Revenue operations (RevOps) has emerged as a critical new technology category as companies seek to increase sales, marketing and customer care productivity through digital channels, data and artificial intelligence.
One company at the forefront of this new approach to managing revenue growth is People.AI. Founded in 2016, the San Francisco-based company is an artificial intelligence (AI) platform for enterprise revenue, helping sales, marketing, and customer success teams uncover every revenue opportunity from every customer, by capturing all customer contacts, activity and engagement to drive actionable insights across all revenue teams.
The fast-growing company has attracted $200 million in funding to date, with its latest $100 million series D led by Akkadian Ventures and Mubadala Capital Ventures in August 11, 2021, valuing the company at $1.1 billion. Other investors include UpVentures Capital, ICONIQ Capital, Andreessen Horowitz and Lightspeed Venture Partners.
The idea behind People.ai started with the goal of automating through software a very
successful sales process developed by legendary enterprise software sales executive John McMahon when he was at PTC. “To do that, I needed to build software that uses activity data of people to make them more productive, ideally in sales. And so, the initial version of People.ai basically was turning the PTC MEDDIC (Metrics, Economic buyer, Decision criteria, Decision process) process into software and then slowly overlaying AI on it to make it more automated, less manual until now we have it fully automated,” says People.ai founder and CEO Oleg Rogynskyy.
Rogynskyy had previously successfully exited a business he founded called Semantria that applied machine learning and artificial intelligence at scale in solving the challenge of analysing and categorising massive amounts of content from texts and emails for the legal industry and was looking for his next challenge.
Of his experience in building Semantria, Rogynskyy says, “I learned that there is a lot of value and knowledge sitting in internal and external communications inside your email, your calendar, your video conferencing account, et cetera. There’s a lot of answers here to questions we’re not asking. And then when I sold that company, I moved out to the valley. And that’s when in February 2016, I had a moment where one of my investors literally calls me up and says, ‘Hey, let’s grab a coffee.’ We go for a coffee on third street in San Francisco at the Creamery and he’s like, ‘Hey, look, are you happy not having your own company after you had success?’ I’m like, ‘not really’. And he literally pulls out a $150,000 check, gives it to me and says, ‘Why don’t you go start a company today? Here’s your first investment.’”
He now had an investor in a business before he had a plan on what the product should be. So he decided that he would apply what he learned building Semantria to the challenges of sales productivity. There was very little data around sales at the time and much of the process was based on manual data entry. “I understand that there’s a ton of value in all of the activity data coming from email, calendar, zoom, et cetera, that nobody has tapped into before. I know exactly how to put it all together, based on all the AI technology I learned over the years and I know exactly the five people I’m going to call to join me on day one, in this journey,” says Rogynskyy.
The fledgling company got into YCombinator and Rogynskyy credits the organization with helping him define the problem he was addressing and better articulate his go-to-market strategy. And after speaking with more than 40 potential customers, it became clear that they were still managing their employees based on manual processes and not much data. And that leads to a natural ceiling to how productive and effective leaders can make their employees. “That led me to realize that there is no future in which we don’t have software that understands what our employees do today, figures out what exactly are my best people doing that my not so good people are not doing. Find a difference and then give me as a manager, a coaching plan or guidance on how to get my whole team to be more like my best performers,” says Rogynskyy.
His sales approach seems to be working. “We can now say to a CRO, ‘Hey, look, what would you do if in a quarter we could make your sales force 40% more productive with the same head count?,” says Rogynskyy. Today the 300 person company is growing fast, experiencing triple digit growth. Customers include the likes of PTC, Zoom, TIBCO, ThoughtSpot, Splunk, Zendesk and AppDynamics.
Rogynskyy was born in the Ukraine and considers himself lucky to have attended Boston University in the US. During his time there he started his first company. “That’s where my first experience with selling happened. I was selling advertising for the start-up that I started and I realized how hard and non-repeatable the process is. And that didn’t work out. I had to shut down my own start-up and learned all the lessons from it,” says Roginsky. The company was a Facebook-like, photo feed and comments application before Facebook.
After graduating, he moved to Canada and joined one of the first AI companies called Nstein Technologies as one of its first salespeople. There he worked with Dr. Yoshua Bengio, who is credited to be one of the people inventing deep learning back in early two thousands. That company ended up going public and then being acquired by OpenText. “I learned how to sell AI technology before anybody who even knew what AI stands for. Back then it was called statistical analysis and machine learning, at best. So that was one of the first enterprise AI solutions ever existing and I was in the forefront of that just by luck,” says Rogynskyy. He then went on to found Semantria in 2011 that was acquired by Lexalytics in 2014 prior to founding People.ai.
As for the future? While the company has achieved success focusing on sales productivity, Rogynskyy feels his approach can be applied to any industry and segment of the enterprise. “I’m still focused on the same thing. We are making the software that uses all this data sitting in silos to make humans more productive. My hope and dream is to build a software that makes employees more productive and more importantly makes leaders better at leading people,” concludes Rogynskyy.