DEATH MATCH: SeekOut's CEO Anoop Gupta


And the winner is ... The competition for Death Match dominance was hard-fought, bloody and mind-blowing, but at the end of the day, only one company was left standing. Enter Seekout, whose founder, Anoop Gupta, brought his A Game to Austin and took home the championship chain. Enjoy this Alexander Mann exclusive.​

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Chad: Welcome to Death Match North America 2019 part four of four the grand champion edition. This Chad and Cheese Death Match episode features Anoop Gupta founder and CEO of Seekout. Death Match took place at TA tech on September 26th, 2019 in Austin, Texas with a room full of TA tech practitioners, Chad and Cheese double fisted Micheladas while the judges took aim at their last target. Enjoy, right after a word from our sponsor.

Joel: Death Match is brought to you by Alexander Mann Solutions. Hiring great people is no easy feat. There are new obstacles around every corner and your competition for talent is intense. Together we need to be bold in our approach to tackling these challenges. Alexander Mann Solutions can be your bold next step with a team of nearly 5,000 professionals around the globe delivering market, leading recruitment, outsourcing, and talent consulting services. And in early 2020 AMS will unveil an exciting new digital solution that will disrupt how you connect with job seekers and hire the best fit candidates.

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Intro: Hide your kids. Lock the doors. You're listening to HR's most dangerous podcast. Chad Sowash and Joel Cheesman are here to punch the recruiting industry right where it hurts. Complete with a breaking news, brash opinion and loads of snark. Buckle up boys and girls, it's time for the Chad and Cheese Podcast.

Peter Weddle: All right. If you've not been to a TA tech event before, you are in for a memorable treat. You're not here to see me so without further ado, let me introduce Podcaster's extraordinary Chad and Cheese.

Chad: Raise that drink everybody. So thanks first and foremost, thanks Peter and TA tech or making sure that we had alcohol in the morning because a lot of us got in late. We need that. Yeah, keep the party going. So Death Match, who's seen a Death Match before? This is our third Death Match. There we go. So you know, that's why you're here, right? Death Match really a variation of firing squad. This is more the onstage live version. So obviously for of the podcast, check out firing squad every single one of these pitches today. Without further ado, today we have four startups. They will have two minutes to pitch. After those two minutes. We have a stunning panel of judges who includes Cindy Songne from Talroo, Quincy Valencia from Alexander Mann Solutions, woo-hoo give it up, and Robert Ruff Sovren Technologies everybody. All amazing sponsors and we love them.

Chad: All right, you can hear the music. Get ready. We have a new Anoop Gupta from SeekOut. This is the anticipation. He's building anticipation. There it is. Oh, there we go. Sucking up to the judges. Very good. Buttering up the judges. Looking good. Are you ready? All right Joel, are you ready?

Anoop: Ready to be here. I am Anoop Gupta, co-founder and CEO of SeekOut. We are a startup in the Seattle area. Every company is going through digitalization. They need to hire developers, engineers, scientists, first to simply just survive. If they're not going to go to the digital age, they're going to fail and not to thrive. Now the people that you're hiring here have some of the worst LinkedIn profiles. They don't list a lot of information, many of the profiles are simply missing, they don't even have the profiles, and also diversity is very important for this particular audience.

Anoop: And so LinkedIn, the product that everybody else uses simply doesn't suffice for this very critical piece of talent. So the solution that SeekOut is building. The first thing we do is we build aggregated whole-person profiles. So we not only take the LinkedIn information if it exists, we combine it with what they've done on GitHub, we take it for what papers, patents, all of the information, bring it together, and then we infer properties from that. It might be gender, you know ethnicity, it might be the coder score, it might be programming languages, frameworks they are familiar with.

Anoop: The second aspect is an intelligent search engine

because how you write your job description, what are equal in things, how do you find the same person on a get hub site? Okay, what is listed. So there's a very smart ML AI engine there to do the matching. The third big component is hyper-personalized messaging. You tell a developer you rock in Java and you think they're going to respond to you? Zero chance. Right, so we can hyper-personalize based on these rich profiles, what they do ... we are used by some of the largest companies in tech industry and pharma-

Chad: Stop!

Anoop: And banks. Okay. Everywhere else. So ... thank you.

Joel: First, I think it's worth mentioning that you were once a direct hire to Bill Gates, so to see you come in in that fashion was very entertaining for me with that knowledge. There's some real questions about how you get LinkedIn data. There's some legal cases. How do you get access to LinkedIn? Are you paying LinkedIn to get it? Are you scraping? How are you getting that information from them?

Anoop: Basically what for use on the LinkedIn side is public profiles and there are many providers off the public profile data and what the legal precedent that's building is public profile is public profile data. That information is owned by the candidates. And then there is a lot of other data we get from Google, Bing, GitHub, you know, we have a deal with Microsoft and papers patterns so there's a lot of stuff we get.

Joel: Okay. So knowing that legally, you know, it seems like there'll be a precedent to say these are public profiles and you can get information, but there's also some reason to believe that LinkedIn does not want people to get this data and playing a game of Whac-A-Mole with how do I keep the spiders, you know, on their toes. How do I change, you know, URL structures, information structures. And I think knowing that Microsoft owns LinkedIn as well as GitHub, which you get GitHub data as well, does that impact your business and do you think that LinkedIn will win that game of Whac-A-Mole and keep the scrapers off their site?

Anoop: I personally don't think LinkedIn will really follow the Whac-A-Mole. They got into pretty big trouble with Haiku and from monopolistic ... so you know, they are just a lot of issues in following that strategy. LinkedIn is hugely growing their business on advertising, marketing, everything else. That's the biggest growth opportunity and I think it helps them to have innovation happening on top of their platform.

Quincy: Good morning. Good morning question. So I heard what you said and I hear where you get your data from. And I think it's a really interesting concept, but I don't really understand your business model. Are you creating a database of these candidates?

Anoop: Yes so we-

Quincy: How are you marketing it? How do you get the candidates? How are you getting people to go to SeekOut to get that information?

Anoop: So you know we have 450 million public profile, 16 plus million GitHub data, 87 million people that papers patents. So this is our database that we have where we have looked at that, analyzed it, indexed it's the best search engine on top of that, the business model is, we sell licenses today like LinkedIn. So you know, we have licensed prices of three thousand five thousand and $10,000 per

seat license. And then we also getting into enterprise wide licenses.

Quincy: Got it. And how do you verify accuracy of the profiles that you're creating? So how do you know if you say Anoop Gupta has 10 patents or has written these papers? There's more than one Anoop Gupta out there.

Anoop: Yes. Yes. So there is actually DPI and I'm involved in that too. In general there's a trade off called precision versus recall. You can match me totally, exactly a hundred percent confidence or 90% confidence. So we understand those confidence levels and we picked thresholds of, you know, very high confidence that they are the right match.

Quincy: And one more thing for me cause he keeps saying things that prompt new questions. I understand tech and engineering is your focus, but I also saw on your site you're also focused on diversity. Can you-

Anoop: Yes.

Quincy: Talk about that a bit please?

Anoop: Yes. So we infer diversity for women, for African Americans, Latinos, veterans and things like that. But the way we think about diversity first is insights. You need to understand that you know ordinary company, you need to understand competition. You need to understand for roles. So we have very rich talent pool insights in the platform so you can understand all of that.

Anoop: Secondly, we give you filters so you can find women candidates, African American candidates. Totally we have a blind hiring mode that reduces unconscious bias. Everybody becomes a cat, the names gets removed, the email to get redacted. So you can always do all of that. When you share this information with the hiring managers, you can turn blind hiring mode on. So you are nudging them towards unconscious bias. And finally we are also a messaging platform so you can message in, you know, ethnic gender appropriate ways when you're reaching out. So it's a pretty comprehensive solution.

Chad: So being pretty comprehensive solution, especially when you're dealing with all of that data. How are you actually going after companies? What's your market strategy in being able to really sell this product? Is it straight to recruiters? Is it talent acquisition, RPO? Where's your focus on the sale side?

Anoop: So we are not focused on RPOs today. Our focus is directly to enterprises, it's on the largest enterprises in retail and tech and banking are our customers. It is a both bottom up and top down strategy. So I was at SourceCon right before this and you know, lots of people are fans. So in their keynotes et cetera they talk about how SeekOut is an amazing solution. They go to their managers. We also go directly to directors of TA of HR and sell from that.

Chad: So RPO and staffing really understand tech and tech stacks and this data inefficiencies much better than talent acquisition. Right? Because it's their business. TA it's their job. So why did you make that decision not the focus on the actual quote unquote professionals versus-?

Anoop: So one is we are only a two year old company and you've got to start somewhere and you know, that is where we have started. That's where we saw early success, that's where we had connections. We've had from the limited conversations with RPOs because they're so large. So actually there are small RPOs who are customers that is there. The decision process, the cost sensitivity. So there's just a bunch we don't understand our fault and many of your here. I would love to chat with you afterwards show you the solutions and see where we can be a fit. So great question. I love to have connections afterwards.

Cindy: That was the same question that I would have and it was more that the RPOs are proactive. They're not waiting for the candidates to come to them. And it seems like your system would be better for those that are actively recruiting people rather than the talent acquisition folks no insults needed. But for those folks who tend to wait for the candidates come to them.

Anoop: So no we are not active so we are much more passive. So you know for most of the TAC is totally passive. So you go and find candidates on our system and then you reach out and hyper personalize it.

Cindy: Right. And that's what I'm saying an RPO recruiter is more proactive. They will use the system to go to it. Yes. My other question is how do you keep it fresh and do you, are you I guess two questions. How do you keep it fresh and also are you marketing to a job seeker candidates also?

Anoop: No. So we are not marketing to job seeker candidates while on the freshness pipe we try and keep it roughly every three months data within three months that is there. And that is a lot of effort, energy, money that is spent on making sure that's happening.

Cindy: Okay. Thank you.

Robert: I want to ask again about the integrity of the data that you're pulling on. So you're augmenting data that ... starting with let's say a profile from LinkedIn and then you're going out and you're finding other sources.

Anoop: Yes.

Robert: I'm going to challenge you on that and I want to see if you'll give me a little more specific answer.

Anoop: Yes. No of course.