Measuring the success of products is critical to data science and analytics interviews. Generally, this question is an encapsulation of every time a product manager or executive asks the question: “So, how is it doing?”.

As infuriating as that question can be, the answer should usually be something quick and easy to understand at a high level (KISS - keep it simple stupid). But as a data scientist, the interviewer is always interested in understanding how you tackle a full-fledged analysis.

Examples of questions like this are usually in the form of asking about a particular feature within a product, such as:

• How do you measure success for Facebook Events?
• How would you measure success for Yelp reviews?
• How would we measure the success of acquiring new users on Netflix through a free trial?
• How would you measure the success of private stories on Instagram, where only certain chosen friends can see the story?
• What metrics would you track for analyzing the health of Google Docs?

So what is the interviewer looking for when asking these questions?

Understanding the scope

Can you ask clarifying questions to understand more about what you’re dealing with?

For example: What does the product do and who is the target audience? What is the goal of the feature or product that we’re working on? Why is it important to the business?

Structure of Answer

Are you randomly shooting out ideas and rambling, or are you structuring points with examples and metrics? Are you being specific about how you would implement strategies, or generalizing these ideas without metrics?

Business Intuition

Lastly, make sure that you understand how to answer the problem intelligently by using metrics to support your answers. Are you creating hypotheses that make sense and could be backed up by these metrics?