📊 Blinkit Power BI Dashboard

India's Last Minute App - Data Insights Dashboard

This Power BI dashboard provides a comprehensive analysis of sales performance, item categorization, outlet distribution, and customer ratings for Blinkit, a quick-commerce grocery and retail delivery service.

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📌 Overview

The dashboard summarizes key business metrics to help stakeholders quickly evaluate:

• Sales performance across outlets
• Product-type contribution to revenue
• Outlet performance by size, location, and type
• Customer satisfaction ratings
• Fat content influence on product sales

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📈 KPIs

Metric	Value	Description
Total Sales	$1.20M	Total revenue generated
Avg Sales	$141	Average sales per item
No. of Items	8523	Total items analyzed
Avg Rating	3.9	Average customer rating (out of 5)

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📊 Dashboard Features

🎛 Filters

• Outlet Location Type
• Outlet Size
• Item Type

These allow interactive and dynamic filtering for detailed exploration.

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🔍 Sales Breakdown

📦 Fat Content

• Low Fat: $425.36K
• Regular: $776.32K

🏬 Fat by Outlet Tier

• Tier 3 leads in both low fat and regular product sales.

📌 Top-Selling Item Types

• Fruits and Vegetables: $0.18M
• Snack Foods: $0.18M
• Household, Frozen, and Dairy items follow.

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🗓 Outlet Establishment Over Time

A line chart illustrates annual sales from 2012 to 2022:

• Peak: $205K in 2018
• Lowest: $78K in 2012

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🏪 Outlet Analysis

📏 Outlet Size Contribution (Pie Chart)

• Medium: $507.90K
• High: $444.79K
• Small: $248.99K

📍 Outlet Location

• Tier 3: $472.13K
• Tier 2: $393.15K
• Tier 1: $336.40K

🏷 Outlet Type Summary

Outlet Type	Sales	Items	Avg Sales	Rating	Visibility
Supermarket Type1	$787.55K	5577	$141	4	0.06
Grocery Store	$151.94K	1083	$140	4	0.10
Supermarket Type2	$131.48K	928	$142	4	0.04
Supermarket Type3	$130.71K	935	$140	4	0.06

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⭐ Key Insights

• Regular Fat products dominate overall sales.
• Tier 3 outlets contribute the highest revenue.
• Supermarket Type1 is the most profitable outlet type.
• Fruits, Snacks, and Household items are top sellers.
• Medium-sized outlets lead in total sales contribution.

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🔧 Usage Instructions

1. Open the dashboard in Power BI Desktop or Power BI Service.
2. Use the slicers on the left panel to explore:
   • Outlet Location Types
   • Outlet Sizes
   • Item Categories
3. Hover over charts and visuals to view detailed data tooltips.
4. Analyze patterns between fat content, location, outlet type, and sales volume.

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📂 Data Source

The data used in this dashboard is from an Excel file titled BlinkIT Grocery Data.xlsx, which contains structured information about:

Item Types (e.g., Fruits, Snacks, Dairy, Household)

Outlet Types (e.g., Supermarket, Grocery Store)

Outlet Sizes (Small, Medium, High)

Outlet Locations (Tier 1, 2, 3)

Sales Data (Total Sales, Average Sales)

Item Attributes (Fat content, Ratings, Visibility)

This data has been used to analyze and visualize Blinkit's retail performance across multiple dimensions using Microsoft Power BI.

📥 Download the Dataset

Note: This dataset is intended for educational and portfolio demonstration purposes only. It may be synthetic or anonymized to avoid sharing proprietary business data.

👩‍💻 Author

Rashmi Murugkar
📧 [email protected]
🔗 LinkedIn
💻 GitHub

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📎 License

This project is licensed for educational and portfolio use. Please contact the author for commercial or extended use.