A History of the Magic Number

“It’s… Magic!” Every superhero has an origin story. Here’s how one humble SaaS metric became the super-useful Magic Number.

Part one of the this series is a founder's primer on Sales Efficiency fundamentals

A History of the Magic Number - Scale Venture Partners - MN+EV-Rev animatedRoll back the tape to 2005, when SaaS represented only 10% of all software-related venture capital investment. At the time, many of the nuances of a subscription-based revenue model were not nearly as well understood as they have become today. During the process of evaluating Omniture for an eventual investment, Scale’s Rory O’Driscoll was analyzing the company’s revenue traction relative to its investment in Sales & Marketing. Seeing that they were able to generate more than $2 in first-year revenue for every $1 invested in their go-to-market engine, he exclaimed, “It’s Magic!” The rest, as they say, is history.

Analyzing Ten Years of Data on Private and Public SaaS

In the early 2000’s, SaaS and cloud-based computing were still nascent concepts and poorly understood by most of the business world. Salesforce and Amazon Web Services (AWS), which have become the two dominant players in the SaaS application and cloud computing universes, were not launched until 1999 and 2002, respectively. Sure, there had been prior attempts at subscription-based models in other areas within the wider technology ecosystem (e.g. telecommunications and cable providers), but the advent of players like Salesforce and AWS marked the first real shift from CapEx to OpEx spend and forced the broader market to understand how these business models should be evaluated. 

Stepping back, it is remarkable to see how far we have come in the past two decades. What this progress has given us is more than 20 years worth of data on how this ecosystem has performed and evolved over time, all the way down to the company level. And while progress within SaaS and cloud has been lightning fast as compared to other corners of the economy, these advancements have not happened without immense amounts of capital investment. Many of today’s SaaS and cloud businesses have raised hundreds of millions of dollars on the path to IPO. 

As early stage SaaS investors, we are always trying to understand how the ecosystem is changing. How are things different now versus last quarter, versus last year, and five years, and a decade ago? What does it take to build an category-leading SaaS business today compared to the past? Do any patterns emerge?

To better understand this dynamic, we wanted to start by looking closely at how capital investment within the SaaS universe has changed over time. To do so, we created a data set of private company data from Scale Studio and our Scale SaaS Index of public companies in order to track two data points: 

  • Magic Number, a measure of go-to-market efficiency that broadly reflects “return” on capital investment 
  • EV / Revenue multiple, a measure of point-in-time valuations over the past decade. 

It’s important to note that for this analysis, we specifically took aim at how Magic Numbers in the private universe are affected by revenue multiples in the public universe as we believe there is some pull-through effect from publics to privates.

The Past Decade of Private Company Magic Numbers 

As we saw in our primer on sales efficiency metrics, Scale’s rule of thumb is that a Magic Number of 0.7x is a fairly healthy efficiency baseline for most SaaS businesses. That means for every dollar invested in Sales & Marketing, the company generates $0.70 of revenue after the first year. Within these parameters, so long as a customer’s lifetime value exceeds the amount of time it takes the company to recoup its investment in S&M, this dynamic tends to lead to extremely profitable unit economics in the long run. 

As we look at our SaaS database over the past decade, the long-term median Magic Number has hovered around 0.7x. But to say that this benchmark has held steady over time isn’t necessarily true among private SaaS companies. While the median does hold around 0.7x, it has bounced around quite a bit and most recently has been trending down.

A History of the Magic Number - MN over time

Bookmark that thought for now, we’ll get back to it in a moment.

The Last Decade of Public Company Revenue Multiples

A few years ago, my colleague Alex Niehenke wrote a piece on long-term SaaS valuations, in which he plotted how EV / Revenue multiples have changed over time. We took this same chart (shown below) and updated the revenue multiples to match the same time period as our Magic Number chart above.

A History of the Magic Number - Scale Venture Partners - EV-Rev over time

I think it’s safe to say that, as of this writing, we’re well above the long-term median SaaS revenue multiple of 5.0x. In fact, as of the close of the most recent quarter, we hit a high of 11.7x EV/revenue -- which points to the market’s continued exuberance for SaaS and cloud. Investors are betting on the future growth of this segment of the market, in no small part because of its decades-long streak of consistent top-line growth. Looking ahead, that which has not digitized soon will. And COVID-19 has only accelerated that trend.

Magic Number x Revenue Multiple

We’ve seen fluctuations in both public SaaS revenue multiples and private SaaS sales efficiency. The big surprise about these metrics comes when looking at these two trend lines plotted on the same chart. There is a correlation between the two, and it’s negative.

A History of the Magic Number - Scale Venture Partners - MN+EV-Rev

In general, the higher the multiple in the public markets, the lower the median sales efficiency in the private markets. 

What to Make of This?

Why does the data show an inverse relationship? Here is one theory. 

For many venture-backed startups, the siren song of an open IPO window with high valuation multiples pushes pre-IPO companies to step on the gas to achieve critical mass as quickly as possible. Some are ready and can maintain (or even improve) their go-to-market efficiency as they continue to scale. These are the success stories that you hear about, but they’re few and far between. 

It is unfortunately more common that early stage SaaS businesses try to scale prematurely only to see efficiency quickly degrade due to stresses on shaky processes, lack of real product- market fit, or heavy competitive pressure. These companies may achieve the growth needed to reach escape velocity, but they will burn through quite a bit of cash on their journey to get there. 

The lesson here for founders is this: In an environment where capital is cheap and easily accessible, SaaS businesses can continue to finance their growth round after round. Early- and mid-stage startups can tap a growing pool of venture investors and, more recently, a myriad of cross-over and corporate venture investors trying to take advantage of the SaaS market’s momentum. 

The risk is that when capital gets more expensive or a company starts preparing for a public market debut, sloppy (inefficient) growth can carry consequences. In these instances, management needs to quickly implement a strategy to get back to a highly efficient go-to-market model, lest the company face the discount that late-stage or public investors apply to cash hungry, inefficient go-to-market models.

In the next blog post, we’ll talk more about this pre-IPO push as we start to analyze go-to-market efficiency by size and growth rate. 

Sam Baker contributed to the research and writing of this series.

Originally published September 24, 2020.