A product analyst is a hybrid role between a data analyst and a business analyst. Product analysts work with people from other departments to bring new products to market. They do this by using data to help them make decisions.
Product analyst interviews assess the unique skill set needed to pull this balancing act off. There will be a lot of questions about data analytics, like writing SQL and statistics, as well as questions about business and products. These interviews are designed to test your ability to use data in making sound product decisions.
It looks like you’re getting ready for your product management analyst interview. If so, buckle up, because this complete guide is about to give you the information and tips you need to ace it. We’ll look at 35 in-depth interview questions that cover a wide range of topics, from data analytics and behavioral questions to product case studies and SQL queries. Get ready to show off your skills in the interview and get your dream job!
Product Case Studies: Putting Your Product Mindset to the Test
Product case studies are a chance to show that you can look at data, find insights, and make good decisions about products. Here are some common questions you might encounter:
- How would you determine why the number of comments per user is decreasing at a social media company?
- What’s the first change you would make or new feature that you would add to product X?
- How can you use the Facebook app to promote Instagram?
- You have ten experiment ideas for improving conversion rates on an ecommerce website. How do you choose which ideas to test?
- Which variables might Uber use to estimate pick-up ETA, besides the ETA from the GPS system?
SQL Queries Unleashing Your Data Analysis Prowess
SQL queries are essential for extracting valuable insights from data. Be prepared to answer questions like:
- What is the difference between the WHERE and HAVING clause?
- What are the different types of joins? Explain them.
- How would you isolate the date from a timestamp in SQL?
- Write a SQL query to get the last transaction for each day.
- How will you write a query to get the post success rate?
Data Analytics Unraveling the Mysteries of Data
Data analytics questions test your ability to analyze data and draw meaningful conclusions. Get ready for questions like:
- We have a hypothesis that the Clickthrough Rate (CTR) is dependent on the search result rating. Write a query to return data to support or disprove this hypothesis.
- Given three tables representing customer transactions and customer attributes, write a query to get the average customer order value by gender.
- Given a table with customer purchase data, write a query to output a table that includes every product name a user has ever purchased.
A/B Testing and Experimentation Mastering the Art of Optimization
A/B testing is crucial for optimizing product features and user experience Be prepared to answer questions like
- What is the difference between a t-test and a z-test?
- How do you structure a hypothesis for an A/B test?
- What types of questions should you ask before designing an A/B test?
- You are A/B testing a feature to increase conversion rates. The results show a .04 p-value. How would you assess the validity of the result?
- How would you measure the impact that financial incentives have on user response rates?
Python Interview Questions: Demonstrating Your Coding Prowess
Some product management analyst roles may require basic Python skills, Be ready for questions like
- What is a split in Python? Why is it used?
- Write a Python function to sort a numerical dataset.
- Write a function that can take a string and return a list of bigrams.
- Write a function to generate N samples from a normal distribution and plot the histogram.
Statistics and Probability Questions: Understanding the Numbers Game
Statistics and probability questions assess your ability to analyze large datasets and make informed decisions. Be prepared for questions like:
- How would you explain p-value to a non-technical person?
- Determine the cause of drop in capital approval rates.
- Given two fair dice, what is the probability of getting scores that sum to 4? to 8?
Product Management Analyst Behavioral Interview Questions: Revealing Your Soft Skills
Behavioral interview questions delve into your personality, work ethic, and problem-solving abilities. Be ready for questions like:
- What are your favorite data visualization techniques?
- What are some of your favorite products and why?
- The product manager provides you with unclear directions for a project. What do you do?
- How do you stay updated on market trends?
- How would you assess the quality of a dataset?
- What would your first 90 days on the job look like?
Bonus Resources: Fueling Your Interview Preparation
- Join Interview Query to access exclusive interview resources and practice questions.
- Read articles on product management, data analysis, and interview tips.
- Connect with product management professionals on LinkedIn and seek their advice.
Remember that being ready, sure of yourself, and excited about the job are the most important things you can do to do well in your product management analyst interview. It will not take long for you to get your dream job if you follow this guide.
How would you isolate the date from a timestamp in SQL?
Date and time values can be used with EXTRACT to get temporal data types like date, time, timestamp, and interval.
If you wanted to find the year from 2022-03-22, you would write EXTRACT ( FROM ):
More context. You are given a table of bank transactions with columns for id, transaction_value, and created_at (which is the date and time of each transaction). You need to write a query to get the last transaction for each day. The output should include the id of the transaction, datetime of the transaction, and the transaction amount. Order the transactions by datetime.
Since the created_at column is in DATETIME format, we can have more than one entry that was made on the same date but at different times. For example, transaction 1 could happen on ‘2020-01-01 02:21:47’, and transaction 2 could happen on ‘2020-01-01 14:24:37’.
To make partitions, we should remove information about the time that the transaction was created. But, we would still need that information to sort the transactions.
Is there a way you could do both these tasks at once?
Let’s say you wanted to make a histogram that showed how many comments each user got in January 2020. Assume the bin buckets have intervals of one.
If we use a histogram with one-size bin buckets, we don’t have to deal with the extra work of putting frequencies into specific intervals.
As an example, to get a five-size histogram, we would need to run the following SELECT statement:
More context. A table contains information about the phases of writing a new social media post. For example, if a user starts to write a post and then fails (post_submit), or if they decide to cancel their post (post_cancel), the action column can have the value “post_enter.”
Write a query to get the post success rate for each day in the month of January 2020. You can assume that a single user may only make one post per day.
Before we start the problem, let’s make sure we have a clear idea of the metrics we want to calculate. We want the post success rate for each day over the past week. To get that metric let’s assume post success rate can be defined as:
(total posts submitted) / (total posts entered)
Since the success rate needs to be broken down by day, we also need to make sure that each post is finished on the same day it is begun. What comes next?.
Think about possible insights. What do you think the distribution of the number of conversations each user starts each day looks like? Write a query to get the distribution of the number of conversations each user starts each day in 2020. This visualization can also help you hone the insights to be gleaned.
See a step-by-step solution to this problem on YouTube:
Analytics questions are a subset of SQL questions, and often require SQL code writing. These questions assess your ability to pull actionable insights from data. In these questions, you might be asked to pull metrics or perform a multi-step data analytics case study.
This is a classic data analytics case study type question, in that you are being asked to:
- Create a metric to analyze a problem.
- Pull the metric you created with SQL.
With this question, start by thinking about how we could prove or disprove the hypothesis. Let’s say that the hypothesis is true if CTR is high when search ratings are high and low when search ratings are low. So, to solve this issue, look at search results that are split up into different rating groups.
Quick solution. For this question, let’s say that the question asks for the average order value of all users who have placed at least one order. Therefore, we can apply an INNER JOIN between users and transactions.
More context. The products table includes id, name and category_id information for customers. Also, your output should have a boolean column that says “1” if the customer has bought that type of product before and “0” otherwise.
The table should also have a boolean column that has a value of 1 if the user has bought that type of product before and 0 if this is their first time buying something from that type of product.
Your output should look like this:
| product_name | category_previously_purchased |
|---|---|
| toy car | 0 |
| toy plane | 1 |
| basketball | 0 |
| football | 1 |
| baseball | 1 |
2 Write a Python function to sort a numerical dataset.
Output:
At its core, bi-grams are two words that are placed next to each other. Two words versus one word feature in engineering for a NLP model that gives an interaction effect. To actually parse them out of a string, we need to first split the input string. We would use the python function . split() to create a list with each individual word as an input. Create another empty list that will eventually be filled with tuples.
Then, once we have identified each individual word, we need to loop through the list k-1 times (if
k is the number of words in a sentence) and add the current word to the next word to make a tuple. This tuple gets added to a list that we eventually return.
The problem is pretty easy: we just need to set up our distribution and take n samples from it. These samples are then plotted. In this question, we make use of the scipy library which is a library made for scientific computing.
First, we will declare a standard normal distribution. For those who may have forgotten, a standard normal distribution is the normal distribution where the mean is 0 and the standard deviation is 1. To declare a normal distribution, we use the scipy stats. norm(mean, variance) function and specify the parameters as mentioned above.
The Top 10 Product Manager Interview Questions (And How To Answer Them)
FAQ
How do I prepare for a product analyst interview?
What does a product management analyst do?
Why do you think you are fit for the role of a product analyst?
How do you interview a product analyst?
Common Product Analyst interview questions, how to answer them, and sample answers from a certified career coach. As a product analyst, you need to have the right mix of technical and business skills. You must be able to analyze data, come up with solutions, and communicate those solutions clearly to stakeholders.
What questions should a product analyst ask a manager?
An interview may ask you questions about your experience and background as a product analyst. This can give them a sense of your qualifications for the position. Here are some questions a manager might ask to assess your experience: What is your educational background? What makes you qualified for this position?
What makes a good product analyst?
Landing a role as a product analyst entails showcasing a profound understanding of data analysis coupled with a strategic mindset. This comprehensive list of interview questions and their well-crafted answers are designed to help you prepare and present yourself as a proficient candidate in your next interview.
How do you answer a product management interview question?
This question is another opportunity to discuss product management from a big-picture perspective. Especially at smaller start-ups, you’ll work closely with the people conducting the interview. Be personable and share what motivates you every day. Highlight your strengths.
