8 LegalZoom SQL Interview Questions (Updated 2024)

Updated on

March 3, 2024

At LegalZoom, SQL is used across the company for analyzing legal trends based on customer data and optimizing product offerings through customer behavior analysis. That's why LegalZoom almost always asks SQL coding questions in interviews for Data Science, Analytics, and & Data Engineering jobs.

To help you ace the LegalZoom SQL interview, here’s 8 LegalZoom SQL interview questions – how many can you solve?

8 LegalZoom SQL Interview Questions

SQL Question 1: Calculate Average Monthly Review Ratings for LegalZoom Products

LegalZoom relies heavily on customer reviews to evaluate their product performance and gauge customer satisfaction. As an interviewee for a data analyst position, you are asked to analyze the dataset, which holds information about the different reviews submitted by users for various LegalZoom products.

Each row in the dataset has the following columns:

  • - ID of the review
  • - ID of the user who submitted the review
  • - Date and time when the review was submitted
  • - ID of the reviewed product
  • - Number of stars given for the review (from 1 to 5)

Write a PostgreSQL query that calculates the average monthly review rating for each LegalZoom product. Round your answer to the nearest two decimal places.

Example Input:
617112306/08/2022 00:00:00500014
780226506/10/2022 00:00:00698524
529336206/18/2022 00:00:00500013
635219207/26/2022 00:00:00698523
451798107/05/2022 00:00:00698522


In this query, the function extracts the month from the date of the review, which allows us to group the reviews by month. The function calculates the average number of stars for the reviews grouped by product and month, and rounds the result to two decimal places. Finally, the clause sorts the results by month and product ID.

Please note the "mth" and "product" are column aliases created using the AS keyword to make the final data output more readable.

Pro Tip: Window functions are a popular SQL interview topic, so practice every window function problem on DataLemur

SQL Interview Questions on DataLemur

SQL Question 2: LegalZoom Customers and Orders Analysis

LegalZoom, an online marketplace that helps people create legal documents, wants to understand its customer behavior across different types of legal services. The main goal is to determine the customers who utilized most services (number of orders) per each legal category in the year 2021. Assume following are the tables with required details.

Example Input:
Example Input:
Example Input:
401Estate PlanningWills & Trusts
528LLC FormationBusiness Formation


This script first joins the three tables to link customers to the services they have ordered. We then filter for records solely from the year 2021. The clause groups the records by both customer and service category. The counts of orders are calculated for each customer per each legal category. The clause sorts the output first by service category, and then in descending order of the count of orders. This way, the customers with the highest number of orders in each category are shown at the top.

SQL Question 3: What's the difference between and ?

Before we address vs. question, let's address the clause which is used in a statement to group rows into a set of summary rows. It's typically used in conjunction with aggregate functions such as:

  • `MIN

The clause is used to filter the groups created by the clause. It's similar to the clause, but it is used to specify conditions on the groups created by the clause, rather than on the individual rows of the table.

For example:

This query retrieves the total salary for each department and groups the rows by department. The clause then filters the groups to include only LegalZoom departments where the total salary is greater than $1 million

Note that the clause must be used after the clause and can only reference columns listed in the clause or aggregated columns selected by the statement.

LegalZoom SQL Interview Questions

SQL Question 4: Calculate the Average Duration for Document Preparation

As a Data Analyst at LegalZoom, you are tasked with analyzing the turn-around time for document preparation. The company is interested in understanding the average duration it takes to prepare different types of legal documents. Can you write a SQL query to find the average duration (in days) for each type of document prepared by the company?

Example Input:
102Living Trust2022-08-022022-08-09
103Power of Attorney2022-08-032022-08-11


This query calculates the average number of days it takes to prepare each type of document. It first calculates the duration for each document by subtracting the submission date from the finalization date. Then it calculates the average of these durations for each . The function is used to get the number of days from the date interval. Finally, it groups the result by to get the average duration for each type.

To practice a very similar question try this interactive Amazon Average Review Ratings Question which is similar for calculating averages or this Alibaba Compressed Mean Question which is similar for rounding off to a decimal place.

SQL Question 5: What is a database index, and what are the different types of indexes?

A database index is a way to optimize the performance of a database by reducing the amount of data that needs to be searched to retrieve a record.

There are several types of indexes:

  • unique & non-inuqie indexes
  • primary & composite indexes
  • clustered & non-clustered indexes

SQL Question 6: Find the average revenue from each type of Legal Service every month.

LegalZoom offers different types of legal services like 'Will Preparation', 'LLC Formation', 'Trademark Registration', etc. The company wants to identify the average revenue from each type of service every month.

Assume we have a table named 'services' to record each service sold and a table named 'service_type' to categorize each service.

Example Input:
Example Input:
2001'Will Preparation'
2002'LLC Formation'
2003'Trademark Registration'
Example Output:
6'Will Preparation'300.00
6'LLC Formation'155.00
7'Will Preparation'350.00
7'LLC Formation'170.00


This SQL query will join the 'services' table with the 'service_type' table based on 'service_type_id'. It will extract the month from the 'purchase_date' in the 'services' table and group by this month along with 'service_name' from the 'service_type' table. The average revenue is calculated for each type of service every month with the AVG() function.

SQL Question 7: What distinguishes a left join from a right join?

Both left and right joins in SQL allow you to combine data from different tables based on a shared key or set of keys. For a concrete example of the difference between these two join types, say you had sales data exported from LegalZoom's Salesforce CRM stored in a PostgreSQL database, and had access to two tables: and .

: retrieves all rows from the left table (in this case, the sales table) and any matching rows from the right table (the table). If there is no match in the right table, NULL values will be returned for the right table's columns.

  • : retrieves all rows from the right table (in this case, the customers table) and any matching rows from the left table (the sales table). If there is no match in the left table, NULL values will be returned for the left table's columns.

SQL Question 8: Revenue Trend Analysis for LegalZoom Services

LegalZoom provides various legal services and they want to analyze their revenue trends on a monthly basis. Calculate the monthly revenue, along with the month-over-month revenue growth percentage (to two decimal places) for their top selling service 'Estate Planning'.

Example Input:

Example Input:


This query will return a table showing each month, the revenue for 'Estate Planning' service during that month, and the month-over-month growth percentage to the two decimal places. This allows LegalZoom to evaluate the month over month sales trend for its 'Estate Planning' service.

The two most similar questions are "Y-on-Y Growth Rate" and "Highest-Grossing Items".

"Y-on-Y Growth Rate" is similar because it involves calculating a growth rate using SQL, much like the requested month-over-month growth for the 'Estate Planning' service.

"Highest-Grossing Items" is similar because it involves identifying the top items in terms of revenue, which is a related concept to analyzing trends in the revenue of the top-selling service.

Here is the requested markdown output:

To practice a very similar question try this interactive Wayfair Y-on-Y Growth Rate Question which is similar for calculating a growth rate using SQL, or this Amazon Highest-Grossing Items Question which is similar for identifying top items in terms of revenue.

Preparing For The LegalZoom SQL Interview

The key to acing a LegalZoom SQL interview is to practice, practice, and then practice some more! Beyond just solving the above LegalZoom SQL interview questions, you should also solve the 200+ tricky sql questions on DataLemur which come from companies like FAANG tech companies and tech startups. DataLemur SQL and Data Science Interview Questions

Each exercise has hints to guide you, fully explained answers along with a discussion board to see how others solved it and best of all, there's an online SQL code editor so you can right in the browser run your SQL query answer and have it checked.

To prep for the LegalZoom SQL interview you can also be helpful to practice SQL questions from other tech companies like:

But if your SQL skills are weak, forget about jumping right into solving questions – go learn SQL with this SQL interview tutorial.

Interactive SQL tutorial

This tutorial covers SQL topics like creating pairs via SELF-JOINs and grouping by multiple columns – both of these come up routinely during LegalZoom SQL assessments.

LegalZoom Data Science Interview Tips

What Do LegalZoom Data Science Interviews Cover?

Besides SQL interview questions, the other question categories tested in the LegalZoom Data Science Interview are:

  • Probability & Stats Questions
  • Coding Questions in Python or R
  • Business Sense and Product-Sense Questions
  • Machine Learning Questions
  • Behavioral & Resume-Based Questions

LegalZoom Data Scientist

How To Prepare for LegalZoom Data Science Interviews?

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  • 201 interview questions sourced from FAANG, tech startups, and Wall Street
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