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Hadar's Product Interviewing Toolkit

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Hadar's Product Interviewing Toolkit

Execution

What is the goal? What are the trade-offs? Qualitative first, then quantitative.

What they're looking for

How you identify and prioritize opportunities

How you analyze a set of constraints and problems to come up with goals / success metrics

How you adapt your plans and troubleshoot problems with new information and changing circumstances

There are a couple ways you might be asked an execution question. Make sure your answers more or less cover the following:

"Goal-setting" questions (eg: "How would you set goals for {product} at {company}?)

Mission of company

What is the company as a whole's mission?

Why is this area you're evaluating relevant to that mission (user and business perspective)

Goal of product area in question from user perspective

Qualitatively, how does the area you're setting goals for help enforce the company's overall mission? What user value does it provide?

Metrics that quantify us meeting that goal (if didn’t exist then what)

If it weren't true that this product existed yet, and all of a sudden it did, what would be different about the company's topline metrics?

Would the users in question retain or engage more? Would new users join? Would we be able to make more money?

Keep this to high-level "North Star" metrics for now

Pick one as your main metric to move forward with

Note proxy metrics (short-term)

This "North Star" metric probably takes a while to detect statistically significant changes to

What

proxy metrics⁠

would correlate well with the North Star metric, for which changes be detected more quickly?

Trade-offs of that metric vs other metrics (avoid gaming)

Why might the North Star metric you picked be a bad one? Or proxy metrics? Layer trade-offs and critical thought throughout

"Trade-off" questions (eg: "How would you decide between doing X or Y?")

What is the trade-off (plug in infinite to both sides)

If you're weighing between two things, imagine you only did one of the forever and went all in on it. What positive things would happen short term, but what might not go well long-term?

Find the common thread between them both

eg: Facebook: ad versus organic engagement module both long-term optimize for money

eg: Lyft: Getting one more Driver hour versus getting a Rider to book one more ride both long-term optimize for most aggregate rides

Objective function (goal to meet through experimentation)

The right point in the trade-off is what will maximize the common long-term goal that both sides you're considering have

You can run experiments with different levels of both sides and whichever mix is best for your long-term goal is the right mix!

Further optimize (network effect, personalization, etc.)

The above is a starting point. You can always better optimize over time by having different mixes for different circumstances

eg: Facebook: for highly-engaged users who aren't ad-sensitive, can show more ads

eg: Lyft: in a region where there are too many Drivers, might have less need for one incremental hour from a Driver

"Root cause analysis" questions (eg: "XY metric is down. What happened?")

The goal here is to systematically explore all reasonable explanations that could have contributed to the metric changing

You basically want to make

one of these⁠

that cover areas like specific technical attributes, specific funnel step, region, time frame, product/feature change, and demographic

There's no right answer. There's no root cause that you have to get to pass. The goal is breadth so don't worry at all if you never find the "correct answer"

In fact, when I ask candidates this question, if they ever guess the "correct" root cause I had in mind, I just change it to keep them going 😈

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👉 Next up:
`Behavioral / Leadership`⁠
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