A comprehensive, interactive Power BI dashboard analyzing Blinkit's (India's last-minute grocery delivery app by Zomato) sales performance, customer satisfaction, and inventory distribution across outlets.
Key Highlights: $1.20M Total Sales · $140.99 Avg Sales · 8,523 Items · 3.92 Avg Rating
blinkit-powerbi-analysis/
│
├── BlinkitGroceryData.xlsx # Raw dataset (8,523 rows × 12 columns)
├── BlinkitAnalysis.pbix # Power BI report file
├── assets/ # Icons and background images used in dashboard
│ ├── sales_icon.png
│ ├── items_icon.png
│ ├── rating_icon.png
│ └── avg_sales_icon.png
└── README.md
Conduct a comprehensive analysis of Blinkit's:
- Sales performance across product types and outlet categories
- Customer satisfaction through ratings data
- Inventory distribution across outlet sizes, locations, and types
The goal is to surface actionable insights for stakeholders using an interactive, filterable Power BI report.
| Property | Details |
|---|---|
| Source | Excel file (BlinkitGroceryData.xlsx) |
| Rows | 8,523 |
| Columns | 12 |
| Column | Description |
|---|---|
Item Fat Content |
Fat level of the product (Low Fat / Regular) |
Item Identifier |
Unique item code |
Item Type |
Category (Fruits, Snacks, Dairy, etc.) |
Outlet Establishment Year |
Year the outlet was established |
Outlet Identifier |
Unique outlet code |
Outlet Location Type |
Tier 1 / Tier 2 / Tier 3 city |
Outlet Size |
Small / Medium / High |
Outlet Type |
Grocery Store / Supermarket Type 1/2/3 |
Item Visibility |
How prominently the item appears in-app |
Item Weight |
Weight of the item |
Sales |
Revenue generated per order |
Rating |
Customer rating for the order |
Cleaning steps performed in Power Query Editor:
- Standardized Item Fat Content values:
LF→Low Fatlow fat→Low Fatreg/R→Regular
- Verified column quality (Valid %, Error %, Empty %) for all fields
Item Weightcontains ~16% null values — retained as-is since it's not used in KPI calculations
Total Sales = SUM('BlinkitGroceryData'[Sales])
Average Sales = AVERAGE('BlinkitGroceryData'[Sales])
Number of Items = COUNTROWS('BlinkitGroceryData')
Average Rating = AVERAGE('BlinkitGroceryData'[Rating])
A Field Parameter (Metrics) was also created to allow dynamic switching between Total Sales, Average Sales, Number of Items, and Average Rating across charts.
| KPI | Value |
|---|---|
| Total Sales | $1.20M |
| Average Sales | $140.99 |
| No. of Items | 8,523 |
| Average Rating | 3.92 |
| Chart | Type | Insight |
|---|---|---|
| Fat Content | Donut Chart | Low Fat (64.6%) vs Regular (35.4%) of total sales |
| Fat by Outlet | Clustered Bar Chart | Sales breakdown by fat type across Tier 1/2/3 |
| Item Type | Horizontal Bar Chart | Fruits & Vegetables and Snack Foods are top sellers |
| Outlet Establishment | Line Chart | 2018 outlets are the highest performing |
| Outlet Size | Donut Chart | Medium outlets contribute the most (42.27%) |
| Outlet Location | Funnel Chart | Tier 3 leads at $472.13K |
| Outlet Type | Matrix Table | Supermarket Type 1 dominates with $787.55K in sales |
- Outlet Location (Tier 1 / Tier 2 / Tier 3)
- Outlet Size (Small / Medium / High)
- Item Type (multi-select dropdown)
- Metric Selector (Total Sales / Avg Sales / No. of Items / Avg Rating)
- Reset / Clear All Filters button
- All chart slices and bars act as cross-filters (configured via Edit Interactions)
- Clicking any segment dynamically filters the entire dashboard
- Power BI Desktop — Report building and DAX calculations
- Power Query Editor — Data cleaning and transformation
- Microsoft Excel — Source data
- DAX — Custom measures and field parameters
- Download
BlinkitGroceryData.xlsxandBlinkitAnalysis.pbix - Open
BlinkitAnalysis.pbixin Power BI Desktop - If prompted, update the data source path to point to your local copy of the Excel file:
- Go to Home → Transform Data → Data Source Settings
- Click Refresh to load the data
- Explore the dashboard using the filter panel on the left
- Low Fat products account for ~65% of total sales, indicating strong health-conscious demand
- Fruits & Vegetables and Snack Foods are the highest-selling item categories
- Tier 3 outlets generate the most revenue despite being in smaller cities — likely due to higher outlet count
- Supermarket Type 1 outlets outperform all other outlet types significantly
- 2018-established outlets have the highest cumulative sales among all establishment years
- Average customer rating of 3.92/5 signals room for improvement in delivery quality and product satisfaction
This project was built by following the tutorial: "Blinkit Sales Analysis Power BI Dashboard" — available on YouTube.
Built as a learning project to practice end-to-end Power BI development including data connection, cleaning, DAX, and interactive dashboard design.