9 EverCommerce SQL Interview Questions (Updated 2024)
At EverCommerce, SQL is used frequently for analyzing customer usage patterns for EverCommerce's suite of software products targeted at field service pros, health & wellness professionals, and small medical practices. Because of this, EverCommerce asks SQL coding questions during interviews for Data Science, Analytics, and & Data Engineering jobs.
Thus, to help you ace the EverCommerce SQL interview, we've curated 9 EverCommerce SQL interview questions – how many can you solve?
9 EverCommerce SQL Interview Questions
SQL Question 1: Calculate Average Monthly Revenue per Product Using Window Function
EverCommerce operates in the service sector, providing numerous business management software solutions. Let's consider a part of EverCommerce's business where they offer various products (or services). Each product has multiple transactions associated with it.
Your task is to write a SQL query that calculates the monthly average revenue per product using window functions. This information will help EverCommerce calculate the most profitable product in each month.
For this task, we will consider 2 tables: products and transactions.
Example Input:
| product_id | product_name |
|---|---|
| 50001 | EverService-Standard |
| 69852 | EverManage-Premium |
Example Input:
| transaction_id | product_id | transaction_date | amount |
|---|---|---|---|
| 6341 | 50001 | 06/05/2022 | 100 |
| 7893 | 50001 | 06/25/2022 | 150 |
| 5375 | 69852 | 06/10/2022 | 200 |
| 6522 | 69852 | 06/20/2022 | 250 |
| 8210 | 50001 | 07/01/2022 | 125 |
| 4630 | 69852 | 07/15/2022 | 300 |
Example Output:
| month | product_name | avg_revenue |
|---|---|---|
| 6 | EverService-Standard | 125.00 |
| 6 | EverManage-Premium | 225.00 |
| 7 | EverService-Standard | 125.00 |
| 7 | EverManage-Premium | 300.00 |
Answer:
Here is a sample query you could use:
With this query, we're using a window function to calculate the average revenue per product for each month. The clause is dividing the data into partitions based on the product id and transaction month. The window function then calculates the average () revenue for each of these partitions.
This query provides crucial insights into the performance of different products on a monthly basis, allowing the company to identify the most consistently high-performing products.
Pro Tip: Window functions are a popular SQL interview topic, so practice all the window function problems on DataLemur
Sure, here is a SQL interview question related to EverCommerce which offers business management software, marketing services, and customer retention solutions for businesses in the service sector. The question is related to business performance analysis, particularly how to handle service orders and their finanical tracking.
SQL Question 2: EverCommerce Service Financial Analysis
Assume EverCommerce wants to know the total revenue for each service in each year to understand the business trends. To do this, we need to create two tables, and . The table contains each service's information, and the table contains information about each order for services, including the pricing and order date.
Here is the sample data:
Table
| service_id | service_name | description |
|---|---|---|
| 101 | Cleaning | Professional Cleaning Service |
| 102 | Repair | Home Repair Service |
| 103 | Maintenance | Home Maintenance Service |
Here is the sample data:
Table
| order_id | service_id | order_date | price |
|---|---|---|---|
| 5001 | 101 | 01/12/2021 | 120 |
| 5002 | 101 | 06/15/2021 | 90 |
| 5003 | 102 | 03/01/2021 | 200 |
| 5004 | 102 | 04/15/2022 | 250 |
| 5005 | 103 | 05/03/2022 | 450 |
| 5006 | 103 | 06/20/2022 | 300 |
Now, design a SQL query to find the total revenue for each service every year.
Answer:
Below is the SQL query assuming PostgreSQL:
This query first joins the and tables based on . Then it groups the table by and and calculates the total revenue for each service by . It orders the result by and then by in descending order.
SQL Question 3: What's a database view, and when would you use one?
Database views are virtual tables based on the results of a SQL statement. They're just like vanilla tables, except views allow you to create simplified versions of tables or hide sensitive data from certain users.
In PostgreSQL, you can create a view by using the command. Here's an example for the table:
SQL Question 4: Filter EverCommerce's Customers Based on Their Subscription Status
Given an customers table, write an SQL query that filters the records to only show customers located in the USA, who have an active subscription and whose total spend is greater than $500.
Here's a sample of the EverCommerce customers table:
Example Input:
| customer_id | full_name | country | subscription_status | total_spend |
|---|---|---|---|---|
| 1048 | John Doe | USA | Active | 1500 |
| 2039 | Jane Smith | Canada | Cancelled | 4000 |
| 3472 | Wilbur Wright | USA | Active | 800 |
| 4291 | Orville Wright | USA | Cancelled | 3000 |
| 5504 | Roger Johnson | USA | Active | 450 |
Example Output:
| customer_id | full_name | country | subscription_status | total_spend |
|---|---|---|---|---|
| 1048 | John Doe | USA | Active | 1500 |
| 3472 | Wilbur Wright | USA | Active | 800 |
Answer:
This query first checks for customers who are from the USA using the clause. It then adds the conditions that the customer's subscription must be Active, and their 'total_spend' should be greater than 500. The operator is used to ensure all these three conditions are met.
SQL Question 5: Could you clarify the difference between a left and a right join?
A join in SQL combines rows from two or more tables based on a shared column or set of columns. To demonstrate the difference between a and , say you had a table of EverCommerce orders and EverCommerce customers.
LEFT JOIN: A retrieves all rows from the left table (in this case, the Orders table) and any matching rows from the right table (the Customers table). If there is no match in the right table, NULL values will be returned for the right table's columns.
RIGHT JOIN: A retrieves all rows from the right table (in this case, the Customers table) and any matching rows from the left table (the Orders table). If there is no match in the left table, NULL values will be returned for the left table's columns.
SQL Question 6: Click-Through Conversion Rates for EverCommerce
EverCommerce is interested in comparing the click-through conversion rates from viewing a digital product to adding that product to the customer's cart in the first quarter of 2022. The company also wants to look at the total number of views each product received during this time period.
Given two tables, and , which represent all views and add-to-cart actions of products respectively, calculate the click-through conversion rate for each product. Click-through conversion rate is defined as the number of add-to-carts divided by the number of views, multiplied by 100 (to get a percentage).
Example Input:
| view_id | user_id | view_date | product_id |
|---|---|---|---|
| 1 | 123 | 01/05/2022 00:00:00 | 7001 |
| 2 | 265 | 01/10/2022 00:00:00 | 7002 |
| 3 | 362 | 01/21/2022 00:00:00 | 7001 |
| 4 | 192 | 02/15/2022 00:00:00 | 7002 |
| 5 | 981 | 03/15/2022 00:00:00 | 7003 |
Example Input:
| add_id | user_id | add_date | product_id |
|---|---|---|---|
| 1 | 123 | 01/10/2022 00:00:00 | 7001 |
| 2 | 362 | 01/21/2022 00:00:00 | 7001 |
| 3 | 192 | 02/16/2022 00:00:00 | 7002 |
Answer:
The SQL command utilizes a LEFT JOIN to combine the 'views' and 'add_to_cart' based on matching 'product_id' and 'user_id'. It then calculates the total count of view and add_to_cart actions. The click-through conversion rate is then calculated by dividing the total number of add_to_cart actions by the total number of views, and multiplying by 100 to get the rate in percentage. The WHERE clause ensures that only data from the first quarter of 2022 is considered.
To practice another question about calculating rates, try this TikTok SQL question on DataLemur's online SQL coding environment:
SQL Question 7: Can you explain the concept of a constraint in SQL?
Constraints are just rules for your DBMS to follow when updating/inserting/deleting data.
Say you had a table of EverCommerce employees, and their salaries, job titles, and performance review data. Here's some examples of SQL constraints you could implement:
NOT NULL: This constraint could be used to ensure that certain columns in the employee table, such as the employee's first and last name, cannot contain NULL values.
UNIQUE: This constraint could be used to ensure that the employee ID is unique. This would prevent duplicate entries in the employee table.
PRIMARY KEY: This constraint could be used to combine the NOT NULL and UNIQUE constraints to create a primary key for the employee table. The employee ID could serve as the primary key.
FOREIGN KEY: This constraint could be used to establish relationships between the employee table and other tables in the database. For example, you could use a foreign key to link the employee ID to the department ID in a department table to track which department each employee belongs to.
CHECK: This constraint could be used to ensure that certain data meets specific conditions. For example, you could use a CHECK constraint to ensure that salary values are always positive numbers.
DEFAULT: This constraint could be used to specify default values for certain columns. For example, you could use a DEFAULT constraint to set the employee hire date to the current date if no value is provided when a new employee is added to the database.
SQL Question 8: Analyzing Monthly Average Revenue
EverCommerce provides business management software, marketing services, and customer retention solutions. Suppose, you have access to their 'order' database table which consists of information around each order placed such as the order ID, the customer ID who placed the order, the date of the order, and the total cost of the order (excluding tax and shipping).
As a data analyst, you are tasked to find out the monthly average revenue for each product.
Here's some sample data:
Example Input:
| order_id | customer_id | order_date | product_id | total_cost |
|---|---|---|---|---|
| 3281 | 246 | 06/08/2022 00:00:00 | 58301 | 350.00 |
| 4252 | 879 | 06/20/2022 00:00:00 | 10258 | 120.00 |
| 2783 | 762 | 07/18/2022 00:00:00 | 58301 | 450.00 |
| 5812 | 635 | 07/07/2022 00:00:00 | 10258 | 200.00 |
| 7812 | 327 | 07/15/2022 00:00:00 | 10258 | 150.00 |
Expected output for this dataset would be:
Example Output:
| month | product_id | avg_revenue |
|---|---|---|
| 06 | 58301 | 350.00 |
| 06 | 10258 | 120.00 |
| 07 | 58301 | 450.00 |
| 07 | 10258 | 175.00 |
Answer:
Here is a PostgreSQL query that would generate the required result:
In this query, we first extract the month from the order_date using the to_char function in PostgreSQL. We then group by the extracted month and product_id. The total_cost is averaged over each group to obtain the desired average revenue. Finally, we order the result by month and product_id.
SQL Question 9: Calculate Monthly Subscription Cancellations
EverCommerce provides service commerce software and marketing services to service businesses. Assume this company provides monthly subscriptions to different service businesses. As a business analyst, you are supposed to analyze the monthly cancellation of subscriptions.
You have a table named with the following schema:
Example Input:
| sub_id | service_id | customer_id | subscription_date | cancellation_date |
|---|---|---|---|---|
| 1001 | S101 | C801 | 2019-02-03 | 2019-09-04 |
| 1002 | S102 | C501 | 2019-06-30 | NULL |
| 1003 | S101 | C702 | 2020-08-25 | NULL |
| 1004 | S103 | C403 | 2020-09-30 | 2021-07-01 |
| 1005 | S102 | C801 | 2021-01-01 | 2021-04-15 |
Write a SQL query to calculate the number of subscription cancellations each month. The output table should include the year, month, and number of cancellations.
Example Output:
| year | month | cancellations |
|---|---|---|
| 2019 | 9 | 1 |
| 2021 | 4 | 1 |
| 2021 | 7 | 1 |
Answer:
This query extracts the year and month from the column for each cancelled subscription, then counts the number of cancellations grouped by year and month. Note that this query will only include the months where cancellations occurred; months without cancellations will not be in the output. The condition ensures that only cancelled subscriptions are counted. The result is then ordered by year and month for readability.
How To Prepare for the EverCommerce SQL Interview
The best way to prepare for a EverCommerce SQL interview is to practice, practice, practice.
Besides solving the above EverCommerce SQL interview questions, you should also solve the 200+ SQL Interview Questions on DataLemur which come from companies like FAANG and tech startups.
Each problem on DataLemur has hints to guide you, step-by-step solutions and best of all, there's an interactive SQL code editor so you can right online code up your SQL query and have it checked.
To prep for the EverCommerce SQL interview it is also a great idea to solve SQL questions from other tech companies like:
But if your SQL foundations are weak, forget about jumping right into solving questions – refresh your SQL knowledge with this SQL tutorial for Data Analytics.
This tutorial covers topics including handling date/timestamp data and GROUP BY – both of these come up frequently during EverCommerce interviews.
EverCommerce Data Science Interview Tips
What Do EverCommerce Data Science Interviews Cover?
In addition to SQL query questions, the other topics tested in the EverCommerce Data Science Interview are:
- Probability & Statistics Questions
- Python or R Programming Questions
- Product-Sense Questions
- Machine Learning and Predictive Modeling Questions
- Behavioral & Resume-Based Questions
How To Prepare for EverCommerce Data Science Interviews?
To prepare for EverCommerce Data Science interviews read the book Ace the Data Science Interview because it's got:
- 201 interview questions sourced from tech companies like Google & Microsoft
- a crash course covering SQL, Product-Sense & ML
- over 900+ 5-star reviews on Amazon