Definitive guide to Revenue Architecture: Part 2 - Metrics Matter (until they don’t)
Definitive guide to Revenue Architecture: Part 2 - Metrics Matter (until they don’t)
How to deconstruct and influence them.
👋 Hey, Toni from Growblocks here! Welcome to another Revenue Letter. Every week, I share cases, personal stories and frameworks for GTM leaders and RevOps.
This is the second part of a four-part series on revenue architecture. Over the next weeks, I’ll provide structured outlines, core frameworks, and models that will help you grow in today’s new SaaS environment.
Part 2: Metrics matter (until they don’t) - This post
Don’t want to wait until the whole series is out? I’ve put together the entire first draft in one place. Get your copy here.
Last Thursday I wrote about the foundational GTM frameworks you have to be fluent in if you want to have a chance at success - especially with the state of SaaS today.
Today I’m covering the next logical step: metrics.
So, why do metrics matter?
It’s the stuff that you can look at daily or weekly to see if you’re on track. And since we’re in SaaS - we need to be aware that even small changes in how your metrics are performing, might create disturbing ripple effects.
To avoid any whiplash, you need to understand what metrics matter, how they influence each other, and at what stages they matter.
If used right, data is what Dave Kellogg calls a tool of enlightenment. The numbers will tell you what’s not working. And yes, some of them will take time to fix. But now you have something to talk about.
Yet, metrics and data cause many pains, and the problems are endless.
“If you torture the data long enough, it will confess to anything”
- Ronald H. Coase
The number one problem I see across the board - and I mean at every single company I get a peek inside of: the chiefs of the company steer the company using high-level metrics.
The reason they do it is because these folks talk to investors a lot. And they’re really only interested in metrics that they can compare different companies by.
Those are usually ratios that combine a lot of things at the same time. Great for investors sipping espressos - bad for operators grinding.
Jacco van der Kooij calls these metrics “Investment Metrics”: CAC:Payback, CAC:CLTV, Rule of 40 etc.
These metrics are all absolutely great. But they are impossible to work with operationally.
As you’ll see after this walkthrough, if used correctly you’ll be able to fairly accurately predict future outcomes based on where you are today.
And that’s pretty important because some of the questions we hear from GTM leaders over and over again are:
Where do we cut?
Where do we invest the next $?
When can we accelerate?
Will our core metrics improve?
How do we grow the business according to expectations?
And you’ll need to be able to answer and discuss these to make the right decisions.
9 months later
Now, what everyone will tell you is that “it takes a while to end all the problems data and metrics can cause internally”. And that you need to start by:
Agreeing on what metrics matter
Agreeing on how they’re calculated
Agreeing on how the data is sourced
If you do this, you’re basically re-inventing the wheel.
And I know from talking to some of you that you totally want to do that. What you’ll discover is that in 9 months you’ll still be very close to square one - the reason?
You need to get everyone to nod to all your metric definitions. And this alignment has already killed hundereds of BI projects.
There’s a simpler 80% solution here. Use the standards that are already out there.
These standards will:
Tell you which metrics are key for your SaaS
Provide you with the battle-tested definitions
Help you to source all of this from your GTM tools
And in case you want a shortcut, Growblocks can help you.
But one thing is having the metrics, another thing entirely is understanding how they work together, and when to use them. And honestly, this is where most companies start to feel a lot of the pain.
Metrics hierarchy
“Once you start measuring a series of numbers, your team will realize the importance of those numbers and start work to improve them”
David Skok
As we’ve talked about different types of metrics in relation to the bowtie; volume, conversion rate and time – you probably realized that it’s just a fraction of the metrics being used in a business. That means it’s important to know which metrics to highlight to whom.
That’s why we’ve organized the core SaaS metrics into four categories:
Investment: Used to compare and assess businesses as investments
Financial: Portraying overall business health and performance
GTM: Bridge between financial and operational
Operational: Focused on short-term & daily activities
It’s important to note that the higher the metric lives on the stack:
The longer it takes to impact
The bigger your paycheck is if you care about them
For example, what would happen if you go to the sales floor and scream that rule of 40 is down?
Crickets.
Not sure if you’ve tried it, but you could yell at your SDR team to “improve CAC Payback or ELSE you’re all on a PIP!!”
While the instinct is actually right, meaning if your SDRs “improved” you probably would see a better CAC Payback. But using this way of trying to improve it won’t work.
Since you’re trying to impact a higher level metric, you’ll need to follow its way “down” to the operational level.
At the operational level, you might end up talking about “Calls per day”. And that might be what you want to yell at your SDRs (but really, don’t yell).
And at the same time, if you’re in a board meeting and start talking about “we‘ll get daily calls per SDR from 37 to 40 - which is almost a ten-point lift,” people will think you’re in the wrong meeting room.
So what you really need to understand is that metrics belong to different layers. And you need to match the layer to the audience.
Investors want to see investor metrics to compare the businesses. Leadership will need financial and operational metrics to guide decision-making.
To visualize it more clearly, we created a simple cut of some of the most important metrics and what layer they belong to.
Again, notice that the higher in the layers you go, the longer it takes to change those metrics (unless you start tinkering with the definition).
Keep in mind, financial metrics and those at the higher levels are scorecards - an outcome. They don’t tell you why they’re good or bad - nor how to improve them.
The other facet of these metrics that really matter, is how they’re connected.
As you begin to measure some of these metrics, you’ll notice both good and bad things - triggering a conversation on how to improve the business.
All the while - realizing that the only way you’ll ever improve any of those financial metrics is by working bottom-up, e.g. impacting the metrics several layers below.
So let's dive into that.
Deconstruct metrics & find solutions
Most simply put, you might want to improve CAC Payback (Investment) by raising prices (ACV - Operational).
The way this works is:
ACV (Operational), Pipeline & won business go up (GTM),
New ARR per Q goes up (Financial), with CAC staying flat (Financial)
Your CAC Payback (Investment) will improve.
Once you see how all of this is connected, a world of options opens up. Because it’s not just ACV you could choose to improve, its actually many, many others too.
So let's deconstruct some of the metrics to show you how they connect from investment to operational.
And by the way, this is not a novel concept. In fact, most business schools will teach you about the DuPont metrics tree from the 1920s. Simply put, it’s the deconstruction of core metrics through tree branches.
In effect, you’re “unblending” metrics to see what it’s derived from mathematically. In other words, it helps you clarify a range of possible options to improve a metric.
Let’s stick with CAC Payback for a second.
Folks will tell you that you need to be below 12. And if you’re at 16, your options to improve payback periods are either to decrease CAC by reducing fixed costs (staff, tools) or variable costs (marketing spend etc).
Besides cutting costs, can you lift MRR? Well yes, but it can be broken down further, as MRR is largely a result of operational metrics:
Volume of opportunities (which is a function of leads / SDRs)
ACV (pricing, discount structure)
Win rate (result of a process & skill)
Sales cycle length (capacity, process)
Suddenly, you go from very few options (do we cut people, spend or both?) to actual business conversations: Can we reduce sales cycle length? Can we decrease discounts without impacting winrates? And much more.
As you start to consider what operational metrics to move, you can run the numbers to uncover the impact they’ll have on CAC:PB over time.
Stage matters
But there’s also another perspective to take on metrics. Not every metric is equally important at different times in your company’s lifetime. So let’s use this lens next:
Pre-scaleup companies will be focussed on acquisition. So newbiz metrics will be a top priority for the company.
Once you reach the scaleup stage, you adopt a balanced approach as retention becomes a bigger factor.
And in the post-scaleup world, you’ll find most of your growth comes from retention and expansion.
So as you move stages, so should your focus when it comes to what operational metrics to watch.
It’s not that metrics become irrelevant at later stages, more so that new metrics becomes more important. No one really obsess over churn at the startup stage, nor should they.
The mechanics of your motion
This grasp of metrics will help you find inefficiencies in your engine. But the greater questions are still ahead.
How do we know we have GTM fit? And how do we know that the motions we have running are the right ones for us?
In the next post, I’ll be covering the mechanics of your motions, and how to choose the right ones based on your model.
Really insightful article! Thank you :)