10 Metrics Every SaaS PM Should Use by fmr Facebook Product Leader

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In today's episode, we're talking data with former Facebook product leader, a non a review

car escape.

He'll be going over how to work towards your metrics and how to decide which ones you shouldn't

bother with in which ones really are necessary.

Keep listening to learn more about using data to drive value and be successful.

Hello, good day all.

Welcome to the product school session today.

I'm Ann and I'm Karasu.

I'm heading product at the Refersion.

It's a fast growing rocket ship focused on influence and athlete marketing.

And I wanted to talk about the metrics that every SaaS PM should use and care for for

the today's session.

I hope that you find a lot of value in my session today and get both stuff out of it.

Let's go into the session.

Quick introduction about myself.

I've been in the tech space for last 15 years, started as a software engineer.

Kind of like, what's curious about why and how things are going to be built, then I ended

up working as a product manager, started as a product manager 10 years ago and started

in the valley and was lucky enough to both the startups that I worked was acquired and

an example, the company that I worked longer was later acquired for 800 million dollars.

And then I was in product roles with them and most of that were martek and ed tech.

And then I went on to work with Facebook as a product growth leader there and I had the

opportunity to be part of a few successful launches there.

One was messenger business to people platform, key part of that product.

And then I went to also work for commerce areas, leader part of it, including Instagram.

And then I actually ended up taking on coming back to startups and building companies from

scratch.

And that was what my journey is today, is to help for early stage startups to late stage.

And being so far going to it, I started with the company called Grand After Instagram and

Facebook and it was good, the companies in a really good place today.

And now I'm building a company called Refersion for the past six, seven months building

both the product and design teams here, we are a rocket ship growing really fast.

On the side, I've also advised and mentor a lot of people both helping them understand

product management, also be cracking interviews or like also supporting a lot of accelerators

on the side, especially early stage startups, you understand and build their product journey.

And some of them are now late stages, wow.

So that's a little bit about myself and being experiencing SaaS for a while, being at even

a drive and when they were providing some SaaS solutions out there, leader at some of

the companies like Ben site, which is all business service providers.

So being part of the SaaS journey for a while, I've seen a march shift in how SaaS

companies has been doing, people call it consumerization of SaaS or the moment, the

Slack moment that happened where SaaS companies have now become, there is, it's no more

boring, it's like really intuitive and helping users achieve their final goal, there's

a big mark shift in how SaaS companies are being built.

And you know, being there and helping companies build it, love to talk about that and help

you guys focus today on the metrics aspect.

So I want to start with the 10 metrics that I think that every SaaS PM should know or

like work to build on their dashboard or these, these are the 10 metrics.

So I classify them into three categories, I call them the business metrics, that is focused

on the business or the company that you're part of and then the product metrics, the actual

product that you're leading or the entire product suit and then last but not the least

the customer metrics, I classify them for a reason, a lot of product managers, I understand

they're coming from B2C or B2B side, focus a lot of their time and product metrics alone,

this is how their products are being used and MAUs, DAUs and things like that, but there

is so much more valuable information that they can get if they can bring their perspective

a little bit more wide and then in the interest of time, I just want to focus on 10 of

these metrics, there's definitely more metrics that I could talk about, I took the

liberty to put together a sketch format on all this, took some time, but I thought it'll

be more intuitive and helpful as you learn about these metrics, this session is really good

for people who are either early stage product managers, late stage product managers, even

product leaders in SaaS companies who are getting to build their dashboards and understanding

what should they track.

So let me start with business metrics, I look at business metrics that are 4 key metrics

that I look at, that are important to track, the monthly recurring revenue, customer lifetime

value, customer acquisition cost and shurn, that can also touch a little bit on retention

rate.

So on that side, I want to talk about what does these metrics mean and then why is

it important for a product manager or a product leader to know about these metrics?

The same thing I wanted to do on the product metric side, I think it's most of UPMs are

already aware of, but I want to give a little bit more dimension and color here, beat

on the usage, taking us on the feature level, adoption retention and quality and efficiency

of your product.

Last but not the least, I want to talk about customer metrics and the last metric that

I want to talk about is mission metric, I don't think this is used extensively, I'm a huge

proponent of this or probably I want to, in fact, kind this term and make every SaaS company

use it, I'll tell you why as we go into that.

So first I want to start with business metrics.

The first one I wanted to focus is monthly recurring revenue, we call them MRR or like

some of the companies measure ARR, which is annual recurring revenue, what does it mean?

It's actually telling you how much is your company making month or month, so amount that

you're building your customers monthly to the number of customers.

You might ask, hey, my company might have several plans, there's a free plan, there is

a premium plan, premium plus plan.

So we take into account in this case all the paying customers, depending on the plan they

are in and then multiply the corresponding bill in amount that you do for that particular

category and then sum them up.

As you can see here, it's very important, this metric is tracked to the company level,

we all know that, but it's also important for a PM to understand this metric, not only

because it gives you a glimpse on whether your company is generating revenue or not, right,

which means users are staying and paying for the product that you're both, but also it's

a very good indicator of how our things performing and also could be a great indicator

for blue.

It helps you build features that customers would want, right, like you're building a certain

feature and people are using it and paying for it and that's growing, it's just a strong

indicator that what you're building, people are willing to pay for what you're building.

So this is a very important first metric that I would definitely put it in my dashboard.

The second thing I call them customer lifetime value, right, customer lifetime value, again,

lifetime value is how much a particular user or a customer is paying to the business over

time.

So it's nothing but average value of sale from that customer, number of transactions that

they're making in a year and then the total amount of time that they're staying in, are

coming back to buy and then the overall profit margin coming from then.

So that all tells me how much is the customer work.

So that's customer lifetime value.

Why is this metric so important?

This actually helps me prioritize a couple of things, right, as a PM.

So if a certain high value customer is asking for a certain feature, it should be given

higher priority based on other things as well, like you're looking at the mission mission

of the company and direction you want to go.

But I also wanted to take and feed back from different customers at different levels and

prioritize them accordingly and this is a huge metric to use for that reason.

So this also helps you allocate resources on certain things these customers are asking.

For a high value LTV customer is asking for, compared to a low value customer who is

trying to just use the product for the minimal value is giving.

So that's why this metric is very important.

I want to talk about the third metric which is customer acquisition cost.

This is a really like very broadly looking at this.

This is like the total expense of the company does to acquire a certain acquire customers.

Right.

That is net net.

The cat is the total sales expense, marketing expense, the company spending.

To the total number of customers it has acquired, which tells me on average how much does

it cost to get in a customer.

This alone in itself might look like, you know, it's a marketing and a sales metric, why should

I care as a PM.

But if you combine this metric to the LTV metric, then you can actually learn a lot about

what type of customer segments we should go behind and what kind of products and features

should be prioritized for that.

So when you combine this, you want to be able to understand that the customer lifetime value

should be much higher than the character you're spending.

This is an important ratio that you need to be looking at in a constant basis.

Now that you understand these two three metrics on the business side, I want to talk about

another important metric that you look at on the business side at the customer level, not

necessarily at the user level.

When I say user, a particular brand or a customer logo, we call it, we'll have multiple

user seats available on your product.

So I want to look at the business to understand the broader direction, and then when

I go into the product, I'll go more deeper on the user level as well.

The other important metric is to understand churn and retention rate.

These are like kind of opposite to each other in some sense, to understand how many users

are churning to the number of users that are being acquired, like, what is the exit rate

versus the rate of acquisition?

So that's one thing.

But also like of the people who are acquired, what does their retention rate look like?

How long, how often do they come back to visit our product and find value in our product?

Could slightly vary by product to product.

Some SaaS products, there is a need to come on a daily or a weekly basis.

Some SaaS products, you set up things and go, and people can come on a monthly basis.

So based on your product, you take either a weekly or a monthly retention rate to measure

the success of this metric.

This is a very important metric to understand again from a business standpoint for a

PM, because it will help you decide which features will help you do better retention and

actually build this code on this one.

Now I want to go, that's a little bit about product metrics, right?

Before I go there, I want to consolidate what I said about the business metrics.

So the first thing I, as I mentioned, is the monthly recurring revenue.

The second one, I wanted to touch about was customer acquisition costs, then customer life

time value, and last but not the least they're turned on retention rate.

These are not the only four business metrics we should be aware of.

These are the top ones.

There are a couple of more that comes to my mind.

One is called quick ratio, which will also help to understand how much of these user

who are coming in are actually retaining and adding value and also spending on it.

So things like that.

There are a couple of few more business metrics I want to touch, but I want to

sense we are prioritizing here and staying with the top 10 metrics.

I'm going to stop here and move into the product metrics area.

So on the product metrics area, the first metric that we all know, I think we all will be using

our regular basis is the product usage metric.

In general, like how many how long the users are spending time in a product to all the

way from how many users are using my key features and things like that.

The way I look at product usage, I classify that into four big buckets.

One is the breadth dimension, the depth dimension, the frequency dimension,

and the usability of my of the product.

I kind of like both this framework looking at different aspects from different tools that I've

used before, you know, kind of being a good example of a tool that I've used before or like

I've used heap metrics as well, that like amazing tools to use.

So the first thing is understanding breadth, like total number of users, right?

Total number of users are active in your product or like total number of users for a given

customer who are using your system, right?

Measure one of the example of measurement would be number of active users for a given customer

in the last 30 days.

Depth is something about like what exactly are they using the product for,

which is let's say we identify certain key features in the product and then we want to measure

number of customers or percentage of customers that are regularly using these key features.

Frequency is like something like, oh, often they access it, how often they come to find value.

It's a good metric. It's actually leading indicator for retention and also it also tells you

like if a customer is going to turn out or not. If they're not finding value and then you're

filling them on a monthly basis, at some point they're going to turn around and say hey,

I'm not using the product enough and and leave the product.

So how often they access the product is a very good product metric.

It could be number of logins that they're doing across their users or like number of sessions that

they're having. Last but not the least is the usability metric. How long does it take to

for a customer or a user to complete the set of tasks?

Let's say understand your product as a funnel and see like from this point to this point,

how long does it take? How easy it is for them to infer certain things before they like

exit or they reach out to ask customer success or they trace tickets. Like any of those hurdles

or like any of the product hurdles that they have is too very important to understand over time

is the usability aspect of your product. So overall from a usage standpoint, if you're

able to get these metrics built in your dashboard, that'll be amazing for you as a product manager.

And I think like this is one area that I don't have to tell why this is important as a product

manager. This is probably one of the most important areas that you have to close and understand.

This episode is brought to you by Amplitude. The pioneer in digital optimization software

that helps product leaders innovate faster and smarter by answering the strategic question

how do our digital products drive our business? 1,400 plus customers like Atlassian,

Instacard, and Under Armor rely on Amplitude's best in class product analytics solution

to unlock insights, build winning products faster, and turn products into revenue.

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The next important metric I kind of would vote for is the product stickiness.

It's like off the number of daily active users or coming into your product, how many of them

are coming back on a monthly basis. It's retention, not at the customer level, but you can

put it at the user level. Within the company, there are multiple users using a product.

And this is how sticky use your product, how awesome they come and work at it and use it

is a very important metric to understand. There's a couple of reasons,

like also understanding which features they're using and coming back again and again will be

a good indicator as well to prioritize certain features or like doubling down on certain features.

So that's why I call products stickiness is a very important metric.

I mean, I'm repeating an insert in research, stickiness is connected to somewhat connected

to journey retention. So this is all very important for you to build as your product is

maturing, you know, from that early chasm of product market fit into a latest stages.

The next other important metric, this is I think post people will be already using

in your launch KPIs and all of that is your featured adoption. How many users are adopting

the features that you're saying, how frequent they're using it and then how often do they come

back and use it, right? By different feature sets, you can call them product lines, feature sets,

or product groups, any of that, right? Overall to understand which of them should I continue to

build on, which of them I can actually even remove it out of the product at some point and say,

like, okay, we are not going to support those as there's less number of adoption for these features.

It's a constant learning about your customers. So this is one of the metrics you also use for

your goals and KPIs as you launch any particular product and see what the adoption

looks like, how much value they're finding are they coming back and using it or not.

The next most important metric, my mind from a product standpoint,

for many more metrics, for me, the next most important metric is actually being quality and efficiency.

You might release a lot of good features and everything, but if it's fully of, it has a lot of

bugs and people are reporting on it. It actually unites the user a lot and then you might actually

remember this, right? Your early product adopters are the people who trust you and come and use your

product and they're willing to take some level of bugs and issues. But the more you're going to

put these bugs and issues on them, they're not going to find the right value on time and then

they have to reach out to customers, you're going to make their lives harder and that's actually

not a good sign. So it's very important to understand what is your bug reduction rate, like how

fast are you able to fix bugs, how fast, so the number of bugs that are open to the number of bugs

that are getting fixed in a given quarter, how quickly are you able to do that, right? And also,

the other thing to understand is, breaking your product into feature sets of product lines

and looking at which of these areas are buggy, very highly buggy and trying to put more

engineers or more resources onto that and fix it over time will have more, will have the customer

and start using that feature more. So that these are the two areas that I will look at,

right, the buggyness by features and then the overall bug reduction rate to understand how good

you're moving in terms of quality and efficiency. There are two or three more metrics that I would

think about when I look at product as well. One other metric is product deliverability,

metric or predicting your delivery over time. This is helpful for marketing sales teams.

The other metric I would also look at is I kind this term ecosystem metric. If you're connecting

your product with more APIs and more other other partners, you want to measure how often these

APIs and metrics are being used, so you can actually double on on some of them and remove some

of them, so you can make your customers like easy also think about how you can build your road

map based on that. So I think like the ecosystem metrics and other one that I've considered,

again, even these are the four top priority metrics I've used for product coming to the last

section, which is customer metrics, right. So there are two important metrics that I would

measure on the actual customer side, getting direct inputs from them. One is the NPS, some companies

measure CSAC with I feel both of them will help us get a very strong signal from the customer

on what they think about your product. We in fact, some companies use this as a very important

metric and add rightfully so it not only gives you the metric aspect, but also gives you a little

bit of the quality aspect. So how does this metric gets calculated? What is net promoter's code?

So you send a survey of 1 to 10 on whether your customer likes your product and would recommend

to somebody else and 1 being the least favorite and then 10 being they would definitely go ahead

and do it. So if you send this over time and build this metric over time, then you will get a

signal on, now like who your promoters are, people who are scoring at 9 and 10 and then who

your treat directors are, people who kind of moderately like your feature or don't like your

product at all, they're just using it because they company bought the service. So people are scoring

0 to 6. So basically getting the percentage of your product promoters, minus your product first

and age of detractors will help you get an NPS. This ranges from minus 100 to plus 100. So the

more positive you are in this code over time on a statistical significance basis, you can understand

that you're moving in the positive direction. So start building this metric and throwing it out

there to start collecting this data point. One this takes over long time to build this metric.

So this could be one of those metrics. You have to start triggering it out and sending it out.

Sample your audience, send it to a sample in any given time and start collecting the metric

over time. You could also collaborate with your customer success because they also love to understand

this metric. So the two important levers here are customer success and product team,

both gets benefited out of this metric. The last and most important metric that I think a lot of

companies don't measure are also not seen in many product analytics boards is the customer

mission metric. To explain this very clearly, is your product able to help your end customer

or not. Are they coming to you? Are they able to find success for the reasons they've

reached out to you or for the value that they've gained out of you? For example, you're providing

a marketing tech product where they're coming, where a particular company or a business is coming

and using your product to promote and get more sales. So if you have a way to understand how

much sales you're creating and minus the cost that is incurred in including the software

SaaS price, including the reach out cost or the ads cost, and also the product cost, then you

cannot kind of understand the net revenue that they're able to get out of your product. And you

have to look at the different customers and see who are using your product wisely and not

wisely and then see like what percentage of your customers are actually succeeding and by what

level they are succeeding. This is very important to track over time because it also gives you a strong

proof point that your product is working for someone and then you go understand and bulkage

studies on them and understand some of the best practices and start making it available for

more of your customers to make your product work for them. And for me, if you ask me one metric

off of your 10 metric that makes sense, I would say this is the one metric. Is your actual customer

end of the day is feeling successful with your product or not or is actually finding value

on your product or not. Doesn't matter how much they use, they might not use it fully, they might

use it less, doesn't matter all of that if your end customer is not finding success in your

product. So if you ask me one metric that you would go yourself on a bulk start building an

understanding that would be this that could be some leading indicators that you can also build on this.

So as I said, these are the top 10 metrics in my mind that every product manager should build

a dashboard over time on and start tracking. As a conclusion, I wanted to say a couple of things,

right, like these are the top 10 metrics. These are the not the only metrics that you should care

about. There are other metrics that you should be also be thinking which I kind of brought you listed

and we should talk about as well. But as a PM, these are the minimum things that you should be

understanding over time and putting it as part of your dashboard. Before I come to conclusion of

the session, I hope you've found a value in understanding these metrics. I want to talk about a

couple of things. One is things to avoid while building these metrics. There's been a thing that I've

seen over time that this approach on one North Star you build and then you always stick to that

in irrespective of other things that are happening could be a dangerous area. I've done that myself

like built a North Star and stuck, this is the one North Star, that I realized that could be other

guardrails that you need to build, that could be other metrics you have to keep a site on and not

just go with one metric that matters approach. You should have a, you should, you can go against

one metric but you should have a whole set of other secondary metrics that you should be tracking

and having and thinking about as guardrails. So don't fall into this approach. Hey, this one metric

is everything and imagine this is a hundred different ways that people would gamify that metric as

well. The second thing I would say is I've also seen is like not having the right

measurements systems in place could cause a lot of issues. So it also depends on the

right of right tool choices, right way you set it up is very important and I see like definitions

are also very by the companies and tools you use. So working with them to make sure that

you are comfortable with those tools and techniques is very important or choosing the right

partner in helping you measure is also important. The last but not the least, these quantitative

metrics are awesome to measure over time, but I would also keep my eyes on some qualitative signals,

some surveys that we do and direct one on ones that you have with your customer. Try to also

have that regular call with customers at least once in a week to different customers to get a sense

of what they're saying, what they're doing, that quality in signal is very very important because

metric can only tell you so much. So having a idea of qualitative signals with the quantitative

metrics approach will balance it both. Yeah, that comes to the end of session for today.

I hope you guys enjoy and got a ton of value or the session. Yeah, thank you again. Thank you

product school for organizing this session and helping me, you know, like share my two cents

with the product community feel free to connect and follow and connect with me in my LinkedIn

in short, like it's www.linkton.com slash i n slash on and there you go feel free to reach out to me.

I'm also working on building a book in a similar area very soon. Would love to share more

insights, tips on these areas as you build yourself as a product leader in any sales organization.

Thank you. Thanks again for all the patience and listening to me for this whole session.

I hope you find a lot of value and meaning in the session. Have a great take us.

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