What was the total sales amount last month?
Calculate the average order value over the past three months.
Show total sales by product category.
Find the top 10 products by sales amount.
Which products have the fastest sales growth in the past week?
Show the total purchase amount for each customer.
What were the sales for the "Electronics" category in Q1 2024?
Analyze the sales trend for the "Books" category by month over the past year.
Which customers purchased items from the "Apparel" category?
Calculate the average number of orders per category.
Find the 5 products with the fewest orders.
Show daily total sales.
Analyze quarterly sales by category.
Show all customers' names and emails.
Find the number of customers living in "New York".
Count customers by country.
Show all store names and their cities.
Find the number of stores in the "East" region.
Which employees work at "Store 1"?
Show all employees' names and hire dates.
Find employees hired before 2023.
Show all shipment IDs and their corresponding order IDs.
Find the number of shipments with "Delivered" status.
Show all return IDs and return reasons.
Find the number of products returned for "Defective" reasons.
Calculate the total sales amount for all orders.
Find the customer with the highest sales amount.
Show sales for each product in different cities.
Analyze quarterly sales by region.
Find customers who haven't placed orders in the last 6 months.
Show the number of employees per store.
Find orders with sales amount exceeding 10,000.
Show sales by product category and city.
Calculate the average order amount per customer.
Find new customers registered in the last 30 days.
Show total sales per store.
Find the store with the lowest sales.
Show the number of orders handled by each employee.
Find the employee with the longest tenure.
Show all shipments with "In Transit" status.
Find the number of orders shipped in the last 7 days.
Show all returns with "Wrong Size" reason.
Find the product category with the highest return rate.
Calculate the total return amount.
Show the number of orders per customer.
Find the customer with the most purchases.
Show total sales by product name.
Find total sales by city.
Show average order value per store.
Find the store with the most employees.
Show average sales per employee.
Find customers who haven't returned items in the past year.
Show the number of orders by shipment status.
Find orders with shipment dates within a specific range.
Show the number of returns by return reason.
Find the customer with the highest return amount.
Calculate total sales volume for all products.
Find the best-selling product.
Show average purchase frequency per customer.
Find average order value by country.
Show sales growth rate per store.
Find the store with the highest average employee age.
Show sales ranking for each employee.
Find orders that haven't been shipped in the last 3 months.
Show average shipping time by shipping method.
Find products with more than 50 returns.
Show average return amount by return reason.
Calculate total purchase amount for all customers.
Find the customer with the highest purchase amount.
Show sales for each product in different regions.
Analyze sales trends by year and category.
Find customers who haven't purchased in the past year.
Show average employee sales per store.
Find the fastest-growing store by sales.
Show total sales by employee.
Find the most recently hired employee.
Show all shipments with "Pending" status.
Find the number of orders shipped in the last 30 days.
Show all returns with "Damaged" reason.
Find the product with the lowest return rate.
Calculate return frequency per customer.
Show average sales per product.
Find the product with the lowest sales.
Show average order count per customer.
Find average sales by city.
Show sales per store.
Find the store with the fewest employees.
Show order count per employee.
Find orders that haven't been shipped in the last 6 months.
Show average shipment amount by shipment status.
Find products with the fewest returns.
Show average return count by return reason.
Calculate average sales per order for all orders.
Find the customer with the highest average order value.
Show sales for each product in different stores.
Analyze regional sales trends by month.
Find customers who haven't purchased in the past 2 years.
Show average employee sales per store.
Find the store with the fastest declining sales.
Show average order value by employee.
Find employees hired within a specific date range.
Show all shipments with "Cancelled" status.
Find the number of orders shipped in the last 90 days.
Show all returns with "Unwanted" reason.
Find the product with the lowest return amount.
Calculate average return amount per customer.
Show all shipment IDs and their corresponding order IDs.
Find the number of shipments with "Delivered" status.
Find the number of orders shipped in the last 7 days.
Show the number of orders by shipment status.
Show average shipping time by shipping method.
Show all shipments with "In Transit" status.
Find orders that haven't been shipped in the last 3 months.
Find the number of orders shipped in the last 90 days.

# Complex Query Question List

## Analysis Questions (50 questions)

1. Analyze sales trends for each product category over the past year and predict growth for the next three months.
2. Compare customer purchasing behaviors across different cities and identify the city with the strongest purchasing power.
3. Analyze the relationship between employee tenure and sales amount. Do more experienced employees have higher sales?
4. Evaluate the impact of different return reasons on overall sales performance and propose improvement suggestions.
5. Analyze shipping efficiency across regions. Which region has the shortest average shipping time?
6. Compare sales performance of different stores. Identify the best and worst performing stores and analyze the reasons.
7. Study the relationship between customer purchase frequency and return rate. Do frequent buyers have lower return rates?
8. Analyze the relationship between product categories and return rates. Which category's product quality may need improvement?
9. Evaluate the relationship between employee count and store sales. Do more employees mean higher sales?
10. Analyze the proportion of orders by different shipping statuses. Is there a shipping delay problem?
11. Study the impact of seasonal factors on sales. Which months are peak sales periods?
12. Analyze how customer geographic distribution affects purchasing preferences. What products do customers from different countries prefer?
13. Evaluate the impact of promotional activities on sales (based on order date fluctuations).
14. Analyze customer lifetime value and identify the most valuable customer segments.
15. Study the relationship between product price and sales volume. Is there a price elasticity phenomenon?
16. Compare purchasing behaviors of new vs. existing customers. Is the first purchase amount of new customers lower?
17. Analyze inventory turnover rates by product category (based on sales volume estimation).
18. Evaluate customer satisfaction (through return rates and repeat purchase rates).
19. Study the impact of employee turnover on store performance. What's the difference in sales performance between new and veteran employees?
20. Analyze the cost-effectiveness of different shipping methods. Which shipping method offers the best value?
21. Study customer churn patterns and identify characteristics of customers likely to churn.
22. Analyze product combination sales. Which products are frequently purchased together?
23. Evaluate pricing strategy effectiveness by analyzing sales performance across different price ranges.
24. Study the ratio of customer acquisition cost to customer lifetime value.
25. Analyze the distribution of time intervals between return products and original orders. Is there a concentration of returns in specific time periods?
26. Evaluate the impact of marketing activities on new customer acquisition.
27. Study customer referral behavior through order data analysis of customer networks.
28. Analyze the impact of competitors on sales (through market share change analysis).
29. Evaluate supply chain efficiency by analyzing average time from order to shipment.
30. Study the correlation between customer complaints and return reasons to identify major problem areas.
31. Analyze the relationship between employee performance and customer satisfaction. Do high-performing employees bring more satisfied customers?
32. Evaluate the impact of product update frequency on sales. Do new products drive sales growth?
33. Study the effectiveness of customer loyalty programs by analyzing purchasing behavior differences between members and non-members.
34. Analyze the impact of different payment methods on order amounts. Are there significant differences?
35. Evaluate advertising campaign effectiveness by analyzing sales growth during advertising periods.
36. Study the relationship between customer age groups and purchasing preferences (assuming age data exists).
37. Analyze the distribution of product defect types to identify the most common quality issues.
38. Evaluate customer service quality by measuring shipping speed and return processing time.
39. Study the impact of holidays on sales and identify peak sales periods.
40. Analyze the relationship between customer feedback and product improvements to optimize product design based on return reasons.
41. Evaluate inventory management efficiency by analyzing the proportion and characteristics of slow-moving products.
42. Study the relationship between customer geography and shipping costs. Is shipping to remote areas more expensive?
43. Analyze the relationship between employee training and sales performance. Does training improve sales skills?
44. Evaluate the rationality of product pricing strategies by analyzing the elasticity relationship between price and sales volume.
45. Study the impact of brand influence on customer choices and analyze brand loyalty.
46. Analyze differences between online and offline sales channels by comparing sales performance across channels.
47. Evaluate the quality of customer acquisition channels. How do customers acquired through different channels differ in value?
48. Study the relationship between product packaging and return rates. Do packaging improvements reduce shipping damage?
49. Analyze customer complaint handling efficiency and evaluate the speed of problem resolution.
50. Conduct a comprehensive evaluation of enterprise operational efficiency through analysis of sales, shipping, and returns across multiple dimensions.

## Various Ways of Asking Questions (30 questions)

1. I need to know last month's total sales. Can you check that for me?
2. Can you show total sales by product category?
3. Which customers have purchase amounts exceeding 1,000 yuan?
4. How many new orders were added yesterday?
5. What was the return rate in the past week?
6. Which city has the most customers?
7. What is the average sales amount per employee?
8. What is the shipment volume so far this month?
9. Which product has the highest sales volume?
10. What percentage of returns are due to "Product Damage"?
11. Can you generate a sales report for the last quarter?
12. I'd like to understand the performance of each store. Can you sort by sales amount?
13. Have there been any customer complaints about product quality? What are the details?
14. How many employees were hired in the past month?
15. Can you show all orders with "Pending Shipment" status?
16. What is the average order value for different product categories?
17. Are there customers who haven't purchased in three consecutive months?
18. Which region has the fastest shipping speed?
19. Among returned products, which category has the most returns?
20. Can you show a sales trend chart by month for last year?
21. I'd like to see the sales performance ranking of employees.
22. Which customers have never had a return?
23. How many new customers were added in the past month?
24. Show all orders that are "Shipped" but not "Delivered".
25. Which store has the highest employee turnover rate?
26. How do different product categories sell in different cities?
27. Show the number of orders handled by each employee and their return rate.
28. Are there customers who placed multiple orders on the same day?
29. Among returned products, how many are due to "Wrong Size"?
30. Count the number of new customers added each month over the past year.

## Other Complex Queries (220 questions)

1. Show all order IDs with their corresponding product names and customer names.
2. Find orders with sales amounts above the average and their customer information.
3. Group by product category and city, show total sales amounts.
4. Calculate the number of orders and total purchase amount for each customer.
5. Find customers with more than 10 purchases and their total spending.
6. Show the number of orders and average order value for each product category.
7. Find customers who haven't purchased in the last three months.
8. Show total sales by month for each month of 2024.
9. Find sales amounts and employee counts for each store.
10. Show the top 5 products by sales amount and their categories.
11. Calculate customer counts and average order values for each region.
12. Find product categories with return rates above 15%.
13. Show sales amounts and order counts handled by each employee.
14. Find employees with more than one year tenure and in the top 10 sales rankings.
15. Group by shipping status, show order counts and average shipping times.
16. Find orders with shipping times above the average shipping time.
17. Show order counts and average return amounts for each return reason.
18. Calculate customer counts and total purchase amounts for each city.
19. Find the fastest-growing store by sales in the past 6 months.
20. Show sales situations for each product in different stores.
21. Find the product category with the highest sales amount for each month of the past year.
22. Group by customer country, show order counts and average order values.
23. Find customers who have never returned items and their total purchase amounts.
24. Show employee sales rankings for each store.
25. Calculate sales volumes and return rates for each product category.
26. Find the customer with the highest purchase amount in the past three months.
27. Group by shipping date, show daily shipment counts and average order amounts.
28. Show orders with sales above 10,000 and their customer and product information.
29. Find the top 3 customers by sales amount in each city.
30. Group by product category and shipping status, show order counts.
31. Calculate the correlation between employee tenure and sales amounts.
32. Find the product category with the highest return rate for each month of the past six months.
33. Show shipping efficiency rankings for each store.
34. Find customers who purchased products in the "Electronics" category.
35. Group by return reason and product category, show return counts.
36. Calculate average return rates for each customer group (grouped by purchase amount).
37. Find sales trends for each product in the past three months.
38. Show store counts and total sales for each region.
39. Find stores with sales below average but return rates also below average.
40. Group by shipping status and return status, show order counts.
41. Calculate customer repurchase rates for each product category.
42. Find the fastest-growing store by sales for each quarter of the past year.
43. Show average shipping times for orders handled by each employee.
44. Find customers who purchased at least 5 different product categories.
45. Group by customer city and product category, show sales amounts.
46. Calculate customer satisfaction indices for each store (based on return rates and shipping times).
47. Find the product category with the lowest sales amount for each month of the past six months.
48. Show the distribution of product categories for each return reason.
49. Find products with sales above average and return rates below average.
50. Group by shipping date and shipping status, show order counts and average amounts.
51. Calculate purchasing preferences for each customer group (by age assumption).
52. Find monthly sales growth rates for each store in the past year.
53. Show the relationship between employee hire years and average sales amounts.
54. Find customers who purchased "Books" category products but never returned items.
55. Group by product category and customer country, show sales amounts.
56. Calculate average employee sales for stores in each region.
57. Find the fastest shipping store in the past three months.
58. Show monthly sales trends for each product category.
59. Find purchase frequencies for each customer in the past year.
60. Group by shipping status and customer city, show order counts.
61. Calculate sales proportions for each product in different cities.
62. Find the store with the fastest declining return rate in the past six months.
63. Show average return rates for orders handled by each employee.
64. Find the top 100 customers by purchase amount but with the lowest return rates.
65. Group by product category and shipping time, show order counts.
66. Calculate customer retention rates for each store.
67. Find monthly return rates for each product category in the past year.
68. Show average customer purchase amounts for stores in each region.
69. Find stores with the fastest sales growth and highest employee satisfaction.
70. Group by shipping status and return reason, show order counts.
71. Calculate customer satisfaction (based on return rates) for each product category.
72. Find the store with the lowest return rate for each quarter of the past year.
73. Show the relationship between employee sales performance and store performance.
74. Find customers who purchased "Sports Equipment" category products and live in specific cities.
75. Group by product category and customer purchase frequency, show sales amounts.
76. Calculate the relationship between average employee sales and total store sales for each store.
77. Find the city with the highest sales amount for each month of the past six months.
78. Show the distribution of product categories for each return reason.
79. Find the top 20 products by sales amount and bottom 20 by return rate.
80. Group by shipping date and customer country, show order counts.
81. Calculate average order values for each customer group (by city grouping).
82. Find quarterly sales growth rates for each store in the past year.
83. Show the relationship between employee tenure and return rates for orders handled.
84. Find customers who purchased "Beauty Products" category but never purchased "Food" category.
85. Group by product category and customer region, show sales amounts.
86. Calculate the correlation between employee counts and sales amounts for each store.
87. Find the store with the fastest customer growth in the past three months.
88. Show seasonal sales performance for each product category.
89. Find average order amounts for each customer in the past year.
90. Group by shipping status and product category, show order counts.
91. Calculate sales proportions for each product in different seasons.
92. Find the store with the highest return amount in the past six months.
93. Show average shipping times for orders handled by each employee.
94. Find the top 50 customers by purchase amount and highest repurchase rates.
95. Group by product category and shipping efficiency, show order counts.
96. Calculate customer acquisition costs for each store (assumption).
97. Find quarterly sales trends for each product in the past year.
98. Show average return rates for stores in each region.
99. Find stores with stable sales growth and low employee turnover.
100. Group by shipping status and customer purchase amount, show order counts.
101. Calculate customer loyalty indices for each product category.
102. Find the region with the fastest sales growth for each quarter of the past year.
103. Show the relationship between employee sales performance and tenure.
104. Find customers who purchased "Toys" category products and are within a specific age range (assumption).
105. Group by product category and customer age group, show sales amounts.
106. Calculate the relationship between employee satisfaction and customer satisfaction for each store.
107. Find the store with the highest shipping accuracy in the past three months.
108. Show sales performance for each product category during different holidays.
109. Find return rates for each customer in the past year.
110. Group by shipping status and customer region, show order counts.
111. Calculate sales proportions for each product category during different holidays.
112. Find the store with the fewest returns in the past six months.
113. Show average order amounts for orders handled by each employee.
114. Find the top 30 customers by purchase amount who never returned items.
115. Group by product category and customer satisfaction, show sales amounts.
116. Calculate the relationship between employee training investment and sales performance for each store (assumption).
117. Find monthly sales growth rates for each product in the past year.
118. Show average shipping times for stores in each region.
119. Find stores with the fastest sales growth and highest customer satisfaction.
120. Group by shipping status and customer loyalty, show order counts.
121. Calculate market shares for each product category.
122. Find the region with the lowest return rate for each quarter of the past year.
123. Show the relationship between employee sales performance and customer complaint rates.
124. Find customers who purchased "Household Goods" category products and have incomes within a specific range (assumption).
125. Group by product category and customer income level, show sales amounts.
126. Calculate the relationship between marketing investment and sales growth for each store (assumption).
127. Find the store with the highest customer satisfaction in the past three months.
128. Show sales performance for each product category during different promotional campaigns.
129. Find the diversity of purchase categories for each customer in the past year.
130. Group by shipping status and customer category count, show order counts.
131. Calculate sales proportions for each product category during promotional campaigns.
132. Find the fastest-growing store by sales in the past six months.
133. Show customer satisfaction for orders handled by each employee.
134. Find the top 20 customers by purchase amount with the fewest return reasons.
135. Group by product category and customer promotional participation frequency, show sales amounts.
136. Calculate inventory turnover rates for each store (based on sales data estimation).
137. Find quarterly return trends for each product in the past year.
138. Show average customer repurchase rates for stores in each region.
139. Find stores with stable sales growth and obvious employee skill improvements.
140. Group by shipping status and customer engagement, show order counts.
141. Calculate brand influence for each product category (based on customer loyalty).
142. Find the customer group with the fastest sales growth for each quarter of the past year.
143. Show the relationship between employee sales performance and customer referral rates.
144. Find customers who purchased "Food" category products and have high purchase frequencies.
145. Group by product category and customer purchase frequency, show return rates.
146. Calculate customer acquisition channel effectiveness for each store (assumption).
147. Find the store with the highest return processing efficiency in the past three months.
148. Show performance for each product category in different sales channels (assumption).
149. Find average shipping times for each customer in the past year.
150. Group by shipping status and customer acquisition channel, show order counts.
151. Calculate sales proportions for each product category in different sales channels.
152. Find the region with the fastest customer growth in the past six months.
153. Show average return processing times for orders handled by each employee.
154. Find the top 10 customers by purchase amount with the highest customer satisfaction.
155. Group by product category and customer satisfaction rating, show sales amounts.
156. Calculate supply chain efficiency for each store (based on shipping times).
157. Find monthly customer satisfaction for each product in the past year.
158. Show average customer acquisition costs for stores in each region (assumption).
159. Find stores with stable sales growth and continuously declining return rates.
160. Group by shipping status and customer value, show order counts.
161. Calculate innovation indices for each product category (based on new product sales performance).
162. Find the store with the most obvious return rate improvement for each quarter of the past year.
163. Show the relationship between employee sales performance and team collaboration scores (assumption).
164. Find customers who purchased "Apparel" category products and have high brand loyalty.
165. Group by product category and customer brand loyalty, show sales amounts.
166. Calculate digital transformation effects for each store (based on online sales proportion assumption).
167. Find the store with the lowest customer complaint rate in the past three months.
168. Show performance for each product category in different e-commerce platforms (assumption).
169. Find average return processing times for each customer in the past year.
170. Group by shipping status and customer complaint rate, show order counts.
171. Calculate sales proportions for each product category in different e-commerce platforms.
172. Find the store with the fastest employee satisfaction improvement in the past six months.
173. Show average customer satisfaction for orders handled by each employee.
174. Find the top 5 customers by purchase amount who never complained.
175. Group by product category and customer complaint rate, show sales amounts.
176. Calculate sustainability indices for each store (based on return reduction and efficiency improvement).
177. Find quarterly customer satisfaction trends for each product in the past year.
178. Show average employee satisfaction for stores in each region.
179. Find stores with stable sales growth and continuously improving customer satisfaction.
180. Group by shipping status and customer lifecycle stage, show order counts.
181. Calculate social responsibility indices for each product category (based on return reduction and customer satisfaction).
182. Find the region with the fastest customer growth for each quarter of the past year.
183. Show the relationship between employee sales performance and innovation ability scores (assumption).
184. Find customers who purchased "Electronics" category products and are environmentally conscious (assumption).
185. Group by product category and customer environmental awareness, show sales amounts.
186. Calculate internationalization levels for each store (based on customer country diversity).
187. Find the store with the highest customer referral rate in the past three months.
188. Show performance for each product category in different international markets (assumption).
189. Find average customer satisfaction for each customer in the past year.
190. Group by shipping status and customer international background, show order counts.
191. Calculate sales proportions for each product category in different international markets.
192. Find the region with the most obvious customer satisfaction improvement in the past six months.
193. Show average customer referral rates for orders handled by each employee.
194. Find the top 3 customers by purchase amount with the highest customer loyalty indices.
195. Group by product category and customer loyalty index, show sales amounts.
196. Calculate innovative product sales proportions for each store.
197. Find monthly customer referral rates for each product in the past year.
198. Show average customer loyalty indices for stores in each region.
199. Find stores with stable sales growth and outstanding innovation capabilities.
200. Group by shipping status and customer innovation preferences, show order counts.
201. Calculate future growth potential for each product category (comprehensive assessment).
202. Find the store with the most obvious innovation capability improvement for each quarter of the past year.
203. Show the relationship between employee sales performance and learning growth scores (assumption).
204. Find customers who purchased new products and actively participated in feedback.
205. Group by product category and customer engagement, show sales amounts.
206. Calculate digital customer experience scores for each store (assumption).
207. Find the store with the highest customer engagement in the past three months.
208. Show performance for each product category in community marketing (assumption).
209. Find average engagement scores for each customer in the past year.
210. Group by shipping status and customer community engagement, show order counts.
211. Calculate sales proportions for each product category in community marketing.
212. Find the store with the fastest customer engagement improvement in the past six months.
213. Show average customer engagement for orders handled by each employee.
214. Find the top 1 customer by purchase amount who actively participates in community activities.
215. Group by product category and customer community influence, show sales amounts.
216. Calculate omnichannel integration effects for each store (assumption).
217. Find quarterly customer engagement trends for each product in the past year.
218. Show average customer community engagement for stores in each region.
219. Find stores with stable sales growth and continuously improving customer engagement.
220. Group by shipping status and customer omnichannel usage, show order counts.