Sessions are down 20% today - why?
(Want to skip ahead to a sample question? Start here
- currently working on Product, Data and Growth at Coda, previously startup Founder/CEO, and before that a PM at Google and YouTube. I’ve been both the interviewer and interviewee for product analytics questions countless times. This is the first time I’ve shared my playbook.
You’re interviewing for your dream job as a
at Unicorn, Inc. You’ve researched the company, used the product, and even have your list of ideas ready for how to improve it. But you didn’t see these data questions coming and don’t know where to begin. Why didn’t you click on that link “How to Ace Your PM Data Interviews” you saw scrolling through your feed the other day? Just kidding! Let’s dive in. 👊
How to read this
My hope is that after reading this post you have a cheat sheet for how to answer common
analytics interview questions and you have some easy next steps to get even better prepared.
This page focuses on high level context and strategy. We’ll walk through kinds of questions you’ll be asked, each of which have deep dives on their own pages. We’ll break down what interviewers are looking for and in the following pages we’ll dig into detailed sample questions, with example strong and weak answers at each step.
The meat of this is post in the detailed walkthroughs:
. There’s also an extensive bank of
While we’ll focus on
interview questions, in practice these same kinds of questions often show up for Software Engineers, Marketers, Data Analysts, and other roles.
What interviewers are looking for
Keep in mind interviews are more about understanding how you think than getting a “right answer.”
Candidates often make the mistake of getting caught up trying to get to a “right solution” and skip explaining their reasoning. Reasoning is
the main thing
an interviewer is trying to assess. So it’s much better to have amazing reasoning but not fully get to a final answer than an answer that’s hard to contextualize or reason about.
Back when I was at Google, most interviews were scored on a 5 point system (1 being poor and 5 being strong). Here at Coda, we use a 4 point system - which is much clearer: you cannot do OK. As an interviewer, if I’m on the fence, that rounds down to a no.
Three types of data interview questions
There are three main types of data interview questions. We’ll break each down in detail in the following pages.
Dig into a change in metrics to uncover why it changed.
Decide what metric a product should optimize for and why.
Identify, compare or use growth levers for a feature or product.
Note these types of questions go by many different names at different companies. For example, Facebook has a mix of these under an Execution Interview header, Thumbtack calls these Analytical Interviews, and here at Coda we have a Marketecture Interview. The reality is these questions types aren’t as discrete as I outline here, but exist on a spectrum. That said, I’ve found these three types useful as “corners of the tent” to show a range of problem solving formats, with the more common case somewhere in the middle.
Three simple steps to frame your answers
Here’s my simple framework to use on all of these questions:
Reiterate and clarify goals, constraints, and important factors to the problem or solutions.
Brainstorm solutions to the prompt, get more constraints from the interviewer if appropriate, and discuss pros and cons.
Select your solution. Describe mitigators, things that would change your answer, and followups.
pointed out this is similar to
. Here’s what this looks like applied to each kind of question:
It’s worth calling out that having a good framework for your answer is necessary but not enough by itself. There’s a common type of poor interviewee who is overly focused on a high level framework, and fails to engage in the gritty detailed discussion and trade-offs of concrete options and ideas. Don’t be “just a framework person” - make sure you continue to connect it back to the details.
If it sounds too simple and easy, you’re half right. It is simple, but it’s not easy. Like most things, it comes down to how you do it. The best way to do it well is to practice. 👇
Practice makes perfect
Interviewing is a skill that, like all skills, you get better at the more you do it. One of the best ways to practice is to go through sample questions with friends or colleagues and have them give you feedback. Getting more examples under your belt always helps. In that spirit, we’ll walk through example questions together and analyze a range of different sample answers. Or you can skip ahead to the
. Read on to the next pages for more detailed tear-downs per question type: