Browsing articles from "February, 2010"

The Brown Swan Theory

Venture investors continue to be attracted to consumer internet investments like moths to a candle. VentureBeat and ChubbyBrain (what a name!) indicated that Internet sector investments surged in Q4 of 2009 by 40% over Q3 to $1.5 billion. Yet the distribution of returns to Internet investors remains both highly consolidated. Granted, Internet sector can mean a lot of things to a lot of people, but it begs the question: Why do investors continue to pour money into the segment?

  1. The opportunity for hugely outsize returns: The black swan.
  2. Visibility. Activity begets activity, and visible activity especially so. It may not directly impact investment return, but it certainly enhances a firm’s profile (unless the investment is unsuccessful, of course), attracting more black swan opportunities, in a virtuous cycle.
  3. Scale begets scale. This point is perhaps least appreciated. Unlike in B2B plays, successful consumer internet companies experience a period of growth during which revenue becomes easier to scale with size, rather than harder. This third point, I believe, is what makes the sector so appealing and fundamentally enables the opportunity for outsize returns.

Scaling A Business to Business Company

Enterprise Growth Curve

In Business to Business companies, even those with a SaaS delivery model, scaling revenue goes from very difficult to difficult, then to easier, then back to very difficult. The very first revenue is hard won. Companies can spend a long time trying to find the right product / market / sales model fit, doing under, to pick a number, a million dollars in revenue per quarter.

Companies that get out of this stage and into, say, a million or more of revenue per quarter can often scale their way to between $10M and $50M or even $100M of revenue per year at a “good” growth rate – with the great ones achieving 50 – 100% year over year growth.

But continuing to grow sales at this rate is historically unsustainable in the long run, and investment bankers looking at potential IPO’s have indicated that a growth rate in the 25% year over year range is more believable.

Why Does Sales Growth Slow?

Scaling sales past the $50M – $100M range requires leverage. It requires not only a very large market, but an efficient sales infrastructure to sell into that market, both in the form of new sales and additional sales to existing customers.

That kind of leverage and efficiency comes from a large channel that can support selling to the market – either directly, through the hiring of large numbers of sales people, or indirectly, through existing channel partners that can reach the volume of customers required to obtain that level of revenue – and growth.

Leverage is hard to get and ultimately reaches a limit, leading to reduced year over year growth.

The Consumer Internet Paradox

The appeal of successfully monetized consumer internet businesses (and the promise of those that are scaling users but not yet scaling revenue) is the long period of hyper-growth these businesses experience.

Consumer internet businesses are relatively easy to start, but it’s hard for them to get momentum. But if a consumer internet company can get the flywheel spinning, monetization at scale becomes easier and easier for a much longer period of time than for business to business companies.

That’s because successful consumer Internet companies — particularly those with a viral user acquisition dynamic — get unbelievable customer (user) acquisition leverage. That leverage comes in the form of existing customers (users) acquiring more user, virtually for free: zero cost user acquisition.

In the business world, scale delivers some leverage in the form of customer references and category leadership, but the company still has to sell the product — existing customers don’t sell the product to other customers. In the consumer world, they do.

Scaling A Consumer Internet Company


The challenge for investors is that investing in a great consumer internet company is very hard to do, because consumers are incredibly fickle and behave as a crowd. The right consumer Internet investment strategy? Invest early in a lot (that is, potentially 100′s of deals) with an ultra high probability of losing all the money (but a a very small chance to make a ton) or invest late,  waiting until real traction is proven.

Nassim Nicholas Taleb is well-known for his Black Swan Theory. Although talks about taking advantage of positive black swan events, he often focuses on rare negative events (“avoid being the turkey”).

In venture investing, the weight is flipped. It’s absolutely essential to identify risks, but first and foremost in generating returns is exploiting rare positive black swan opportunities when they occur.

Just as valid as asking why investors continue to invest in the Internet sector given the low probably of success is asking why they don’t make that high beta investment sector their only one in an asset class invested in for its high beta-ness.

The answer might best be called The Brown Swan Theory: Managing large pools of capital requires a strategic framework that allows for identifying and investing in positive Black Swans when they occur, and for doing it at the same time as demonstrating a path to market outperforming returns on a regular basis.

That’s the easy part. The hard part, of course, is not missing too many black swans.

Feb 22, 2010

When It Makes Sense To Take Sales Risk

Why should investors take sales risk?

By default, they shouldn’t.

Sales development is by far the biggest cost in venture-backed startups. Some investors estimate that as much as 70% of venture investment goes toward sales development. Few startups get it right on the first try. That frequently means an indeterminate number of additional rounds of funding to remove sales risk.

People have been selling for a lot longer than the professional venture industry has been around. So why does every company have to learn to sell? On the surface, it seems like getting up Mark Leslie’s famous Sales Learning Curve (SLC) should be easily repeatable. Tens of thousands of startups have taken a hard run at the curve, and some have succeeded. Just teach the right process, or better yet, hire an exec that has succeeded before.

The reason replicating sales success is so difficult is because success just isn’t that easy to replicate.

It’s the reason that the same team doesn’t win the Superbowl every year, that the same investors don’t make all the money year after year, the reason top mutual fund managers eventually break their S&P beating streak.

It’s quite possible, in fact highly likely, that an entrepreneur or sales executive benefited the first time from a great market and a great product. Not that they weren’t incredibly talented, but trying to repeat that success is as likely to depend as much on finding a tornado market as on the talents and expertise of the entrepreneur or executive.

Getting up the SLC is difficult because you have to get a lot right. The right market, product, and team. The right market is one in which customers or users want the offering now. They can’t live without it. The right product is one that delivers on its promise. The right team executes — it repeatedly runs experiments — and is expert at rapidly scaling the few that work.

Repeating the process, once developed, isn’t hard. What is hard is getting to a repeatable process.

There are lots of tools available that can help mitigate risk in the sales development process, including methodologies like High Probability Selling. But once the process is figured out, the best way to replicate it is through great hiring. There is little more frustrating than poor execution due to on the job training in a great market.

When Should Investors Take Sales Risk?
Why invest early when you could just wait, especially in markets where multiples are relatively low?

The answer is that, in many cases, you shouldn’t. There are few companies that are going to go from $100 million to a billion or more. The risks of investing later are: being wrong about where a company truly is on the sales learning curve and the opportunity cost of the money invested in a company that never truly has the capability to go from $100M to $500M or $1B+.

So when should investors make these early bets in relatively low multiple markets in which scaling sales is expensive?

  • When the investor can buy a large portion of the company and believes he can get leverage on the early money. By leverage, I mean, backing an entrepreneur who will either be able to run a very low burn experiment to reach the inflection point of the curve, and/or has the ability to raise Other People’s Money (also known as OPM) repeatedly to iterate the sales model until the company moves up the curve.
  • When a huge existing market is being radically disrupted or an entrepreneur has the ability to disrupt a market. Or put another way, when human behavior is changing (example: the shift from time spent offline to online) and a startup can take advantage of it.

As Chris Chase wrote in his Super Bowl summary, “Super Bowls are usually defined by conservative play. It rarely pays for coaches to be risky in the game. Little good can come from it. Nobody criticizes the safe play, only the bold one that doesn’t work. But when it works, it’s the stuff from which Super Bowl legends are made.”

One might easily say the same about investing.

Feb 8, 2010

Product First, Platform Second

The debate about investing in startups that rely on cloud infrastructure has long raged within the venture community. Investors are rightfully cautious about backing companies that have a large dependency on another entity that could control a startup’s economics. That’s because platform providers have long been known to encourage startups to build on their platforms, and then once a strong ecosystem is established, to take the majority of the economics out of that ecosystem. That’s not to say that entrepreneurs can’t make a lot of money building applications on other platforms — they can. The question is whether investors can.

  • For a startup to be successful building on top of a platform, there are a few considerations. If that functionality is close to the platform, the startup has to believe it can stay ahead of the platform integration expansion curve. This has been done but it is a constant treadmill — think Rational / Microsoft for development tools.
  • Another option is to look at verticals, especially verticals that are overdue for disruption or that are highly fragmented. While these can be successful, they are difficult to execute — there’s a reason verticals stay fragmented and it often more to do with channel establishment than technology adoption.
  • A startup can build on top of a platform where the application or applications truly are different than the core platform functionality.
  • Finally, a startup can build an application that gets deployed on multiple platforms but potentially launches on one platform first. This is difficult in a world of many, many platforms (think client based applications for mobile phones before the iPhone). But in a world of two or three platforms, it is not a bad bet.

The other risk with playing too close to the platform is that over time platforms tend to integrate much of the adjacent functionality delivered by ecosystem vendors into the core platform. In many cases, while the size of a participant’s business while large by itself is relatively small in the context of the platform provider’s revenue total stream for platform related revenue, platforms by their nature add core functionality by going after the next closest piece to the platform.

Risk Mitigation
For those evaluating the risk of investing in companies building on a particular platform, rather than investing in a company that some day has the potential to be a platform in and of itself, the question is whether they can invest in the company and have it get to an interesting size so that it can have a near equal relationship with the platform. By interesting size, I mean, on a path to go public or to actually go public as a tool to have the public markets support its market position and valuation.

While Amazon may change their business model for Web Services in the future, all indications so far point to delivering a great platform for its partners by competing on operational efficiency at scale – as signaled by the recent price decrease. And Amazon is well positioned to deliver on that promise given the scale of the operation it runs.

Other platforms tend to have an innate desire to deliver not only platform functionality upon which applications can be built, but to involve themselves in distribution as well. It goes without saying that platforms, by their very nature, need applications to be successful. A platform without applications built on top of it is much like a tree falling in the forest with no one to hear it. To get these applications developed, platforms build their own applications (Office on Windows) to seed the platform, and then work to get adoption of the platform by others. They help the early ecosystem partners not only on technology but also with distribution, that is, customer acquisition.

Getting leverage on distribution cost is critical to the sucess of a venture backed company. And a platform can be a very appealing partner in getting that distribution, at the beginning. In most cases, in fact, it is simply too good an opportunity to pass up. The risk to the startup comes later when the platform provider has the option of changing the economics of the relationship. Or when the platform provider integrates external functionality that is too close to the platform.

Amazon, one of several in the platform game, is doing an excellent job signaling that it is truly a platform upon which it wants others to build. AWS appears to be about easiest access, low cost utility computing first, and distribution control a distant second, if at all. That could change, of course, but it is unlikely because it would undermine the core value proposition of AWS as a cloud platform.

That’s good news for startups and venture investors alike.

It is typically a bad idea to set out to build a platform company from the get-go. That’s because people buy and use products, not platforms. But those companies that are huge do ultimately become platforms. was a CRM application first. Now is endeavoring to become a platform. Amazon was a book-seller first, now it’s a platform. Facebook was an application first, now it too is trying to become a platform. What is common across all these platforms and platforms-to be are that they were products first, platforms second. What will be different is the extent to which new application companies come to rely on them for distribution.

As I wrote some time ago, I’d rather have a company that ultimately defines the ecosystem and owns the customer (or user) than a company that is part of the ecosystem. I’m certainly not against investing in companies that are not ultimately platforms — many valuables ones have and will continue to be built. And by the nature of platform success, you’re a product before you’re a platform.

But those that are able to obtain product success and then make the transition to platform have proven time and again to be most valuable.

Feb 3, 2010