Time Between First and Second Order
For each customer with at least two orders (any status), return the dates of their first and second orders and the number of days between them. Orders on the same date are ordered by order_id.
Expected output
customer_id, first_order_date, second_order_date, days_between (integer). Any row order.
Row order is not 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
- Monthly Revenue Trend (easy)
- Quarterly Cancellation Rate (medium)
- Top 2 Products in Each Category (medium)
- Days from Signup to First Order (medium)
- Running Revenue Total for 2025 (medium)