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Recruiting marketplace Woo raises $7M; launches new AI-driven headhunter

Helena will recruit, approach and sell candidates on behalf of prospective companies

Financial trends and news by Steven Loeb
November 14, 2017
Short URL: http://vator.tv/n/4a83

If you've looked for a job recently, then you know that machines are already a big part of the recruiting process. Thanks to keyword searches and other technologies, resumes have to go through a screening process before a human ever sees them. It's a process that, frankly, isn't great for employees, nor for the employers. It means good prospects can be overlooked, while employers can miss out on the chance to hire people that the algorithm has deemed to be not a good fit.

The answer to the problem lies in artificial technology, which can go beyond simple keywords to find candidates that would be overlooked otherwise, despite being a good match for the job and the company. That's why Woo, a marketplace for matching employers and passive job seekers, announced the launch of its news AI-driven headhunter called "Helena" on Tuesday. The technology is able to automatically scout, approach and source the best candidates on behalf of employers.

The reason Woo built Helena is that the vast majority of the resources being spent in the recruiting space are being wasted on both companies and candidates filtering each other, said Liran Kotzer, Woo’s founder and CEO, in an interview.

"Companies are getting a lot of candidates that apply through job boards or other channels, and 97 percent of them are being filtered, so they're wasting a lot of time on those candidates. On the other side, companies go to places like LinkedIn and basically approach as much talent as they can, and those candidates are filtering opportunities they are getting from companies. Even if they get to the interview stage, most of the interviews end with no hires, so that's another place where they're being filtered," he said.

"There's a lot of filtering going on out there so we decided that it doesn't make sense. We're living in a new era, things need to be much more efficient. It doesn't make sense for both of the parties to be using the spray and pray approach on each other in that way. We need to create a much more efficient ecosystem where there is much more efficiency rather than filtering."

How Helena works

When Woo first started, Kotzer told me, the company made a conscious decision to serve both sides of the market, rather than focusing on one or the other. 

“We said that the first thing we have to do in order to create an efficient market is have both sides on the platform. We cannot only represent one side. There are so many solutions that do only one side and we said, ‘You cannot create the perfect experience if you know only one side. You need to get to know both of them'," he said.

The first phase of company was started on the candidate’s side, offering them the ability to set up a wish list regarding what they would consider an interesting opportunity for them going forward. That could mean anything from wanting to relocate to moving to a new industry or to get better compensation. From there, the only companies that are allowed to approach that candidate were those that can offer the kind of opportunity that person was looking for.

Once a company approaches, the candidates will get info on the company and they can decide whether they want to move forward or pass the opportunity. If they want to move on, Woo makes sure the company will review your profile, and will contact the candidate as quick as possible.

Woo already has 20,000 candidates on board, and it is only focusing currently on software engineers. 80 percent of those candidates are interested in upgrading their job, but they not doing anything proactively to make that happen, according to Kotzer.

With Helena, now Woo is tackling the other side of the equation as well. When the company first started, it did allow companies to view LinkedIn profiles, but the company quickly understood that the real value for recruiters was in saving them time. That's where Helena comes in. 

"Places like LI require a lot of time going out there searching for candidates, approaching them and then some of them will answer and some will not. We wanted to address that problem. What we built for them is the world’s first headhunter that is powered by AI technology. We said, 'The best thing for the recruiting team is that we want to spare the time that they’re investing running after candidates and finding those that eventually will be able to come into on sight interviews.' In order to do that, we wanted to give them the best experience, the ultimate experience, and the ultimate experience is giving them a dedicated headhunter," said Kotzer.

"Helena scouts the right candidates, approaches them and sells  them the opportunity. Only candidates that show interest eventually will be directed to the employer. They basically don’t need to do anything in order to generate value from out system. Helena is working 24/7 on behalf of them. Instead of chasing after candidates, and making sure those candidates get in, we get the best experience from quick interviews and quick responses and we create a much more efficient process.”

Helena has already been showing results, with one out of every two candidates headhunted by the program starting an interview; that's compared to a 3 percent conversion rate on job boards and a 17 percent rate at recruiting agencies. The better success rate comes because, Kotzer explained, "AI technology is unbiased."

"When recruiters try to explain what kind of candidate they’re looking for, they have their own way of defining it. They can say, ‘I need guys with X number of years experience, this is the technology they need to know, they need come from Ivy League universities, etc.’ The way to express what they want is by those data points. If you think about it, the main mission of the recruiter is not to define those data points, it's to bring in people who can get things done. What happened with Helena is that, because it's AI, she tried to understand, in addition to the data points that were provided by the recruiter, what other candidates could be a good fit for this position, even though they don’t have the specific data points that the recruiters explicitly asked for," he told me. 

Woo found numerous examples of Helena trying to recruit candidates that were outside the given parameters set by the recruiters, and, despite initial resistance, a number of those candidates eventually being hired. 

"For us, it was amazing to see because Helena can eventually open the mind of the recruiting team to options that they never thought of. She knows that even though this guy is not coming from the Ivy League, he worked on a similar project that this company is trying to hire an engineer for. She knows because she is going out and going to places like LinkedIn and Crunchbase and trying to understand for each company: what are the projects they’re working on and to see who are the people that this guy worked with and get more information allow her to understand that this is a great fit for you, though you didn’t ask for this candidate," Kotzer said.

"This is the true breakthrough, as I see the AI technology in that space. It opens up things that, until today, were really hard to define because it would require the recruiter to try to find all the alternatives out there and they cannot do it. Those AI machines will eventually be able to open their mind and expand their prospects."

New funding

In addition to the launch of Helena, Woo also announced the close of its $7 million Series A investment round led by Lord David Alliance, with participation from existing investors. This new round brings the company's total funding to $11.4 million.

"The money is going to be invested in two main channels: one is to keep pushing the technology and product. We have big vision of what we want to do next: we want the AI eventually to spare more, not just the matching of the candidate, but also a lot of the interview process. We think that can eventually be spared through good AI matching," said Kotzer. 

The new funding will be also be used fuel the company’s U.S. expansion beyond its offices in San Francisco and New York to cities that include Seattle, Boston, Los Angeles and Austin. It will also expand to new verticals and industries. 

"We want to start providing our marketplace to more business verticals like marketing people, sales people, biz dev but eventually we're going to expand to more industries. Vision wise, Helena eventually will serve every candidate from every industry," Kotzer said.

Taking the human out of the equation

While AI will eventually become a larger part of the headhunting process, that doesn't mean that the candidates themselves are open to that prospect. 

A Pew report from October that showed the 67 percent of people are worried about the development of hiring algorithms. Even worse, 76 percent said that they wouldn't want to apply for a job if they thought that a computer was going to be evaluating them. Even among those 18 to 29, the youngest generation in the workforce and those most used to technology, only a little over a third said they would be comfortable in that situation.

That might present something of a problem for a company like Woo trying to deploy technology like Helena. While Kotzer acknowledges that it may take some time before people fully trust the technology, he does think that, eventually, people who learn to trust it. 

"I don't think we're at the point where people fully trust machines to make crucial decisions, but I think it's coming in stages," he said.

"In order for companies to eventually trust a machine to determine if it should hire or not, it will take a few years to get there but, eventually, it will be there because we're building trust. Machines are making decision in our lives today. If I took you 10 or 15 years back, you'd probably say that there's no way companies would trust in machines for making decisions in every aspect of their lives. But this is where we're going. We can love it or not, but this is the trend and we need to adapt and to adjust ourselves to it. I don't think it's a bad thing, assuming that the machine is not biased and can do things for us in a good way."

Ultimately, his vision of the world is one where there won't even be humans involved in the hiring process at all, where people will be recruited and start jobs without even needing to be interviewed. 

"The way we see the market eventually going, I'm not sure if it's going to be five or 10 years from now but somewhere around there, the way you're going to consume your next job is you're going to say, 'I want to move to San Francisco, I want to work in the gaming industry as a CEO and earn $160,000 a year.' Once you click on the button, we will offer you four companies that you can start work with. You're going to select one and we'll tell you, 'You're going to start Monday at 8 am, good luck.' It sounds a bit sci-fi but what stands behind it is that, eventually, the machine is going to be so accurate that it will know that you are going to be a perfect match because we know so much about you and we know so much about the company, so if we said you are a good match, nobody will question it," he said.

This will be important as people shift the way they think about work: studies have shown that, over the last 20 years, people have started to job hop more and more. For those who graduated from college in the latter half of the 1980s, they averaged 1.6 jobs. Jump to those who graduated in the latter half of the last decade, it’s now 2.85 jobs. 

"In order to support this shift in the way people think about the workplace, they will need to have really powerful systems that eventually will eventually be able to switch jobs for people really quickly. This is the system that we're working on building. It requires deep information, it requires us to keep users on the system for the long run, and it requires powerful technology that can create unquestionable matches."


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