Are you made of the right stuff?
An ambitious and interesting project aimed at discovering the patterns at successful internet startups was announced on Saturday and is called Startup Genome. Over 650 businesses have been surveyed in quite some detail, so the results should be telling. The concluding reports will, I predict, turn out to be some of most influential pieces of research ever done on internet startups.
It’s important to state that this study is about internet startups specifically. There are lessons that other businesses can take from the report but one needs to be careful not to generalise. Also it’s important to remember that, as far as I know, the results are largely based on startups in Silicon Valley. As we all know, things don’t happen the same elsewhere: Availability of risk capital is much scarcer, for one thing. Also much of the initial report relates to companies that raised investment funding in seed and VC rounds. We can learn as much, if not more, from failures, of course. Some interesting findings, about that, have now been published here.
Six stages of company evolution are proposed as follows (personally I like this model), which I’ve paired with my personal take as shown in italics :
1) Discovery: Create something useful and listen or die
2) Validation: Find ways to get customers to part with cash
3) Efficiency: Get more customers whilst burning cash effectively
4) Scale: Growing pains of every type
5) Profit Maximization: Milk your customers, oops sorry: Reward your shareholders
6) Renewal: Start your next venture
The authors propose four classes of startups, as follows, with some well known examples:
- Automizer: Google, Dropbox, Hipmunk
- Social Transformer: Ebay, Skype, Airbnb
- Integrator: PBworks, Uservoice, Flowtown
- Challenger: Oracle, Salesforce, Yammer
These classes are provided without a clear explanation of what they constitute, although helpfully, they have provided a list of example companies and typical characteristics. So, what the hell, let’s have a go at trying to clarify this thinking.
OK, I contend that all the classes of startups are aiming to provide:
- More efficient & effective ways….
- to do stuff….
- for different classes of users
I would then propose to define the four classes as being focussed, on different users, as follows:
- Automizer: Individuals and small groups
- Social Transformer: Individuals, in a network, who interact and transact
- Integrator: SMEs
- Challenger: Enterprises in complex & rigid markets
OK, I’ve over simplified. But I think their classification of startups is interesting and insightful. I find it helps when thinking about my past experience and current activities.
At Century Dynamics (sold to NASDAQ: ANSS) where I was a co-founding technical director then managing director, we were definitely a “Challenger”. OK, we were largely pre-interweb but we were a software company selling globally, so the model still works. Also we were never funded by anybody outside the company. That’s one of the reasons it was a long road of bootstrapping and 14 years from startup to exit. It did not seem much of an achievement at the time but reading this post makes me question whether we actually did extremely well, particularly since we were selling to some glacially slow engineering sectors.
With the current startups that I am closely involved in, we are an “Automizer” (Pitchie) and a “Social transformer” (Tripbod).
Actually with Pitchie we are in our first month, at the Discovery stage, so it’s quite possible we will end up positioning differently: But to talk about that further would be revealing our plans for world domination, which we are keeping quiet about for now😉
Tripbod is very much a social transformer. We are driven by our desire to cut out economic leakage in the tourism industry, where much of the money is taken by middlemen. We are all about connecting travellers directly with local travel providers making us a bona fide network business.
Part of the report findings were that Automizers and Social transformers have as their primary motivation a desire to change the world. Similarly the desire to build a great product was found to be the main drive for Integrators and Challengers. Tellingly only 8% of entrepreneurs surveyed said they care more about money than impact (68%) or experience (27%).
One of the main hypotheses, that the authors set out to test, is that success correlates with founders who are open to learning. Their initial findings are, they say, strongly suggestive of that and cite the following evidence, which is interesting but hardly conclusive:
- Companies that track metrics effectively, and thus learn, achieved 3 to 4 times better growth rates of users
- They considered that following thought leaders was a proxy for willingness to learn. Those companies that did so were 80% more likely the raise funding
- Companies with helpful mentors were significantly more successful and raised around 7 times as much investment capital
The average funding received by company stage is shown below:
- Discovery = $150,000
- Validation = $600,000
- Efficiency = $900,000
- Scale = $3,000,000
The authors recommendations on what they think should be raised are $10,000 to $50,000 at Discovery and $100,000 to $1,500,000 at Validation. They further propose that nothing more is raised at the Efficiency stage. They suggest that the stark differences in the funding raised and what the authors recommend is due to angels over investing in startups. But remember this is in Silicon Valley: I don’t see that problem in the UK and neither does Scott Allison of Teamly.
Surely a difference today is that it costs a lot less to build an internet business than it did even two years ago. Many of the companies surveyed must have started out before that time.
Apparently there was no difference in whether investors were helpful or not on a daily basis. They conclude “We think this may be because investors’ main value add is their ability to increase the valuation in future rounds, and get larger exit sizes. Their help on a daily basis, which consists mostly of introductions and help with recruiting is not that signiﬁcant because great entrepreneurs will ﬁnd a way to get introduced to the people they want to hire and build a great team even if their investors don’t help.”
The most telling finding, in my opinion, is buried in the Miscellaneous section. They found a dramatic difference in the market size estimates made by the companies for their target markets, as shown here.
For companies that did not raise funding:
- Discovery: $200Bn
- Validation: $120Bn
- Efficiency: $50Bn
- Scale: $8Bn
For companies that did raise funding:
- Discovery: $0.16Bn
- Validation: $1.3Bn
- Efficiency: $20Bn
- Scale: $9Bn
Enormous differences you will agree at the first two stages! One is tempted to conclude that if you have failed to raise early funding then it’s very likely you are deluded.
Finally here is an interesting statistic that is reported without explanation or context: 81% of entrepreneurs don’t care about rules.
What do you think, fellow troublemakers?
- How would you classify your startup? Do you like the classification used? Is it helpful?
- Are mentors important for your learning? Or are they just good for contacts, so raising funding becomes easier?
- What are you going to do differently having read this blog post or the report?