Category: benchmarks
Posts
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Payback period is one of the best composite diagnostic metrics of product market fit. I've written before about the benefits of short payback periods. In short, startups with shorter payback periods require less capital and also grow more quickly. In 2020, what is an excellent payback period[1]?
Here is a group of publicly traded companies sorted by estimated payback period[2]. Zoom is at the top with a payback period of just over 3 months.
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If you're starting a SaaS company, should you prefer to sell to B2B or B2C companies? And if you would like to sell to both, how should you allocate your sales teams? If you were to hazard a guess about the share of B2C vs B2B companies, what would it be?
I often find myself wondering this question in a board room or reading through S-1s of soon-to-be-public companies. What are the demographics of the customer base and how are they reflected in the sales team?
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Our portfolio company Chorus.ai released the State of Conversational Intelligence 2020. The report uses data from 5m sales and customer calls to benchmark sales team performance.
There’s lots of great data in the report. Some of the data reaffirms rules of thumb. For example, the typical win rate of a sales qualified lead is 19%.
Other data points are surprising. For example, the average SDR dials 106 people to schedule one meeting.
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When I shared the Redpoint SaaS Metrics Template, I wrote about the difficulty I had identifying key engineering metrics. I was grateful for all the responses from leaders at many startups to share their expertise. I’ve updated the template with a few metrics.
Reliability - percent of application requests that load. 1 minus reliability is the percentage downtime. This measures the durability of the application.
Availability - percent of application requests that load within a certain latency.
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How much can a customer success manager manage? I'd heard the wisdom of $1-2M in ARR per year and around 80 accounts. But I hadn't come across any data. Last summer, Gainsight posted the results of their survey on the topic. The truth is most CSMs manage between $2-5M in ARR and somewhere between 10-500 accounts. But it varies by segment.
The charts above display Gainsight's data. I've reformatted them to compare segments side-by-side.
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How far along was the typical SaaS Series A in 2018? The median business was at $1.8M in ARR and growing at 250%. The chart below shows a representative sample of SaaS Series As’ ARR and projected ARR growth rate for 2018.
Breaking this down a bit more into quartiles, the ARR quartiles were:
25th 50th 75th 1.4 1.8 3.0 And the ARR growth rate quartiles were:
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A founder asked me recently if there were any trends in professional services across public SaaS companies. I had examined the gross margins and share of revenue from professional services about 3 years ago. Professional services are consulting fees software companies charge to customers for software configuration, customization and education. What has changed over the past 3 years?
First, we have more comprehensive data set, since many more companies have gone public.
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How quickly do the fastest growing software companies build their teams? The answer is incredibly quickly. In fact, this data bolsters the notion that management team's top priority is recruiting, especially after the business has reached product market fit and capitalized itself well.
Above, I've charted the headcount growth rate for 10 of the fastest growing software companies in recent history. I've normalized the years for when all the businesses were roughly at the same headcount - fewer than 50 people.
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Numbers provide us a certain certainty. With their precision, they offer a sense of black and white, in or out. But, metrics alone aren't enough. All the quantitative analysis in the world won't lead me to the next great idea for startup. Those figures can't create empathy, develop the right culture, or hire the right people. I've been thinking about this quite a bit because in both the recent Software Engineering Daily podcast I did with Jeff, and the presentation I gave at Launch Conference, the question of the limits of metrics surfaced.
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Earlier this week, I published benchmarks on [What Percentage Of Revenue Should SaaS Startups Spend On operating expense?](http://tomtunguz.com/how-much-should-spend-on-operating expense/) Several founders asked to see this data broken down further. What fraction of operating expense is spent on sales & marketing, and what fraction of op is spent on engineering? Most businesses spend 2x more on sales & marketing than engineering.
Looking at all publicly traded SaaS companies for four years before and four years after their IPOs, we see they spend about 40% of their operating expense on sales and marketing.
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What percentage of revenue should be spent on payroll? In 2001, Salesforce spent $35.6M on payroll and generated $5.4M in revenue. NetSuite spent $38M on payroll generated $17M in 2004. as both of these companies scaled and approached IPO, the operating expense ratio (OER) or operating expense divided by revenue, asymptotes to 0.8. For every dollar of revenue, both of these companies spent $0.80 in payroll at scale.
The OER is a metric of efficiency.
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At SaaStr 2016 and SaaS Office Hours in New York, I shared an analysis of the fastest growing SaaS companies over the last 3 years. In particular, I benchmarked the revenue, growth rates and round size characteristics of these businesses at their Series A. I've embedded the slides here.
Benchmarking Exceptional Series A SaaS Companies from Tomasz Tunguz These are the key bullet points from the deck about exceptional SaaS companies.
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Of the ten most important metrics on a startup's financial statements, revenue might seem to be the most important. But it isn't. Gross margin matters more because it is directly tied to a company's ability spend to grow and achieve profitability.
Imagine two startups, both selling products at $1M price points. The first has 5% gross margins and the second has 95% gross margins. The first company will be able to spend about $50k per sale on Sales & Marketing, Research & Development and general operational costs.
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In the past, we have benchmarked the revenue per employee of large publicly traded SaaS companies and determined that the average is about $200k of revenue per person. But, that analysis examined revenue per employee that only one point in time.
As Jesse Hulsing pointed out to me, examining this figure over five years reveals quite a bit about the health of the business. Jesse was kind enough to provide data on a handful of category defining enterprise companies, which I've used in this analysis.
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The WSJ published a recent chart of the 49 startups with billion dollar valuations. According to their research, there have never been as many privately held companies with such high valuations ever. The absolute number of these massively valuable companies alone is amazing. Ten years ago, most of them would have gone public by now. But what other insights can we tease from the data about these very special businesses?
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Bill Gurley and Fred Wilson have focused on burn rates as an important topic for startups. The immediate question that follows this commentary is: How much does the typical startup burn throughout its life? And what is a “risky” burn rate for a company?
I use a rule of thumb to evaluate the burn rate of a Series A startup. I multiply the number of employees by about $10-12k, depending on the location of the company.
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Yesterday, SAP announced it would acquire Concur for $8.3B, the single largest SaaS acquisition in history in dollar terms.
To put this acquisition in context, I looked at six other public-to-public acquisitions, where one publicly traded company acquired another. Because the acquired target is public, much of their financial information is readily available. As the chart above shows, the Enterprise Value/Trailing 12 Month Revenue (EV/TTM Rev) multiple SAP paid for Concur is tied for the highest among any public-to-public SaaS acquisitions.
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After reading a few of the S-1 analyses on this blog, an entrepreneur asked me to look into the balance sheets of public SaaS companies. More specifically, how much cash should SaaS hold? How much equity do they raise? And do they employ debt to grow?
The chart above shows the median cash on the balance sheet by year of founding for publicly traded SaaS companies. By its second year in business, the median SaaS company in this data has about $7M on its balance sheet at year two, from either the combination of a large seed round and Series A, or just a large A.
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Is there an optimal price for a product to maximize a SaaS startup's sales efficiency? As I've been analyzing the S-1s of publicly traded SaaS companies, most recently of HubSpot and Zendesk, I've been asking myself that question. Do million-dollar enterprise price points and field sales people create more efficient sales organizations than content-marketing-driven SMB startups? Or are the high-velocity inside sales teams of the pursuing the mid-market, the most efficient?
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Following this week's post Benchmarking HubSpot's S-1, Josh and Nikos raised an interesting question on Twitter. What are the right ways to benchmark SaaS companies from their early days through IPO? I have always used years-since-founding as the time axis to compare companies, because if I were a founder, that's how I might think about benchmarks. But after their comments I wondered if there were better ones.
Some potential alternatives are:
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According to the WSJ, GoPro is the largest consumer hardware IPO in 23 years, though like most entrepreneurs, I don't remember the Duracell IPO. The last consumer hardware company IPO I remember is Tivo, which was in 1999.
Because GoPro is the first sizable consumer hardware IPO in eons and because the startup world has a blossoming hardware segment, I thought it would be interesting to compare and contrast a top consumer hardware startup with the benchmarks of public SaaS companies using GoPro's S-1.
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Last week, the team at Wharton in San Francisco invited me to speak at the Entrepreneurs Workshop. I chose the topic of the “Five Forces Shaping the Fundraising Market” and prepared a Mary Meeker style presentation, with a chart and a bullet point on each slide, to illustrate the forces in tension. It was great fun.
I've embedded the slides from the presentation above and will link to the video once it's live.
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Several weeks ago, I wrote a post about the Optimal Contract Value for a SaaS company. I wondered whether startups serving enterprises might be more or less valuable than those serving small-to-medium businesses (SMBs). Interestingly, the data showed there was no optimal customer value to build a publicly traded SaaS company.
Having written that post, I began to wonder about other differences between different types of SaaS companies. In particular, do SaaS startups serving SMBs spend more or less than their counterparts in the mid-market and enterprise?
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Last week, we proved SaaS startups are raising more than they have in the past and newer SaaS companies seem to be generating more revenue per dollar invested. But do newer SaaS companies actually spend less on sales and engineering than their older counterparts?
In fact, the 2014 cohort of public SaaS companies spend more on sales & marketing and engineering than previous IPO cohorts. But this increased spend results in faster revenue growth and consequent higher revenue.
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If you visit Yahoo Finance today, type in the ticker of every SaaS stock, copy and paste the image into a document, you might create a chart that looks like the one above. A cursory glance at the plunging lines in most of these names might send you into a panic, only to tweet in alarm that the bottom is falling out of the SaaS market. Chicken little. Chicken little.
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Last week, we analyzed the fund raising history of billion dollar SaaS companies and determined SaaS startups are raising nearly twice as much capital as 16 years ago before going public. Given that trend, I wondered if there is there any truth to the idea that startups today require less capital than before to succeed.
To answer that question, I've taken the same basket of public SaaS companies and computed a revenue-on-invested-capital (ROIC) across the four 4-year IPO cohorts from 1998-2014.
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One of the cloud's great promise has been cost-reduction and for a while, we've chanted a mantra that startups require less capital than before to get started and ultimately succeed. As the number of publicly traded SaaS companies has grown with time, it's possible today to examine whether those statements are proven in the data, at least for those 41 publicly traded companies.
I've gathered the financing histories of the 41 publicly traded SaaS companies and adjusted them for inflation.
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Yesterday, Box filed for its IPO and released its S-1. I enjoy going through S-1s because quite a bit about a private company is revealed and though only a subset of information is released, the S-1 discloses some very important details about the business operations.
Over the past several months, I've analyzed the basket of the roughly 40 public SaaS companies many different ways. With the Box S-1 in hand, I can now benchmark Box's business against other publics, and in particular, SaaS companies nine years after founding.
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One way of measuring the efficiency of a company's revenue model is to benchmark revenue per employee. Google and Facebook, the two most efficient companies, generate $1M per revenue per employee per year.
Setting aside those exceptional cases and focusing instead on SaaS companies, the typical average revenue per employee is about $190k to $210k per year. The histogram above shows the ranges for publicly traded SaaS companies.
In the scatterplot above, which compares revenue per employee to revenues (in log10 scale), the outliers pop out.
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Raising money for a startup is expensive. The typical legal fees for a Series A are about 1% of the total money raised: roughly $40k on $4M. Of course, this doesn't factor in the time for the process and the dilution of the investment.
But if your startup is considering an IPO be prepared to pay eight times as much in fees. Across 360 venture backed technology IPOs in the last 10+ years which on average raised $107M, 8.
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Constrained by a limited budget while seeking to grow as quickly as possible, startup founders must decide how to balance growing their engineering teams with their sales & marketing teams. To help inform those decisions, I've benchmarked the relative sizes of the sales and engineering teams of the 36 publicly-traded SaaS companies from founding to IPO, typically 7 years later.
The graph above shows the average Sales & Marketing allocation in turquoise and Research & Development investment in red.
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In 2013, growth trumps all other considerations. For the average 2013 venture backed tech IPO, half of the startup's enterprise value is explained by its growth rate, while none of it is explained by profitability.
The market has spoken and startups have responded. Of the 25 IPOs I surveyed, both pending and completed, only 20% are profitable. On average, these startups operate at about -20% net income margins but are growing at 162% annually.
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There's an interesting phenomemon occurring in founder compensation for post-Series A companies: founding CEOs are swapping cash for larger equity stakes in their companies. Founding CEO salaries, post Series A, have fallen by about 24% while founder equity has increased by 32%.
This trend is broad. Each year, Redpoint portfolio companies participate in a compensation survey along with the portfolio companies of about 50 other firms, totaling about 800 startups. A third party pools the data to benchmark compensation trends across the executive functions in startups (CEO, VP of Product, VP of Marketing, VP of Sales, and so on) across the different financing series, locations, development stages and founders vs non-founders.
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There's a perpetual and roaring debate in Startupland about the ideal founding team. Should the ideal team be entirely computer scientists? How important to success is having an MBA/business person? What about the stories of billionaire dropouts?
To answer that question, I've aggregated the academic backgrounds of 30 of the top startups of the past few years and analyzed the make up of each of those founding teams.
Above is a chart comparing the number of “billion” dollar startups by the total number of founders and the share of technical founders.
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It’s an important question and one that arises most often as a SaaS startup scales. Churn, masked by growth, becomes a limiting factor of growth. How much should the business invest in managing churn? Our SaaS benchmarks from earlier this week tell us the average public SaaS company has a 3% monthly revenue churn or a 2 year lifetime and a sales efficiency of 0.8, which implies a 5 quarter pay back period on cost-of-sales and cost-to-serve.
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One number investors use to benchmark SaaS startups across sectors and industries is sales efficiency. There are a handful of variants of this metric, sometimes called the magic number, but ultimately they all aim to provide some sense of the incremental revenue returned by sales and marketing investment.
To make it more concrete, if a startup invests $500k in marketing and sales this quarter and generates $1M in incremental revenue, net of the cost to provide the service, for the next 12 months, the sales efficiency would be 2.
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One of the most frequent questions entrepreneurs ask me is how does their business compare to others? Benchmarking is a great tool, if you can get access to representative data. Pacific Crest and David Skok have released a fantastic survey benchmarking SaaS metrics for early and growth stage companies. The entire report is well worth reading. Below is my list of the six most important benchmarks and observations from that report.
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How much should your SaaS startup spend on sales and marketing? I’ve written about using unit economics and lead funnel performance to answer this question. Emulating the patterns of successful SaaS companies is another technique.
There are about 34 publicly traded SaaS companies that have published their revenue and sales & marketing expenses. Though their revenue growth rates are each unique, the sales and marketing spend patterns are quite similar. The revenue ramps of public SaaS companies follow the familiar exponential growth path.
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Over the past few years, there has been a pronounced shift in the seed market. VCs now participate quite actively in the market. As a result, seed investment volumes have roughly doubled in the past year.
But is the seed strategy working for startups and VCs? Do hugely successful businesses raise seed capital? Do those businesses include VCs in their seed rounds? And most importantly, do the VCs follow on in the Series A?
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With more than 80% of venture capital investments occurring in enterprise and with the public markets disproportionately rewarding SaaS companies with huge enterprise value-to-revenue multiples (median is 7.6), it’s no surprise that interest Software-as-a-Service is booming. After meeting quite a few SaaS companies, I’ve compiled a list of my ideal characteristics for a SaaS business below.
Characteristic 1: Product Is Core to the Operation of the Business The product is essential to the operation of a customer’s business.
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With the analytics tools today, it’s easy to measure hundreds if not thousands of different metrics for your business. Cutting through all the chaff to determine the most important or insightful metrics can be quite a challenge. Below are the ten metrics I’ve found to be most useful in board meetings. They answer the questions of how should a startup founder might measure the business at the highest level. You should have many more metrics than these, but I’ve highlighted the ones that I recommend presenting to your board and reviewing each week.