📊 Online Retail Store Database Queries
🔢 🗂️ Assumed Schema
Customers(customer_id, name, email, City, join_date)
Products(product_id, Product_name, category, price)
Orders(order_id, customer_id, order_date)
Order_Items(order_id, product_id, quantity, Total_price)
Payments(payment_id, order_id, payment_date, payment_method, amount)
Shipments(Shipment_id, Order_id, Shipment_date, Delivery_date, Carrier, status)
🟢 Beginner Level Queries (1–7)
1️⃣✅ Show all products with name, price, and Category ?
🔰View the current product listings and their availability.
SELECT Product_name
, price
, Category
FROM Products;
2️⃣🧑 List all customers with email and join date ?
🔰Useful for sending welcome offers or newsletters.
SELECT Name
, Email
, Signup_date
FROM Customers;
3️⃣🛒 Retrieve all orders made by customers with End of Month & Year ?
🔰Tracks when and what customers ordered.
SELECT order_id
, customer_id
, order_date
FROM Orders
ORDER BY Order_Date DESC;
4️⃣📦 Get all Low-of-stock products price ?
🔰Identifies products that have low price less than 50.
SELECT Product_name
FROM Products
WHERE Price <= 50;
5️⃣🔍 Search products by category 'Electronics' ?
🔰Filters products for browsing in a specific category.
SELECT *
FROM Products
WHERE category = 'Electronics';
6️⃣💸 Find all payments made using 'Credit Card' ?
🔰Understand how often each payment method is used.
SELECT *
FROM Payments
WHERE payment_method = 'Credit Card';
7️⃣📝 Show all Details for a specific Order ?**
🔰Customer Query for a given Order (e.g., Order_Id = 250)
SELECT *
FROM shipments
WHERE Order_Id = 250;
🟡 Moderate Level Queries (8–14)
8️⃣🔎 Top 10 Best-Selling Products ?
🔰Finds most sold products by quantity
SELECT Products.Product_name
, SUM(Order_items.quantity) AS total_sold
FROM Order_items
JOIN Products ON Order_items.product_id = Products.product_id
GROUP BY Products.Product_name
ORDER BY total_sold DESC
LIMIT 10;
9️⃣👥 Top 5 customers by number of orders ?
🔰Identifies the most frequent buyers
SELECT C.name
, COUNT(O.order_id) AS total_orders
FROM Customers C
JOIN Orders O ON C.customer_id = O.customer_id
GROUP BY C.name
ORDER BY total_orders DESC
LIMIT 5;
🔟💰 Total revenue by month ?
🔰Analyzes sales trends over time
SELECT DATE_TRUNC('month', order_date) AS month
, SUM(OI.Total_Price) AS monthly_revenue
FROM Orders O
JOIN Order_Items OI ON O.Order_ID = OI.Order_ID
GROUP BY month
ORDER BY month;
1️⃣1️⃣🧾Most sold products (by quantity) ?
🔰Helps decide what products to keep or promote.
SELECT P.Product_name
, SUM(OI.quantity) AS total_sold
FROM Order_Items OI
JOIN Products P ON OI.product_id = P.product_id
GROUP BY P.Product_name
ORDER BY total_sold DESC
LIMIT 10;
1️⃣2️⃣ 🔁 Repeat customers ?
🔰Target these users with loyalty campaigns
SELECT Customer_id,
COUNT() AS Order_Count
FROM Orders
GROUP BY Customer_id
HAVING COUNT() > 1
ORDER BY Order_Count DESC;
1️⃣3️⃣ ⏳ Repeat customers Having the Most Order Counts ?
🔰Target this users with loyalty campaigns
WITH TopCustomer AS (
SELECT Customer_id,
COUNT(*) AS Order_Count
FROM Orders
GROUP BY Customer_id
ORDER BY Order_Count DESC
LIMIT 1
) SELECT C.*
FROM Customers C
JOIN TopCustomer T ON C.Customer_id = T.Customer_id;
1️⃣4️⃣⏳ Orders placed in the last 30 days ?
🔰Get recent activity or new trends
SELECT *
FROM Orders
WHERE order_date >= CURRENT_DATE - INTERVAL '30 Days';
🔴 Advanced Level Queries (15–20)
1️⃣5️⃣📬 Customers with no orders (abandoned signups) ?
🔰Reach out with personalized emails to re-engage.
SELECT C.customer_id, C.name
FROM Customers C
LEFT JOIN Orders O ON C.customer_id = O.customer_id
WHERE O.order_id IS NULL;
1️⃣6️⃣📊 Profit by product (requires cost_price in Products) ?
🔰Determines which products generate the most profit.
SELECT P.Product_Name
, SUM((OI.Total_price - P.price) * OI.quantity) AS total_profit
FROM Order_Items OI
JOIN Products P ON OI.product_id = P.product_id
GROUP BY P.Product_Name
ORDER BY total_profit DESC;
1️⃣7️⃣ 🛍️ Frequently bought together products ?
🔰Used to suggest combos or bundles.
SELECT oi1.product_id AS product_1
, oi2.product_id AS product_2
, COUNT(*) AS frequency
FROM Order_Items oi1
JOIN Order_Items oi2 ON oi1.order_id = oi2.order_id AND oi1.product_id < oi2.product_id
GROUP BY product_1, product_2
ORDER BY frequency DESC
LIMIT 10;
1️⃣8️⃣ 🕒 Average delivery time (requires delivery_date) ?
🔰Monitors logistics performance.
SELECT ROUND(AVG(S.delivery_date - O.order_date),3) AS avg_delivery_days
FROM Orders O
JOIN Shipments S ON O.Order_ID = S.Order_ID
WHERE delivery_date IS NOT NULL;
1️⃣9️⃣ 🔢 Product category contribution to revenue ?
🔰Identify top-performing categories.
SELECT P.category, SUM(OI.Quantity * OI.Total_price) AS revenue
FROM Order_Items OI
JOIN Products P ON OI.product_id = P.product_id
GROUP BY P.category
ORDER BY revenue DESC;
2️⃣0️⃣ 🔗 Most active days (peak order days)
🔰Helps plan marketing and promotions around high-traffic days.
SELECT Order_date, COUNT(*) AS Total_Orders
FROM Orders
GROUP BY Order_date
ORDER BY Total_Orders DESC
LIMIT 10;
✅ Online Retail Store File's Embedded
🔰Online Retail Store related csv file's
customers.csv
order_items.csv
orders.csv
payments.csv
products.csv
shipments.csv
