This project simulates how a Data Analyst at a Food Delivery Company would support cross-functional teams by building targeted SQL queries to uncover customer behavior patterns, measure campaign performance, and support decision-making for growth, retention, and marketing strategies.
Below are the key use cases addressed in this project:
1. Top Outlets by Cuisine (No LIMIT)
Purpose: Rank outlets by cuisine type.
Use Case: Find top 3 outlets per cuisine without using LIMIT or TOP.
2. Daily New Customer Trend
Purpose: Track daily customer acquisition.
Use Case: Measure how many new users joined each day since launch.
3. Single-Order Users (Jan 2025)
Purpose: Identify one-time users.
Use Case: Find customers who only ordered once in January and churned.
4. Dormant Promo Users
Purpose: Spot inactive promo-acquired users.
Use Case: List users acquired a month ago via promo with no recent orders.
5. Milestone Order Triggers
Purpose: Support personalized messaging.
Use Case: Identify users who placed their 3rd, 6th, 9th (etc.) order.
6. Promo-Only Loyal Users
Purpose: Analyze promo-dependent behavior.
Use Case: Find users with multiple orders all using promo codes.
7. Organic Acquisitions (Jan 2025)
Purpose: Measure organic user growth.
Use Case: Calculate % of new Jan 2025 users who ordered without promo.