10 Months ago I embarked on a new journey in Enterprise software. I wrote about my decision to join Blackbird in my post: I’m a VP of Sales! I’ve been asked a bunch of times why I chose to go the route I did and so figured it would be worth sharing..
When I decided to leave Box, I thought long and hard about what I wanted to do next. I knew I wanted to go back to early stage days to take what I’d learned over the past decade at SuccessFactors & Box to see if I could slot into a leadership role from the beginning and apply my experience as the first sales leader to help other folks reach incredible goals.
Once I settled in on the role I wanted to play and the stage of the company, my next step was to narrow down the focus on the type of SaaS startup. We are fortunate to live in arguably the hottest tech bed in the world so there are many directions to go!
When I reflected on what stimulated me most about my previous gigs it became pretty obvious. I was a finance major at Santa Clara and my favorite class was Statistics. In my stats class we talked a lot of theory (sample size, standard deviations, outliers etc) but we also used software to analyze large amounts of data to make predictions. I love spreadsheets and math (I’m admittedly not a real serious “math” guy but I have always loved the idea of taking numbers, working them and arriving at an outcome). I hadn’t really connected the dots until many years later but my favorite things about SuccessFactors & Box were 1) the idea that you can make information available at your fingertips 2) You can aggregate data from many sources, visualize it in charts and unlock new insights about your operations to make your business FASTER!
Much has been written about the cloud, SaaS, mobile, big data etc but the thing that is happening behind the scenes, that most people don’t quite grasp yet, is a whole revolution with AI that has now been unlocked by all these converging trends. Advances in computing and microprocessing, ubiquitous access to information on devices, advanced logging of user behavior, inexpensive access to massive compute power etc. But what does that all mean? Where is it heading?
A few years back I began to become intrigued by the concept of a variation of statistics called “Machine Learning“. The idea that with all of these trends we can now use computers and GPUs to analyze all of this rich data more efficiently and instead of using human intervention to arrive at outcomes, train systems to “learn” and help us move even FASTER! So it became obvious to me that enterprise software UI would eventually just be the wrapper that supplies AI to the world. If you know who Eric Schmidt is, he’s extremely bullish on this idea…He believes every successful IPO in 5 years will be powered by it 🙂
So after interviewing and talking to quite a few companies in the field of applying machine learning to SaaS I decided to join Blackbird. Not only were they using machine learning but they were using an even more advanced version called “Deep Learning” in the fields of Image Recognition, Natural Language Processing and Ranking to optimize eCommerce purchase conversions. They also were not beholden to another platform to supply the data. They do not rely on companies like Linkedin, Facebook, Salesforce or Google to supply them data. Instead they had an API platform that itself captured and generated the data itself to build on and “learn” from.
In a nutshell at Blackbird (www.blackbirdai.com) we have developed a SaaS platform that democratizes the type of technology that companies like Google and Amazon use to serve products and ads to consumers. We make this advanced capability inexpensive and accessible to eCommerce brands of any size. thredUP and Tophatter are live. Nasty Gal just signed on and we have pilots going with some of the largest online stores in the US. So at this point I’m a firm believer in the revolution! I’ve directly seen what impact this technology can have and I’m convinced, like Eric Schmidt, that this is the future of enterprise software.
* If you see an acronym or word anywhere on my blog that you haven’t seen before, I might have posted an explanation on my glossary of terms. If not tell me and I’ll add it!*