🍔 Restaurant Orders Data Analysis & Key Performance Metrics (KPMs) using SQL

🚀 Project Overview

This project showcases advanced SQL techniques used to analyze and derive critical Key Performance Metrics (KPMs) from a transactional database of restaurant orders for an e-commerce food delivery platform. The analysis was designed to gauge the performance of a new vertical launched in Dubai on January 1st, focusing on customer acquisition, retention, and channel performance.

Case - Noon launched food items in Dubai on 1st of January and the line manager has asked to share key performance meterics to gauge the performance of the verticals. All the data of orders is being stored in the below table which is used to write queries and find insights.

Table Name - orders

The following queries address critical business questions, demonstrating proficiency in advanced SQL techniques:

1. Top N Analysis without LIMIT

2. Daily New Customer Count from Launch Date

3. Count of Customers Acquired in a specific month who only placed one order in that period

4. List of Customers with no order in the last 7 days but were acquired one month ago with their first order on promo

5. Trigger Query for Customers after their every third order

6. Customers who placed more than one order and all of their orders were on promo only

7. Percent of Customers Organically Acquired in a specific month

This database project has been designed by Ankit Bansal. I have used the dataset for practice purpose.