- Identify top-performing product categories
- Understand customer ratings and item visibility
- Provide a clear, business-ready retail analytics dashboard
The dataset represents one retail company with multiple outlets and includes:
- Outlet attributes: Outlet Size, Outlet Location Tier, Outlet Type, Establishment Year
- Product attributes: Item Type, Fat Content, Item Visibility
- Performance metrics: Total Sales, Average Sales, Number of Items, Average Rating
- KPI Cards: Total Sales, Average Sales, Number of Items, Average Rating
- Sales Trend Analysis: Outlet establishment year vs sales
- Category Analysis: Sales by item type and fat content
- Outlet Analysis:
- Sales by outlet size (Small, Medium, High)
- Sales by outlet location (Tier 1, Tier 2, Tier 3)
- Performance comparison by outlet type
- Interactive Filters:
- Outlet Location Type
- Outlet Size
- Item Type
- Power BI – Data modeling, DAX, and dashboard creation
- Excel – Source dataset
- Medium and high-sized outlets contribute the highest sales
- Tier 3 locations show strong overall performance
- Fruits, snacks, and household items are top-selling categories
- Regular fat items generate higher sales compared to low-fat items
- Download the Power BI (.pbix) file
- Open it using Power BI Desktop
- Interact with slicers to explore insights dynamically
- Sales performance monitoring across outlet sizes and locations
- Identifying high- and low-performing outlets for strategic action
- Product category optimization based on sales contribution
- Customer preference analysis using fat content and ratings
- Location-based decision making for expansion and promotions