Referral Leaderboard
For each customer who referred at least one person, count their referrals and the total completed revenue those referred customers generated. Referred customers who never bought count as 0.
Expected output
customer_id (the referrer), name, referrals, referred_revenue (rounded to 2 decimals). Sorted by referred_revenue descending, then customer_id.
Row order is checked. Column names are not checked; numbers are compared to 2 decimals.
Dataset: E-commerce store
An online store selling electronics, home goods, books, apparel and beauty products to customers in six countries (Jan 2025 to Mar 2026).
customers
One row per registered customer.
| customer_id | INTEGER | primary key |
| name | TEXT | |
| country | TEXT | US, UK, DE, IN, BR or CA |
| signup_date | TEXT | YYYY-MM-DD |
| referred_by | INTEGER | customer_id of the referrer, NULL if none |
products
Product catalog with current list price.
| product_id | INTEGER | primary key |
| name | TEXT | |
| category | TEXT | |
| price | REAL | list price in USD |
orders
One row per order. Only completed orders count as revenue.
| order_id | INTEGER | primary key, increases with order_date |
| customer_id | INTEGER | |
| order_date | TEXT | YYYY-MM-DD |
| status | TEXT | completed, cancelled or returned |
order_items
Line items. Revenue of a line = quantity * unit_price (unit_price may include a discount).
| order_id | INTEGER | |
| product_id | INTEGER | |
| quantity | INTEGER | |
| unit_price | REAL | price actually charged per unit |
Engine: SQLite. Dates are text (YYYY-MM-DD); use strftime(), date() and julianday() for date math.
Related problems
- Revenue by Product Category (easy)
- Monthly Revenue Trend (easy)
- Average Order Value by Country (easy)
- Repeat Purchase Rate (medium)
- Days from Signup to First Order (medium)