Blinkit Operations Dashboard

Data-Driven Insights for Quick Commerce Performance

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Anirudh Chaudhary

Business Analyst | Data Visualization Specialist

This interactive dashboard provides comprehensive insights into Blinkit's quick commerce operations, analyzing delivery performance, order patterns, and customer behavior metrics. Designed to help optimize operations and enhance customer experience in the fast-paced quick commerce industry.

Total Orders
0
Across all service areas
Avg Delivery Time
0
Minutes per order
Active Customers
0
Repeat buyers
Top Category
Groceries
Highest order volume
Blinkit Power BI Dashboard
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Operations Performance Analysis

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The Operations Performance Analysis provides a comprehensive view of delivery metrics across service areas and time periods. Key findings include:

Delivery Efficiency

Deliveries are most efficient in urban centers with average delivery times under 10 minutes. Suburban areas show slightly longer delivery times averaging 15-20 minutes during peak hours.

Order Patterns

Evening hours (5-9 PM) account for 45% of daily orders, with groceries being the most frequently ordered category. This suggests opportunities for targeted promotions during these high-traffic periods.

  • Consistent order growth observed month-over-month, with 15% increase in repeat customers
  • Delivery partners maintain an average rating of 4.7/5 across all service areas
  • Opportunity to optimize delivery routes in suburban areas to match urban efficiency

Product Category Insights

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Detailed analysis of product category performance reveals strategic opportunities for inventory optimization:

Top Performing Categories

Groceries and snacks show particularly strong performance, accounting for 60% of total orders. The personal care category shows growing demand with 25% month-over-month growth.

Inventory Strategy

With average order value of ₹450, there's potential to bundle high-margin items with fast-moving grocery products to increase basket size.

  • Essential items show steady demand throughout the day, indicating reliable inventory requirements
  • Snacks and beverages show peak demand during evening hours, suggesting targeted stocking
  • Opportunity to expand product range in high-growth categories like personal care

Geographical Performance

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The geographical analysis highlights key markets and service areas with optimization opportunities:

Top Performing Areas

Central business districts and high-density residential areas emerge as the strongest markets, with highest order frequency and fastest delivery times. These areas should be prioritized for marketing campaigns and inventory placement.

Expansion Opportunities

Suburban areas show consistent demand but may benefit from optimized delivery routes and localized inventory to improve service times. The data suggests potential for "dark store" placement in these areas.

  • Delivery data reveals efficient coverage in urban centers with room for optimization in suburban areas
  • No significant regional preference for specific product categories observed
  • Potential to optimize dark store locations based on geographical demand patterns

Customer Behavior

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Analysis of customer metrics reveals patterns and opportunities in user engagement:

Order Patterns

Customers show strong preference for evening deliveries (5-9 PM), accounting for 45% of daily orders. The average order frequency is 2.3 times per week for active customers.

Retention Metrics

30-day customer retention rate stands at 65%, with repeat customers having 35% higher average order value than first-time buyers. This highlights the importance of loyalty programs and retention strategies.

  • Mobile app users show 20% higher order frequency than web users
  • Opportunity to implement personalized recommendations based on order history
  • Potential to optimize push notification timing based on customer order patterns

Strategic Recommendations

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Based on the comprehensive data analysis, the following strategic actions are recommended:

Operations Strategy

1. Optimize delivery routes in suburban areas to match urban efficiency
2. Implement dynamic delivery pricing during peak hours to manage demand
3. Expand dark store network in high-growth suburban areas

Inventory Strategy

1. Increase stock of high-demand items during peak evening hours
2. Create bundled offers combining groceries with high-margin items
3. Expand personal care category based on growing demand

Customer Engagement

1. Develop loyalty program to increase repeat purchases
2. Optimize push notification timing based on customer order patterns
3. Implement personalized recommendations to increase basket size

Download Full Dashboard Report (PDF) Download PowerBI File

Technical Skills Applied

Power BI

Data modeling, DAX measures, and interactive visualizations

Data Analysis

Operational metrics and KPI development

Geospatial Analysis

Delivery area performance mapping

Business Strategy

Data-driven recommendations for growth

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