Category Archives: Startups

Some High-Tech Career Counseling Tips

I get a fair number of emails and calls from former colleagues and friends asking for career advice.  I’m always happy to provide it and the process of doing so is both thought-provoking and fun.  I have a learned a lot from having these conversations and have noticed a few patterns and principles in that process.

I’ll share them in this post.

  • You are responsible for your career development.   Some folks, particularly at larger companies, seems to think the onus is on the company to provide career development for you.  While I’d say it is indeed smart for larger companies to do this as a retention incentive, it does not change the simple fact that you and you alone are responsible for your career development.  You can use company-provided mentors, coaches, courses, rotations as help, but in the end — at the risk of sounding existentialist — you and you alone will have to live the results and ergo you and you alone are responsible for your career development.  Don’t confuse assistance with responsibility.
  • Brands matter.  People are going to look first at where you worked and then second at what you did.  So if you have an MIT MBA, then worked at Salesforce for 5 years, and then did 3 two-year stints at failed startups, it’s time to go to NewRelic or Zendesk or some other hot brand to polish up the resume.  You need to actively manage the brands on your resume.  It’s fine to take risks and if they work out well, then great.   A failed startup or two is a red badge of courage in Silicon Valley.  Just don’t get too many of them in a row.
  • Patterns matter.  To the prior point, everyone is looking for a pattern of success.  Success ideally meaning you had a growing and successful career at a growing and successful company.  Rising up a shrinking organization at a dying startup doesn’t do much for your CV.  Growing through an organization as a company goes from $10M to $100M does a lot.  Why?   Because companies want to hire people on upward trajectories who have experienced growth.  (Why?  Because invariably they are planning to grow and want you to help them do so.)
  • Do new things at your current employer.  Beware any employer willing to hire you to do something you haven’t done before, because in theory they shouldn’t be willing to.  If you look at the matrix below, companies will periodically give new opportunities to known performers in order to help develop and retain them.  But why would you ever hire a total stranger and pay them to learn on-the-job in doing something they haven’t done before.  When you move across companies you should plan on doing things you know how to do, and thus when you are at a company and performing well, you should be pushing to learn new things.

  • Don’t take job B and hope to switch into job A.  Because brands matter, people are sometimes tempted to join a great organization in a bad job.  “I’m really a product marketing director, but the only job they had open was competitive analyst, so I’ll take that and switch.”  There are two problems with this logic:  (1) the second you join the company as competitive analyst you are a competitive analyst (you’ll be the only person thinking you’re a slumming product marketing director), and (2) if you are not great at job B then you probably won’t be offered job A.  Sometimes people do this strategy and pull it off.  But at least understand the risk:  it’s a Hail Mary play if there ever was one.
  • Categories matter.  In addition, you need to manage the categories in which you work.  You might see yourself as a general software marketer, but if you’ve worked at BEA, Oracle, VMware, and Cloudera, the world is going to see you as a middleware / database / infrastructure person and you will have trouble finding, for example, jobs at SaaS applications companies.  Be mindful of the positioning you are creating by virtue of the categories you work in.  The world does not see you as a generalist.
  • Boxes matter.  Like it or not and for better and for worse, Silicon Valley — the valley of innovation — is incredibly “in the box” when it comes to hiring.  Companies want to hire experienced people in known roles.  This means you need to be careful in managing your career because sometimes companies create unusual roles (e.g., chief of staff, certain CTO roles, certain VP individual contributor roles, various special project roles) that might leverage your strengths and meet your interests but end up damaging your resume.  While it can be fun to spend some time out of the box, be careful that you end up on no headhunters to-call list.  Put in reverse, how many people are going to to call a headhunter and say “get me a senior product manager out of Salesforce” vs. “get me a interdepartmental facilitator at Unicornia.”  Some new roles (e.g., sales productivity) get institutionalized and become “normal” over time.  Most don’t.
  • Take the time to network, but with the intent to do your job better (e.g., best practice sharing), not with the intent to find your next job.  If there’s no obvious “club” at which to do so, then make your own.  One of my CMOs called our board members for referrals and created a portfolio-company CMO club that met once/month to share best practices.   You’ll get both better connected and, more importantly, better at your job.
  • Don’t be too busy to learn.  Read books, attend webinars, and ask to attend executive executive programs.  (If you can get your company to pony up, the executive education programs offered by the Stanford Graduate School of Business are excellent.)
  • Make VCs money or go to Stanford.  To the extent you want work at and/or found startups, remember my (only half-joking) view of how VCs view people, below.  The moral is that one of the best opportunity-creators you can have is a VC for whom you’ve made money.  So get to know the VCs on your board if you can — and yes, don’t forget to make them money (and yourself some in the process).  Either that or go to Stanford.  Ideally, both.  :-)

vc people view

A Review of SalesHood by Elay Cohen

I recently completed SalesHood by my former Salesforce colleague Elay Cohen and wanted to do a quick book review in this post.

Net/net:  I think SalesHood, along with Predictable Revenue (by another former Salesforce leader Aaron Ross) are two of the best books out there on contemporary business-to-business high-technology sales. Between these two books, you can capture decades of valuable experience in building and leading sales teams (SalesHood) as well as in building “the machine” that drives opportunity creation for them (Predictable Revenue).

Over the past decade enterprise technology sales has changed radically – in fact, the only discipline that has changed more is marketing which has (happily) transformed from largely unaccountable black art to highly-accountable demand generation science.

At Salesforce Elay ran, among other things, arguably the best sales productivity programs in the business. As such, SalesHood contains not only a lot of great Salesforce best practices, but also a healthy dose of Salesforce culture. For example, Elay says to “start with values” – which is very aligned with the Salesforce culture and the V2MOM (vision, values, methods, obstacles, metrics) planning framework.

Overall, I would describe SalesHood as less ground-breaking and more best-practice-sharing. If you’ve somehow missed the changes in sales over the past decade (e.g., say you’re a rep at IBM or SAP), then the book is a must-read to catch you up with the state of the art. On the flip side, if you’ve been working at a leading startup, I’d still recommend SalesHood not so much as to introduce you to a slew of new ideas but so as to help you structure and organize them.

Some of Elay’s advice is sales motherhood and apple pie (e.g., always be hiring, compete with intensity, win as a team, it’s all about first-line sales management). Good sales people and sales managers can never get enough repetition of these basics and a book like SalesHood can be used to drive them into your culture and get everyone on the same page.

In other areas, Elay offers fresh takes on old problems. I particularly liked:

  • The sales huddle concept, frequent small team meetings to focus on key topics that arise during the quarter.
  • The general concept of more social/peer-led sales training. Death to death by corporate PowerPoint!
  • The chapter on story-telling, where the only twist I’d add is to challenge the customer during the exercise – the relevancy of a story is defined in the mind of the customer, not the salesrep.
  • Elay’s (and Barry Rhein’s) thoughts on curiosity and why it matters so much in sales.  Genuinely curious salespeople sell more – and get blind-sided less — than their non-inquisitive counterparts.

To wrap it up, even though I was familiar with many SalesHood concepts, I found the book a great synthesis of them, along with some great new concepts thrown in.

Host Analytics Raises $25M to Fuel Aggressive Growth

Last week we announced that we had successfully closed a $25M round of financing and received some pretty good coverage in the media, including this story in TechCrunch, this story in Talking Cloud, and this one in the Silicon Valley Business Journal.

In this post, I thought I’d offer a few thank-you’s and share a little perspective on the round.

First, the thank-you’s:

  • Thanks to our amazing customers who entrust us with helping them solve their financial planning, budgeting, forecasting, consolidation, and reporting challenges.  Without you, nothing else happens.
  • Thanks to our fantastic partners who help us deploy within customers, co-market with us, and refer us into new opportunities.
  • Thanks to the wonderful employees who constitute the Host Analytics team.  We have done amazing things in the past two years and will do even more amazing ones in the two years to come.
  • Thanks to our superb investors for having faith in the company, the market opportunity, and the team.  And a special thanks to our new investor Centerview Capital, who led the round and with whom we very excited to work to build a market-defining company.

In terms of perspective, here are some thoughts:

  • We believe that Host Analytics is the fastest-growing company in the cloud EPM space.  This year we will grow new subscriptions at over 120%.  This validates that the strategic and operational decisions we have made over the past two years have been correct, if not always obvious.
  • I am proud that we have driven this success by focusing on the customer.  While at least one competitor competes heavily on the basis of chest-thumping and corporate FUD, we have competed based on customer focus and on a consultative approach to solving business problems.  This isn’t easy to do — it requires both deep category knowledge and a strong constitution.  And  while we routinely get broad-sided, we do not let that distract us from our focus on solving the customer’s problem.  I often tell the team to forget the competition and follow the advice from the secret advocate in Disclosure:  “solve the problem.”
  • We have a huge opportunity before us to unite financial and operational planning.  Over the past decade, a lot of work that was traditionally done by the financial planning and analysis (FP&A) department, has silently moved outside finance and into the operations.  Salesops does sales forecasting, commission forecasting, territory management, and quota-setting.  Marketingops does marketing budgeting, lead forecasting, and pipeline coverage analysis.  Servciesops does services planning, forecasting, and margin analysis.  The good news is that businesses are more data-driven than ever.  The bad news is that all these teams are disconnected from finance and the financial planning system.  There is a big opportunity to bring this all back together and put the E (enterprise) back in EPM.  We are going to lead the market in pursuing that opportunity.

Thanks to everyone who has helped make our progress thus far possible.  I believe the next two years are going to be even better than the past two.

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:

JMP

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.

# # #

Appendix

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.

# # #

Footnotes:

[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

Why I’m Against Succession Planning at Startups

I have to admit I’m not a fan of succession planning in general, at startups in particular, and especially when the successee is involved in the process. Why? Because the process quickly ends up presumptuous and political.

In my experience, the successee is more concerned with being a “good guy” on the way out than with what’s best for the business. Consider the retiring CFO of a $500M company. Eighteen months before he wants to retire, he starts succession planning, picks his favorite division-level finance chief, anoints her the chosen one, and starts the grooming process (“one day all this will be yours”). The chosen one starts showing at meetings to which she’s not usually invited, and demonstrates some new swagger with peers.

The CFO eventually retires and the CEO and board replace him not with the chosen one, but with an experienced CFO coming from a $2B company. Feelings are hurt, strong performers are demotivated, and hub-bub generated — all for nothing. The chosen one didn’t even make the first cut of requirements in the job spec. The retiring CFO didn’t (and shouldn’t) get a vote.

The thing to remember with startups (and high-growth companies in general) is that you don’t want to hire the person you need now; you want to hire the person you need three years from now. And the odds that the person you need three years from now is working for the current boss today are pretty low. Put differently (and most certainly when going outside for a hire), the job should grow into the person; the person shouldn’t grow into the job.

The default succession plan for almost any startup executive – including the CEO – is therefore to go hire someone from outside who’s overqualified for the current job. If you wonder why someone overqualified would take the job … well, that’s why the Gods created stock options.

Before you think I’m an anti-career-development cretin, this is not to say that companies should always go outside to backfill key roles. Sometimes people are able to grow within fast-growing organizations. I myself did this as I rose from technical support engineer to director of product marketing over 7 years at a company that grew from $30M to $240M along the way. So I’m all in favor of it; it just doesn’t happen very often. And more often than not, managers who consistently only want to promote from within are actually saying they’re afraid to go outside and find strong direct reports who will challenge them. Remember, I’m talking about patterns and rules here; there will always be exceptions.

The reality is in high-growth startups, just “holding on” to your current management or executive job is both hard enough and a big growth opportunity. Running product management, sales, or HR at $10M is quite different from running it at $300M. During my tenure at Business Objects, as we grew from $30M to over $1B in revenues, only one other team member and myself “held on” during that growth. Out of about 15-20 people that made up the broadly defined leadership team, every other person got replaced, sometimes two or three times, along the way.

That’s why I think succession planning – making plans for how to replace Jane when Jane is healthy, happy, and doing a great job for the company – is a waste of time. Let’s keep Jane focused on growing the business, which is hard enough. If she gets hit by the proverbial bus, well, let’s just deal with that when it happens. We pretty much know what we’re going to do anyway (i.e., call a recruiter).

The best argument against my viewpoint is the case we’ll call Marty. Let’s say Marty would be a great candidate for the CFO job. He’s a great controller, has great leadership skills, and strong business sense — but hasn’t spent much time in FP&A. After Jane gets hit by the bus, we might think “darn, Marty would have been great if we’d moved him into FP&A last year to develop him.”

My two-part response to this is:

  • Yes, sometimes it makes sense and if Marty’s got his act together he’ll be pushing for the FP&A job if it opens up along the way — best developing himself and positioning himself for any eventual CFO opportunity. Since there is always risk associated with any outside hire, Marty should pitch that the risks associated with him learning the job are less than those associated with taking a new person into the organization.
  •  The decision whether to give Marty the job will come down to how fast the company’s growing and whether the company is better off with a talented-but-rookie FP&A head, an internally promoted FP&A manager, or a veteran outsider. Yes, we want to help develop Marty, but if the company’s growing super-fast, then just “hanging on” should provide plenty of development and financial benefit (i.e., stock option appreciation) for him along the way.

Some would note that if we turn down Marty for the FP&A job, he may quit because he feels he has no opportunity for career growth. I understand; I quit a job myself once for that very reason. But I did so in an environment where company growth had stalled and I wasn’t going to get either financial reward or career development for sticking around. If the company is growing fast, then Marty will get both. If it’s not, most of the principles I describe here don’t apply because this post is about succession planning at startups and high-growth companies.

In fact, succession planning makes a lot of sense at low-growth companies, where the organization is static and people move through it. If you want to retain your people over time, you better think about those career paths, and rotate your Marty’s through FP&A to keep them having fun and learning. And, in those environments, the best person to take over for the retiring CFO might well be one of his/her direct reports (and dangling that opportunity might well help retain a few of them along the way).

The real problem is when big company types come to a high-growth company and say “let’s do succession planning (because we did it at my last company and it’s just something that one does)” – and nobody asks why.

Most of the time, in a high-growth startup, it won’t make sense. Or, if you make a succession plan, it will simply be 1-800-HEIDRICK, 1-800-DAVERSA, or 1-800-SCHWEICHLER.

Strategic Focus: I’m Just Trying to Get My Space Together

As a long-time Grateful Dead fan, I have to say that I was advantaged in understanding how the Blown to Bits problem would affect digital media businesses.  You see, for years, the Dead had changed the business model of the music industry, choosing to use “albums” as a loss leader and choosing to make money on live concerts, playing some 2,300 concerts together, not to mention those done individually be band members. (Think:  Jerry Garcia at the Keystone Berkeley.)

steal your face

The Dead even had a “tapers” section at most concerts and sometimes could be heard literally stopping the show to allow someone to move back their microphones.  The Dead have a valid claim to “we did Freemium 30 years before Freemium was cool.”

While I won’t go as far to say that Everything I Learned about Business, I Learned from the Grateful Dead (a good book, by the way, that takes a top ten set of lessons from “the long, strange trip”), I do believe the Dead were both musical and business model innovators.

Improvisation as strategy was profiled in Competing On The Edge:  Strategy as Structured Chaos, published by Harvard Business School press.  Excerpt:

The Grateful Dead met this challenge through improvisation […] as distinguished by two key properties:  first, performers intensely communicate with each other in real time […] second, they rely on a few very specific rules, such as who plays first, what are the permitted chords, and who follows whom.

While I’m riffing on the Dead, I should probably also mention Marketing Lessons from the Grateful Dead, a great booking on topics like community, branding, customer centricity, teamwork, category creation, technological innovation, disruptive business models, disintermediation, and giving back.  The Dead, indeed, were innovators in all these areas and the book is well worth reading.

My favorite Dead-related quote, however, comes not from that book but  from The Grateful Dead Movie, in a famous scene where a completely zonked head is ambling around outside the concert and tells a security guard the inimitable:

“I’m just trying to get my space together, so that I can go into the show.”

..

I always think of this guy whenever I talk to a startup about strategy.  Why?  Because startups are very much about trying to get your space together.

  • What space do you want to be in?
  • Against whom do you want to compete?
  • Where do you draw the boundaries on your space?
  • What adjacent spaces, if any, do you want to incorporate into your space?
  • In what adjacent spaces do you want to partner?
  • How do you see the boundaries on your space evolving over time?

My meta-answer to these questions is “the world is a very large place.”  How does that relate?  In two ways.  It means first that you better define your space in such a way that you are truly world-class within it — and not using world-class as a nice sounding compound adjective, but really grokking its meaning:  what can truly be best in the world at doing?  Second, it means that because the world is a big place that you can turn what might appear to be a small niche into a  very big business if you are truly the best at it in the world.  So don’t be afraid to focus.

Most startups forget focus too early and delude themselves into thinking they can be world-class in across a number of areas.  Take enterprise performance management (EPM) — the space in which Host Analytics competes –for example.  EPM is a $4B market for financial analytic applications that is adjacent to the broader $13B business intelligence (BI) market.  Some of our competitors consider themselves addressing the (incorrectly calculated) “$33B BI market” and are either building or acquiring products in the broader BI space?  It sounds good from a total available market (TAM) perspective.  Wow!  You’ve tripled your TAM.

But think for a minute — what are the odds that  your cheaply-acquired or hastily built BI tools are world-class?  None.  So all you’ve really done is dilute your focus on EPM by complementing it with some third-tier BI.  A far better solution (and the one we follow at Host Analytics) is to partner with someone else who is spending all their energy focused on being world-class in the adjacent space.  In our case, that partner is Birst who is focused on being world-class at cloud BI.

So if you’re thinking of starting a company, ask yourself:  what can we really be world-class at doing?

Answering that question is the only way to get your space together, before you go into the show.

Burn Baby Burn: A Look at the Box S-1

I’m pretty busy this week so I was hoping not to dive into the Box S-1, but David Cummings’ excellent summary served only to whet, as opposed to satiate, my appetite.

Perhaps it was the $168M FY14 operating loss.  Maybe it was the $380M in financing raised during the last three years.  Or the average quarterly burn rate of $23M.  But somehow, I got sucked in.

I just had to know their CAC ratio.  Of course, it’s not going to be easy to calculate.  While they give us quarterly S&M expense, that’s only half the equation; we’re going to have a figure out –as best we can — quarterly new annual recurring revenue (ARR).

Billings as a Sales Metric

While many SaaS companies don’t disclose “billings,” Box does — but on an annual basis only — in their S-1.

[Click on the images to see full size.]

box billings

..

Billings is an attempt to triangulate on new sales (or bookings) in a SaaS company.  The standard way to calculate billings is to add revenue plus change in deferred revenue.

The idea is that if you want to know how “sales” went during a given period, then revenue is not a great indicator because, in a SaaS company, revenue is an indicator of how much you sold in prior periods, not the current one.  So you look at deferred revenue trying to pick up the volume of new orders.  The problem is that things quickly get very complicated because (1) deferred revenue is moving both down (as past deals convert into revenue) and up (as new deals are signed) and (2) deferred revenue itself is limited only to deals that are prepaid — if a company does a constant business volume but suddenly starts doing a lot of two-year prepaids, then deferred revenue will skyrocket and if, for example, hard economic times drive loyal customers to ask for bi-annual billing, then deferred revenue will plummet, all without any “real” change in underlying subscription business.  In addition, multi-year non-prepaid deals are invisible from a deferred revenue perspective (because there’s nothing, i.e., no cash prepayment, to defer).

In short, any metric built upon deferred revenue is only as a good as deferred revenue at reflecting the business.

To demonstrate the relationship between billings and new ARR, I built a model which assumes a SaaS company that starts from scratch, increases new ARR added each quarter by $500K (i.e., $500K in its first quarter, $1M in its second, $1.5M in its third), does only one-year prepaid deals, and has a 90% renewal rate.  Here’s what happens.

(You can download the spreadsheet with Box financial summary and the full version of the model here.  Be sure to download as an Excel file, not a PDF.)

generic model

..

While in year one, billings is equivalent to new ARR, as you build up the renewals base, it contributes more to revenue and muddies thing up.  For a company of the above size, growth, and renewal rate, the ratio of new ARR to billings ends up 0.4.

When you take this same model and (manually) force fit the new ARR numbers to try approximate Box’s revenue and billings from 2012-2014, you get:

box like model

..

A CAC of ~1.6

In this case (and given my assumption set) you end up with a new-ARR/billings ratio of 0.6.  To make life easier, I also calculated a new-ARR/revenue ratio (see the full sheet), which ends up around 0.8.  I’ll use to this number to calculate my CAC, which comes out to between 1.5 and 1.8.  While not quite an idyllic 1.o to 1.2, it’s well below 2.0 and helps explain why Box has been able to raise so much money:  their growth has been deemed scalable.

Billings = Ending ARR

In reviewing my models, it’s hard not to notice that billings for a period equals ending ARR for that period.  This turns out to be true under my assumption set of subscription-only (no services), one-year deals only, and everything pre-paid.  Why?  Because for any deal taken at any point during the year, we will recognize some percent of it (X) and the rest (Y) will go to deferred revenue.  The difference between X and Y changes across the year but X+Y= the deal size at all times.

This is not true when you have consulting or do multi-year prepaid deals (which can make billings > ending ARR).  It’s also not true when you do semi-annual billing (which can make billings < ending ARR).

If you assume for any given company that these factors are roughly constant, then even though uniformly inaccurate, it does provide a simple way to approximate new ARR:  take the difference in ending ARR two periods, add a churn assumption, and bang you have new ARR during the period.

Key Metrics, Cashflow, and the P&L

Here are some summarized key metrics (using yellow to highlight points of interest).

box key metrics

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Of note:

  • Year over year growth, while high at 97% is slowly decelerating.
  • Gross margins are nice at nearly 80%
  • Operating expenses are massive:  278% of sales in 1Q12 down to “only” 182% in 4Q14.
  • S&M expense are a seemingly very high 121% of revenues.  This looks bad, but to really know what’s going on we need to examine the CAC, which looks pretty good.
  • Return on sales is -112%
  • That burn rate sure grabs you:  $22M per quarter

In many ways you see a typical “go big or go home” cloud computing firm, burning boatloads of cash but acquiring customers in a reasonably efficient manner and doing a nice job with retention/cross-sell/up-sell as judged by their retention numbers. When you look big picture, I believe they see themselves in a winner-take-all battle vs. DropBox and in this case, the strategy — while amazingly cash consumptive — does make sense.

Here is  a look at cashflow and billings:

box cashflow and billings

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And last, but certainly not least, here is the P&L:

box p+l

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Of note:

  • I’m always amazed  by the R&D spend of seemingly simple consumer services.  They spent $46M in R&D last year … on what?
  • The $171M in S&M expense sure grabs your attention
  • As does the $168M net loss!

Burn baby burn!

[Revised and expanded 3/27/14 9:18 AM]

# # #

I am not a financial analyst.  I do not make buy, sell, or hold recommendations on stocks.  See my FAQ for affiliations and disclaimers.

To Pre-Meet Or Not To Pre-Meet: That Is The Question

I once asked one of my board members which CEO ran the best board meetings across his portfolio companies.  His answer was, let’s call him, Jack.  Here’s what he said about him:

  • Jack got the board deck out 3-4 days in advance of the board meeting
  • Jack would call him — and every other board member — 2-3 days before each board meeting and walk through the entire deck and answer questions, taking maybe 2 hours to do so.
  • Board meetings with Jack would go very quickly and smoothly because all the questions had been asked in advance.

When I heard this, I thought, well, I have a few issues with Jack:

  • He spends a lot of time managing his board instead of running his business.  (I guess he got his CEO job by managing-up.)
  • He completely violates my “do it in the meeting” principle by having a series of pre-meetings before the actual meeting.

While I may have my doubts about Jack, others don’t seem to.  Consider entrepreneur and VC Mark Suster’s recent post, Why You Shouldn’t Decide Anything Important at Your Board Meetings.  Suster straight out recommends a 30 minute pre-meeting per board member.  Why?

  • Agenda input so you can adhere to the Golden Rule of Board Meetings:  “no surprises.”
  • So you can “count votes” in advance as know where people stand on important and/or controversial issues.
  • So you can use board members to convince each other of desired decisions.
  • Ultimately, because in his opinion, a board meeting is where you ratify decisions that are already pre-debated.

OK, I need to chew on this because, while practical, it violates every principle of how I think companies should conduct meetings — operational ones, at least.  When it comes to operational meetings, nothing makes me grumpier than:

  • Pre-meeting lobbying
  • Post-meeting “pocket vetoes”

My whole philosophy is that meetings should be the place where we debate things and make decisions.  Doing everything in advance defeats the purpose of meeting and risks encouraging political behavior (e.g., “if you vote for my bridge in Alaska, I’ll vote for your dam in Kentucky”), with managers horse-trading instead of voting for ideas based on their merits.

The only thing worse that teeing up everything in advance is what one old boss called the “pocket veto,” where a manager sits in a meeting, watches a decision get made, says nothing, and then goes to the CEO after the meeting and says something akin to “well, I didn’t feel comfortable saying this in the meeting, but based on point-I-was-uncomfortable-raising, I disagree strongly with the decision we reached.”

I remember this happened at Business Objects once and I thought:  “wait a minute, we’ve flown 15 people from around the world (in business class) to meet at this splendid hotel for 3 days — costing maybe literally $100,000 — and the group talked for two hours about a controversial decision, came to resolution, and made a decision only to have that decision overruled the next day.”  It made me wonder why we bothered to meet at all.

But I learned an important lesson.  Ever since then, I flat refuse to overrule decisions made in a meeting based on a pocket veto.  Whenever someone comes to me and says, “well, I didn’t feel comfortable bringing it up in the meeting (for some typically very good sounding reason about embarrassing someone or such), but based upon Thing-X, I think we need to reverse that decision,” I say one thing and only one thing in response:  “well, I guess you should have brought that up in the meeting.”

You see, I believe, based on a bevy of research, that functional groups of smart people make better decisions than even the smartest individuals.  So my job as CEO is to then assure three things:

But I’ve got a problem here because while we know that boards like pre-meetings, operationally I am opposed to both pre- and post-meetings.  Would it hypocritical for to say that pre-meetings are OK for me to conduct with the board, but that managers internally should avoid them?

Maybe.  But that’s what I’m going to say.   How can I sleep at night?  Because I think we need to differentiate between meetings with a decision maker  and meetings of a decision-making body.

Most people might think that the pricing committee, product strategy committee, or new product launch committee are democratic bodies, but they aren’t.  In reality, these are meetings with a decision maker present (e.g., the CEO, the SVP of products) and thus the committee is, perhaps subtly, an advisory group as opposed to a decision-making body.  In such meetings, the decision-maker should want to encourage vociferous debate, seek to prevent pre-meetings and horse-trading, and eliminate pocket vetoes because he/she wants to hear proposals debated clearly and completely based on the merits in order to arrive at the best decision.

However, board meetings are different.  Boards truly are a decision-making bodies ruled by one-person, one-vote.  Thus, while I reject Suster’s advice when it comes to conducting operational meetings (which I believe are inherently advisory groups), I agree with it when it comes to decision-making bodies.  In such cases, someone needs to know who stands where on what.

And that person needs to be the CEO.

Insight Ventures Periodic Tables of SaaS Sales and Marketing Metrics


I just ran into these two tables of SaaS metrics published by Insight Venture Partners (or, more precisely, the Insight Onsite team) and they are too good not to share.

Along with Bessemer’s awkwardly titled 30 Questions and Answers That Every SaaS Revenue Leader Needs to Know, financial metrics from Opex Engine, and the wonderful Pacific Crest Annual SaaS Survey, SaaS leaders now have a great set of reference documents to benchmark their firms.

(And that’s not to mention David Skok’s great post on SaaS metrics or, for that matter, my own posts on the customer acquisition cost (CAC) ratio and renewals rates / churn.)

Here is Insight’s SaaS sales periodic table:

ivp saas sales

And here is Insight’s B2B digital marketing periodic table:

ivp saals mkting

The Customer Acquisition Cost (CAC) Ratio: Another Subtle SaaS Metric

The software-as-a-service (SaaS) space is full of seemingly simple metrics that can quickly slip through your fingers when you try to grasp them.  For example, see Measuring SaaS Renewals Rates:  Way More Than Meets the Eye for a two-thousand-word post examining the many possible answers to the seemingly simple question, “what’s your renewal rate?”

In this post, I’ll do a similar examination to the slightly simpler question, “what’s your customer acquisition cost (CAC) ratio?”

I write these posts, by the way, not because I revel in the detail of calculating SaaS / cloud metrics, but rather because I cannot stand when groups of otherwise very intelligent people have long discussions based on ill-defined metrics.  The first rule of metrics is to understand what they are and what they mean before entertaining long discussions and/or making important decisions about them.  Otherwise you’re just counting angels on pinheads.

The intent of the CAC ratio is to determine the cost associated with acquiring a customer in a subscription business.  When trying to calculate it, however, there are six key issues to consider:

  • Months vs. years
  • Customers vs. dollars
  • Revenue on top vs. bottom
  • Revenue vs. gross margin
  • The cost of customer success
  • Time periods of S&M

Months vs. Years

The first question — which relates not only to CAC but also to many other SaaS metrics:  is your business inherently monthly or annual?

Since the SaaS movement started out with monthly pricing and monthly payments, many SaaS businesses conceptualized themselves as monthly and thus many of the early SaaS metrics were defined in monthly terms (e.g., monthly recurring revenue, or MRR).

While for some businesses this undoubtedly remains true, for many others – particularly in the enterprise space – the real rhythm of the business is annual.  Salesforce.com, the enterprise SaaS pioneer, figured this out early on as customers actually encouraged the company to move to an annual rhythm, for among other reasons, to avoid the hassle associated with monthly billing.

Hence, many SaaS companies today view themselves as in the business of selling annual subscriptions and talk not about MRR, but ARR (annual recurring revenue).

Customers vs. Dollars

If you ask some cloud companies their CAC ratio, they will respond with a dollar figure – e.g., “it costs us $12,500 to acquire a customer.”  Technically speaking, I’d call this customer acquisition cost, and not a cost ratio.

There is nothing wrong with using customer acquisition cost as a metric and, in fact, the more your business is generally consistent and the more your customers resemble each other, the more logical it is to say things like, “our average customer costs $2,400 to acquire and pays us $400/month, so we recoup our customer acquisition cost in six months.”

However, I believe that in most SaaS businesses:

  • The company is trying to run a “velocity” and an “enterprise” model in parallel.
  • The company may also be trying to run a freemium model (e.g., with a free and/or a low-price individual subscription) as well.

Ergo, your typical SaaS company might be running three business models in parallel, so wherever possible, I’d argue that you want to segment your CAC (and other metric) analysis.

In so doing, I offer a few generic cautions:

  • Remember to avoid the easy mistake of taking “averages of averages,” which is incorrect because it does not reflect weighting the size of the various businesses.
  • Remember that in a bi-modal business that the average of the two real businesses represents a fictional mathematical middle.

avg of avg

For example, the “weighted avg” column above is mathematically correct, but it contains relatively little information.  In the same sense that you’ll never find a family with 1.8 children, you won’t find a customer with $12.7K in revenue/month.  The reality is not that the company’s average months to recoup CAC is a seemingly healthy 10.8 – the reality is the company has one very nice business (SMB) where it takes only 6 months to recoup CAC and one very expensive one where it takes 30.  How you address the 30-month CAC recovery is quite different from how you might try to squeeze a month or two out the 10.8.

Because customers come in so many different sizes, I dislike presenting CAC as an average cost to acquire a customer and prefer to define CAC as an average cost to acquire a dollar of annual recurring revenue.

Revenue on Top vs. Bottom

When I first encountered the CAC ratio is was in a Bessemer white paper, and it looked like this.

cac picture

In English, Bessemer defined the 3Q08 CAC as the annualized amount of incremental gross margin in 3Q08 divided by total S&M expense in 2Q08 (the prior quarter).

Let’s put aside (for a while) the choice to use gross margin as opposed to revenue (e.g., ARR) in the numerator.  Instead let’s focus on whether revenue makes more sense in the numerator or the denominator.  Should we think of the CAC ratio as:

  • The amount of S&M we spend to generate $1 of revenue
  • The amount of revenue we get per $1 of S&M cost

To me, Bessemer defined the ratio upside down.  The customer acquisition cost ratio should be the amount of S&M spent to acquire a dollar of (annual recurring) revenue.

Scale Venture Partners evidently agreed  and published a metric they called the Magic Number:

Take the change in subscription revenue between two quarters, annualize it (multiply by four), and divide the result by the sales and marketing spend for the earlier of the two quarters.

This changes the Bessemer CAC to use subscription revenue, not gross margin, as well as inverts it.  I think this is very close to CAC should be calculated.  See below for more.

Bessemer later (kind of) conceded the inversion — while they side-stepped redefining the CAC, per se, they now emphasize a new metric called “CAC payback period” which puts S&M in the numerator.

Revenue vs. Gross Margin

While Bessemer has written some great papers on Cloud Computing (including their Top Ten Laws of Cloud Computing and Thirty Q&A that Every SaaS Revenue Leader Needs to Know) I think they have a tendency to over-think things and try to extract too much from a single metric in defining their CAC.  For example, I think their choice to use gross margin, as opposed to ARR, is a mistake.

One metric should be focused on measuring one specific item. To measure the overall business, you should create a great set of metrics that work together to show the overall state of affairs.

leaky

I think of a SaaS company as a leaky bucket.  The existing water level is a company’s starting ARR.  During a time period the company adds water to the bucket in form of sales (new ARR), and water leaks out of the bucket in the form of churn.

  • If you want to know how efficient a company is at adding water to the bucket, look at the CAC ratio.
  • If you want to know what happens to water once in the bucket, look at the renewal rates.
  • If you want to know how efficiently a company runs its SaaS service, look at the subscription gross margins.

There is no need to blend the efficiency of operating the SaaS service with the efficiency of customer acquisition into a single metric.  First, they are driven by different levers.  Second, to do so invariably means that being good at one of them can mask being bad at the other.  You are far better off, in my opinion, looking at these three important efficiencies independently.

The Cost of Customer Success

Most SaaS companies have “customer success” departments that are distinct from their customer support departments (which are accounted for in COGS).  The mission of the customer success team is to maximize the renewals rate – i.e., to prevent water from leaking out of the bucket – and towards this end they typically offer a form of proactive support and adoption monitoring to ferret out problems early, fix them, and keep customers happy so they will renew their subscriptions.

In addition, the customer success team often handles basic upsell and cross-sell, selling customers additional seats or complementary products.  Typically, when a sale to an existing customer crosses some size or difficultly threshold, it will be kicked back to sales.  For this reason, I think of customer success as handling incidental upsell and cross-sell.

The question with respect to the CAC is what to do with the customer success team.  They are “sales” to the extent that they are renewing, upselling, and cross-selling customers.  However, they are primarily about ARR preservation as opposed to new ARR.

My preferred solution is to exclude both the results from and the cost of the customer success team in calculating the CAC.  That is, my definition of the CAC is:

dk cac pic

I explicitly exclude the cost customer success in the numerator and exclude the effects of churn in the denominator by looking only at the new ARR added during the quarter.  This formula works on the assumption that the customer success team is selling a relatively immaterial amount of new ARR (and that their primary mission instead is ARR preservation).  If that is not true, then you will need to exclude both the new ARR from customer success as well as its cost.

I like this formula because it keeps you focused on what the ratio is called:  customer acquisition cost.  We use revenue instead of gross margin and we exclude the cost of customer success because we are trying to build a ratio to examine one thing:  how efficiently do I add new ARR to the bucket?  My CAC deliberately says nothing about:

  • What happens to the water once S&M pours it in the bucket.  A company might be tremendous at acquiring customers, but terrible at keeping them (e.g., offer a poor quality service).  If you look at net change in ARR across two periods then you are including both the effects of new sales and churn.  That is why I look only at new ARR.
  • The profitability of operating the service.  A company might be great at acquiring companies but unable to operate its service at a profit.  You can see that easily in subscription gross margins and don’t need to embed that in the CAC.

There is a problem, of course.  For public companies you will not be able to calculate my CAC because in all likelihood customer success has been included in S&M expense but not broken out and because you can typically only determine the net change in subscription revenues and not the amounts of new ARR and churn.  Hence, for public companies, the Magic Number is probably your best metric, but I’d just call it 1/CAC.

My definition is pretty close to that used by Pacific Crest in their annual survey, which uses yet another slightly different definition of the CAC:  how much do you spend in S&M for a dollar of annual contract value (ACV) from a new customer?

(Note that many vendors include first-year professional services in their definition of ACV which is why I prefer ARR.  Pacific Crest, however, defines ACV so it is equivalent to ARR.)

I think Pacific Crest’s definition has very much the same spirit as my own.  I am, by comparison, deliberately simpler (and sloppier) in assuming that customer success not providing a lot of new ARR (which is not to say that a company is not making significant sales to its customer base – but is to say that those opportunities are handed back to the sales function.)

Let’s see the distribution of CAC ratios reported in Pacific Crest’s recent, wonderful survey:

pac crest cac

Wow.  It seems like a whole lot of math and analysis to come back and say:  “the answer is 1.

But that’s what it is.  A healthy CAC ratio is around 1, which means that a company’s S&M investment in acquiring a new customer is repaid in about a year.  Given COGS associated with running the service and a company’s operating expenses, this implies that the company is not making money until at least year 3.  This is why higher CACs are undesirable and why SaaS businesses care so much about renewals.

Technically speaking, there is no absolute “right” answer to the CAC question in my mind.  Ultimately the amount you spend on anything should be related to what it’s worth, which means we need relate customer acquisition cost to customer lifetime value (LTV).

For example, a company whose typical customer lifetime is 3 years needs to have a CAC well less than 1, whereas a company with a 10 year typical customer lifetime can probably afford a CAC of more than 2.  (The NPV of a 10-year subscription increasing price at 3% with a 90% renewal rate and discount at 8% is nearly $7.)

Time Periods of S&M Expense

Let me end by taking a practical position on what could be a huge rat-hole if examined from first principles.  The one part of the CAC we’ve not yet challenged is the use of the prior quarter’s sales and marketing expense.  That basically assumes a 90-day sales cycle – i.e., that total S&M expense from the prior quarter is what creates ARR in the current quarter.  In most enterprise SaaS companies this isn’t true.  Customers may engage with a vendor over a period of a year before signing up.  Rather than creating some overlapped ramp to try and better model how S&M expense turns into ARR, I generally recommend simply using the prior quarter for two reasons:

  • Some blind faith in offsetting errors theory.  (e.g., if 10% of this quarter’s S&M won’t benefit us for a year than 10% of a year ago’s spend did the same thing, so unless we are growing very quickly this will sort of cancel out).
  • Comparability.  Regardless of its fundamental correctness, you will have nothing to compare to if you create your own “more accurate” ramp.

I hope you’ve enjoyed this journey of CAC discovery.  Please let me know if you have questions or comments.