SQL: Analyzing Motorcycle Part Sales
You're working for a company that sells motorcycle parts, and they've asked for some help in analyzing their sales data!
They operate three warehouses in the area, selling both retail and wholesale. They offer a variety of parts and accept credit cards, cash, and bank transfer as payment methods. However, each payment type incurs a different fee.
The board of directors wants to gain a better understanding of wholesale revenue by product line, and how this varies month-to-month and across warehouses. You have been tasked with calculating net revenue for each product line and grouping results by month and warehouse. The results should be filtered so that only "Wholesale" orders are included.
They have provided you with access to their database, which contains the following table called sales:
Sales
| Column | Data type | Description |
|---|---|---|
order_number | VARCHAR | Unique order number. |
date | DATE | Date of the order, from June to August 2021. |
warehouse | VARCHAR | The warehouse that the order was made from— North, Central, or West. |
client_type | VARCHAR | Whether the order was Retail or Wholesale. |
product_line | VARCHAR | Type of product ordered. |
quantity | INT | Number of products ordered. |
unit_price | FLOAT | Price per product (dollars). |
total | FLOAT | Total price of the order (dollars). |
payment | VARCHAR | Payment method—Credit card, Transfer, or Cash. |
payment_fee | FLOAT | Percentage of total charged as a result of the payment method. |
Your query output should be presented in the following format:
product_line | month | warehouse | net_revenue |
|---|---|---|---|
| product_one | --- | --- | --- |
| product_one | --- | --- | --- |
| product_one | --- | --- | --- |
| product_one | --- | --- | --- |
| product_one | --- | --- | --- |
| product_one | --- | --- | --- |
| product_two | --- | --- | --- |
| ... | ... | ... | ... |
-- Start coding here
SELECT product_line,
CASE WHEN EXTRACT('month' from date) = 6 THEN 'June'
WHEN EXTRACT('month' from date) = 7 THEN 'July'
WHEN EXTRACT('month' from date) = 8 THEN 'August'
END as month,
warehouse,
SUM(total) - SUM(payment_fee) AS net_revenue
FROM sales
WHERE client_type = 'Wholesale'
GROUP BY product_line, warehouse, month
ORDER BY product_line, month, net_revenue DESC
Extended Project below
The finance team is exploring ways to reduce transaction costs and improve profitability. They’ve asked you to determine the most profitable payment method for each warehouse in each month. Calculate the net revenue for each payment method, grouped by warehouse and month, and identify the top payment method for each combination.
SELECT warehouse, TO_CHAR(date, 'Month') as month, payment,
SUM(total) - SUM(payment_fee) AS net_revenue
FROM sales
GROUP BY warehouse, month, payment
ORDER BY net_revenue DESCThe marketing team is planning a targeted campaign and wants to know the most popular product lines for retail and wholesale customers.
They have given you the task to find the top 3 most ordered product lines for each client type.
WITH ranked_sales AS (
SELECT client_type, product_line, SUM(quantity) AS total_quantity,
RANK() OVER (PARTITION BY client_type ORDER BY SUM(quantity) DESC) AS rank
FROM sales
GROUP BY client_type, product_line
)
SELECT client_type, product_line, total_quantity, rank
FROM ranked_sales
WHERE rank <= 3
ORDER BY client_type, rank, total_quantity DESC;