This Power BI Dashboard provides an in-depth analysis of Blinkit’s Sales Performance across multiple business dimensions — including Outlet Size, Outlet Type, Location, Product Categories, and Customer Spending Behavior.
The goal is to empower management with data-driven decision-making insights by tracking KPIs like Total Sales, Average Rating, Items Sold, Outlet-wise Performance, and Fat Content Distribution.
- Analyze yearly sales trends to identify growth opportunities.
- Identify top-selling products and fat content categories driving maximum profit.
- Compare Outlet Size vs Location Type to determine store performance.
- Evaluate Sales distribution by Outlet Type for targeted marketing.
- Provide insightful visual analysis to enhance Blinkit’s strategic planning and operations.
- Medium-sized outlets generate the highest total sales and customer engagement.
- Urban outlets outperform Tier-2 cities due to higher average ratings and purchase frequency.
- Low Fat products contribute significantly to revenue, aligning with customer health trends.
- Top-performing categories: Snacks, Beverages, and Dairy Products.
- Steady sales growth observed across multiple time periods, reflecting customer retention.
| Aspect | Details |
|---|---|
| Tools Used | Power BI, Microsoft Excel, SQL |
| Data Source | BlinkIT Grocery Data.xlsx (included in repository) |
| File Name | Blinkit Report.pbix |
| Visual Types | Pie Chart, Clustered Bar Chart, Stacked Bar Chart,Line Chart, KPI Cards, Donut Chart, Matrix Table, Slicers |
| Purpose | To analyze Blinkit’s overall sales and performance through dynamic, interactive dashboards |
- Data Cleaning & Transformation using Power Query & SQL
- Data Modeling to connect outlet, product, and sales tables
- DAX Measures for KPIs and advanced calculations
- Dynamic Visuals for real-time business insights
- KPI & Performance Tracking Dashboards for executives
- Business Intelligence Storytelling for retail analytics
- Total Sales by Outlet Type & Location
- Top Selling Products
- Fat Content Sales Contribution
- Sales Trends by Year
- Average Customer Rating
- Number of Items Sold per Outlet
- This dashboard enables Blinkit’s management and analysts to:
- Identify top-performing outlets and regions for expansion.
- Optimize product mix based on sales trends and fat content.
- Strengthen marketing and pricing strategies using performance data.
- Enhance customer satisfaction through quality and rating analysis.
- Make data-backed operational and strategic decisions for growth.
Dataset: BlinkIT Grocery Sales Data (Retail Analysis Dataset for Educational Use)
License: Open Educational / Learning Purpose
Format: Excel – Cleaned, modeled, and visualized using Power BI.
Created by:Paramesh Mandapaka 📧 mandapakaparamesh9@gmail.com
⭐ If you find this project helpful, give it a star on GitHub!