Hi, I'm a partner at Redpoint
. I invest in Series A and B SaaS companies. I write daily, data-driven blog posts about key questions facing startups. I co-authored the
book, Winning with Data
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Australia, Canada, Israel, China, India. SaaS startups are thriving in these countries and many more. Next generation software companies hail from many different parts of the world, and some of them are worth billions of dollars. Shopify and Hootsuite in Canada. Atlassian in Australia. Xero in New Zealand, just to name a few. As these successful startups have boomed, how has the early stage fundraising market for them evolved?
SaaS startups often find themselves in one of three different states when contemplating their burn rate. The first is the David Farragut strategy. Damn the burn rate, full speed ahead. The second is the conservative approach - attaining profitability using only the cash on the balance sheet. Those two are easy. Circumstances dictate the respective aggression or conservatism. Lots of cash or not so much. The more complicated state is the one in between, and that is the one that most SaaS startup operate within.
Sales leaders consistently underinvest in sales team training and development. As SaaS startups scale, sales execution becomes the most tangible metric of a business' success, and the one by which the business' health is benchmarked. Not to mention how the head of sales is evaluated. When is the right time to invest in sales training? And how much should a business invest?
When I say bubble, you likely conjure images of people speculating on real estate or stocks or tulips in your imagination. Like me, you might dismiss the folly of these bubbles as the collective action of a multitude of people who lose all rationality when bidding on these assets. But, as I learned from a recent interview with Brian Christian, bubbles can be created even when everyone acts rationally. This phenomenon is called an information cascade.
What is your SaaS startup worth in an acquisition? To answer that question, we can analyze the data set of all software companies acquired over the last six years and benchmark them by enterprise value-to-revenue multiples.
For hundreds of startups in the as-a-service world, the scores of product launches at last week's Amazon Web Services Reinvent Conference each were a warning shot across their bows. We are coming. We are coming right after you, with tens of billions of dollars on our balance sheet, hundreds of salespeople, and the broadest suite of software and infrastructure since Oracle. Anything that's open source with traction, we will host. Any business where we see margin is our opportunity. We are coming fast and hard. At least, that's the way I interpreted it.
In June, Frank Bien and I published our book, Winning with Data. It describes through case studies how some of the most successful startups use data to create sustainable competitive advantage. Since then, we've sold thousands of copies. Today, we're releasing an Audible version of the book.
Bookings, MRR, Revenue. All these metrics form part of the financial statements of SaaS companies. For as long as SaaS companies have existed, we've used one way of counting revenue, called GAAP. Starting in 2017, revenue recognition for SaaS companies will change, and SaaS startups will have more flexibility in the way they record revenue than in the past.
As a SaaS startup begins to reach critical mass, the business generates more of its revenue from upsells and expansions, reaching about 30% at between $40-75M in revenue, which is in line with some of the models we've created. Many times startup teams ask how to compensate a sales team for renewals and upsells. The 2016 PacCrest Survey contains a wealth of information about these types of go to market questions.
Numbers provide us a certain certainty. With their precision, they offer a sense of black and white, in or out. But, metrics alone aren't enough. All the quantitative analysis in the world won't lead me to the next great idea for startup. Those figures can't create empathy, develop the right culture, or hire the right people. I've been thinking about this quite a bit because in both the recent Software Engineering Daily podcast I did with Jeff, and the presentation I gave at Launch Conference, the question of the limits of metrics surfaced.