Category Archives: IPO

Thoughts on the Coupa S-1

It’s been a while since I dove into an S-1 and while I almost never get all the way through, here we go with another quick romp through a recent S-1.

Coupa, a ten-year old company that sells cloud-based spend management software and who pitches “value as a service” (ugh) recently filed its S-1.  Before diving in, I wonder if I should mention the potential irony in a company that sells “spend management” software running with a 40% operating loss.

But, remember the average SaaS business, per research from my friends at JMP, has negative operating margins at IPO time:  the median is -21% and the mean -36%.   So cheap jabs aside, Coupa is running a bit on the high side and, more importantly, in a time where I thought the markets were demanding better profitability than in the past.  That’s the interesting part.  From an operating margin perspective, Coupa is looking like a typical IPO in a market that was supposedly setting a higher bar.

Coupa’s most recent $80M private round put it in unicorn status (i.e., meaning that it was raised at a $1B+ valuation).

Estimating the shares outstanding after the offering is frankly quite confusing (e.g., share counts in the summary P&L seem to not include conversion of the preferred) and after spending 20 minutes trying to figure this out, I think there will be something like 180M shares outstanding after the offering.

Normally that might suggest a reverse split prior to IPO (as Talend recently did, an eight-for-one) but since I can’t find any evidence to suggest that, I’ll have to assume that Coupa and its bankers are bullish on valuation.  Otherwise, if I’ve got the right share count, any valuation less than about $1.8B will put them in single-digit stock price territory (which is the condition companies do reverse splits to avoid).

Highlights from the first pages of the S-1:

  • They connect 460 organizations (customers) with over 2M suppliers, globally
  • They estimate they have saved their customers $8B to date, on a cumulative basis
  • Fiscal year (FY) ends 1/31
  • FY15 revenues of $50.8M, FY16 of $83.7M, 65% YoY growth
  • FY15 net losses of $27.3M, FY16 of $46.2M, 68% YoY growth
  • 1H16 revenues of $34.5M, 1H17 of $60.3M, 75% YoY growth – accelerating

Now, let’s look at the income statement, which I’ve cleaned up and color-highlighted.


Income statement comments:

  • Approximately 90%/10% mix of subscription to services, generally good
  • $83.7M revenues in last full FY is appropriate IPO scale by recent historical standards
  • 75% accelerating YoY growth in 1H17 over 1H16 is pretty strong
  • Subscription gross margins running 77% to 80%, pretty standard
  • Services gross margins of -89% in FY16 and -59% in 1H17 are horrific.  Happily it’s only 10% of the business.
  • Overall gross margins run around 60%, which strikes me as a bit low, but according to my JMP data, is roughly on target
  • 1H17 R&D of 25% of revenues, at the mean
  • 1H17 S&M of 58% of revenues, 7% above the mean
  • 1H17 G&A of 17%, 4% below the mean – but after running at a shocking 32% in 1H16
  • 1H17 total opex of 100% of revenues, about 3% above the mean
  • 1H17 operating margin of -39%, about 3% below the mean

They also present a non-GAAP operating loss which I can’t easily benchmark. They define it as:  operating loss before stock-based compensation, litigation-related costs and amortization of acquired intangible assets.  There was about a $12.9M delta between GAAP and non-GAAP operating income in FY16, which reduces to only $3.8M in 1H17.

Back to highlights from the S-1 body copy:

  • They typically do 3-year contracts
  • They say “we rely heavily on Amazon Web Services (AWS)” as a risk in the risk factors
  • 29% of revenues from international in 1H17
  • They had a “material weakness” in their FY14 audit, unusual
  • 25 pages of risk factors in total, normal
  • They’ve raised $165M in venture capital, and have $80M in cash
  • Almost $7M in litigation costs in FY15
  • They claim an estimated LTV/CAC that exceeds 6.0 in each of the past 3 years
  • They do an interesting analysis of their 2013 customer cohort concluding that its contribution margin was -249% in FY13, but 75% in FY14-16. (Page 53.)
  • Average ARR/customer up from $138K in FY15 to $183K in FY16

Here are the quarterly numbers; things look pretty consistent except for 2QF15, where among other things, they had $7.5M in stock-based compensation expense.


More highlights

  • Operating cash burn of about $4M/quarter (page 67)
  • The CEO made $660K in cash comp in FY16, $320K and $340K bonus
  • The EVP of sales made $497K in cash comp in F16, $250K base and $247K commissions

Let’s take a closer look at the unicorn round:

  • It raised $80M at $4.18/share (page 119)
  • The beneficial ownership analysis (page 121) is based on 162.8M shares outstanding as of 7/31/16, but I believe excludes 61M shares associated with granted and un-granted stock options (page 43)
  • 162.8M + 61M = 223.8M shares on a fully diluted basis x $4.18/share = $935M
  • Not a unicorn you cry! ($935M < $1B)
  • But remember these claims are usually based on post-money valuation
  • $935M + 80M = $1.015B
  • So the math appears to hold up, but it’s also pretty clear Coupa was holding out for a valuation that squeaked them into the club

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Be sure to read my disclaimers.

Thoughts on Jeff Weiner’s “Pay No Attention to the Stock” Message

From everything I’ve heard for a long time, Jeff Weiner is a wonderful guy and great CEO.  In addition, LinkedIn is certainly a great company, so please don’t view this post as dissing either Jeff or the company.

I will say, however, that I found media coverage of Jeff’s now famous all-hands speech after the stock fell nearly 50% in a day (and the company lost $11B in market cap) to both be rather fawning and to miss one absolutely critical point.

Here’s the video:


What Jeff Got Right

  • He faced the issue directly.
  • He communicated quickly.  (Conveniently they seem to have biweekly all-hands meetings already in place which made that easier.)
  • He made good arguments (e.g., this happens in public markets; we are the same company we were yesterday, with the same vision and the same team; we are well positioned against macro trends)
  • He spoke with great delivery and articulation
  • He was authentic and sincere

What the Media Missed
Jeff’s basic message — when you strip to the core — is “ignore the stock price.”  This is absolutely the right message.  Markets are fickle, stocks go up and down seemingly without reason, markets over-correct punishing errors severely (particularly for companies price-for-perfection liked LinkedIn) — having worked at several public companies and often with insider status, I can assure you that (1) daily fluctuations are usually inexplicable from the inside and (2) employees will go crazy if they pin their emotions to the ups and downs of the stock market.  So the best advice is:  ignore it.

However, the place where most CEOs fail is that they only want to ignore the stock price when it goes down.  You can’t send emails celebrating* a big uptick, have a party when you break $50/share, or anything like that and then have an ounce of credibility when delivering the message that Jeff so successfully did.

I know Jeff Weiner is very smart, so I’m guessing that LinkedIn never put employee focus on the stock price on the way up, so Jeff’s message is credible on the way down.

But the question isn’t how beautifully your CEO can say “ignore the 50% drop in the stock price” the day after the stock goes down.  The question is what the CEO says and how he or she behaves on the way up.

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* I’m OK with celebrating IPOs as long as you celebrate liquidity and not the day-one stock uptick.  One way to see the day-one uptick is the amount of value left on the table that the company did not capture for itself in the IPO pricing process.  Some of that is normal and part of the process; too much of that is, well, nothing to celebrate.

The Great Reckoning: Thoughts on the Deflation of Technology Bubble 2.0

This post shares a collection of thoughts on what I’ve variously heard referred to as “the tightening,” “the unwinding,” “the unraveling,” or “the great reckoning” — the already-in-process but largely still-coming deflation of technology-oriented stock valuations, particularly in consumer-oriented companies and particularly in those that took large, late-stage private financings.

The Four Horsemen

Here are four key signs that trouble has already arrived:

  • The IPO as last resort.  Box is the best example of this, and while I can’t find any articles, I have heard numerous stories of companies deciding to go public because they are unable to raise high-valuation, late-stage private money.
  • The markdowns.  Fortune ran a series of articles on Fidelity and other mutual funds marking down companies like Snapchat (25%), Zenefits (48%), MongoDB (54%), or Dataminr (35%).  A unique feature of Bubble 2.0 is publicly-traded mutual funds investing in private, VC-backed companies resulting in some CEOs feeling, “it’s like we went public without even knowing it.”
  • The denial.  No bubble would be complete without strong community leaders arguing there is no bubble.  Marc Andreessen seems to have taken point in this regard, and has argued repeatedly that we’re not in a technology bubble and his firm has built a great data-rich deck to support that argument.

The Unicorn Phenom

If those aren’t sufficient signs of bubbledom, consider that mainstream media like Vanity Fair were writing about unicorns  and describing San Francisco as the “city by the froth” back in September.

It’s hard to talk about Bubble 2.0 without mentioning the public fascination with unicorns — private tech companies with valuations at $1B+.  The Google search “technology unicorn” returns 1.6M hits, complete with two unicorn trackers, one from Fortune and the other from CBInsights.  The inherent oxymoron that unicorns were so named because they were supposed to be exceptionally rare can only be lost in Silicon Valley.  (“Look, there’s something rare but we’re so special, we’ve got 130 of them.”)  My favorite post on the unicorn phenom comes from Mark Suster and is entitled:  Why I Effing Hate Unicorns and the Culture They Breed.

As the bubble has started to deflate, we now hear terms like formercorns, onceacorns, unicorpses, or just plain old ponies (with birthday hats on) to describe the downfallen.  Rumors of Gilt Groupe, once valued at $1.1B, possibly selling to The Hudson’s Bay Company for $250M stokes the fire.

What Lies Ahead?

While this time it’s different is often said and rarely true, I do believe we are in case when the unwinding will happen differently for two reasons:  (1) the bubble is in illiquid assets (private company preferred shares) that don’t trade freely on any market and (2) the owners of these illiquid shares are themselves illiquid, typically structured as ten-year limited partnerships like most hedge, private equity growth/equity, or venture capital funds.

All this illiquidity suggests not a bubble bursting overnight but a steady deflation when it comes to asset prices.  As one Wall Street analyst friend put it, “if it took 7 years to get into this situation, expect it to take at least 3.5 years to get out.”

Within companies, particularly those addicted to cheap cash and high burn, change will be more dramatic as management teams will quickly shift gears from maximizing growth to preserving cash, once and when they realize that the supply of cheap fuel is finite.

So what’s coming?

  • Management changes.  As I wrote in The Curse of the Megaround, big rounds at $1B+ valuations come wrapped in high expectations (e.g., typically a 3x valuation increase in 3 years).  Executives will be expected to deliver against those expectations, and those who do not may develop sudden urges to “spend more time with the family.”  Some CEOs will discover that they are not in the same protected class as founders when these expectations go unmet.
  • Layoffs.  Many unicorns are burning $10M or more each quarter.  At a $10M quarterly burn, a company will need to layoff somewhere between 200 and 400 people to get to cashflow breakeven.  Layoffs of this size can be highly destabilizing, particularly when the team was putting in long hours, predicated on the company’s unprecedented success and hypergrowth, all of which presumably lead to a great exit.  Now that the exit looks less probable — and maybe not so great — enthusiasm for 70-hour weeks may vanish.
  • Lawsuits from common stockholders.  Only recently has the valuation-obsessed media noticed that many of those super valuations were achieved via the use of special terms, such as ratchets or multiple liquidation preferences.   For example, if a $100M company has a $300M preference stack and the last $100M went in with a 3x preference, then the common stock would be be worthless in a $500M sale of the company.  In this case, an executive with a 0.5% nominal ownership stake discovers his effective ownership is 0.0% because the first $500M of the sale price (i.e., all of it) goes to the preferred shareholders.  When people find they’re making either “no money” or “car money” when they expected “house money,” disappointment, anger, and lawsuits can result.  This New York Times story about the sale of formercorn Good Technology provides a real example of what I’m talking about, complete with the lawsuits.
  • Focus will be the new fashion.  Newly-hired replacement executive teams will credit the core technology of their businesses, but trash their predecessors for their lack of focus on core markets and products.  Customers unlucky enough to be outside the new core business will be abandoned — so they should be careful to ask themselves and their vendors whether their application is central to the company’s business, even in a downturn or refocus scenario.
  • Attention to customer success.  Investors are going to focus back on customer success in assessing the real lifetime value of a customer or contract.  People will remember that the operative word in SaaS is not software, but service, and that customers don’t pay for services that aren’t delivering.  Companies that emphasized TCV over ARR will be shown to have been swimming naked when the tide goes out, and much of that TCV is proven theoretical as opposed to collectible.
  • Attention to switching costs.  There is a tendency in Silicon Valley to assume all markets have high switching costs.  While this is certainly true in many categories (e.g., DBMS, ERP), investors are going to start to question just how hard it is to move from one service to another when companies are investing heavily in customer acquisition on potentially invalid assumptions about long-term relationships and high pricing power.

Despite considerable turmoil some great companies will be born from the wreckage.  And overall, it will be a great period for Silicon Valley with a convergence to the mean around basics like focus, customer success, and sustainable business models.  The real beauty of the system is not that it never goes out of kilter, but that it always returns to it, and that great companies continue to be produced both by, and in cases despite, the ever-evolving Silicon Valley process.

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This post was inadvertently published on 12/23/15 with an incomplete ending and various notes-to-self at the bottom.  While I realized my mistake immediately (hitting PUBLISH instead of SAVE) and did my best to pull back the post (e.g., deleted the post and the auto-generated tweet to it, created a draft with a new name/URL), as the movie Sex Tape portrays, once something gets out in the cloud, it can be hard to get it back.

Kellblog Ten Predictions for 2015

As we move into the third week of January, I figured it was “now or never” in terms of getting a set of predictions out for 2015.  Before jumping into that, let’s take a quick review of how I did with my 2014 predictions and do some self-grading.

  1. 2014 to be a good year in Silicon Valley.  Correct.
  2. Cloud computing will continue to explode.  Correct.
  3. Big data hype will peak. Gartner seems to agree, placing it in August midway past peak on the way to trough of disillusionment. Correct.
  4. The market will be unable to supply enough data science talent. Mashable is now calling data scientist 2015’s hottest professionPer McKinsey, this is a problem that’s going to continue for the next several years. Correct.
  5. Privacy will remain center stage.  Correct.
  6. Mobile will continue to drive both consumer and (select) enterprise. I got the spirit correct on this one, but I think the core problem is probably better thought of as multi-device access to cloud data than mobile per se.  That is, it’s not about using Evernote on my phone, but instead about uniform access to my cloud-based notes from all my mobile (and non-mobile) devices. Basically, correct.
  7. Social becomes a feature, not an app. Correct again.  The struggles of companies like Jive only validate that (enterprise) social should be a feature of virtually all apps, and not a category unto itself.
  8. SAP’s HANA strategy actually works. Well SAP didn’t seem to agree with this one, when Hasso Plattner wrote a post blasting customers for not understanding its business benefits.  But my angle was more – the merits of the strategy aside – when a company the size of SAP shows total commitment to a strategy it’s going to get results.  And it has.  And SAP continues to drive it.  Mostly correct.
  9. Good Data goes public. While this didn’t happen, I continue to believe that Good Data has a smart strategy and a solid product.  They raised $25M in September.  Maybe this year they will make me an honest man.
  10. Adaptive Planning (now, Adaptive Insights) gets acquired by NetSuite. This didn’t happen, either.  The prediction was based on the fairly well known play of OEM-ing something before acquiring it.  Time may well prove me right on this one, but a swing-and-a-miss for 2014.

Our “bonus” prediction last year was that my company, Host Analytics, would have a great year and indeed we did.  We grew new subscriptions well in excess of 100%, making us, I believe, the fastest growing company in the category.  We launched a new sales planning solution as part of our vision to unite financial and operational planning.  We hired scores of great new people to join us on our mission to create a great EPM company, one that transforms how enterprises manage their financial performance.  And we raised $25M in venture capital to boot.

So, all in all, for the 2014 predictions, let’s call it 8.5 out of 11.

Here are my predictions for 2015.

  1. The good times continue to roll in Silicon Valley. If you feel “bubble,” remember that unlike in the dot-com days that most companies experiencing great success today have real, often recurring, revenue and real customers.   From a cycle perspective, to the extent there is a bubble coming, I’d say we’re in 1999 not 2001.
  1. The IPO as a down-round trend continues. One of the odder things about this time period is that I’m repeatedly hearing that successful IPO companies are pricing at down-rounds relative to their last private financings.  This doesn’t spell danger in general – because the public market valuations are both healthy and supportable – it just suggests a highly competitive later-stage private financing market is overbidding prices.  I suspect that will calm down in 2015 but down-round IPOs will continue in 2015.
  1. The curse of the megaround will strike many companies and CEOs. As part of the prior bullet companies are now often able to raise unprecedented amounts of capital at high valuations.  While those companies today may celebrate their $100M, $150M or $200M+ financing rounds, tomorrow they will wake up with a hangover that looks like:  huge pressure to invest that money for growth, even in dubious growth opportunities; anxious board members who need a 3x return in three years atop already stratospheric valuations; companies missing plan when the dubious growth opportunities don’t deliver; and CEOs who get replaced for missing plans that were unrealistic in the first place.  Before you take a megaround, be careful what you wish for — you sometimes get it.
  1. Cloud disruption continues. Megavendors will continue to wrestle cloud disruption and their cloud strategies.    They will continue to talk about success and high growth in the 10% or less of their business that is cloud, while asking investors to ignore the lack of health in the 90% that is non-cloud.  As part of a general Innovator’s Dilemma problem, they will be forced to explain and defend cloud strategies that will hopefully help them long term but depress results in the short term (as SAP had to do last week.)
  1. Privacy becomes a huge issue. People who were once too busy to care when Facebook changed their security setting are now asking who can access what and how.  The Internet of Things will only exacerbate this focus as more data than ever will be available.  In the past, you could see my pictures and status updates.  Now you can know where I am, when, how many hours I sleep at night, when I exercised, what temperature I set my thermostat to, and when I’m home.  The more data that becomes available, and the more readily you can be de-anonymized, the more you will start monitoring your privacy settings and previously unread site terms and conditions.
  1. Next-generation apps continue to explode. Apps like Slack and Zenefits will continue to redefine enterprise software.  While Slack is a technology, design, and integration play in the collaboration space, Zenefits is more of a business-model disruption play (i.e., give us the rather large commissions you rather invisibly paid your health insurance broker and we’ll give you free, high-quality HR software).  Either way, consumerization, design, and the search for new business models / revenue opportunities will continue.
  1. IBM software rebounds. IBM used to be a stronger player in software than it is today (e.g., recall that they invented the relational database). Watson aside, things have been pretty quiet on the IBM software front. Cloud-wise, while they claim to have a $7B business, it’s pretty invisible to me, and it does seem that Amazon has beaten them in low-level categories like IaaS.  While I’m not sure what happened – I don’t track them that closely – they do seem to have just faded away.  Once thing’s for sure – it can’t continue.  While there are contradicting stories in recent press, IBM does appear to be in the midst of a large re-organization, and I’m going to bet that, as a result, they come to market with a stronger software and cloud story.
  1. Angel investing slows. Much has been written about the financing chokepoint where tens of thousands of angels are funding companies that then need to get in line to get funded by the approximately 100 or so VCs who do A rounds.  The first-order result is that many companies think “wow this is easy” on raising a angel round only to die 12-18 month later when they fail to raise VC.  The second-order result, which I think will start kicking in this year, is that angel money will be harder to come by as the system corrects back to a balanced state.
  1. The data scientist shortage continues. With more “big data” and a huge supply of analytic tools and computing power, the limiting factor on analysis-driven business is neither data nor technology.  It’s our ability to find people who can correctly leverage it.  Tell every college kid you know to take lots of stats, analytics, and computing classes.  Or better yet, to go get a degree in data science.
  1. The unification of planning becomes the top meme in enterprise performance management (EPM). EPM has a long history of helping finance departments prepare annual operating budgets and financial reports, but increasingly—in recent years – planning has quietly decentralized to the various departments and divisions within the enterprise.  For example, sales ops increasingly builds the sales plan, marketing ops the marketing plan, and services ops the consulting and professional services plan.   (This is why I sometimes call this trend the “rise of the ops person” as they are increasingly acting as stealth FP&A.)  What’s needed is to unite all these plans and put them on a common planning framework so the CFO and CEO can do what-if analysis and scenario planning holistically across the organization.

It Ain’t Easy Making Money in Open Source:  Thoughts on the Hortonworks S-1

It took me a week or so to get to it, but in this post I’ll take a dive into the Hortonworks S-1 filing in support of a proposed initial public offering (IPO) of their stock.

While Hadoop and big data are unarguably huge trends driving the industry and while the future of Hadoop looks very bright indeed, on reading the Hortonworks S-1, the reader is drawn to the inexorable conclusion that  it’s hard to make money in open source, or more crassly, it’s hard to make money when you give the shit away.

This is a company that,  in the past three quarters, lost $54M on $33M of support/services revenue and threw in $26M in non-recoverable (i.e., donated) R&D atop that for good measure.

Let’s take it top to bottom:

  • They have solid bankers: Goldman Sachs, Credit Suisse, and RBC are leading the underwriting with specialist support from Pacific Crest, Wells Fargo, and Blackstone.
  • They have an awkward, jargon-y, and arguably imprecise marketing slogan: “Enabling the Data-First Enterprise.”  I hate to be negative, but if you’re going to lose $10M a month, the least you can do is to invest in a proper agency to make a good slogan.
  • Their mission is clear: “to establish Hadoop as the foundational technology of the modern enterprise data architecture.”
  • Here’s their solution description: “our solution is an enterprise-grade data management platform built on a unique distribution of Apache Hadoop and powered by YARN, the next generation computing and resource management framework.”
  • They were founded in 2011, making them the youngest company I’ve seen file in quite some years. Back in the day (e.g., the 1990s) you might go public at age 3-5, but these days it’s more like age 10.
  • Their strategic partners include Hewlett-Packard, Microsoft, Rackspace, Red Hat, SAP, Teradata, and Yahoo.
  • Business model:  “consistent with our open source approach, we generally make the Hortonworks Data Platform available free of charge and derive the predominant amount of our revenue from customer fees from support subscription offerings and professional services.”  (Note to self:  if you’re going to do this, perhaps you shouldn’t have -35% services margins, but we’ll get to that later.)
  • Huge market opportunity: “According to Allied Market Research, the global Hadoop market spanning hardware, software and services is expected to grow from $2.0 billion in 2013 to $50.2 billion by 2020, representing a compound annual growth rate, or CAGR, of 58%.”  This vastness of the market opportunity is unquestioned.
  • Open source purists: “We are committed to serving the Apache Software Foundation open source ecosystem and to sharing all of our product developments with the open source community.”  This one’s big because while it’s certainly strategic and it certainly earns them points within the Hadoop community, it chucks out one of the better ways to make money in open source:  proprietary versions / extensions.  So, right or wrong, it’s big.
  • Headcount:  The company has increased the number of full-time employees from 171 at December 31, 2012 to 524 at September 30, 2014

Before diving into the financials, let me give readers a chance to review open source business models (Wikipedia, Kellblog) if they so desire, before making the (generally true but probably slightly inaccurate) assertion:  the only open source company that’s ever made money (at scale) is Red Hat.

Sure, there have been a few great exits.  Who can forget MySQL selling to Sun for $1B?  Or VMware buying SpringSource for $420M?  Or RedHat buying JBoss for $350M+?  (Hortonworks CEO Rob Bearden was involved in both of the two latter deals.)   Or Citrix buying XenSource for $500M?

But after those deals, I can’t name too many others.  And I doubt any of those companies was making money.

In my mind there are a two common things that go wrong in open source:

  • The market is too small. In my estimation open source compresses the market size by 10-20x.  So if you want to compress the $30B DBMS market 10x, you can still build several nice companies.  However, if you want to compress the $1B enterprise search market by 10x, there’s not much room to build anything.  That’s why there is no Red Hat of Lucene or Solr, despite their enormous popularity in search.    For open source to work, you need to be in a huge market.
  • People don’t renew. No matter which specific open source business model you’re using, the general play is to sell a subscription to <something> that complements your offering.  It might be a hardened/certified version of the open source product.  It might be additions to it that you keep proprietary forever or, in a hardcover/paperback analogy, roll back into the core open source projects with a 24 month lag.  It might be simply technical support.  Or, it might be “admission the club” as one open source CEO friend of mine used to say:  you get to use our extensions, our support, our community, etc.  But no matter what you’re selling, the key is to get renewals.  The risk is that the value of your extensions decreases over time and/or customers become self-sufficient.    This was another problem with Lucene.  It was so good that folks just didn’t need much help and if they did, it was only for a year or so.

So Why Does Red Hat work?

Red Hat uses a professional open source business model  applied to primarily two low-level infrastructure categories:  operating systems and later middleware.   As general rules:

  • The lower-level the category the more customers want support on it.
  • The more you can commoditize the layers below you, the more the market likes it. Red Hat does this for servers.
  • The lower-level the category the more the market actually “wants” it standardized in order to minimize entropy. This is why low-level infrastructure categories become natural monopolies or oligopolies.

And Red Hat set the right price point and cost structure.  In their most recent 10-Q, you can see they have 85% gross margins and about a 10% return on sales.  Red Hat nailed it.

But, if you believe this excellent post by Andreessen Horowitz partner Peter Levine, There Will Never Be Another Red Hat.  As part of his argument Levine reminds us that while Red Hat may be a giant among open source vendors, that among general technology vendors they are relatively small.  See the chart below for the market capitalization compared to some megavendors.

rhat small fish

Now this might give pause to the Hadoop crowd with so many firms vying to be the Red Hat of Hadoop.  But that hasn’t stopped the money from flying in.  Per Crunchbase, Cloudera has raised a stunning $1.2B in venture capital, Hortonworks has raised $248M, and MapR has raised $178M.  In the related Cassandra market, DataStax has raised $190M.  MongoDB (with its own open source DBMS) has raised $231M.  That’s about $2B invested in next-generation open source database venture capital.

While I’m all for open source, disruption, and next-generation databases (recall I ran MarkLogic for six years), I do find the raw amount of capital invested pretty crazy.   Yes, it’s a huge market today.  Yes, it’s exploding as do data volumes and the new incorporation of unstructured data.  But we will be compressing it 10-20x as part of open-source-ization.  And, given all the capital these guys are raising – and presumably burning (after all, why else would you raise it), I can assure you that no one’s making money.

Hortonworks certainly isn’t — which serves as a good segue to dive into the financials.  Here’s the P&L, which I’ve cleaned up from the S-1 and color-annotated.

horton pl

  •  $33M in trailing three quarter (T3Q) revenues ($41.5M in TTM, though not on this chart)
  • 109% growth in T3Q revenues
  • 85% gross margins on support
  • Horrific -35% gross margins on services which given the large relative size of the services business (43% of revenues) crush overall gross margins down to 34%
  • More scarily this calls into question the veracity of the 85% subscription gross margins — I recall reading in the S-1 that they current lack VSOE for subscription support which means that they’ve not yet clearly demonstrated what is really support revenue vs. professional services revenue.  [See footnote 1]
  • $26M in T3Q R&D expense.  Per their policy all that value is going straight back to the open source project which begs the question will they ever see return on it?
  • Net loss of $86.7M in T3Q, or nearly $10M per month

Here are some other interesting tidbits from the S-1:

  • Of the 524 full-time employee as of 9/30/14, there are 56 who are non-USA-based
  • CEO makes $250K/year in base salary cash compensation with no bonus in FY13 (maybe they missed plan despite strong growth?)
  • Prior to the offering CEO owns 6.8% of the stock, a pretty nice percentage, but he was a kind-of a founder
  • Benchmark owns 18.7%
  • Yahoo owns 19.6%
  • Index owns 9.5%
  • $54.9M cash burn from operations in T3Q, $6.1M per month
  • Number of support subscription customers has grown from 54 to 233 over the year from 9/30/13 to 9/30/14
  • A single customer represented went from 47% of revenues for the T3Q ending 9/30/13 down to 22% for the T3Q ending 9/30/14.  That’s a lot of revenue concentration in one customer (who is identified as “Customer A,” but who I believe is Microsoft based on some text in the risk factors.)

Here’s a chart I made of the increase in value in the preferred stock.  A ten-bagger in 3 years.

horton pref

One interesting thing about the prospectus is they show “gross billings,” which is an interesting derived metric that financial analysts use to try and determine bookings in a subscription company.  Here’s what they present:

horton billings

While gross billings is not a bad stab at bookings, the two metrics can diverge — primarily when the duration of prepaid contracts changes.  Deferred revenue can shoot up when sales sells longer prepaid contracts to a given number of customers as opposed to the same-length contract to more of them.  Conversely, if happy customers reduce prepaid contract duration to save cash in a downturn, it can actually help the vendor’s financial performance (they will get the renewals because the customer is happy and not discount in return for multi-year), but deferred revenue will drop as will gross billings.  In some ways, unless prepaid contract duration is held equal, gross billings is more of a dangerous metric than anything else.  Nevertheless Hortonworks is showing it as an implied metric of bookings or orders and the growth is quite impressive.

Sales and Marketing Efficiency

Let’s now look at sales and marketing efficiency, not using the CAC which is too hard to calculate for public companies but using JMP’s sales and marketing efficiency metric = gross profit [current] – gross profit [prior] / S&M expense [prior].

On this metric Hortonworks scores a 41% for the T3Q ended 9/30/14 compared to the same period in 2013.  JMP considers anything above 50% efficient, so they are coming in low on this metric.  However, JMP also makes a nice chart that correlates S&M efficiency to growth and I’ve roughly hacked Hortonworks onto it here:


I’ll conclude the main body of the post by looking at their dollar-based expansion rate.  Here’s a long quote from the S-1:

Dollar-Based Net Expansion Rate.    We believe that our ability to retain our customers and expand their support subscription revenue over time will be an indicator of the stability of our revenue base and the long-term value of our customer relationships. Maintaining customer relationships allows us to sustain and increase revenue to the extent customers maintain or increase the number of nodes, data under management and/or the scope of the support subscription agreements. To date, only a small percentage of our customer agreements has reached the end of their original terms and, as a result, we have not observed a large enough sample of renewals to derive meaningful conclusions. Based on our limited experience, we observed a dollar-based net expansion rate of 125% as of September 30, 2014. We calculate dollar-based net expansion rate as of a given date as the aggregate annualized subscription contract value as of that date from those customers that were also customers as of the date 12 months prior, divided by the aggregate annualized subscription contract value from all customers as of the date 12 months prior. We calculate annualized support subscription contract value for each support subscription customer as the total subscription contract value as of the reporting date divided by the number of years for which the support subscription customer is under contract as of such date.

This is probably the most critical section of the prospectus.  We know Hortonworks can grow.  We know they have a huge market.  We know that market is huge enough to be compressed 10-20x and still have room to create a a great company.  What we don’t know is:  will people renew?   As we discussed above, we know it’s one of the great risks of open source

Hortonworks pretty clearly answers the question with “we don’t know” in the above quote.  There is simply not enough data, not enough contracts have come up for renewal to get a meaningful renewal rate.  I view the early 125% calculation as a very good sign.  And intuition suggests that — if their offering is quality — that people will renew because we are talking low-level, critical infrastructure and we know that enterprises are willing to pay to have that supported.

# # #


In the appendix below, I’ll include a few interesting sections of the S-1 without any editorial comments.

A significant portion of our revenue has been concentrated among a relatively small number of large customers. For example, Microsoft Corporation historically accounted for 55.3% of our total revenue for the year ended April 30, 2013, 37.8% of our total revenue for the eight months ended December 31, 2013 and 22.4% of our total revenue for the nine months ended September 30, 2014. The revenue from our three largest customers as a group accounted for 71.0% of our total revenue for the year ended April 30, 2013, 50.5% of our total revenue for the eight months ended December 31, 2013 and 37.4% of our total revenue for the nine months ended September 30, 2014. While we expect that the revenue from our largest customers will decrease over time as a percentage of our total revenue as we generate more revenue from other customers, we expect that revenue from a relatively small group of customers will continue to account for a significant portion of our revenue, at least in the near term. Our customer agreements generally do not contain long-term commitments from our customers, and our customers may be able to terminate their agreements with us prior to expiration of the term. For example, the current term of our agreement with Microsoft expires in July 2015, and automatically renews thereafter for two successive twelve-month periods unless terminated earlier. The agreement may be terminated by Microsoft prior to the end of its term. Accordingly, the agreement with Microsoft may not continue for any specific period of time.

# # #

We do not currently have vendor-specific objective evidence of fair value for support subscription offerings, and we may offer certain contractual provisions to our customers that result in delayed recognition of revenue under GAAP, which could cause our results of operations to fluctuate significantly from period-to-period in ways that do not correlate with our underlying business performance.

In the course of our selling efforts, we typically enter into sales arrangements pursuant to which we provide support subscription offerings and professional services. We refer to each individual product or service as an “element” of the overall sales arrangement. These arrangements typically require us to deliver particular elements in a future period. We apply software revenue recognition rules under U.S. generally accepted accounting principles, or GAAP. In certain cases, when we enter into more than one contract with a single customer, the group of contracts may be so closely related that they are viewed under GAAP as one multiple-element arrangement for purposes of determining the appropriate amount and timing of revenue recognition. As we discuss further in “Management’s Discussion and Analysis of Financial Condition and Results of Operations—Critical Accounting Policies and Estimates—Revenue Recognition,” because we do not have VSOE for our support subscription offerings, and because we may offer certain contractual provisions to our customers, such as delivery of support subscription offerings and professional services, or specified functionality, or because multiple contracts signed in different periods may be viewed as giving rise to multiple elements of a single arrangement, we may be required under GAAP to defer revenue to future periods. Typically, for arrangements providing for support subscription offerings and professional services, we have recognized as revenue the entire arrangement fee ratably over the subscription period, although the appropriate timing of revenue recognition must be evaluated on an arrangement-by-arrangement basis and may differ from arrangement to arrangement. If we are unexpectedly required to defer revenue to future periods for a significant portion of our sales, our revenue for a particular period could fall below  our expectations or those of securities analysts and investors, resulting in a decline in our stock price

 # # #

We generate revenue by selling support subscription offerings and professional services. Our support subscription agreements are typically annual arrangements. We price our support subscription offerings based on the number of servers in a cluster, or nodes, data under management and/or the scope of support provided. Accordingly, our support subscription revenue varies depending on the scale of our customers’ deployments and the scope of the support agreement.

 Our early growth strategy has been aimed at acquiring customers for our support subscription offerings via a direct sales force and delivering consulting services. As we grow our business, our longer-term strategy will be to expand our partner network and leverage our partners to deliver a larger proportion of professional services to our customers on our behalf. The implementation of this strategy is expected to result in an increase in upfront costs in order to establish and further cultivate such strategic partnerships, but we expect that it will increase gross margins in the long term as the percentage of our revenue derived from professional services, which has a lower gross margin than our support subscriptions, decreases.

 # # #

Deferred Revenue and Backlog

Our deferred revenue, which consists of billed but unrecognized revenue, was $47.7 million as of September 30, 2014.

Our total backlog, which we define as including both cancellable and non-cancellable portions of our customer agreements that we have not yet billed, was $17.3 million as of September 30, 2014. The timing of our invoices to our customers is a negotiated term and thus varies among our support subscription agreements. For multiple-year agreements, it is common for us to invoice an initial amount at contract signing followed by subsequent annual invoices. At any point in the contract term, there can be amounts that we have not yet been contractually able to invoice. Until such time as these amounts are invoiced, we do not recognize them as revenue, deferred revenue or elsewhere in our consolidated financial statements. The change in backlog that results from changes in the average non-cancelable term of our support subscription arrangements may not be an indicator of the likelihood of renewal or expected future revenue, and therefore we do not utilize backlog as a key management metric internally and do not believe that it is a meaningful measurement of our future revenue.

 # # #

We employ a differentiated approach in that we are committed to serving the Apache Software Foundation open source ecosystem and to sharing all of our product developments with the open source community. We support the community for open source Hadoop, and employ a large number of core committers to the various Enterprise Grade Hadoop projects. We believe that keeping our business model free from architecture design conflicts that could limit the ultimate success of our customers in leveraging the benefits of Hadoop at scale is a significant competitive advantage.

 # # #

International Data Corporation, or IDC, estimates that data will grow exponentially in the next decade, from 2.8 zettabytes, or ZB, of data in 2012 to 40 ZBs by 2020. This increase in data volume is forcing enterprises to upgrade their data center architecture and better equip themselves both to store and to extract value from vast amounts of data. According to IDG Enterprise’s Big Data Survey, by late 2014, 31% of enterprises with annual revenues of $1 billion or more expect to manage more than one PB of data. In comparison, as of March 2014 the Library of Congress had collected only 525 TBs of web archive data, equal to approximately half a petabyte and two million times smaller than a zettabyte.

# # #


[1]  Thinking more about this, while I’m not an accountant, I think the lack of VSOE has the following P&L impact:  it means that in contracts that mix professional services and support they must recognize all the revenue ratably over the contract.  That’s fine for the support revenue, but it should have the effect of pushing out services revenue, artificially depressing services gross margins.  Say, for example you did a $240K that was $120K of each.  The support should be recognized at $30K/quarter.  However, if the consulting is delivered in the first six months it should be delivered at $60K/quarter for the first and second quarters and $0 in the third and fourth.  Since, normally, accountants will take the services costs up-front this should have the effect of hurting services by taking the costs as delivered but by the revenue over a longer period.

[2] See here for generic disclaimers and please note that in the past I have served as an advisor to MongoDB

A Look at the Zendesk S-1 (IPO)

I thought I’d take a quick read of the Zendesk S-1 today, so here are my real-time notes on so doing.  Before diving in, let me provide a quick pointer to David Cummings’ summary of the same.

My notes:

  • 40,000 customers in 140 countries
  • 2012 revenues of $38.2M
  • 2013 revenues of $72.0M, 88% growth
  • 41% of revenues from international.  (High for a SaaS company at this size, but makes sense given their roots.)
  • Net loss of $24.4M and $22.6M in 2012 and 2013, -30% net loss in 2013
  • Zendesk approach:  beautifully simple, omni-channel, affordable, natively mobile, cloud-based, open, proactive, strategic.  They do this well.  (I’ve always viewed them as a very well run, low-end-up market entrant.)
  • Founded in Denmark in 2007.
  • 115M shares outstanding anticipated after the offering with seemingly another 40M in options under various options and ESOP plans.  (Seems like a lot of dilution looming.)
  • 65% gross margins.  (Though they don’t break out subscription vs. service which probably depresses things a tad.)
  • 20% of revenue spent on R&D.  (Normal.)
  • 52% of revenue on S&M.  (High, particularly for freemium which is notionally low-cost!)
  • 22% of revenue on G&A  (Normal to high, probably due to IPO itself.)
  • $53M in cash at 12/31/13
  • Headcount growth from 287 to 473 employees in year ended 12/31/13, up 68%
  • They have experienced security breaches:

“We have experienced significant breaches of our security measures and our customer service platform and live chat software are at risk for future breaches as a result of third-party action, employee, vendor, or contractor error, malfeasance, or other factors. For example, in February 2013, we experienced a security breach involving unauthorized access to three of our customers’ accounts and personal information of consumers maintained in those customer accounts.”

  • “[We are] highly dependent on free trials.”  (These guys define freemium model for enterprise software in my opinion.)
  • S&M org grew from 85 to 165 employees in period ending 12/31/13.
  • Owe $23.8M on a credit facility.  (Rare to see this much debt, but probably a smart way to reduce equity dilution.)
  • The three principles that drive the founders:  Have great products.  Care for your customers.  Attract a great team.  (Beats “Don’t Be Evil” any day in my book.)
  • Dollar-based “net expansion rate” (closest thing they discuss relative to renewals or churn):

    “We calculate our dollar-based net expansion rate by dividing our retained revenue net of contraction and churn by our base revenue. We define our base revenue as the aggregate monthly recurring revenue of our customer base as of the date one year prior to the date of calculation. We define our retained revenue net of contraction and churn as the aggregate monthly recurring revenue of the same customer base included in our measure of base revenue at the end of the annual period being measured. Our dollar-based net expansion rate is also adjusted to eliminate the effect of certain activities that we identify involving the transfer of agents between customer accounts, consolidation of customer accounts, or the split of a single customer account into multiple customer accounts. […] Our dollar-based net expansion rate was 126% and 123% as of December 31, 2012 and 2013, respectively. We expect our dollar-based net expansion rate to decline over time as our aggregate monthly recurring revenue grows.”

  • $66M accumulated deficit
  • Have data centers in North America, Europe, and Asia
  • 4Q13/4Q12 growth rate = 83% compared to 2013/2012 growth rate = 88%.  (Suggests growth is gently decelerating.)
  • Cashflow from operations in 2013 = $4.0M.
  • But they had -$24.1M in cashflow from investing activities.  (This is confusing because it’s a mix of items but broken into $12.4M in “marketable securities, property and equipment,” $7.1M to build data centers, and $4.7M in capitalized software development.  I’m not an accountant but if you ask me if “the business” is cashflow positive, the answer is no despite the $4.0M positive cashflow from operations. Building data centers and developing software, regardless of accounting classification, are all part of running the business to me.)
  • I am surprised they capitalize R&D.  Most software companies, far as I know, don’t.

zendesk common fmv


The FMV of the common stock is depicted above, by my math an annual 68% appreciation rate.

  • Huge number of leads are organic:  “the quarter ended December 31, 2013, 70% of our qualified sales leads, which are largely comprised of prospects that commence a free trial of our customer service platform, came from organic search, customer referrals, and other unpaid sources.”
  • SVPs listed (CFO, R&D) earn $240K base + $40K bonus
  • Automatic 5% share expansion / “overhang” built into the stock option and incentive plan.  Pretty rich in my experience and haven’t noticed anyone else doing it automatically before.
  • Letting execs buy stock with promissory notes … hum, I thought that went out with leg warmers.  Both loans were paid off by 12/31/31 and maybe that’s why.
  • CEO will own 7.1% of shares after the offering, including 4.3M (of the 8.1M beneficially owned) granted as options at the 2/14 board meeting.  (Seems odd to me; a huge option grant right before the IPO.  Hum.)
  • Nice banker line-up:  Goldman Sachs, Morgan Stanley, Credit Suisse, Pacific Crest
  • Raised $71M in preferred equity / venture capital
  • They do monthly, quarterly, and annual invoicing.  (Surprised they offer the short terms, particularly monthly.)
  • $6.5M in advertising expense in 2013
  • $11.4M in capitalized “internal use” software on the balance sheet at 12/31/13
  • They paid $16M for the Zopim (live chat) acquisition
  • Ticker symbol:  ZEN

Some Thoughts on Rocket Fuel, Their Voice, and Their Recent S-1

Silicon Valley is a place built by nerds, arguably for nerds, but once big money gets involved there is always tension between the business people and the technical people about control.  Think, for example, of the famous Jobs/Sculley falling-out back in 1985 where the business guy beat the technical guy.

However, in part because of events like that, the business people don’t always win.  In my estimation, there is a sort of “founder pendulum,” which swings with about a ten-year period between one end (where technical founders are “out”) and the other (where they are “in’).

Through most of the 2000s, founders were “out.”  There are two ways to tell this:  (1) you hear incessant griping about “founder issues” at Buck’s and at the Rosewood and (2) you see young PhD’s paired fairly early in the company’s evolution with business-person CEOs, often as a condition of funding.

Somewhere towards the end of the last decade, founders were “in” again.  This  makes me happy because I think engineers and scientists are the soul of Silicon Valley.  That’s why I had so much fun on the board of Aster Data.  And it’s why I like companies like Rocket Fuel.

Rocket Fuel was co-founded by Stanford computer science PhD George John and two fellow Yahoo colleagues in 2008.  John remains its CEO today.  I met him during my year-off in 2011 and was impressed, so I’ve kept an eye on the company ever since.

During the interim, the thing I most noticed about Rocket Fuel was its corporate personality.  Like Splunk, they do a great job of having a strong corporate voice.  Let’s look at some of the culture and communications that are part of this voice.

  • “The rocket scientists behind Rocket Fuel.”  (Turns out John actually worked for a while at NASA.)
  • “In 2008, a group of data savants came together.”
  • “Rocket Fuel is bringing hardcore science to the art of marketing.”
  • “Rocket Fuel has great machine-learning scientists”
  • Jobs titles like “Rocket Scientist” and “Chief Love Officer.”
  • A professorial founder with a great TEDx speech.
  • Strong recruiting videos on culture and science.  “Geek cult.”
  • The launching of (client-labelled) weather balloons from the Nevada desert at a company event.
  • A “nerdy, but loveable” culture (straight from the S-1 and beats “don’t be evil” any day in my book).
  • And, of course, a great puzzle recruiting billboard


I know that many Silicon Valley companies have odd job titles, geeky events, nerdy billboards, and a focus on recruiting great engineers.  Somehow, however, to me, Rocket Fuel comes off as both more mature and more authentic in this race.  These aren’t geeks trying to look cool, playing sand volleyball, and partying till dawn; these are geeks being geeks, and quite happily so.

I noticed when the company filed for an IPO back in August, but didn’t have time to dig into the (amended) S-1 until now.

Here are some takeaways:

  • Revenue of $44.6M and $106.6M in 2011 and 2012, 139% growth
  • Revenue of $39.6M and $92.6M in 1H12 and 1H13, 133% growth
  • Gross profit of $42.9M in 1H13, up from $17.6M in 1H12, with gross margin of 46%
  • R&D expense of $6.1M in 1H13, up from $1.5M in 1H12 and representing 7% of sales
  • S&M expense of $34.6M in 1H13, up from $15.5M in 1H12 and representing 37% of sales
  • G&A expense of $10.9M in 1H13, up from $2.6M in 1H12, and representing 11% of sales.
  • Operating loss of $8.8M in 1H13, up from $2.1M in 1H12, and representing 9.5% of sales
  • EPS of ($1.43) in 1H13, up from ($0.31) in 1H12

So the financial picture looks pretty clear:  really impressive growth, no profits.  Let’s take a quick look at how things are scaling.

rocket fuel scaling

  • Revenue growth is decelerating slightly as the more recent half-over-half (HoH) growth rate is slightly lower than the YoY
  • R&D expense is way up, growing 307% HoH.
  • S&M expense is up, but is scaling slight slower than revenue (as one generally likes) at 123%
  • G&A expense is way up, growing 319% HoH.  Let’s assume a lot of that is IPO-related.
  • Total operating expenses are growing at 163% versus revenue at 134%.  Usually, you like it the other way around.

The risk factors, which run nearly 20 pages, look reasonably standard and include risks from being able to file as an “emerging growth company,” implying more onerous disclosure, and the potential inability to comply, later.

The most interesting risks related to user rejection of 3rd party cookies, European Union laws, and potential “do not track” standards.  They cite customer concentration as a risk, but their top 20 customers in 2011 and 2012 accounted for (only) 39% and 38% of revenues.  They also cite access to inventory, which makes sense a threat to anyone in this business, particularly in the case of social media and Facebook FBX.

  • As of 6/30/13, the company had about 405 employees.
  • Prior to the IPO, the company has raised about $75M in capital.
  • The company will have 32.5M shares outstanding after the IPO.
  • The increase in the fair market value (FMV) of the stock, as shown in the option grant history table, is impressive.  That’s an 8.9x over the 18 months shown.

fmv rocket fuel

  • After the IPO, the three cofounders will own 10.7%, 9.0%, and 3.9% of the company, Mohr Davidow will own 35.1%, and Nokia will own 8.3% (assuming no exercise of over-allotment).

As per my S-1 tradition, I never get all the way through.  I stopped on page 125 of about what appears to be 185 or so pages.  If you want to dig through the rest of it, you can find the S-1 here.

In conclusion, I will say that I’m an enterprise software guy and don’t know a whole lot about the digital advertising business.  I believe that Rocket Fuel is both a middleman and an arbitrage play, that middlemen can sometimes get squeezed, and that the name of the game in arbitrage is consistently outsmarting the other guys.  So, in reality, I believe there’s more to the geek culture than simple fun:  it’s critical to winning in the strategy.

How this will end?  I don’t know.  Do I think George John can build one heck of a team?  You betcha.  Do the big guys against whom they compete have people as smart as Rocket Fuel’s?  Probably.  Are the big guys’ best-and-brightest working on this particular problem?  I don’t know.

(Often, in my experience, that is the difference.  It’s not whether company X has people as smart as startup Y; it’s where they’ve chosen to deploy them.  Even Facebook and Google have a bottom 20%.)

I do know that programmatic video advertising company recently sold for $405M to AOL and that YuMe had to reduce its IPO pricing, but then got off to a strong first day in the public markets (only to gradually drop and then rebound).  Are these clouds or silver linings?  I’m inclined to think the latter.

I hope things go well for the company going forward and congratulations to them for all the success they’ve had thus far.  #revengeofthenerds

See my FAQ for disclaimers.  I am not financial analyst.  I do not recommend buying, selling, or holding any given stock. I may directly or indirectly own shares in the companies about which I blog.