Over the weekend, there was quite a bit of press about the challenged state of startup IPOs this year. I was curious about the real trends in share prices, so I gathered the data on some of the more salient IPOs.
The chart above shows 11 IPOs at different points in their life cycles. The leftmost column is the price of the shares at IPO, followed by the share price on the first day close, followed by Friday’s price.
Next week, on the 9th of October, Redpoint will host Office Hours with Nick Mehta. Nick is the iconic CEO of Gainsight, the leader in customer success. Nick and his team created the category and know the best practices of the world’s leading customer success organizations.
Customer success is evolving quickly and we’re seeing different models of the practice evolve in our portfolio. Nick will talk about the trends he’s seeing and take questions from the audience.
I’ve been searching for a great history of the venture capital industry since before I joined Redpoint. There are a handful of books that are pretty good. Done Deals. eBoys. Creative Capital. But there’s a great one called VC by Tom Nicholas.
Nicholas traces the history of the venture capital industry back to whaling. They weren’t called venture capitalists back then, but they serve the same role. Men would broker relationships between wealthy individuals and adventuresome captains.
I’ve gotten to know Marc Randolph as a fellow board member at Looker. Marc has helped many companies get off the ground, but the most famous is Netflix. Marc founded the business and served as its first CEO until Reed Hastings took the helm in 2003. In That Will Never Work, Marc recounts the early days of the $130B market cap company first started in Santa Cruz and it’s a remarkable story. One in which Redpoint partner Tim Haley has a cameo (Tim led the Series A.)
Last week, SaaS stocks fell by about 18% on average. The chart above shows the most recent enterprise value to forward multiple for a basket of next-generation software companies. The red line is the value and the blue line is the median over the same time frame.
As of Friday, the median forward multiple is 9.3x which is a 11% drop from the previous high of 10.5x. The current valuation level is still top decile across this time period, despite the drop. In other words, the valuation environment is still at elevated levels.
Selling based on ROI (return-on-investment) sounds great. A salesperson lays out an iron-clad case for how the customer will make 5x or 6x or 10x their initial investment in a piece of software in three years or less. The champion will use ROI math to assuage upper management and procurement’s concerns. Or so the thinking goes.
If we reflect on the most successful software companies, the very largest, very few sell based on ROI. What is the return on investment of a Salesforce or a Workday deployment? How do you calculate it? How does an AE defend it?
I’ve playing with a new mental model for early-stage startups: a pendulum. This pendulum oscillates between the limiting factors of the business at different stages. There are only two limiting factors in this mental model: product and go to market.
At the moment a startup is founded, the business is product limited. You can’t do much without a product. After the company establishes product market fit, the pendulum swings to go-to-market.
There’s a new debate about marketing efficiency recently, and it’s an important one in the era of product-led growth. If a startup has great net dollar retention (NDR), should it be willing to increase its customer acquisition spend proportionately?
I remain a believer that months-to-repay is the best metric for measuring customer acquisition efficiency for a single reason. You know the answer immediately and accurately. With the annual contract you have in your hand and the amount of money you spent in sales and marketing to acquire a set number of customers in a period, you know exactly your MTR.
Recently, we’ve seen a series of product-driven companies building huge customer bases with tremendous account expansion and terrific sales efficiency. DataDog is no exception. DataDog provides a very popular IT monitoring solution that has grown from its founding in 2010 to a huge business. During that time the product has grown from infrastructure monitoring to application performance management, logging and user experience products. The company published its S-1 Friday.
DataDog counts more than 8800 customers, 590 of which spend more than $100k, and 40 of which spend more than a $1M. No customer represents more than 5% of ARR, which means the largest customer isn’t spending more than $15M a year - still huge.
Which sectors see more startup company formation than others? The answer has changed quite a bit over the last 8 years. Some sectors have hit their apogee and are declining. Others have grown by more than 3x. Yet others are growing geometrically. Let’s take a look.
Hot Spaces
Artificial Intelligence - yes, it’s a buzzword but it’s more than that. AI or Machine Learning is a new technology that will benefit nearly every type of sector and we’re still in the very earliest innings. Eight years ago, there were nearly zero AI startups seeded. Today, that number is 400 and the chart is a classic S-curve, tapering after a period of intense growth.