During the last 10 years I had the privilege of interviewing hundreds of people for multiple roles and experience levels, and for several different companies.
In this series, I will share what I am looking for when interviewing product managers, and why I am looking for them.
Thank You Allen
Before we start - a big thanks to Allen Blue who, very early in my career, spend the time explaining to me how he interviews. His thoughts and perspectives are key pillars in how I approach interviewing. Allen’s perspective is that using 45 minutes to fully understand someone’s capabilities is impossible. Instead, we should use that time to pattern match a candidate to the best product thinker / strategist / analytics / executioner we know based on how the candidate thinks and talks about the craft.
To interview effectively, I created a template to help me build what an amazing answer looks like, and during the conversation I begin with a prompt and evaluate how one structures her thinking rather than how she gets to the “right” answer.
Just before we dive into an example, I read multiple perspectives that state there is no right and wrong answer in an interview - I believe there isn’t a single right answer but there are multiple wrong ones. A wrong answer is one that isn’t logically built, one that side steps key issues or skips steps and misses out on key insights.
Let’s Dive In
Let’s assume the interview is for a product role at Lyft. A product sense prompt may look like this: “You’re a PM at Lyft, working on the consumer app. Your manager suggests that you should consider adding Lyft for kids feature, allowing underage kids to safely take a Lyft. Should you do it? If so, how?”
Why do I like this question?
It’s open ended and ambiguous, just like real life problems
It requires the candidate to ask clarifying questions
It allows the conversation to go in many directions and thus it’s not boring to ask over and over again to different candidates
It requires the following skills to fully answer well: strategic thinking, measurement, TAM estimation, marketplace dynamics understanding, pricing
It’s relevant to the business and thus gives the interviewer an edge
How do I think about the answer?
As with real life product problems, in an interview I expect the candidate to provide a logical and coherent framing of the problem, to evaluate the business opportunity and eventually to solve the issue presented. Here is the list of topics that I expect to discuss during an interview. Note that the order matters as one cannot move forward without answering the previous questions.
Who are our users? “Everyone” is not a good answer. 18-30 years old is not good. Generic descriptors signal lazy thinking. Be smart about how you frame the answer so that we start well with a clear audience definition. In this case, a potential answer could be: parents to teenagers in urban environments that highly value their time and are willing to pay a premium for it.
How many of them exist? Either as % of company MAU or overall in a region. We want to solve meaningful problems for large audiences when we design products and features. Make some logical assumptions and get to a number.
What are their problems with the offerings that exist today? Where is the gap? How acute is the gap? We want to solve meaningful problems for many people, but sometimes we will work on small problems for a large number of users or very acute problems for a small number of users. Which type of problems are we facing here?
Are they willing to invest time / effort / money to solve it? Which type of ask do we think we need to work with?
Now we stop and evaluate if we should continue: We continue if this is a meaningful business opportunity. A large audience with an acute problem that is willing to pay us to solve it is the holy grail. A great candidate summarizes the findings from the questions above and sets herself up for success moving forward. I am not in the business of asking trick questions, so the answer here is yes, it’s meaningful. Now let’s continue.
What is our goal? That should be a qualitative description of what we want to achieve. In this case something like: “We want to provide a safe, efficient, reasonably priced, and scalable solution that will allow parents to send their kids on a Lyft with little to no worry that something bad might happen to them.”
What are some success metrics? What are some counter metrics to watch out for? This is not to be confused with the goal. Numbers are important as they allow us to see if we are getting close to the goal and where we still need to put some more work. The easier framework I have here is the simple: “We want more people getting more value and exchanging it for more money every month / year.” There are also proxy numbers that are leading indicators to that statement. New users as % of MAU, repeat customers, spend per week, rides per week, referrals, cancelations, star ratings, etc.
Another stop to summarize. We now agreed with the interviewer that there are meaningful problems to solve for a meaningful number of people. We called out our goal and have success metrics. This has been laborious but made the final part, hopefully, easier:
What is the proposed solution? After setting everything up so nicely, it should be a direct conversation with little gotchas. The proposed solution should tackle the biggest problems we discussed previously for that audience we defined. It should logically flow from the goal why the solution is good and it should also fit nicely with the metrics evaluation framework we set up previously. Overall this section is, in my mind, the least interesting part of the conversation. I am not looking for super creative and innovative solutions during an interview. I’m looking for a framework that allows me to understand if a candidate can unbundle any problem.
Summary
We talked about what I am looking for in a product sense interview, why certain types of questions are good, how to work through a solid and logical answer, and provided some high level examples of good answers.
If you are planning on interviewing, I suggest you practice this framework on random features in products you like. From Snap to Uber Eats, we are lucky to see tons of features in the wild.
Please ask questions in the comments below and share with others who may benefit from this post.
Good Luck!