QuickBite Express - Business Recovery Dashboard

📘 Project Overview

QuickBite Express, a food delivery startup, faced a major drop in orders, customer satisfaction, and delivery performance during a crisis period.
This project uses data analytics and visualization to uncover the key causes of decline and recommend data-driven recovery strategies.

The project was built as part of the Codebasics Power BI Resume Project Challenge, where participants create end-to-end analytical solutions using real-world business cases.

🎯 Objectives

The analysis focuses on six key questions:

1. 🧍‍♂️ Customer Segments: Which customers can be recovered, and which require new strategies?
2. 🛒 Order Patterns: How did order behavior change across Pre-Crisis, Crisis, and Recovery phases?
3. 🚴 Delivery Performance: What were the SLA compliance gaps and delivery delays?
4. 🎯 Campaign Opportunities: How can targeted campaigns rebuild trust and loyalty?
5. 🍴 Restaurant Partnerships: Which partners drive long-term value retention?
6. 💬 Feedback & Sentiment: How did ratings and reviews evolve during the crisis?

🧱 Data Journey

🔹 1. Data Sources

• 8 CSV files (4 fact + 4 dimension tables):

🔹 2. Staging (MySQL)

• All files loaded as VARCHAR into staging tables (stg_*).
• Performed sanity checks:
• ✅ Primary/Foreign key integrity
• ✅ Date and numeric format validation
• ✅ Logical reconciliation (subtotal - discount + delivery_fee = total)

🔹 3. Cleaning & Transformation

• Fixed inconsistent acquisition_channel values.
• Removed invalid customer_id and order_id records.
• Derived columns:
• order_month
• sla_diff
• phase (Pre-Crisis, Crisis, Recovery)
• Ensured consistent date formats (YYYY-MM-DD).

🔹 4. Modeling

• Snowflake schema with fact_orders at center.
• Relationships:
• fact_orders ↔ dim_customer
• fact_orders ↔ dim_restaurant
• fact_orders ↔ fact_ratings
• fact_orders ↔ fact_delivery_performance
• Created calculated measures:
• Total Revenue
• Avg Rating
• SLA Miss %
• Order Drop %
• Customer Churn %

🔹 5. Visualization (Power BI)

• Built 5 interconnected pages:

1. Executive Summary
2. High-Value Customers
3. Restaurant Partnerships
4. Misconception & Assumptions

• Custom theme (QuickBite Theme.json) using brand colors (#4E79A7, #F28E2B, #59A14F).
• Added interactive slicers (Phase, Month, City).

🧠 Key Insights

• 📉 Orders dropped 70% during the crisis period.
• 🕒 SLA breaches increased by 55%, directly impacting customer ratings.
• ⭐ Top 5% high-value customers saw largest rating decline.
• 🏙️ Tier-1 cities like Bengaluru and Mumbai faced sharpest drop in order volume.
• 💬 Sentiment analysis revealed keywords: “late”, “cold”, “cancelled” – indicating delivery reliability issues.

💡 Business Recommendations

1. Operational Excellence:
   Reduce SLA miss rate below 30% via real-time tracking and partner training.
2. Customer Re-engagement:
   Win back high-value customers with targeted loyalty campaigns.
3. Restaurant Stability:
   Retain top partners with guaranteed minimum order volumes.
4. Marketing Strategy:
   Shift budget toward brand trust and service reliability campaigns.

🧩 Tech Stack

🌟 Learnings

• Designed a complete BI workflow from raw data to insights.
• Understood importance of data validation and integrity before modeling.
• Strengthened DAX and storytelling skills for business decision-making.
• Learned how to design professional Power BI themes and backgrounds for consistency.

🏁 Conclusion

This project demonstrates how a data analyst can blend technical skills (SQL, DAX, Power BI) with business understanding to create impactful insights.
The QuickBite Express Dashboard serves as a recovery blueprint for any business looking to rebuild customer trust through data.

🤝 Connect With Me

👤 Akash Gupta
🌐 LinkedIn

🏷️ Tags

#PowerBI #SQL #DataAnalytics #Codebasics #DashboardDesign #BusinessIntelligence #DataStorytelling #PortfolioProject