The SaaSification Of Consumer

The phrase “consumerization of the enterprise” feels a bit tired, but certainly has merit as it applies to consumer design and strategies to infiltrate larger organizations. Lately, I’ve noticed something taking afoot with entrepreneurs, especially those who are building local, mobile service offerings — they’re offering their customers a new service (like ClassPass) but slapping on a subscription model at the end. No more piecemeal transactions. This has been on my mind for a few days, and finally had the time think through why this is happening:

  1. Investors are tired of piecemeal transactions: I could rattle off 10s and 10s of consumer startups which were either p2p or some distributed model where the company had to grind out transactions (usually for physical goods), and things went ok for a while and then just tapped out and flattened. Unless there’s one transaction a week (at minimum), ideally looking for 2-3 per day (hence, food) it seems investors would rather back models like Spotify where the consumer feels he/she cannot live without the service and charge on a monthly basis.
  2. Subscriptions enable bundling: Every businessperson loves a good excuse to bundle. If done correctly, the consumer pays extra for they actually use, even though they have the right to use more. Startups can then also tweak the pricing and tiers to offer specific bundles and create even more options around how to segment customers, thereby (theoretically) extracting the most revenue from them.
  3. Consumers demonstrating a willingness to subscribe: And, maybe investors are pushing this a bit, but well, consumers are responding. Look at ClassPass, growing like a weed and not even yet two years old. Rather then offering freemium models, these startups are just going right for the monthly or annual subscription. Maybe it’s that these early services are focused on cities and customers with disposable incomes. That is certainly a factor for why it’s being adopted. (For instance, I pay a monthly fee to Gmail, Dropbox, Boomerang, Sanebox, HelloSign, Spotify, Netflix, etc….I now wonder if any individual transaction that I make is on the table for a “subscription bundle.”
  4. Consumers also willing to pay more for convenience of subscription: My theory is that having the subscription, even if it may cost a bit more, reducing the cognitive load for customers to not be burdened with each transaction piling up. It removes that disincentive and in turn creates loyalty to the service.
  5. Subscriptions fit nicely with services versus most physical goods: I have been forced to try some physical products on a subscription. I get why they do it, I’m sympathetic to that. But, I rarely end up needing it. As a service, though, it’s easier to subscribe and know that I could use a service once in a month, or maybe 5x that month. It’s nice to not have to think about that.

Venture Capital Firms are Being Disrupted by Software And Data

Over the last decade, the estimated number of new tech startups formed in the U.S. each year ranged from 16,000 to 20,000, and the total amount of venture funding per year for software startups increased from ~$5 billion to $19 billion.

Most recently, over the past five years, terabytes of structured data about these startups have been proliferating on the web (see CrunchBase profile growth and App Annie traffic volume below).

App Annie Data Volume

Crunchbase Data Volume

In addition to reflecting a more active venture industry, these numbers are indicative of a rapidly expanding demographic of founders and emerging geographic hubs of innovation. Despite these changes in the startup formation landscape, internal processes used by venture capitalists to source and create value for founders have not kept pace with modern-day software innovations and the proliferation of data on seed-stage startups.

Demographic Shifts of Early-Stage Startup Founders

There is significant student demand for entrepreneurship in both undergraduate and graduate programs, which is partly a result of an imbalance between an increasing number of college students – many of whom aspire to be mid- to executive-level professionals – and the inherently small number of leadership roles at large companies.

Effectively, the career path for most people in large companies flattens out at the junior and mid-levels. Consequently, there are many recent graduates and experienced professionals who are willing to forfeit their dreams of being a big corporate executive in return for startup equity and the experience of forming or joining early-stage companies.

The difference between this generation and previous tech generations, however, is that this trend is spreading from traditional startup hubs – communities that are surrounded by top research institutions and publicly traded tech companies (i.e. Silicon Valley and Boston) – to new business capitals and urban centers, specifically cities that have access to investors, engineering talent, domain experts, and antiquated industries that are in search of technology innovation.

Emerging tech centers such as New York are embracing the rise of startup activity, with New York specifically beginning to track all of its startup formation activity online at destination sites like Digital.NYC.

The rapid growth of VC deals in NY Metro, Midwest, and LA compared to stable growth in New England.

The rapid growth of VC deals in NY Metro, Midwest, and LA compared to stable growth in New England.

Data and Volume of Startups Formed Are Overwhelming Traditional VC Operations

At the same time that startup activity is expanding across geography and demographics, the volume of data online that tracks seed-stage startups is growing exponentially. The massive quantity of constantly updated data online about startups’ founders, product traction and competitors has only existed for a few years. While much of this data is still fragmented, a large amount of it is easily assessable through APIs, and can be used in real time to detect signals of high growth startup activity.

This has given rise to tools such as DataFox, MatterMark and CB Insights, which are all aiding startup investors in quickly assessing public information on private companies. But these tools are not being used as core, end-to-end solutions that drive ongoing venture investment decisions and value creation for venture firms’ portfolio companies.

Although there has been substantial change in the tech community over the past decade, early-stage venture capital operations and processes are for the most part the same as they were twenty years ago. Conventional venture capital deal sourcing stems from personal relationships that provide access to exclusive and proprietary deals.

This information flow plus thoughtful investment theses, due diligence and sharp character judgments are the primary basis of top investors’ investment decisions – methods that have historically generated alpha for limited partners. Portfolio value creation has been derived from general partners’ personal networks (including existing portfolio companies), community managers, business development functions, and some VCs’ operating experiences/know-how.

These are tried-and-true methods that have always been employed by top VCs, and will continue to be used for years to come. But these approaches overlook new-age founders because there is a growing number of founders who do not inhabit traditional venture capital networks, and the rate at which companies are formed today overwhelms traditional manual methods of deal sourcing and vetting.

Algorithmically Searching the “Gulf of Startup Experimentation for Winners

Because of the reduced complexity to code, shrinking costs to build software, and lowered barriers to access initial funding, new founders are taking advantage of the ease of starting a company. These changes are partly responsible for the significant growth of startup formation in the tech sector, as well as the changing demographics of founders and new methodologies such as Lean Startup which encourage rapid experimentation.

This growth has created an entirely new asset class that is adjacent to the traditional seed to series A funnel (see diagram below). We refer to the extension of the seed market as a massive “Gulf of Startup Experimentation.”


Within the gulf, there is a small group of very talented technologists, product managers, designers, and domain experts who are capable of transforming their experiments into high growth startups that are difficult to replicate. Several of these startup experiments in the gulf are being financed by angels, accelerators and seed investors; and the founders of these startups are making themselves and their companies known online through platforms like Product Hunt, AngelList and CrunchBase.

In order to efficiently discover the companies within this gulf that are capable of raising competitive Series A rounds, top venture capitalists must become more sophisticated at filtering and partnering with the best founders in the gulf – a process that is imperfect if it only relies on human intelligence and personal networks as sources of the information. Traditional methods of deal sourcing and vetting simply cannot scale to sufficiently evaluate the rapid experimentation that is occurring, they need to be supplemented by a technology-based approach.

The future deal flow for top-tier seed to early-stage investors will be complemented by artificially intelligent algorithms that help sharpen investors’ view into the gulf of startup experimentation, specifically through intelligent sourcing and tracking. Investors will also use software to identify opportunities to influence outcomes (i.e. value creation) for startup management teams. These algorithms will analyze general partners’ relationships, understand a firm’s investment strategies, and proactively discover founders that the VC firm is uniquely able to support.

We are in the very early days of the adoption of software and algorithms as a core part of venture capital firms operational DNA. Several VCs have started to experiment with complementary software and statistical models to aid investment decisions; however, very few firms have retrofitted their entire day-to-day operations (i.e. from sourcing to portfolio company management) to be supported by a fully integrated software system and intelligent algorithms that contributes to the VC’s ability to generate alpha for limited partners.

The change in the industry requires innovative and emerging VC firms to discover the role that software plays in venture capital and to share knowledge with the ecosystem.

5 Tips For Building a Strong Corporate Board

Many companies put off the task of assembling an effective board until they run into trouble.

Behind every great CEO is a great board, and I’ve noticed that startup founders tend to put off the task of building strong boards. Consider successful tech companies like Amazon and Google that built their boards early on. They’re more an exception than the rule, however; more often than not, companies find that there are few, if any, consequences until they run into trouble.

Many boards have gotten into trouble when they think they answer only to the CEO.

After years of advising startups on board management and executive search, I believe that the only true role of the board is to hire and fire the CEO. After all, great boards understand that they are accountable to each other and to company shareholders. Also, great boards are diverse – in thought, background, and perspectives. The statistics bear repeating: Just 10% of Silicon Valley directors are women, and the percentage of VC-backed startups with a female founder or CEO is even lower.

So here are some practical tips for assembling a great board.

Know the company’s vision. Where do you want the company to go? Define what you need the board to do to achieve those goals. Keep that in mind as you consider and define the attributes, skills, and experiences that you need of your board members.

Seek the right skills. Create a simple grid combining attributes that actually exist in the market. Draft a table with all the desired aspects of a “final” board. Fill in the table with prospective ideas for each director, ranking each in terms of depth or fit and whether that person can be recruited. Keep this list current, fresh, and ongoing, and make it an active item of discussion at board meetings.

Develop role and responsibilities for members. As Jim Collins says, “Do you have the right people in the right seats on the bus?” It’s never too early to have committees or key areas of responsibility. Do you have the best head of audit, compensation etc.? Who are the lead directors that you as CEO can rely on in each critical area?

Build a culture and invite debate. Foster a culture of open feedback and independence. You want different opinions and perspectives to help you consider alternatives. Consider the culture and interaction you want from your board: passionate and intense debate, or cerebral and deliberative? You want to recruit a board that pushes you, makes you uncomfortable and challenges conventional wisdom. At the same time, you want a board and not an operating committee – so setting boundaries is important.

Break through your comfort zone. Boards tend to reach for what’s familiar and comfortable, which results in homogeneity. Knowing that, you should strive for diversity of opinion and not be afraid to go against the grain. Keeping that top of mind will help you be open-minded to alternatives you would not have considered in the first place.