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Predicting the Trajectory of Very Early Stage Companies

February 28, 2010

Predicting the Trajectory of Very Early Stage Companies

[Sorry this is a longish post, but I kind of felt the need to build to the question I wanted to raise]

It's widely acknowledged that initial startup costs for many internet-enabled companies (SAAS, consumer web, mobile apps, etc all fall into this bucket) have dropped dramatically in the last decade. As a result, many companies can get off the ground and make significant progress on modest amounts of capital... often well under $1M initially.

Countless companies you've never heard of got started on a few hundred thousand dollars or less. Most never become anything, a small portion become small to medium sized companies, and a tiny handful become hugely successful companies. It's easy to think of the ones that got big... like Facebook which started off as a product in a dorm room, and grew as a startup with a $500K investment from Peter Thiel in 2004, entered the realm of VC-backed companies in 2005, and of course today is a worldwide phenomenon and very successful company.

The chart below isn't meant to be a highly precise analysis, but rather a graphical depiction of broad "envelopes" of outcome and capital investment. There are always rare exceptions, but the vast majority of companies that ultimately become $1B+ outcomes raise at least tens of millions of capital (if not significantly more) to get there. Similarly the vast majority of companies that only raise ~$1M or thereabouts in capital result in outcomes of substantially less than $100M.

 

The question of what makes a great seed stage investment has two answers, one absolute and one relative to the investor you're asking. Outcomes in the upper part of any of the envelopes above could be considered absolute successes, but relatively speaking these may not be considered success depending on the type of seed investor. A good outcome (i.e. return on investment of 5-10x+) in the green box may be considered a win for an angel investor if the company remains capital efficient, but it wouldn't be for most VC funds (small or large). A good outcome in the red box might be a win for a small VC fund but probably not for a large VC. A large VC obviously seeks outcomes in the top part of the blue box. These relative answers explain the motivations of different types of investors actively pursuing seed stage companies, as Chris Dixon and plenty of others have discussed.

So for many in the VC and startup ecosystem, none of this is news. What I think remains very much unresolved in this world of lower startup capital requirements is the question of how well investors and entrepreneurs can prospectively predict the potential scale of outcome. I'm not talking about predicting the likelihood of success (obviously important), but rather predicting how big the company might ultimately become and how much capital & time it might take to get there.

There are a range of factors that can help in trying to assess the probability of actually building a company of significant scale:

  • Size & Attractiveness of Market Opportunity - some are obviously big and some are obviously small, though many not entirely clear
  • Caliber of Team - never a precise science judging a team, but well understood ways to evaluating a group of co-founders based on their prior accomplishments, raw intellectual horsepower, charisma, etc. In addition to raising the chances of success, small or large, an exceptional team also usually increases the chance of creating something very big.
  • Founders' Stated Ambitions - most entrepreneurs like to think big, but sometimes they make it clear to seed stage investors that their goals are more modest. Entrepreneurs also make a continuous evaluation over the life of a startup as it reaches various value creation points.
  • Scale of Competitors - if other startups in the space have already achieved real scale a new entrant might also be able to, but again hard for those startups truly pioneering a market or new class of product

Companies where one can prospectively see high probability of a large scale outcome are attractive seed investments for large VCs, provided they believe there's also a good probability of success. It's not uncommon for VC's to write $250-500K "blank checks" to entrepreneurs they know working on a concept that fits this description. Similarly those that are probably not venture scale outcomes (i.e. the green box above is a best case scenario) may receive angel investment but typically not seed funding from VCs.

But what happens to everything in between those two extremes? What's the shape of the probability distribution, i.e. do 10% of startups obviously have large scale potential and 10% obviously have small scale potential, with the remaining 80% hard to assess? Or is the distribution more even?

Take Twitter just as an example... it started life as a side project within a struggling startup called Odeo. In 2006, Ev Williams returned what was left of Odeo's capital to its investors (in fact made them whole out of his own pocket) and was widely praised for doing so. He (and collaborators Biz Stone and Jack Dorsey) was rather uncertain about what sort of scale Twitter or other projects within Odeo's successor corporation (Obvious Corp) might ultimately achieve, and freely admitted it at the time.

So what happens to the startups that have decent potential for success, but real uncertainty about scale of outcome? Do most of these get funded and launched or do most die on the vine without ever taking a shot?

Some large VCs deal with this segment with a "portfolio" approach (or less generously described "spray and pray"), by making a large number of passive seed investments and investing larger amounts only in the small handful that prove out A) some greater potential for scale than at inception and B) some continued probability of success. Some of these companies undoubtedly receive angel funding (e.g. Facebook example above).

A very small portion of VCs have specifically crafted their investment strategy in part to cope with this uncertainty. For example, Josh Kopelman has described First Round Capital's outlook on scale of outcome with the express vs local train analogy. FRC can seed a company and if it exits at $10M or $40M, that works fine for the firm given their strategy and fund size. If it has a chance to take in more capital, but shoot for a $200M+ outcome that's fine too. His point is that this funding path looks like a "local" train whereby you can get to a faraway destination, but also have options to disembark at stops along the way. By contrast seed investments from large VCs can be likened to an "express" train... i.e. they can work just as well and maybe get you there faster, but only if all parties involved are committed to the faraway destination at the outset.

What do you think? How easy or hard is it to prospectively predict potential scale at the seed stage? For those that are difficult to clearly predict scale, what happens to them today? How ought investors (either individuals or VCs) approach these opportunities in the future?

Lee Hower is a Principal with Point Judith Capital.  This blog post was originally published on November 4, 2009.  You can find this blog post, as well as additional content on his blog called Venturesome.

Why I Wish My Competitors Well And You Should Too

February 25, 2010

Why I Wish My Competitors Well And You Should Too

I’m going to start with a story — which includes a confession.

When I started my first company, I didn’t start with a grand mission.  The idea behind the business wasn’t transformational.  It wasn’t going to change the world.  Historians weren’t going to write about it after I was dead.  And all of that was OK.  Even though there was no grand mission — I was solving a problem and meeting a market need that I cared about.  Wait, let me clarify that a bit.  I cared in the sense that if I didn’t solve it, I was restless.  I couldn’t let it go.  I wasn’t satisfied
with the way the problems in that industry were being solved and the solutions that other companies were offering.  That’s what drove me for 10+ years with that startup. 

It wasn’t until much later (well after I had sold that first company), that I gave the topic some additional thought.  How do you know whether or not you care about the problem you’re working on?  Here’s my litmus test:

1.  Define the problem you’re solving in reasonably broad terms.

2.  Answer yes/no:  If the problem was somehow magically “solved” (to your satisfaction), but you weren’t the one that solved it, would you be fine with it?

Let me clarify by shifting back to my story:  In the niche market I was working in, the problem I was working on was relatively small.  But, if one day, I woke up and learned that somehow the problem was magically solved — even if it was by a competitor, I would have been fine.  A little miffed that they had beaten me, but still OK.  As long as they really solved it.  I could have stopped toiling away the sleepless nights working on that particular problem and I would have found other problems to work on.  The concept here is:  You care enough about a problem that you don’t necessarily mind if someone else solves it.  What really frustrates us entrepreneurs is when competitors win, but they don’t actually solve the problem.

One way to explain this concept better is to look at an extreme example.  Lets say the problem you were working on was curing cancer.  Of course, you’d be passionate about finding a cure.  You’d be working hard.  It’s an important problem, and it’s not surprising that you care.  Now, imagine if you woke up one day to learn that someone else had created a cure.  You’d be
glad that the problem was solved — even though it wasn’t you that solved it.  Sure, it would have been great to get the fame and glory, but that surely wouldn’t cause you to wish the other scientists/researchers/doctors ill.  Nope.  You’d wish them well.  Why?  Because fundamentally, you care about having the problem solved.

Now, with my current startup, HubSpot, I’m still passionate.  But the problem happens to be much, much bigger.  This time it’s transformational.  This time it’s a mission.  I’m working furiously on this startup too.  I co-authored a book, “Inbound Marketing” on the topic.  I’m doing a fair amount of public speaking (despite the stress it causes me).  I believe we’re on the path of truth and justice (we’re helping small businesses grow
and reducing junk mail, spam, and marketing calls that interrupt you at dinner).  We’re hoping to be the ones that end up transforming the marketing industry.  But, if someone else ends up doing it, and winds up delivering on our mission, well, then, more power to them. 

I care enough about the problem that I don’t mind if someone else solves it. 
That’s why I truly wish my competitors well. 

But, just because I wish them well doesn’t mean I’m going to make it
easy for those competitors.  After all, like you, I’m an entrepreneur and as such, I’m fiercely competitive.

Summary:  When possible, work on really big problems.  They’re more fun, and it’s easier to get excited.  But, even if you’re not working on a really big problem, it’s OK, as long as you at least care enough about the problem you are solving that you don’t care who solves it.  You just want it solved.

What do you think?

If you're a startup junkie, you can follow me on twitter @dharmesh. Also, if you found this useful, please share it.

Dharmesh Shah is the CTO & Founder of HubSpot in Cambridge, Massachusetts.  This blog post was originally published on February 22, 2010.  You can find this blog post, as well as additional content on his blog called On Startups.

Gillmor Gang episode featuring Laura Fitton, Founder of oneforty

February 23, 2010

Gillmor Gang episode featuring Laura Fitton, Founder of oneforty

oneforty's Founder - Laura Fitton (@pistachio) was a participant on last Friday's Gillmor Gang / Real-time segment on building43.  Hosted by Steve Gillmor, this episode also includes Robert Scoble, Dan Farber, Kevin Marks, and Andrew Keen. 

Laura gives an update on oneforty and the recent round of funding.  The group also talks in detail about Google Buzz.

 

Cloud Computing Trends and Opportunities

March 2, 2010

Cloud Computing Trends and Opportunities

At Flybridge, we periodically dive deep into areas in which we see significant market growth and investment opportunity.  Recently, we did so in the whole field of Cloud Computing and thought it would be interesting to share some of our thoughts.  I would also like to thank our great summer associate, Ravi Inukonda, who worked with me over the last few months on this effort.

If you have been following trends in enterprise IT as of late, you have been unable to miss Cloud Computing and all the bad puns that normally accompany such commentary (“Forecast Mostly Sunny for Company Opting for Cloud Computing” or “Future bright for cloud computing” being two such examples).  

While the ideas are not new - IBM called it Utility Computing back in 2002 - the Cloud Computing trend really gained steam over the past couple of years.  The momentum is more than marketing, as the advent of Cloud Computing has really been enabled by advances in server/CPU architectures, storage and networking subsystems, open source software adoption and most importantly virtualization, all of which were perhaps too nascent to truly enable the cloud until recently.  In addition to the technical advances, the current economic environment has furthered these trends, as customers look for ways to reduce capital expenditures and increase the efficiency of their IT operations.  As a result, we now believe that Cloud Computing is at a tipping point and that it represents a fundamental architectural shift that will create numerous opportunities up and down the enterprise IT landscape. Past tipping points include the shift to client server architectures, enabled by more powerful PCs and widespread adoption of LANs, and the shift to Internet based three tier enterprise applications, driven primarily by the adoption of the web.

Given that Cloud Computing is used so frequently as an adjective, it is worth a quick segue to define the term and architecture.  Simply put, cloud computing is infrastructure or applications that are delivered as a massively scalable service that is elastic in its ability to quickly scale up and down, where the complexity is abstracted from the end user, that are paid for in some form of a by the drink utility model.  Taking this down a level, we think about clouds along two dimensions.

1. From an architectural approach, cloud computing services tend to be Infrastructure as a Service, for example Amazon's EC2 compute platform, but also including other compute, networking and storage infrastructure; Platforms as a Service, for example Salesforce.com's Force.com platform, that allow developers to rapidly build and deploy clound-based applications; or Applications as a Service (SaaS), such as Netsuite's ERP and accounting applications.   

2. The other dimension is whether these services are offered to customers as public clouds by third party organizations, private clouds in an enterprise's own data-centers or as a hybrid of the two.

From Flybridge’s lens as an early stage venture capital investor, we believe that starting a company focused on public clouds offering infrastructure as a service is a fool's errand.  In that field, the keys to success are massive scale, a low cost of capital and operational excellence.  These capabilities are in abundance at places like Amazon, Google and Microsoft, but not at start-ups.  Further, we think that general purpose Platforms as a Service are also difficult for start-ups given the need to drive developer adoption and the long gestation cycle as the platform is built, users recruited, applications deployed and ultimately scaled.  The exception to this rule of thumb will be companies that successfully latch onto existing developer communities, such as what Engine Yard has done for the Ruby on Rails community.  Finally, we also believe that many of the horizontal SaaS application opportunities have been played out.  Whether it is Salesforce for CRM, NetSuite for ERP or Workday for HR, most if not all of the obvious markets have credible, large, well-funded companies with market leading positions offering solutions.

Does that mean that all the promising opportunities are already covered or are there big white space opportunities for new companies?  We think there are a few trends and themes that offer great promise, each one of which can support numerous successful companies:


  • Enable enterprise data centers to be more cloud like. CIOs of large companies that we speak to are generally concerned about control, security and delivering a good, reliable service to their end-users.  The first two issues lead to a generic concern with seeing any of their mission critical or sensitive applications hosted in a public cloud.  That said, the mere existence of services such as Amazon's Web Services puts pressure on their ability to deliver a good service to their end-users as they fundamentally change expectations.  If a user can have a full server OS, storage and networking provisioned on AWS in minutes, the current enterprise service level of weeks or months to provision the same looks pretty weak.  As a result, enterprise CIOs that are responsible for data centers will over time look to manage and operate these data centers much in the same way as a public cloud.  This will, therefore, create opportunities around management, provisioning, billing, access control and other technologies that allow a private cloud to be effectively operated.  As an aside, there will also be an opportunity at the networking layer as the deployment of cloud architectures in enterprise IT data centers will create the need for high speed, low latency, low power, non-blocking network switches.
  • Bridge the cloud and enterprise boundary.  The advent of public cloud infrastructure will create opportunities for companies that bridge the divide and smooth the transition between private and public clouds.  While there is a risk that the Platform as a Service vendors will view this as their domain, witness Amazon's recent VPC announcement there are many services such as backup and email archiving that benefit from a combination of on-premise and cloud based software that will be outside of the domain of the platform providers.  The other approach that we see promise with along this front are applications and platforms that support cloud-bursting, in other words an application that runs most of the time in an enterprise data center but under heavy load relies on the public cloud for scalability.  
  • Provide tools to better manage cloud environments. Any time there is a fundamental architectural shift in the enterprise IT landscape, it has created opportunities for new companies to move more quickly into the space than incumbent vendors with installed bases to protect and legacy applications to support can.  These companies have generally focused on systems management, network management, security and the like.  This trend is already underway in the cloud market and can been seen in the success of companies such as RightScale and New Relic. In addition to tools for the management of the cloud, we also believe that new infrastructure services, such as horizontally scalable databases written solely for cloud applications, will see great adoption as more applications are written from the outset to be run in the cloud.
  • Develop SaaS applications for vertical markets. While there may not be much whitespace in major horizontal application markets, there are many vertical market niches that can support the creation of very large companies.  In these markets, a start-up can build deep domain knowledge around the problem set and offer its applications in a cost-effective manner (often leveraging public clouds for their infrastructure), making their solutions easier to adopt, maintain and extend as compared to traditional enterprise applications in the same field.  We are seeing this with the success of our insurance SaaS company, FirstBest Systems, but there are numerous other examples in the healthcare IT, bio-medical research, energy and other fields.
  • Create companies that are enabled by the Cloud.  One of the aspects of cloud computing that excites us the most is that it is a huge enabler of innovation.  Cloud computing makes it so easy to develop and deploy applications that it levels the playing field for start-ups versus large, well capitalized, competitors.  As an entrepreneur, I can now buy access to world-class data center infrastructure for dollars an hour that would have previously cost me millions to purchase and deploy.  As a result, savvy start-up executives can look to create companies that would have previously been too capital intensive to contemplate.  This is especially true if the computing need of such applications, for example software testing (see SOASTA for one such provider) or financial modeling are intermittent for any one customer but relatively smooth across many such customers.

Given the benefits of a more flexible, dynamic and efficient IT environment, Cloud Computing, under this name or new ones to come, will see significant adoption across the enterprise IT market over the next several years. This will create many opportunities for savvy entrepreneurs, so if you have ideas or thoughts, please let us know!

Chip Hazard is a General Partner with Flybridge Capital Partners.  This blog post was originally published on September 2, 2009.  You can find this post, as well as additional content on his blog called Hazard Lights

A Geek's Guide to Startup Banking - What do you do after you close financing

February 23, 2010

A Geek's Guide to Startup Banking - What do you do after you close financing

This is my 2nd post in the “Geek’s Guide” series about all the things that entrepreneurs hate to do, are not good at doing them, but have to do them anyway. These things include office space (My first post is on this topic), legal, HR, administration, banking, accounting, insurance, payroll, etc.

I am going through these things myself at Yottaa. This is my 2nd time in going through these things. My first time was around 2000 to 2001 when I started Nexaweb. Nobody was doing blogging at the time. Frankly, I wish I blogged about what I learned at the time. Because when I need this knowledge again, I remember absolutely nothing about these things. —We are genetically programmed to suck at such stuff and our memory got erased quickly even if we force ourselves through a learning process.

Anyway, through Yottaa, I think that I’ve become a semi-expert in these things now. I’m determined to write down what I learned so that they might be useful for my fellow entrepreneurs. This post focuses on banking.

What is the first thing you should do when you close financing? Well, even before the unbelievable party that you are going to throw:-), you’d better have a bank account that you can deposit the money. How are you going to do that? The followings outline the considerations you should think about from a banking point of view.

  • Account types: banks offer many types of accounts, ranging from checking accounts, simple saving account, and money market account to more sophisticated investment accounts. It is helpful to know the differences between these account types.

    At minimum you need a checking account which permits unlimited transactions in and out. But checking accounts do not bear Interest. Interest bearing accounts include saving accounts, money market accounts and so on, but they only permit a limited number of transactions per month. For example, saving accounts only permit 6 transactions per month by legal regulations.

 

  • Liquidity vs. investment: The money you raised will be consumed over a period of time. During the period, you want to make sure that cash is available when you need it. On the other side, it also makes sense to consider some form of “investment” for the portion of your cash not needed initially.

    There are many forms of investments banks offer, ranging from simple saving accounts, money market account, CD account, to even more sophisticated ones. Different type of investment service has different risk/reward profiles. For example, simple saving accounts are the safest (insured by FDIC), liquid, and yield interest but the current interest rate is very low (0.25% for example). Money market accounts are not FDIC insured but they are safe as long as the bank itself is safe. Monday market accounts provide liquidity and offer better interest rate than simple saving accounts. CD accounts may offer even higher return but typically require you to commit to a certain period of time (6 months minimum, typically 12 months), during which there is no liquidity.

    The common choices for startups I have seen are to stay with simple saving accounts or money market accounts.

 

  • Banking fees: banking services normally charge fees. Such fees are part of the banking cost that you should take into consideration. Most banks may waive such fees if you maintain a certain level of account balance.

    Some banks give you “earning credit” for your checking account balance. “Earning credit” is different from “interest” that does not generate additional cash, but can be used to offset some of the banking fees. If your balance reaches a certain level, you could have enough earning credit to offset all your banking fees.

 

  • Online banking service: Most banks provide online banking service that you access and manage your accounts from a web browser. Nevertheless, it is still a good idea to check it out to make sure such service is available.

 

  • Do you need equipment financing or loan from the bank? Most banks do not offer equipment financing or loans to startups (they typically require a long credit history, revenue, etc in order to be considered for loans). The only exception is Silicon Valley Bank (SVB). Even SVB is nearly impossible to get a loan for young startups, but they at least offer you a glimpse of hope.

 

  • Do you need international banking? This one is tricky as it highly depends on local regulations. You would most likely choose another set of banks in the other country. In Yottaa’s case, we need banking in China because we have a team in Beijing. Fortunately, Bank of America provides banking operations in Beijing so my life is slightly simpler (Still work in progress. After a few weeks, I have not been able to move capital yet. So I’m very much homeless in Beijing:-) Any tips would be appreciated!).

 

Which bank should you choose? It depends on what you need. In my case (for Yottaa), I evaluated a few banks and eventually picked Bank of America. There is no way that Yottaa can get a loan from them, but it is ok because Yottaa does not plan to get a loan. The other attributes of Bank of America make them look like a better choice for Yottaa(lower fees, better service and engagements, international presence, I love their account service team, etc).

Coach Wei is the CEO of Yottaa and Founder & Chariman of Nexaweb.  This blog post was originally published on November 23, 2009.  You can find this post as well as additional content on his blog called: Dijital Life.

What Makes Boston's Start-Up Scene Special?

February 22, 2010

What Makes Boston's Start-Up Scene Special?

A few weeks ago, Fred Wilson posted a presentation he delivered on What Makes the NYC Start-Up Scene Special.

I was inspired to deliver a similar presentation to a group of Harvard Business School students who are interested in entrepreneurship in Boston. There's been alot of chatter in the community about a start-up renaissance in Boston.  Don Dodge of Microsoft had a great post listing out all the amazing start-up resources in the Boston community that's worth reviewing as well.

Yahoo's ex-president (and fellow HBS EIR) Susan Decker was there to serve as a good foil for my Boston vs. Silicon Valley quips.

 

Jeff Bussgang at HBS: What Makes Boston's Start-Up Scene Special? from Jeff Bussgang on Vimeo.

 

Jeff Bussgang is a General Partner with Flybridge Capital Partners.  This blog post is a combination of two posts that were originally published on November 11th and November 13th, 2009.  You can find this post, as well as additional content on his blog called: Seeing Both Sides.

Keep Your Startup Virtual

February 21, 2010

Keep Your Startup Virtual

My advice for those starting a new company: Stay virtual as long as possible.

One thing we did get right at Lookery was minimizing our infrastructure which let us focus our energy and cash on getting our product to market — fast.

We’re following a similar model at my new startup, Performable. So far there are three of us on the team, all working virtually. Unlike with Lookery, at Performable we all live reasonably close to each other so we meet at a local coffee shop several times a week to review our progress and co-work. The virtual setup works great for us since we knew each other previously, and we’re comfortable working together.

At some point we know that we’ll have to get an office space. You usually reach that point when you need to hire outside your personal network or grow beyond  a certain size, the exact size depending on your situation. When it’s time to move it out of your house or the coffee shop, you will know. It’s time to move out only when the the answer to the question “Is getting an office space going to help grow my business?” is a firm, “Yes.”

Back in 1996, when working for my first startup, finding office space was challenging; that was NYC (Silicon Alley) in the boom days, when everyone was paying a premium on huge loft spaces with room for ping-pong tables and Razor scooters.

Ten+ years later that all seems ridiculous; I’ve never witnessed a correlation between cool offices and successful companies. Today there are lots of options for startups: coworking spaces, part-time offices and shared workplaces; let someone else burn their cash on building out an office space (always a liability never an asset).

If you’re in Boston, check out my friend Coach Wei’s post on finding startup office space. But don’t sign on the dotted line until it’s a necessity. At the beginning, use the cash you’d be spending on rent to invest in things that grow your business.

If you like this post, please vote for it on my favorite news site.

David Cancel is the Founder & CEO of Performable and founded Ghostery, Lookery, and Compete.  This blog post was originally published on November 11, 2009.  You can find this post, as well as additional content on his blog called: Making something from nothing.

What Lean Startups are NOT

February 24, 2010

What Lean Startups are NOT

The Lean Startup movement isn’t terribly new, but the level of hype is reaching pretty significant levels. The contrarian in me is always a little wary when anything gets overly hyped.  To be clear, I really really like the concepts of the lean startup and customer development.  I’d recommend any entrepreneur who isn’t familiar with this to at least watch some of Eric Ries’ talks about it and try to internalize Steve Blank’s book.  However, I find that when lots of people start pontificating on topics like this, some parts of the message get lost or the framework gets portrayed incorrectly as some holy grail. Below are a few half-baked thoughts on what I think The Lean Startup is NOT (btw, I’m lumping the customer development methodology and Lean Startup Methodology together).

1. The Lean Startups Is NOT One-Size-Fits-All

I get a little worried when I see too many diagrams of work flows emerging around a particular methodology. I think discussing best practices is generally a good thing, but too much emphasis on the process sometimes fools folks into thinking that it’s a magic formula.  I think the principles of Customer Development and the Lean Startup that are the most important things, and the process is more of a guide. Common sense and independent thought should prevail over workflows and formulas.

2. The Lean Startup is NOT Static

The reason that #1 is important is because the Lean Startup isn’t a static thing. Steve Blank and Eric Ries both often discuss how their thinking is evolving as they think about how their principles apply to different types of businesses and get feedback from folks who practice these principles. Industries and technologies shift as well, and some of the tried and true principles of the Lean Startup will eventually change or major limitations will become well understood.

3. The Lean Startup Is Not a Substitute for Vision

This is my most important point.  Emphasis on creating Minimum Viable Products and finding Product Market Fit I think can be pursued at the expense of thinking hard about a company’s vision.  It’s true that some big companies can/have emerged from iterating and pivoting into new markets (Groupon is my favorite example).  But I think some really big and hairy opportunities can only be addressed if one really does the work to understand the problems and players and have a strong point of view of what could be possible.  I think from there, you can utilize Lean Startup Principles to connect the dots, and the dots may lead somewhere very different (thus, vision evolves as well).  But I think both are required to build industry transforming companies.

For example, I’ve talked a lot about what I see as a huge opportunity in the education publishing industry. I am 100% convinced that we are going to see a massive company emerge in this sector in the next few years.  And it will be a company that completely changes the way students learn and how content is consumed.  But it’s a complicated industry with lots of disparate players (an oligopoly of publishers, Professors, different kinds of educational institutions, Students, device makers, etc) and not one where you can do serious damage without some heavy lifting and crazy vision and conviction.

I’m interested to hear other peoples thoughts on this!  Also, I want to give a quick shoutout to David Vivero and David Cancel, who prompted these thoughts from some recent conversations.

Rob Go is a Senior Associate with Spark Capital in Boston, Massachusetts.  This blog post was originally published on February 19, 2010.  You can find this post, as well as additional content on his blog called robgo.org.

SaaS Metrics – A Guide to Measuring and Improving What Matters

February 18, 2010

SaaS Metrics – A Guide to Measuring and Improving What Matters

This blog post looks at the high level goals of a SaaS business and
drills down layer by layer to expose the key metrics that will help
drive success. Metrics for metric’s sake are not very useful. Instead
the goal is to provide a detailed look at what management must focus on
to drive a successful SaaS business. For each metric, we will also look
at what is actionable.

Before going any further, I would like to thank the management team
at HubSpot, and Gail Goodman of Constant Contact, who sits on the
HubSpot board. A huge part of the material that I write about below
comes my experiences working with them. In particular HubSpot’s
management team is comprised of a group of very bright individuals that
are all very metrics driven, and they have been clear thought leaders
in developing the appropriate tools to drive their business. I’d also
like to thank John Clancy, who until recently was President of Iron
Mountain Digital, a $230m SaaS business, and Alastair Mitchell, CEO and
founder of Huddle.

Let’s start by looking at the high level goals, and then drill down from there:

 

image

Key SaaS Goals

 

  • Profitability: needs no further explanation.
    • MRR Monthly Recurring Revenue: In a SaaS business, one of the most important numbers to watch is MRR. It is likely a key contributor to Profitability.
  • Cash: very critical to watch in a SaaS business,
    as there can be a high upfront cash outlay to acquire a customer, while
    the cash payments from the customer come in small increments over a
    long period of time. This problem can be somewhat alleviated by using
    longer term contracts with advance payments.
    • Months to recover CAC: one of the best ways to
      look at the capital efficiency of your SaaS business is to look at how
      many months of revenue from a customer are required to recover your
      cost of acquiring that customer(CAC). In businesses such as banking and
      wireless carriers, where capital is cheap and abundant, they can afford
      a long payback period before they recover their investment to acquire a
      customer (typically greater than one year). In the startup world where
      capital is scarce and expensive, you will need to do better. My own
      rule says that startups need to recover their cost of customer
      acquisition in less than 12 months.
      (Note: there are other web
      sites and blogs that talk about the CAC ratio, with a complex formula
      to calculate it. This is effectively a more complicated way of saying
      the same thing. However I have found that most people cannot relate
      well to the notion of a CAC ratio, but they can easily relate to the
      idea of how many months of revenue it will take to recover their
      investment to acquire a customer. Hence my preference for the term
      Months to Recover CAC.)
  • Growth: usually a critical success factor to
    gaining market leadership. There is clear evidence that once one
    company starts to emerge as a market leader, there is a cycle of
    positive reinforcement, as customers prefer to buy from the market
    leader, and the market leader gets the most discussion in the press,
    blogosphere, and social media.

 

Two Key Guidelines for SaaS startups

 

image

The above guidelines are not hard and fast rules. They are what I
have observed to be needed by looking at a wide variety of SaaS
startups. As a business moves past the startup stage, these guidelines
may be relaxed.

In the next sections, we will drill down on the high level SaaS Goals to get to the components that drive each of these.

 

Three ways to look at Profitability

 

image

  1. Micro-Economics (per customer profitability):
    Micro-economics is the term used to describe looking at the economics
    of your business on a single customer level. Most business models (with
    a few exceptions such as marketplaces) are based around a simple
    principle: acquire customers and then monetize them. Micro-economics is
    about measuring the numbers behind these two essential ingredients of a
    customer interaction. The goal is to make sure the fundamental
    underpinnings of your business are sound: how much it cost to acquire
    your customers, and how much you can monetize them. i.e. CAC and LTV
    (cost of acquiring a customer, and lifetime value of the customer). In
    a SaaS business, you have a great business if LTV is significantly
    greater than CAC. My rule of thumb is that LTV must be at least 3x
    greater than CAC. (As mentioned elsewhere in this blog, your startup
    will die if your long term number for CAC is higher than your LTV. See Startup Killer: The cost of acquiring customers.)
  2. Overall profitability (standard accounting method):
    This looks a the standard accounting way of deriving profitability:
    revenue – COGS – Expenses.  The diagram also notes that Revenue is made
    up of MRR + Services Revenue. Since MRR is such a critical element,
    there will be a deeper drill down to understand the key component
    drivers.
  3. Profitability per Employee: it can be useful to
    look at the factors contributing to profitability on a per employee
    basis, and benchmark your company against the rest of the industry.
    Expenses per Employee is usually around $180-200k annually for
    businesses with all their employees in the US. (To calculate the number
    take the total of all expenses, not just salaraies, and divide by the
    number of employees.) Clearly to be profitable in the long term, you
    will want to see revenue per employee climb to be higher than expenses,
    taking into account your gross margin %.

 

Drill down on MRR

image

MRR is computed by multiplying the total number of paying customers by the average amount that they pay you each month (ARPU).

  • Total Customers:  a key metric for any SaaS
    company. This increases with new additions coming out the bottom of the
    sales funnel, and decreases by the number of customers that churn. Both
    of these are key metrics, and we will drill down into them later.
  • ARPU – average monthly revenue per customer: (The
    term ARPU comes from the wireless carriers where U stands for user.) 
    This is another extremely imporant variable that can be tweaked in the
    SaaS model. If you read my blog post on the JBoss story,
    you will see that one of the key ways that we grew that business was to
    take the average annual deal size from $10k, to $50k.  Given that the
    other parts of the pipeline worked with the same numbers and conversion
    rates, this grew the business by 5x.  We will drill down into how you
    can do the same thing a little further on.

 

Drill down on Micro-Economics (Per Customer Profitability)

Our goal is to see a graph that looks like the following:

image

To achieve this, lets look at the component parts of each line, to see what variables we can use to drive the curves:

 

image

As mentioned earlier, customer profitability = LTV – CAC.

Drill down on LTV

Drilling down into the factors affecting LTV, we see the following:

LTV = ARPU x Average Lifetime of a Customer – the Cost to Serve them (COGS)

It turns out that the Average Lifetime of a Customer is computed by
1/Churn Rate. As an example, if a you have a 50% churn rate, your
average customer lifetime will be 1 divided by 50%, or 2 months. In
most companies that I work with, they ignore tracking the average
lifetime, but instead track the monthly churn rate religiously.

The importance of a low churn rate cannot be overstated. If your
churn rate is high, then it is a clear indication of a problem with
customer satisfaction. We will drill down later into how you can
measure the factors contributing to Churn Rate, and talk about how you
can improve them.

Drill down on CAC

The formula to compute CAC is:

CAC = Total cost of Sales & Marketing  /  No of Deals closed

It turns out that we are actually interested in two CAC numbers. One
that looks purely at marketing program costs, and one that also takes
into consideration the people and other expenses associated with
running the sales and marketing organization. The first of these gives
us an idea of how well we could do if we have a low touch, or touchless
sales model, where the human costs won’t rise dramatically over time as
we grow the lead flow.  The second number is more important for sales
models that require more human touch to close the deal. In those
situations the human costs will contribute greatly to CAC, and need to
be taken into consideration to understand the true micro-economics.

I am often asked when it is possible to start measuring this and get
a realistic number. Clearly there is no point in measuring this in the
very early days of a startup, when you are still trying to refine
product/market fit. However as you get to the point of having a
repeatable sales model, this number becomes important, as that is the
time when you will usually want to hit the accelerator pedal. It would
be wrong to hit the accelerator pedal on a business that has
unprofitable micro-economics. (When you are computing the costs for a
very young company, it would be fair to remove the costs for people
like the VP of Sales and VP of Marketing, as you will not hire more of
these as you scale the company.)

When we look at how to lower CAC, there are a number of important variables that can be tweaked:

  • Sales Funnel Conversion rates: a funnel that takes
    the same number of leads and converts them at twice the rate, will not
    only result in 2x more closed customers, but will also lower CAC by
    half.  This is a very important place to focus energy, and a large part
    of this web site is dedicated to talking about how to do that. We will
    drill down into the Sales Funnel conversion rates next.
  • Marketing Program Costs: driving leads into the
    top of your sales funnel will usually involve a number of marketing
    programs. These could vary from pay per click advertising, to email
    campaigns, radio ads, tradeshows, etc. We will drill down into how to
    measure and control these costs later.
  • Level of Touch Required: a key factor that affects
    CAC is the amount of human sales touch required to convert a lead into
    a sale. Businesses that have a touchless conversion have spectacular
    economics: you can scale the number of leads being poured into the top
    of the funnel, and not worry about growing a sales organization, and
    the associated costs. Sadly most SaaS companies that I work with don’t
    have a touchless conversion. However it is a valuable goal to consider.
    What can you do to simplify both your product and your sales process to
    lower the amount of touch involved? This topic is covered at the bottom
    of a prior blog post:  Startup Killer: the cost of acquiring customers.
  • Personnel costs: this is directly related to the
    level of touch required. To see if you are improving both of these, you
    may find it useful to measure your Personnel costs as a % of CAC over
    time.

 

Drill down on Sales Funnel Conversion Rates

The metrics that matter for each sales funnel, vary from one company
to the next depending on the steps involved in the funnel. However
there is a common way to measure each step, and the overall funnel,
regardless of your sales process. That involves measuring two things
for each step:  the number of leads that went into the top of that
step, and the conversion rate to the next step in the funnel (see
below).

 

image

 

You will also want to measure the overall funnel effectiveness by
measuring the number of leads that go into the top of the funnel, and
the conversion rate for the entire funnel process to signed customers.

The funnel diagram above shows a very simple process for a SaaS
company with a touchless conversion. If you have a conversion process
involving a sales organization, you will want to add those steps to the
funnel process to get insights into the performance of your sales
organization. For example, your inside sales process might look like
the following:

 

image

 

Here if we look at the closed deals and overall conversion rates by
sales rep, we will have a good idea of who our best reps are. For lower
performing reps, it is useful to look at the intermediate conversion
rates, as someone that is doing a poor job of, say, converting demos to
closed deals could be an indication that they need demo training from
people that have high conversion rates for demos. (Or, as Mark Roberge,
VP of Sales at HubSpot, pointed out, it could also mean that they did a
poor job of qualifying people that they put into the Demo stage.)

These metrics give you the insight you need into your sales and
marketing machine, and those insights give you a roadmap for what
actions you need to take to improve conversion rates.

Using Funnel Metrics in forward planning

Another key value of having these conversion rates is the ability to
understand the implications of future forecasts. For example, lets say
your company wants to do $4m in the next quarter. You can work
backwards to figure out how many demos/trials that means, and given the
sales productivity numbers – how many salespeople are required, and
going back a stage earlier, how many leads are going to be required.
These are crucial planning numbers that can change staffing levels,
marketing program spend levels, etc.

Drill down by Customer Type

If you have different customer types, you will want to look at all
the CAC and LTV metrics for each different customer type, to understand
the profitability by customer type. Often times this can lead you to a
decision to focus more energy on the most profitable customer type.

Drill down into ROI per Marketing Program

My experiences with SaaS startups indicate that they usually start
with a couple of lead generation programs such as Pay Per Click Google
Ad-words, radio ads, etc. What I have found is that each of these lead
sources tends to saturate over time, and produce less leads for more
dollars invested. As a result, SaaS companies will need to be
constantly evaluating new lead sources that they can layer in on top of
the old to keep growing.

image 

Since the conversion rates and costs per lead vary quite
considerably, it is important to also measure the overall ROI by lead
source:

 

image

 

Growing leads fast enough to feed the front end of the funnel is one
of the perennial challenges for any SaaS company, and is likely to be
one of the greatest limiting factors to growth. If you are facing that
situation, the most powerful advice I can give you is to start
investing in Inbound Marketing techniques (see Get Found using Inbound Marketing).
This will take time to ramp up, but if you can do it well, will lead to
far lower lead costs, and greater scaling than other paid techniques.
Additionally the typical SaaS buyer is clearly web-savvy, and therefore
very likely to embrace inbound marketing content and touchless selling
techniques.

From Alistair Mitchell, CEO of Huddle: “Just calculating CAC can be
extremely complicated, given the numerous ways in which people find out
about your service.  To stop getting too bogged down in the detail, its
best to start with a blended rate that just takes your total spend on
marketing (people, pr, acquisition etc) and split this across all your
customers, regardless of type or source. Then, once you’ve got
comfortable with that, you can start to break CAC down by the different
customer types and elements of your inbound funnel, and start measuring
specific campaigns for their contribution to each customer type.”

Drill down into Churn Rate

image

As described in the section on LTV, Churn Rate has a direct effect
on LTV. If you can halve your churn rate, it will double your LTV. It
is an enormously important variable in a SaaS business. Churn can
usually be attributed to low customer satisfaction. We can measure
customer satisfaction using customer surveys, and in particular, the Net Promoter Score.

If you are using longer term contracts, another key metric to focus
on is renewals. From John Clancy, ex-President of Iron Mountain
Digital: “

Non-renewals add to churn, but they can have different drivers. We
spent a lot of time examining our renewal rates and found that a single
digit improvement made a huge difference. Often times the driver on a
non-renewal is economic – the internal IT department has mounted a
campaign to bring the solution back in house. SaaS businesses need to
identify renewal dates and treat the renewal as a sales cycle (it’s
much easier and less expensive than a new sale, but it deserves the
same level of attention) Many SaaS businesses make the mistake of
taking renewals for granted.”

A good predictor of when a customer is about to churn is their
product usage pattern. Low levels of usage indicate a lack of
commitment to the product. It can be a good idea to instrument the
product to measure this, looking for particular features our usage
patterns that are correlated with stickiness, or a likelihood to churn.

Another measurement tool that can be very useful in understanding
churn is to look at a Cohort Analysis. The term cohort refers to a
group of customers that started in the same month. The reason for doing
this is that churn varies over time, and using a single churn number
for all customers will mask this. Cohort analysis shows:

  • How churn varies over time (the green call out below).
  • How churn rates are changing with newer cohorts, (the red call out
    below)  For example in the early days of your SaaS company, you may
    have serious product problems and lose a lot of customers in the first
    month. Over time your product gets better, and the first month churn
    rate will drop.

Cohort analysis will show this, instead of mixing all the churn rates into single number.

 

image

 

Here’s a comment on Cohort Analysis from Alastair Mitchell, CEO of
Huddle: “I actually think this is more important than churn, for the
simple fact that churn varies over the lifetime of a customer cohort,
and just looking at monthly churn can be very misleading.  Also, given
the importance of payback in a year – you really want to look at churn
over the course of a 12 months cohort. For instance, in the first 3
months of a monthly paying customer you will see high churn (3 is a
recurring ‘magic’ number in all of retail), then reduced churn
(sometimes even positive churn) over the next 3 months less and then
probably more stable spend over the next 6 months. The number you
really care about is the % of customers spending after 12 months (not
necessarily on a monthly basis) as that’s what matters for your CAC
payback calculations.”

Two variables that really matter

As we saw above, there are two variables that have a huge effect on
a SaaS business: funnel conversion rate, and churn, and it is not a bad
idea to graph them as shown below.

image

 

Drill down into ARPU (Average Revenue per Customer)

image

ARPU is often different for different customer categories, and
should be measured separately for each category. It can usually be
driven up by focusing on:

  • Product Mix: adding products to the range, and using bundles, and cross-sell and up-sell
  • Scalable Pricing:  there are always some customers
    that are willing to pay more for your product than others. The trick is
    developing a multi-dimensional pricing matrix that allows you to scale
    pricing for larger customers that derive more value from the product.
    This could be pricing by the seat used (Salesforce.com), or by some
    other metric such as number of individuals mailed in email campaigns
    (Eloqua).
    If you are using scalable pricing, it will be valuable
    to measure what the distribution is of customers along the various
    axes. You could imagine taking an action to do after more seats inside
    of existing customers as a way to drive more revenue. etc.

 

Drill down into Cash

 

image

We already discussed Months to recover CAC as a key variable. There
is another way to affect Cash: which is using longer term contracts and
incenting your customers to pay for 6, 12, 24, or even 36 months up
front in advance. This can mean the difference between needing to raise
tons of venture capital and giving away ownership, or being able to
grow the business in a self-funded manner. Given the cost of capital,
you can often calculate what discount makes sense. (If capital is cheap
and freely available, it doesn’t make sense to give much discount.)

If you do use longer term contracts, it will be important to measure “Discretionary Churn”.
Since some of your customers are locked in and cannot churn, they could
artificially lower your overall churn numbers. The way to understand
what is really going on is to look at the discretionary churn, which is
the churn rate for all customers that are at the point where they have
the option to churn, removing those whose contracts would have
prevented them from churning.

Cash Management and forecasting

Cash is one of the most important items to get right in any startup.
Run out of cash, and your business will come grinding to a halt
regardless of how good any of your other metrics may be. One of the
most important ways to run a SaaS company is to look at CashFlow
profitability (not recognized revenue profitability). What is the
difference: If your business only gets paid month by month, there will
be no difference, but if you get longer term contracts, and get paid in
advance, you will receive more cash upfront than you can recognize as
revenue, so your cash flow profitability will look better than your
revenue profitability, and is a more realistic view of whether you can
survive day to day on the money coming in the door.

Here is another comment from Alastair Mitchell of Huddle on this
topic: “SaaS companies tuning their model should think not just in
terms of the months to recover CAC, but also the topline amount of cash
required to get to cashflow profitability (or the next funding round).
This is probably the single biggest mistake I see in early stage
companies. They don’t look ahead, using these metrics, to figure out
that if the time to repay CAC is 12 months, then in aggregate they are
going to need 12 months of CAC spend PLUS the number of months required
of further growth to cover their operating costs (mostly engineering)
BEFORE they are even cashflow positive (let alone revenue
profitability). Most businesses I see fundamentally miss this and end
up short; frequently through under-estimating the time to recover CAC,
and churn. The readers of this blog should be focused on cashflow
profitability, not revenue profitability. (Hence why your point about
annual/upfront contracts is so important)”

Drill down into Growth

image

Focusing on Growth as a separate parameter can be highly valuable.
It is the nature of a SaaS business to grow MRR month on month, even if
you only added the same number of customers every month. However your
goal should be to grow the number of new customers that you sign up
every month. You can do this by focusing on:

  • Improvement in the overall funnel conversion rate
  • Lead Generation Growth
  • Growth in Funnel Capacity

The first two have been covered already. The last bullet: Growth in
Funnel Capacity is an often overlooked metric that can bite you
unexpectedly if you don’t pay attention to it. In my second startup, I
had a situation where sales growth stalled after growing extremely
rapidly for a couple of years. The problem, as it turned out, was that
we had stopped hiring new sales people after reaching 20 people, a
number that felt very large to me, and had maxed out on sales capacity.
We started sales hiring again, and a couple of years later the business
hit a $100m run rate. I witnessed a similar phenomenon at Solidworks,
when after 2-3 years of phenomenal growth, their growth slowed. It
turned out that their channel sales capacity had stopped growing.
Solidworks started measuring and managing something that would later
turn out to be a critical metric: channel capacity in terms of the
number of FTE (Full Time Equivalent) sales people in their channel, and
the average productivity per FTE. This has helped propel them to over
$400m in annual revenues.

Another great way to grow your business is by adding new products
that can be up-sold, or product features that can lead to a higher
price point. Since you already have a billable contract, it is
extremely easy to increase the amount being charged, and this can often
be done with a touchless sale.

Other Metrics

There are a series of less important metrics that can still be
useful to be aware of. I have listed some of these in the diagrams
below:

image

image

After posting the above, I received a note from Gail Goodman of
Constant Contact, noting that they include the cost of on-boarding a
customer in CAC, not LTV as I have shown. Given that they are a public
company with significant accounting scrutiny, this is likely the right
way to do things.

Conclusions

If you have kept reading this long, it likely means that you are
likely an executive in a SaaS company, and truly have a reason to care
about this depth of analysis. I would very much like to hear from you
in the comments section below to see if I have missed out on metrics
that you think are important.

The main conclusion to draw from this article, is that a SaaS
business can be optimized in many ways. This article aims to help you
understand what the levers are, and how they can affect the key goals
of Profitability, Cash, Growth, and market share. To pull those levers
requires that you first measure the variables, and watch them as they
change over time.

It also requires that you implement a very metrics driven culture,
which can only be done from the top. The CEO needs to use these metrics
in her staff meetings, and those execs need to use them with their
staff, etc. Human nature is such that if you show someone a metric,
they will automatically work to try to improve it. That kind of a
culture will lead to true operational excellence, and hopefully great
success.

David Skok is a General Partner with Matrix Partners in Waltham, Massachusetts.  This blog post was originally published on February 17, 2010.  You can find this post, as well as additional content on his blog called For Entrepreneurs.

Welcome to the new and improved VentureFizz Blog...now called Voices!

February 17, 2010

Welcome to the new and improved VentureFizz Blog...now called Voices!

We receive a tremendous amount of feedback from our readers and followers
about how we can make VentureFizz better.  The most requested feature is
to add full length blog content on our site.

The original layout for the blog section on VentureFizz was an aggregation
of blogs that we follow.  Although this format was great for our first
release, we also agreed that it would be a lot more helpful to have the full
details of this content on VentureFizz.

Thus, we are excited to announce our new Blog section, which is properly named Voices!  The goal of
this section is to provide highly useful and relevant content for all parties
interested in Boston’s tech community.

VentureFizz has added a number serial entrepreneurs, venture capitalists,
and experts to its growing roster of guest bloggers.  Sample topics
include: Entrepreneurship, Innovation, Success Stories, Lessons Learned, etc.

To get things kicked off… over the next couple of weeks, we will be
releasing some of our favorite blog posts by our remarkable lineup of guest
bloggers.

Although some of these posts have already been published, we are excited to
include them as part of our new blog section and we feel that they are certainly worth revisiting!

Enjoy!

Please note:  A.  The comments section is being completed and will be released soon.  B.  The original lists of blogs will be moved to our
Resources section shorty.  Each listing will fall under a new category that we will create called "Blogs."

 

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