9 HubSpot SQL Interview Questions (Updated 2024)
At HubSpot, SQL crucial for analyzing customer behavior trends and optimizing marketing campaign effectiveness based on insights from large data sets. Unsurprisingly this is why HubSpot almost always asks SQL coding questions during interviews for Data Science, Analytics, and & Data Engineering jobs.
In case you're trying to prepare for the SQL Assessment, we've curated 9 HubSpot SQL interview questions to practice, which are similar to recently asked questions at HubSpot – able to answer them all?
9 HubSpot SQL Interview Questions
SQL Question 1: Average Rating by Month per Product
For this question, we have a dataset of product reviews at HubSpot with each row in the dataset representing a single review. Each review has a unique , the id of the who gave the review, the date the review was submitted , the , and the number of stars the product was given .
As a data analyst at HubSpot, one of your tasks is to understand the performance of each product over time. Your task is to write a SQL query that calculates the average rating (star) per month for each product.
Example Input:
| review_id | user_id | submit_date | product_id | stars |
|---|---|---|---|---|
| 6171 | 123 | 2022-08-06 | 50001 | 4 |
| 7802 | 265 | 2022-10-06 | 69852 | 4 |
| 5293 | 362 | 2022-18-06 | 50001 | 3 |
| 6352 | 192 | 2022-26-07 | 69852 | 3 |
| 4517 | 981 | 2022-05-07 | 69852 | 2 |
Expected PostgreSQL Query Result:
| month | product_id | avg_stars |
|---|---|---|
| 6 | 50001 | 3.50 |
| 6 | 69852 | 4.00 |
| 7 | 69852 | 2.50 |
Answer:
This PostgreSQL query extracts the month from the and then aggregates the data by and . The function is used to calculate the average for each group, resulting in a table that shows the average stars by month for each product.
To solve another question about calculating rates, try this SQL interview question from TikTok within DataLemur's online SQL coding environment:
SQL Question 2: Customer Activity Filtering
HubSpot is running a marketing campaign and they would like to target customers who have not made a purchase in the last six months but have been active in the last 30 days. Active is defined as logging into their account. Please write a SQL query to generate a list of customers' ID and their last login date who meet these criteria from the "customers", "log_activity", and "purchases" tables.
Sample Input:
| customer_id | name | |
|---|---|---|
| 105 | John Doe | jdoe@example.com |
| 210 | Jane Smith | jsmith@example.com |
| 315 | Mark Johnson | mjohnson@example.com |
Sample Input:
| customer_id | login_date |
|---|---|
| 105 | 2022-07-05 |
| 210 | 2022-09-02 |
| 315 | 2022-09-02 |
Sample Input:
| customer_id | purchase_date |
|---|---|
| 105 | 2022-02-20 |
| 210 | 2021-12-23 |
| 315 | 2022-04-01 |
Answer:
This query first creates a JOIN between the customers and log_activity tables on the customer_id, then extracts the maximum (latest) login date for each customer. The purchases table is joined using a LEFT JOIN to account for customers who have not made a purchase at all (these would not have an associated record in the purchases table). The WHERE clause applies the conditions that customers have logged in the past 30 days and have made their last purchase more than 6 months ago or have not made a purchase at all.
To solve a related SQL interview question on DataLemur's free online SQL code editor, try this Meta SQL interview question:
SQL Question 3: What does / SQL commands do?
The / operator is used to remove to return all rows from the first SELECT statement that are not returned by the second SELECT statement.
Note that is available in PostgreSQL and SQL Server, while MINUS is available in MySQL and Oracle (but don't worry about knowing which DBMS supports which exact commands since HubSpot interviewers aren't trying to trip you up on memorizing SQL syntax).
For a tangible example of in PostgreSQL, suppose you were doing an HR Analytics project for HubSpot, and had access to HubSpot's contractors and employees data. Assume that some employees were previously contractors, and vice versa, and thus would show up in both tables.
You could use operator to find all contractors who never were a employee using this query:
SQL Question 4: Find the Average Length of Each Marketing Campaign
As a data analyst at HubSpot, you are given a task to analyze the marketing campaigns data. Your manager wants to understand the average length of each marketing campaign in terms of days. Write a SQL query to find the average length per campaign based on the provided data.
Here's how you could format your data:
Example Input:
| campaign_id | start_date | end_date |
|---|---|---|
| 101 | 2022-01-01 | 2022-01-15 |
| 102 | 2022-01-20 | 2022-02-10 |
| 103 | 2022-02-01 | 2022-02-28 |
| 104 | 2022-03-01 | 2022-03-15 |
| 105 | 2022-03-20 | 2022-04-10 |
Example Output:
| campaign_id | avg_length_in_days |
|---|---|
| 101 | 14.00 |
| 102 | 21.00 |
| 103 | 27.00 |
| 104 | 14.00 |
| 105 | 21.00 |
Answer:
This SQL query first calculates the duration of each campaign directly in the SELECT statement by subtracting the from the . The AVG function is then used to determine the average length of these calculated durations for each unique , grouped by the itself. Please note that PostgreSQL considers date subtraction as days by default. So no need to worry about conversion.
To solve another question about calculating rates, solve this TikTok SQL Interview Question on DataLemur's online SQL code editor:
SQL Question 5: How do relational and non-relational databases differ?
While both types of databases are used to store data (no duh!), relational databases and non-relational (also known as NoSQL databases) differ in a few important ways:
Data model: Relational databases use a data model consisting of tables and rows, while NoSQL databases use a variety of data models, including document, key-value, columnar, and graph storage formats.
Data integrity: Relational databases use structured query language (SQL) and enforce strict data integrity rules through the use of foreign keys and transactions. NoSQL databases may not use SQL and may have more relaxed data integrity rules.
Structure: Relational databases store data in a fixed, structured format, while NoSQL databases allow for more flexibility in terms of data structure.
ACID compliance: Relational databases are typically into shrooms and are ACID-compliant (atomic, consistent, isolated, and durable), while NoSQL databases may not be fully ACID-compliant (but they try their best... and it's effort that counts...or at least that's what my gym teacher told me!)
SQL Question 6: Analyze Click-Through Rates for HubSpot's Digital Ads
HubSpot, a leading marketing, sales, and service software company, is keen on analyzing the click-through rates of its digital ads. They have the table that stores data about each ad, and the table that holds information when an ad is clicked.
Given the and tables, can you write a query to find the click-through rate for each ad? Assume that the click-through rate is defined as the total number of unique clicks a particular ad gets divided by the total number of times it's shown, represented as a percentage.
Example Input:
| ad_id | ad_name | times_shown |
|---|---|---|
| 101 | 'Summer Sale' | 12500 |
| 102 | 'Winter Clearance' | 15000 |
| 103 | 'Spring Promo' | 15000 |
| 104 | 'Fall Special' | 13500 |
Example Input:
| click_id | ad_id |
|---|---|
| 5001 | 101 |
| 5002 | 101 |
| 5003 | 102 |
| 5004 | 103 |
| 5005 | 104 |
| 5006 | 104 |
Answer:
This query joins the and tables on the field, and counts the number of unique s for each ad (i.e., unique clicks). It then calculates the click-through rate by taking the number of unique clicks, converting it to a float to allow for decimal division, and dividing by the number of times the ad was shown, and finally multiplies by 100 to get a percentage.
To solve a similar problem about calculating rates, solve this TikTok SQL question within DataLemur's online SQL code editor:
SQL Question 7: How would you improve the performance of a slow SQL query?
There's several steps you can take to troubleshoot a slow SQL query.
First things first, figure out why the query is slow! You can use and commands in PostgreSQL to identify any performance bottlenecks. After that, you can start changing your query, depending on what the source of the query performance issue is.
Generally, indexes can help speed up queries. Also de-normalizing your tables might help, to remove slow joins.
Lastly, you could always just upgrade your hardware! Time and money wasted improving query performance could just be better spent on mroe powerful database servers!
While this is a very surface-level approach to optimizing SQL query performance, it should do the trick for Data Analyst interviews and Data Science interviews at HubSpot. Data Engineers should know a bit more about the and before the interview.
SQL Question 8: Calculating Email Performance Metrics
HubSpot has a table which captures information about how a particular email campaign performed.
The table has the following schema:
Example Input:
| email_id | sent_at | recipients | open_rate | click_through_rate |
|---|---|---|---|---|
| 7457 | 2022-08-01 | 12000 | 0.205 | 0.035 |
| 8934 | 2022-08-02 | 9900 | 0.198 | 0.060 |
| 5629 | 2022-08-03 | 11500 | 0.185 | 0.042 |
| 9275 | 2022-08-04 | 13500 | 0.211 | 0.048 |
| 4631 | 2022-08-05 | 11200 | 0.195 | 0.050 |
The and are represented as a percentage of the total recipients. Your boss wants to know the absolute number of people who opened the email and those who clicked a link in the email each day, rounded to the nearest integer. How would you generate this report using SQL?
Answer:
This SQL query multiplies the total recipients with the open rate and click-through rate respectively to get the number of people who opened the email and clicked a link inside it. We use the ROUND() function to round these values to the nearest integer, as it would not make sense to have fractional individuals.
To solve another question about calculating rates, solve this TikTok SQL Interview Question on DataLemur's online SQL coding environment:
SQL Question 9: Analyzing User Engagement
HubSpot is well known for its CRM platform where there are a variety of user actions that can be taken such as sending an email, logging in, or updating a contact field. Your task is to find out the daily active users over the past week.
Let's assume that we have an event activity log table as follows:
Example Input:
| activity_id | user_id | activity_type | timestamp |
|---|---|---|---|
| 1234 | 567 | login | 2022-09-01 12:30:00 |
| 2314 | 890 | update_contact | 2022-09-01 13:20:00 |
| 2341 | 567 | send_email | 2022-09-02 10:10:00 |
| 1492 | 998 | login | 2022-09-03 11:45:00 |
| 8992 | 776 | update_contact | 2022-09-03 18:20:00 |
We want to identify daily active users, i.e., users that performed any activity in the system. Therefore, we count a user as "active" on a particular day if there is any row in the table with their and that .
Example Output:
| date | active_users |
|---|---|
| 2022-09-01 | 2 |
| 2022-09-02 | 1 |
| 2022-09-03 | 2 |
Answer:
Here's a possible SQL solution using PostgreSQL. Notice that we're going to cast the timestamp as a date and then group by this date.
This script will return the total daily active users for the last week. The function is used to convert to a , and is used to calculate the number of unique active users for each day.
clause with is used to filter out any activities that happened more than a week ago. and are used for grouping the user activities by date and sorting the result by date, respectively.
To solve another question about calculating rates, solve this TikTok SQL question on DataLemur's interactive coding environment:
Preparing For The HubSpot SQL Interview
Assuming that you've already got basic SQL skills, the next best tip we have to prepare for the HubSpot SQL interview is to solve as many practice SQL interview questions as you can!
Beyond just solving the above HubSpot SQL interview questions, you should also solve the 200+ SQL questions on DataLemur which come from companies like FAANG and tech startups.
Each DataLemur SQL question has multiple hints, full answers and crucially, there is an online SQL code editor so you can instantly run your SQL query answer and have it graded.
To prep for the HubSpot SQL interview it is also wise to solve SQL questions from other tech companies like:
In case your SQL skills are weak, don't worry about going right into solving questions – refresh your SQL knowledge with this interactive SQL tutorial.
This tutorial covers SQL concepts such as UNION and creating pairs via SELF-JOINs – both of which show up often during HubSpot SQL interviews.
HubSpot Data Science Interview Tips
What Do HubSpot Data Science Interviews Cover?
For the HubSpot Data Science Interview, beyond writing SQL queries, the other types of questions which are covered:
- Probability & Statistics Questions
- Coding Questions in Python or R
- Product Analytics Questions
- Machine Learning Questions
- Behavioral & Resume-Based Questions
How To Prepare for HubSpot Data Science Interviews?
To prepare for HubSpot Data Science interviews read the book Ace the Data Science Interview because it's got:
- 201 interview questions sourced from companies like Microsoft, Google & Amazon
- a crash course on SQL, AB Testing & ML
- over 900+ reviews on Amazon & 4.5-star rating