The ultimate guide to product analytics interviews. Strategies developed by FAANG engineers to craft structured, impactful answers and increase your chances of landing a data science job.

Product analytics interviews evaluate your skills and creativity as an aspiring data analyst. Interview questions evaluate if you can use your technical knowledge to guide the further development of a product. Learning how to answer these questions is crucial to ace most job interviews for data scientists and analysts.

In this course, you’ll first gain an overview of what product analytics interviews look like and what kinds of questions usually come up. Next, you’ll learn to use a framework for answering product analytics questions, showcasing your analytical skills. Finally, you’ll learn how to apply said framework to different kinds of product analytics interview questions by looking at several examples.

With this course, you’ll increase your chances of landing a job in data science by learning how to effectively answer product analytics interview questions. You’ll be able to provide well-structured and well-communicated answers, and show you can creatively tackle any business problem you may face.

Ace the Product Analytics Job Interview

# Feature change problem

Before launching a feature, the first step we’d have to take is analyzing the existing data in our product to make a decision about exactly what to build. This process is what creates the building or change of a feature problem that gets asked in product interviews. Answering feature change questions can be tough in the moment, but in this section, we’ll go over the basic steps we have to take in order to give a comprehensive, thoughtful answer.

Questions about feature changes or additions can look like the following: 

* [How would you analyze the effect of adding a green dot on LinkedIn messaging?](https://www.interviewquery.com/questions/green-dot)
* [How would you analyze the effects of the close friends’ stories on Instagram?](https://www.interviewquery.com/questions/close-friends-story)
* How would you decide whether or not to launch a new personalized recommendation widget on the Amazon home screen?
* How would you analyze the effectiveness of allowing users to trade fractional shares on Robinhood?

For this type of problem, let’s look the following scenario.

Let’s say that you work for Uber. A product manager wants to add a feature to the app that would increase wait times for a lower price. Is this a good idea? We’ll use this scenario to explore the challenges that can emerge with feature changes and measuring success problems in the next chapter. 


Learn how we can answer feature change questions asked in the interview. 

Introduction to Feature Change Questions

Learn how we can answer feature change questions asked in the interview.

Introduction

Investigating Metrics

Fractional Metrics

Measuring Success

Feature Change

Metric Trade-Offs

Growth

Conclusion

Introduction to Feature Change Questions

Feature change problem