Lessons on Capital Efficiency from 21 SaaS IPOs
A common question in the minds of many SaaS founders is the pace of raising capital. How much is too much too early? What amount of capital raise is typical for comparable peers? How capital-efficient are the best-in-class companies?
In the last 30 months (2017 2H onwards), a total of 21 SaaS U.S.-based, VC-backed companies have gone public, including Zoom, Slack, Datadog and others¹. To answer the above questions, I analyzed all 21 companies to understand their fundraising and revenue-generating trajectories.
Here are the summary takeaways from this data set:
1. At IPO, total capital raised² was slightly ahead of annual run-rate revenue (ARR)³ for the median company
Here is a scatterplot of the ARR and cumulative capital raised at the time each company went public. Most companies are clustered close to the diagonal line that represents ARR and capital raised matching each other. Total capital raised is often neck-and-neck or slightly higher than ARR.
For example, Zscaler raised $148 million to get to $146 million of ARR at IPO and Sprout Social raised $112 million to get to $106 million of ARR.
It is useful to introduce a metric instead of looking at gross dollars, given the high variance in revenue of the companies in the data set — Sprout Social had $106 million and Dropbox had $1,222 million in ARR, a 10x+ difference. Total capital raised as a multiple of ARR normalizes this variance. Below is a histogram of the distribution of this metric.
The distribution is concentrated around 1.00x-1.25x, with the median company raising 1.23x of ARR by the time of its IPO.
There are outliers on both ends. Domo is a profligate outlier that had raised $690 million to get to $128 million of ARR, or 5.4x of ARR — no other company comes remotely close. Zoom and Datadog are efficient outliers. Zoom raised $161 million to get to $423 million of ARR and Datadog raised $148 million to get to $333 million of ARR, both representing only 0.4x of ARR.
2. Cash burn is a more accurate measure of capital efficiency and may diverge significantly from capital raised (depending on the company)
How much capital a company raised tells only half of the story of capital efficiency, because many companies are sitting on a significant cash balance. For example, PagerDuty raised a total of $174 million but had $128 million of cash left when it went public. As another example, Slack raised a total of $1,390 million prior to going public but had $841 million of unspent cash.
Why do some SaaS companies end up seemingly over-raising capital beyond their immediate cash needs despite the dilution to existing shareholders?
One reason might be that companies are being opportunistic, raising capital far ahead of actual needs when market conditions are favorable.
Another reason may be that VCs that want to meet ownership targets are pushing for larger rounds. For example, a company valued at $400 million pre-money may only need $50 million of cash but could end up taking $100 million from a VC that wants to achieve 20% post-money ownership.
These confounding factors make cash burn — calculated by subtracting the cash balance from total capital raised⁴ — a more accurate measure of capital efficiency than total capital raised. Here is a distribution of total cash burn as a multiple of ARR.
Remarkably, Zoom achieved negative cash burn, meaning Zoom went public with more cash on its balance sheet than all of the capital it raised.
The median company’s cash burn at IPO was 0.77x of ARR, quite a bit less than the total capital raised of 1.23x of ARR.
3. The healthiest SaaS companies (as measured by the Rule of 40) are often the most capital-efficient
The Rule of 40 is a popular heuristic to gauge the business health of a SaaS company. It asserts that a healthy SaaS company’s revenue growth rate and profit margins should sum to 40%+. The below chart shows how the 21 companies score on the Rule of 40⁵.
Among the 21 companies, eight companies exceed the 40% threshold: Zoom (123%), Crowdstrike (119%), Datadog (76%), Bill.com (56%), Elastic (55%), Slack (52%), Qualtrics (44%) and SendGrid (41%).
Interestingly, the same outliers in terms of capital efficiency as measured by cash burn, on both extremes, are the same outliers in the Rule of 40. Zoom and Datadog, which have the highest capital efficiency, score the highest and third highest on the Rule of 40. And inversely, Domo and MongoDB, which have the lowest capital efficiency, also score lowest on the Rule of 40.
This is not surprising, because the Rule and capital efficiency are really two sides of the same coin. If a company can sustain high growth without sacrificing profit margins too much (i.e. score high on the Rule of 40), it will over time naturally end up burning less cash compared to peers.
To apply all of this to your favorite SaaS business, here are some questions to consider. What is the total capital raised in multiples of ARR? What is the total cash burn in multiples of ARR? Where does it stack compared to the 21 companies above? Is it closer to Zoom or Domo? How does it score on the Rule of 40? Does it help explain the company’s capital efficiency or lack thereof?
While the above takeaways provide an aggregate summary of the dataset, there is more to be learned by looking into each individual company's capital raising and revenue generating trajectories over time. The second half of this post focuses on the below charts that show each company’s annual run-rate revenue (ARR) and cumulative equity funding over time. Read endnotes for details on data source⁶ and methodology⁷. The backup for the full analysis can be accessed here.
I divided the companies into four patterns:
1. The most common pattern
Most commonly, the two curves track each other closely, intersecting multiple times throughout the company’s life leading up to the IPO. At times, ARR is ahead of capital raised, but at other times, the opposite is true.
PagerDuty is a prime example of this pattern. Every time the ARR exceeded the total capital raised, a new round of funding followed, usually within a few quarters. Each funding took the total capital raised back above the ARR and the cycle would repeat. As a result, the two metrics were never too far apart.
I suggest this as a heuristic for SaaS founders regarding fundraising timing: ARR exceeding the total capital raised is a healthy sign that the company is ready to raise a fresh round of capital. There are almost no examples in the entire data set of ARR exceeding total capital raised for extended periods of times, unless the company was approaching an IPO.
2. Capital-hungry companies
Many companies can be described as capital-hungry, their raised capital outpacing ARR from early on and the two curves never intersecting.
Domo is the most extreme example, where the gap widens aggressively over time, its raised capital reaching 5.4x of ARR by the time of its IPO. Domo raised $690 million of capital and spent through most of it to get to just $128 million of ARR at its IPO. The cash burn suggests Domo’s capital-raising was need-driven.
Slack is an interesting example because, despite its abundant fundraising that reached 2.6x of ARR by the time of its IPO, 60%+ of the raised capital was left intact on its balance sheet. The company could have almost omitted its Series G and Series H totaling $840 million of funding. This suggests that Slack’s fundraising was likely more market-driven than need-driven.
What allowed these companies to raise a lot of money from early on?
A common thread across the most salient examples like Domo, Slack and MongoDB are that their founders already had high-profile exits under their belts, like Flickr, DoubleClick and Omniture. Investors are likely to have placed a premium on their track records leading to higher valuations and bigger rounds earlier on.
3. “Capital-lite” companies
On the other end of the spectrum, truly “capital-lite” companies whose ARR was consistently ahead of raised capital are a rare breed.
SendGrid is the only example that comes close to meeting this bar. Its ARR was ahead of capital raised for at least 10 quarters prior to the IPO, and possibly longer. This is an accomplishment unmatched by any other company in the data set.
Qualtrics, Tenable and Zscaler are worth calling out because they were uniquely able to reach IPO with just two or three rounds of institutional funding. They bootstrapped through early growth, effectively skipping early-stage rounds and moving straight into growth equity rounds.
Accordingly, their first institutional rounds were much larger than the typical Series A investments. Qualtrics, Tenable and Zscaler raised $70 million, $50 million and $38 million, respectively, compared to the average $10 million Series A for the other companies in the data set.
While bootstrapping allows for less dilution and more founder control, it comes at the cost of slower growth or self-funding from deep-pocketed founders. Qualtrics and Tenable both took 16 years until their IPO, notably longer than the non-bootstrapper average of 11 years. Zscaler took 10 years, but that was made possible by its founder Jay Chaudhry fueling early growth with his own money.
If you are a SaaS founder, here are some questions to apply to your business. What does your historical ARR and funding curve look like when juxtaposed against each other? Which of the above four patterns does your company most closely resemble? Is your funding need-driven or market-driven? If your ARR is fast catching up to total capital raised, is now a good time to consider raising a new round?
¹ Only includes U.S.-based, VC-backed SaaS companies. Includes Quatrics, even though it did not go public, as it was acquired right before its scheduled IPO.
² Includes institutional investments prior to the IPO. Does not include founders’ personal capital investment.
³ Note that this is not annual recurring revenue, which is not a reporting requirement for public companies. Annual run-rate revenue is calculated by annualizing quarterly revenue (multiplying by four). The two metrics will track closely for SaaS businesses, given that SaaS revenue is predominantly recurring software subscriptions.
⁴ This is a simplified definition as it will capture non-operational uses of cash such as share repurchase from founders.
⁵ Revenue growth is calculated as the growth rate of the revenue during the last 12 months (LTM) over the revenue during the 12 months prior to that. Profit margins are non-GAAP operating margins, calculated as operating income plus stock-based compensation expense divided by revenue over the last 12 months (LTM).
⁶ ARR data is mainly sourced from the IPO prospectus (S-1), which provides up to 10 quarters of business performance prior to the IPO. More dated ARR information is sourced from miscellaneous online sources like the company blog, Inc 5000 and various SaaS blogs. All equity funding data is sourced from Crunchbase .
⁷ The ARR curve is an estimation — it represents the best-fitting exponential curve based on the available historical data points (the red dots). Given the sparsity of early-stage revenue data for most companies, the early portion of the ARR curve may not be an accurate depiction of the company’s actual growth.