Each morning's news seems to bring another fund-raising announcement of ever larger scale. Just a few months ago, Pure Storage raised $150M in the largest ever venture investment in a storage company. These record financings certainly generate significant press interest. But how representative of the fund raising environment are these mega-rounds?
Last week, Sean Ellis made an interesting comment in response to this post on public SaaS companies' growth rates. "Everyone seems to throw out the 15% - 20% month over month MRR growth as the target. But seems like it's just a random target." I'm guilty of giving the same advice to startup founders without providing a transparent rationale. This post is my explanation of why the 15-20% MRR growth number is a reasonably good target for post-Seed/pre-Series A SaaS startups to aim for.
At the time of the IPO, the median Software-as-a-Service (SaaS) company generates $100M in revenue, creates $2.6M in profit and holds $85M in cash on the balance sheet. A company in this position typically raises $107M in its IPO and trades at 11x revenue, for a $1.1B market cap.
SaaS companies are the darlings of the public market. The average publicly traded SaaS company enjoys twice as strong a revenue multiple as ten years ago. SaaS companies' time to IPO has been decreasing steadily from over 10 years since founding to under 7. Despite the decrease in time to IPO, the average dollars raised at IPO has tripled from the early nineties and grown by 50% since 2000.
One of the most important trends in the Internet at the moment is unbundling. Entrepreneurs are picking apart Craigslist and eBay, vertical by vertical. At the same time, other entrepreneurs have replicated the core functions and features of Facebook and LinkedIn, creating hugely valuable companies. But simply calling this trend unbundling doesn't do the movement justice, particularly in the transactional web. The trend is more fundamental.
Since the first transistor, ncreasing speed has been at the core of much innovation in Silicon Valley . Over more than three decades, Moore's Law has remained the engine of progress in chip technology. I've been wondering if a analogous productivity law will be written for data.
Most SaaS companies provide tools to help people accomplish a goal in a better way than they could before. A key part of a SaaS startup's toolkit, then, is changing end user behavior. A startup that doesn't change the behavior of a customer will see the customer churn in a few months or at the expiration of their contract. Customers don't change their behavior for many reasons. Sometimes the friction to adopting a new workflow is too great. Other times, the value proposition isn't compelling enough for users. Or, the use case is too infrequent for users to remember to change behavior.
Over the last 12 years, the number of startups founded has grown each year by 25%, according to Crunchbase data. That's quite an acceleration each year! As the number of companies in a sector grows, do the odds of successfully raising capital decrease?
Raising capital from venture capitalists at any stage can seem like a very strange, ambiguous and amorphous process. I've written about the way Redpoint diligences/researches a startup and its market and what questions we tend to ask at each stage. In this post, I'll focus on the process from entrepreneur's point of view.
The process of creating the right culture in a startup has always been mysterious to me. Each company's culture evolves in its own way. I've wondered whether the culture is set by the personalities of the founders, or prominently displayed value statements and mission, or biases purposely imposed in the hiring processes like Google's googliness filter. Or is understanding the psychological forces at play among employees the most important element?