Most startups go to market with the intent to differentiate their product. Each one of us has an idea what might make a better CRM, marketing automation suite or customer support. Other startups prefer to combine a product innovation with a reinvention of the sales process.
After a SaaS startup has gained traction with SMBs and mid-market customers, they often feel a pressure to move up-market. Sometimes, demand for a product is so great, larger customers the pull the company up-market before they are ready. The startup finds itself in a critical position - both the product and the sales motion must evolve quickly.
Every software company competes with another — if not directly, then at least for budget. With global IT spending flat to down in 2015 and 2016, software businesses are fighting for share of wallet. At this point, the critical marketing imperative is to start a conversation with a receptive buyer, and do it thousands of times per year. But how?
Esquire writer and master storyteller Cal Fussman describes the experience of interviewing his childhood hero, Muhammad Ali, in a podcast with Tim Ferriss. Fussman spends a week with Ali, during which he the Special Olympics and boxes with the great champion. But there's one story that stood out to me.
The public markets have changed the way they value SaaS companies. The median forward revenue multiple for SaaS business reached its peak in February 2014, fell to its nadir two years later, and has since recovered, hovering at around five times forward revenue – where it has remained with little variance over the last six months. However, that's not the whole story.
Draw an image of a bicycle that depicts how the bicycle works. You might draw something like this bike above.
There are three ways to create negative churn that I have observed in the market. First, usage expansion. Second, feature expansion. Third, product expansion.
Founded in 2006, Mulesoft is an 850 person company based in San Francisco that builds data integration tools. The company started originally as an open-source product and then focused on its paid offering. Today, the business generates nearly $200 million annually in revenue, and is growing at 70%. The business filed to go public last week, and the documents reveal a very impressive business operating at scale.
We've taught computers to do many things. We've researched how to teach them to identify cats, spot fraudulent charges, even categorize cucumbers. But what can we apply in our daily lives that computers have taught us? That is the premise of the book called Algorithms to Live By. Which of the advances in computer science can be applied to laundry, choosing an executive assistant, picking the best strategic plan and optimizing your schedule?
From the millions of Amazon Alexas to the self-driving car, new products are coming to market infused with machine learning. The innovation offered by machine learning techniques are real, and they will changed the SaaS world. But how? How can startups use machine learning to their advantage?