Product Manager Interviews: Success Metrics (Execution & Analytical)
By Dianna Yau
Summary
Topics Covered
- North Star Aligns User Values
- Break Down North Star Levers
- Supply Exceeds Demand Macro-Micro
- Word-of-Mouth Fuels Guest Growth
- Avoid Revenue as North Star
Full Transcript
hey there i'm diana and i'm a product manager at a big tech company in silicon valley california and i bring you the best tips to help you get into product management
and show you how you can be successful once you've made it if you're preparing for a product management interview coming up you're probably going to get questions
like this what goals would you set for x product how would you define success for x product how would you
measure whether x product is successful or not in this episode we're going to share a framework to help you think clearly and logically about this question
so that you can stand out in the interview first let's go over what the goals are of why companies even ask this type of question the company
wants to check that you understand the product the value of the product to the multi-sided users the second thing they want to check that you can
prioritize the most impactful metrics for the business and for the users a non-goal is to come up with something like
driving monthly active users by five percent we're not looking for an exact number but we do want to understand how you would come up with an exact number in another episode
of this product management interview series we mentioned the goal of these interviews is to show interviewers and the company that you know how to think
like a product manager so if how you're answering these questions is memorizing a set of metrics that's not going to show the interviewer that you can think
so today i'm going to show you how you can show the interviewer that you're a great product thinker let's first run through a structure of how to tackle these questions the first part
of this structure is product users and value so what is this product we're talking about who are the users and what value are they deriving from using this product
the second part of the structure is the north star metric the north star metric should be something at the intersection of the value that these
users are getting from the product the third you want to break down the north star metric into a formula so you can understand what levers need
to be driven to increase this north star metric and the fourth you want to talk about trade-offs and counter-metrics so
trade-offs are to show that you know what metric to prioritize and counter metrics are to show you understand it's not enough to just drive up the metric
but you want to ensure quality and that your metric isn't being gained let me now show you an example of how this framework can be used
to answer a set a goal for product x type of question and you'll see that this is probably simpler than some of the frameworks
you've memorized with metrics so let's dive in so the example question we're going to go through today is what metric goal would you set for
airbnb i just chose airbnb at random so no i don't work there let's talk about the first part of our structure the product users and value so what is airbnb airbnb is a
marketplace that connects guests who are looking for places to stay with hosts who are renting out their places
what's special about airbnb is hosts rent out their extra apartment or ran out their extra room which is different from the hotel model
and the founders created airbnb to give people traveling a more local homey and affordable experience than hotels let's talk about the three different users here
the first is the guest a guest is successful when they make a booking because it indicates they've found something on the site that they've liked a host is successful when they get their
place booked because they earn money from that and airbnb the company is also successful when a place gets booked because they earn a commission from each
booking so let's move on to the second part of the framework the northstar metric i mentioned you can think about the northstar metric as the intersection of value for all three users in this
case the intersection you'll see is bookings when a booking is made all three parties are happy hopefully so in this case we can think
about the northstar metric as the number of nights booked and why number of nights booked versus bookings because the more nights booked the more
a host earns and the more a host earns the more airbnb makes and also for the guests if they decide to stay short-term or long-term
they're also happy because they're able to find a place to stay if any parts of this is confusing or you have a follow-up question make sure to comment below and i'm happy to follow up after
now let's go into the third section of this framework and break down the north star metric the number of nights booked we just talked about so that metric is made up of the total
number of active guests times the number of nights booked per guest let's further break down the right hand side
into the number of active listings and views of those listings confirmed bookings minus the number of canceled bookings
if we were to further break down the number of active listings that would give us the number of active hosts and the listings per host
and now let's further break down the number of active hosts which is the number of new hosts plus existing on the platform
plus resurrected minus churn so you can see we broke down the formula of the north star metric to help us understand what drives this north star
metric if we want to tactfully improve this metric it also shows us the levers in creating a healthy
ecosystem so in this case one part of keeping a healthy ecosystem is having a macro and micro
supply that is greater than demand by let's say x to y ratio keeping a healthy supply higher than demand is
key to keep customers in this case guests engaged because if guests don't feel like they have enough supply on airbnb they'll easily go to bookings.com
to book a hotel so we want to make sure every time they're on it on airbnb they at least feel like there's plenty of supply
supply needs to be managed in a macro and micro sense meaning total number of supply should outweigh demand but even for
specific places and locations we have to keep a healthy ratio of supply to demand so for example i know every time i go to big sur in california
there's always such a low amount of supply that the prices end up being very high with places charging 500 a night in the middle of
nowhere so in those cases airbnb loses me as a customer because i'm going to bookings.com to find a hotel instead at the same time
the quality of supply is important just because there's a million listings doesn't mean they're all good and especially on airbnb because it's
people's homes and not professional establishments it might be hard for them to take a high quality photo compared to the hotel photos
pens in order to get engagement and views of the listings it'll require that the listing to look nice
and that's why the founders early on in order to jumpstart this ecosystem they actually flew to new york and volunteered to help host take picture nice pictures of their
listings and you'll see even on the platform today they offer a professional photography service and the third part of keeping this
healthy ecosystem is growing demand demand as in guests you want to ensure the number of your guests are increasing
organically coming from word of mouth word of mouth happens when existing users have a good experience for example on airbnb when i'm traveling
i'm usually going on a trip with friends or family and hence if we have a good experience that means the friends and families who go with me
in the future will look to airbnb to book their next vacation hence we need to double down on creating good hosts and educating them on best practices
hence the existing guests serve as advocates and ends up creating a multiplier effect for future
guests which means airbnb has to do really good at upfront getting posts to provide a good experience
but also when guests don't have a great experience they need to provide the service customer service to help them so they
trust airbnb otherwise again these guests can easily go to bookings.com and default to what was the status quo
before airbnb so our fourth part of the structure is talking about trade-offs and counter metrics under trade-offs
one example is the trade-off between optimizing for hosts who have single listings or a few listings
versus more commercial posts who are either listing for other people who are property managers or landlords that are listing multiple
places so when we think about increasing supply do we want to partner with more established organizations of landlords and property managers even
hotel chains and you actually do see that on the platform today airbnb partners with hotels or encourages hotels
to now show supply of hotel rooms on airbnb and the second part of the fourth part of this structure is counter metrics we can most definitely increase lots of
supply of hosts but we want a supply of hosts who provide good experiences
so that other people would be just as satisfied with the booking in this case i would check the number of
listings that have less than four star reviews gives me an indication of high quality versus medium low quality on the platform and i want to make sure
i maintain a healthy ratio of high quality listings b i'd also track the number of listings reported
that can give me an indication of listings that should be taken down that go against our policies again showing maybe low quality supply
that we wouldn't want on the platform even if it helped us grow our numbers so i hope that example helped clarify how to use that structure i would
recommend you practice a couple of questions and see if this framework helps you think clearer faster and more logically and why this framework works is because
it's simple this is versus other metrics frameworks which asks you to list down a bunch of metrics that are usually used for internet companies
and sure those aren't wrong and it's not terrible but it's not going to distinguish you from all the other interviewees who memorize the same framework the last thing i want to call out from
my experience are sub-optimal answers again they're not wrong answers but i hear them all the time to the point where they're almost generic the first one is when
someone i'm interviewing says the north star metric is revenue again not wrong but not optimal if a company continues to prioritize revenue
and not the user goals eventually it's going to run out of users and engagement to be able to make any revenue the second thing i hear all the time is we want more growth
grow more users is the northstar metric always also not the answer imagine you have a product where there's a hundred million users but none of
those hundred million users are taking the action that you need them to take in order for your company to monetize that's not ideal either and the third thing i hear we talked
about how people tend to memorize a framework the usual framework that i hear is the pirate metrics
are that's awareness acquisition retention revenue and referral so again it's not a wrong answer it's just the answer
everyone uses so by the time i hear it for the 500th time it doesn't help me understand how you think it just
tells me that you know how to memorize so to summarize the four things you want to cover in a question like what goals would you set for this metric
is number one the product the user and the value the second one coming up with the north star metric which is the intersection
of the values for the users the third is breaking down your north star metric to understand the formula or the levers to contribute to this metric and number four it's
thinking through trade-offs and counter metrics so you avoid gaming your north star metric so if this was helpful let me know in the comments below what follow-up
questions you might have and make sure to like the video to show your support thanks guys hey guys here are two more videos to help you stand out during the
product manager interview you
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