Sales Analysis II - Problem
You're working as a data analyst for a tech retail company and need to identify specific customer purchasing patterns. You have access to two key databases:
Product Table: Contains product information including ID, name, and unit price
Sales Table: Records every transaction with seller, buyer, product, date, quantity, and final price
Your task is to find all buyers who purchased the flagship "S8" smartphone but deliberately avoided buying the "iPhone". This analysis will help the marketing team understand customer brand loyalty and purchasing preferences.
Think of it as finding customers who chose one premium brand over another - valuable insight for competitive analysis!
Return the buyer IDs of these selective customers in any order.
Input & Output
example_1.sql — Basic Case
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Input:
Product table:\n| product_id | product_name | unit_price |\n|------------|--------------|------------|\n| 1 | S8 | 1000 |\n| 2 | iPhone | 1400 |\n| 3 | iPad | 800 |\n\nSales table:\n| seller_id | product_id | buyer_id | sale_date | quantity | price |\n|-----------|------------|----------|-----------|----------|-------|\n| 1 | 1 | 1 | 2019-01-21| 2 | 2000 |\n| 1 | 2 | 1 | 2019-02-17| 1 | 800 |\n| 2 | 1 | 2 | 2019-06-02| 1 | 800 |\n| 3 | 3 | 3 | 2019-05-13| 2 | 2800 |
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Output:
| buyer_id |\n|----------|\n| 2 |
💡 Note:
Buyer 1 purchased both S8 and iPhone, so excluded. Buyer 2 purchased only S8. Buyer 3 purchased only iPad (not S8). Therefore, only buyer 2 meets the criteria.
example_2.sql — Multiple S8 Buyers
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Input:
Product table:\n| product_id | product_name | unit_price |\n|------------|--------------|------------|\n| 1 | S8 | 1000 |\n| 2 | iPhone | 1400 |\n\nSales table:\n| seller_id | product_id | buyer_id | sale_date | quantity | price |\n|-----------|------------|----------|-----------|----------|-------|\n| 1 | 1 | 1 | 2019-01-21| 2 | 2000 |\n| 2 | 1 | 2 | 2019-06-02| 1 | 800 |\n| 3 | 1 | 3 | 2019-07-11| 1 | 800 |
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Output:
| buyer_id |\n|----------|\n| 1 |\n| 2 |\n| 3 |
💡 Note:
All three buyers purchased S8, and none of them purchased iPhone (since there are no iPhone sales), so all qualify.
example_3.sql — No Valid Buyers
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Input:
Product table:\n| product_id | product_name | unit_price |\n|------------|--------------|------------|\n| 1 | S8 | 1000 |\n| 2 | iPhone | 1400 |\n\nSales table:\n| seller_id | product_id | buyer_id | sale_date | quantity | price |\n|-----------|------------|----------|-----------|----------|-------|\n| 1 | 1 | 1 | 2019-01-21| 2 | 2000 |\n| 1 | 2 | 1 | 2019-02-17| 1 | 800 |\n| 2 | 2 | 2 | 2019-06-02| 1 | 800 |
›
Output:
Empty result set
💡 Note:
Buyer 1 purchased both S8 and iPhone (excluded). Buyer 2 purchased only iPhone (doesn't meet S8 requirement). No buyers meet the criteria of having S8 but not iPhone.
Constraints
- 1 ≤ product_id ≤ 100
- 1 ≤ seller_id, buyer_id ≤ 100
- product_name is case-sensitive
- Products 'S8' and 'iPhone' are guaranteed to exist in Product table
- buyer_id is never NULL in Sales table
Visualization
Tap to expand
Understanding the Visualization
1
Join Tables
Connect sales records with product information to see what each customer bought
2
Find S8 Customers
Identify all customers who purchased the S8 smartphone
3
Find iPhone Customers
Separately identify customers who purchased iPhone
4
Apply Exclusion
Remove iPhone customers from the S8 customer list
5
Return Loyal S8 Users
The remaining customers show S8 brand loyalty
Key Takeaway
🎯 Key Insight: SQL's NOT IN operator efficiently handles set exclusion, making this a clean one-query solution for finding customers with specific purchase patterns.
💡
Explanation
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// Output will appear here after running code