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+---
+title: New Customer Analysis
+description: Practice using multiple CTEs to analyze book sales and customer data
+order: 144
+type: challenge
+setup: |
+  ```sql
+  CREATE TABLE book (
+      id INT PRIMARY KEY,
+      title VARCHAR(100),
+      price DECIMAL(10,2)
+  );
+
+  CREATE TABLE customer (
+      id INT PRIMARY KEY,
+      name VARCHAR(100),
+      joined_date DATE
+  );
+
+  CREATE TABLE sale (
+      id INT PRIMARY KEY,
+      book_id INT,
+      customer_id INT,
+      sale_date DATE,
+      quantity INT
+  );
+
+  INSERT INTO book (id, title, price) VALUES
+      (1, 'SQL Basics', 29.99),
+      (2, 'Advanced SQL', 49.99),
+      (3, 'Data Science', 39.99),
+      (4, 'Web Development', 34.99);
+
+  INSERT INTO customer (id, name, joined_date) VALUES
+      (1, 'John Smith', '2024-12-15'),
+      (2, 'Jane Doe', '2025-01-10'),
+      (3, 'Bob Wilson', '2025-01-15'),
+      (4, 'Alice Brown', '2024-12-20'),
+      (5, 'Charlie Davis', '2025-02-01');
+
+  INSERT INTO sale (id, book_id, customer_id, sale_date, quantity) VALUES
+      (1, 1, 1, '2025-01-01', 2),
+      (2, 1, 2, '2025-01-15', 1),
+      (3, 1, 3, '2025-02-01', 3),
+      (4, 2, 2, '2025-01-20', 1),
+      (5, 2, 3, '2025-02-05', 2),
+      (6, 3, 4, '2025-01-10', 1),
+      (7, 3, 5, '2025-02-10', 2),
+      (8, 4, 1, '2025-01-05', 1);
+  ```
+---
+
+The bookstore wants to analyze how their bestselling books are performing with new customers who joined after January 1st, 2025.
+
+Given the following data in `book` table:
+
+| id  | title           | price |
+| --- | --------------- | ----- |
+| 1   | SQL Basics      | 29.99 |
+| 2   | Advanced SQL    | 49.99 |
+| 3   | Data Science    | 39.99 |
+| 4   | Web Development | 34.99 |
+
+Following data in `customer` table:
+
+| id  | name          | joined_date |
+| --- | ------------- | ----------- |
+| 1   | John Smith    | 2024-12-15  |
+| 2   | Jane Doe      | 2025-01-10  |
+| 3   | Bob Wilson    | 2025-01-15  |
+| 4   | Alice Brown   | 2024-12-20  |
+| 5   | Charlie Davis | 2025-02-01  |
+
+Following data in `sale` table:
+
+| id  | book_id | customer_id | sale_date  | quantity |
+| --- | ------- | ----------- | ---------- | -------- |
+| 1   | 1       | 1           | 2025-01-01 | 2        |
+| 2   | 1       | 2           | 2025-01-15 | 1        |
+| 3   | 1       | 3           | 2025-02-01 | 3        |
+| 4   | 2       | 2           | 2025-01-20 | 1        |
+| 5   | 2       | 3           | 2025-02-05 | 2        |
+| 6   | 3       | 4           | 2025-01-10 | 1        |
+| 7   | 3       | 5           | 2025-02-10 | 2        |
+| 8   | 4       | 1           | 2025-01-05 | 1        |
+
+Write a query using CTEs that shows the top 3 selling books and how many new customers (joined after `2025-01-01`) have purchased each book. Show:
+
+- Book title
+- Total quantity sold
+- Number of new customers who bought the book
+
+## Expected Output
+
+| title        | total_sold | new_customer_count |
+| ------------ | ---------- | ------------------ |
+| SQL Basics   | 6          | 2                  |
+| Advanced SQL | 3          | 2                  |
+| Data Science | 3          | 1                  |
+
+> **Note:** Only the top 3 selling books are shown, ordered by total quantity sold.
+
+## Solution
+
+```sql
+WITH top_selling_books AS (
+    -- Find the top 3 selling books
+    SELECT
+        book_id,
+        SUM(quantity) AS total_sold
+    FROM sale
+    GROUP BY book_id
+    ORDER BY SUM(quantity) DESC
+    LIMIT 3
+),
+recent_customers AS (
+    -- Find customers who joined after 2025-01-01
+    SELECT id
+    FROM customer
+    WHERE joined_date > '2025-01-01'
+)
+SELECT
+    b.title,
+    tsb.total_sold,
+    COUNT(DISTINCT s.customer_id) as new_customer_count
+FROM top_selling_books tsb
+INNER JOIN book b ON b.id = tsb.book_id
+INNER JOIN sale s ON s.book_id = tsb.book_id
+INNER JOIN recent_customers c ON c.id = s.customer_id
+GROUP BY b.title, tsb.total_sold
+ORDER BY tsb.total_sold DESC;
+```