Jeremy Roberts, VP of Customer Experience from Hiring Solved takes the HR Tech stage with Chad & Cheese to talk data and a shocking new announcement.
Do you believe in something so much that you would shut down a product because of that belief?
Hiring Solved explains data, HiQ ruling impact, and why they are shutting down Prophet - their Chrome sourcing extension. Nothing but the best from your beer buddies Chad & Cheese :)
And of course your friends at Jobcase, who supports great EXCLUSIVE podcast content.
PODCAST TRANSCRIPTION sponsored by:
Jobcase: This Chad and Cheese exclusive, HR Tech podcast is sponsored by Jobcase. Jobcase is on a mission to empower hourly workers to achieve work-life success. But don't take my word for it, listen to the words of a Jobcase customer, "Jobcase, there is no one like them. The urgency, the communication, the data, the scalability by brand and by location. The niche versus the standard, they get it all. Jobcase understands our business and the deliverables of high volume hiring teams," Cat Barcelona, Senior Recruiter, Whole Foods Market.
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 breaking news, brash opinion and loads of snark. Buckle up boys and girls, it's time for the Chad and Cheese Podcast.
Chad: Start it off?
Chad: Go ahead. Start it off.
Joel: What's up everybody? HR Tech 2019, let's give it up to this rowdy
Chad: Hey guys.
Joel: Hung over crowd.
Joel: Very nice. We are the Chad and Cheese podcast.
Chad: And we are loud.
Joel: For those of you who don't know, we cover industry on a weekly basis. We do a lot of other fun content. I am your cohost Joel Cheeseman.
Chad: And I am Chad Sowash.
Joel: Is your mic on?
Chad: Is my ... you give me a little bit more?
Joel: Hot mic.
Chad: Gave me more. Oh there it is.
Chad: Man back there is hooking me up.
Joel: I'm surprised a lot of return visitors from yesterday's show, which we were going to do the same content and we said, no, that's not going to work. So we wanted to bring on a special guest, so everyone give it up to Hiring Solved former source con head, Jeremy, you're looking at me like I'm doing this wrong.
Jeremy: You're doing well.
Joel: You want to take it over?
Jeremy: No, you're doing well.
Joel: All right, Jeremy, do you have a nickname? You need a nickname, I
Jeremy: I don't have one. Let's not do it off the fly.
Joel: Racing cap ramer or something, I don't know what it is. All right. Young blue eyes. Because it's the third day and we're taking it easy, we're just going to tap open some Guinness for today. We have a few extras if anyone's interested and to make it more enticing, these are actually from Ireland.
Chad: That's right, Shane Gray from Clinch. [crosstalk 00:00:02:53].
Joel: Can I get a hands up for anyone that wants Dublin Guinness.
Jeremy: Is Shane here?
Chad: He's outside.
Joel: There we go.
Chad: Who wants a beer? Woo, there we go.
Joel: Let's hear for ...
Chad: Guinness, Anyone?
Jeremy: She's even wearing a shirt.
Joel: My name is Shawna Williams. I am ...
Chad: Where's Barry at? Barry wants a beer now. He's over there talking, selling shit. Russell?
Joel: From Dublin dude, come on now.
Jeremy: He's still on coffee.
Joel: All right. All right, so everyone knows who we are obviously. That's really good.
Jeremy: That is good.
Joel: Give us the elevator pitch on you, Jeremy.
Jeremy: My name's Jeremy Roberts. I'm the VP of Customer Experience with Hiring Solved. I've been in recruiting since about 2002 I started off in the agency world and then moved into corporate. I started some sourcing functions with different companies. My last recruiting job, I was a Sourcing Manager for a large RPO and had a team of about 25, and then I moved over to Source Con and I was the Source Con editor and conference organizer for about three and a half years. And from there, I made the transition to the HR tech side and started working with Hiring Solved, so.
Joel: Anyone not know Source Con? Sourcing candidates. Okay, good. So we wanted to bring on Jeremy because there are some really hot issues going on right now with privacy, GDPR, data, profiles, collecting data from all over the web. I want a little bit of a historical perspective of what sourcing data used to look like, simplified. And then we'll get into the dark world that it has become. But I want to set the stage for what 2013 looked like in terms of going out on the internet and getting data.
Jeremy: Yeah, no that's excellent. So basically when I started in recruiting, I remember being in the office and we had to actually, we would print files and resumes. We had what we call back files, just huge file cabinets full of resumes.
Chad: Wow, cabinets.
Jeremy: There was not a lot of electronic things going on.
Chad: Back in the file cabinet days.
Joel: Do you have folders full of women too?
Jeremy: Fast forward, and then we had LinkedIn started and there started to be a lot more data online. So then when I joined as a Source Con editor-
Joel: You don't want to throw this.
Jeremy: When I joined Source Con as an editor in 2013, it was a very manual process. So we were showing people how to go find a profile on a social or professional site, and then how to find them-
Joel: Google query type stuff.
Jeremy: Right and how to use boolean to find all that person's other social presence and then kind of construct this unified profile, and then go find their contact information. If you couldn't find it, how do you guess it? But it was a very manual process. So then in about 2012, 2013 the people aggregator movement started. And I remember we did a panel at the first Source Con I organized in Seattle in 2013 and Sean Burton from Hiring Solved was there. They were launching their first version of hiring solved.
Jeremy: And then we did a panel, people on the panel included like John Bishky from Entelo and Pete Kazanjy from TalentBin. And then we had Dice Open Web, Shravin Goalie was there. And then there were a couple more. So there were a lot of aggregators at that point, and they were all doing the same thing. They were just crawling for public information about people, creating profiles and selling it. And at that point, if you could match a Github profile, to a LinkedIn profile and a Twitter profile everybody was excited. And then if you can find a phone number, they were really excited. So it was pretty innocent at that point. And there was a market for it.
Joel: When did LinkedIn sort of look at this automation thing and say, nah, we're not for that, or we're not happy about that? Like tell talk about the early days of LinkedIn's reaction to the aggregation automation game.
Jeremy: Yeah. So I started to see them right about this time, they were at every conference I organized, they were in the audience kind of listening to what sourcers and recruiters were doing, and I would write an article and then all of a sudden the URL would change. And, oh, they changed the URL pattern now that doesn't work anymore.
Joel: What URL would change?
Jeremy: Well, if you would teach someone how to do something on a social network, and then you publish it.
Chad: URL patterns, right, patterns. Yeah.
Jeremy: So you say, okay, write your search query like this based on this URL pattern, and magically the URL patterns would change.
Jeremy: So I started to notice that in like 2013.
Chad: So that's your whack-a-mole thing.
Joel: The first whack-a-mole was sort of that, right?
Jeremy: If you remember like back when Shally would release his job machine, they would release their cheat sheets, those things would work for years. You would print them and pass them around the office and then you can use those-
Joel: Yeah, that used to be his business card.
Jeremy: Yeah, you could use those Google queries for years. Now pretty much every company with public information, they changed their URL structure and kind of the way everything is out there. So those break in a week or two, you could never circulate something like that for very long.
Joel: All right. So the dawning of the automation game starts, LinkedIn isn't happy about it, starts doing some basic whack-a-mole.
Jeremy: I think everybody did, yeah.
Jeremy: Yeah, everybody did.
Joel: This was around the time, because then Entelo's original model was, we're going to look at LinkedIn activity and say someone is about to leave the company. Right? So they just updated their profile, they added something or they're searching for stuff. So LinkedIn really early said this isn't cool and Entelo had to change their business model. Am I correct on that?
Jeremy: I have no idea on Entelo's business model.
Joel: Okay. I seem to remember I covered their launch and there was something like that.
Jeremy: I do think there were a lot of people who would say they're going to watch everything going on socially to make those kinds of predictions.
Jeremy: I don't think any of them, I don't think the people who are not the owner of that data are doing a great job of making predictions based off social data.
Joel: Gotcha. So at some point in this you guys had some legal, I know you weren't there with the company at that point.
Jeremy: Yeah, I was covering it.
Joel: But there was some legal stuff. Talk about that.
Jeremy: So I was covering it from the SourceCon perspective, and there are a couple of good articles, and there's Matt Charney wrote one a on Recruiting Daily and then I had some on Source Con and there's an interview I did with Sean before I worked at Hiring Solved right after the case settled. So if you could go find those, that would be-
Joel: What were they mad about?
Jeremy: Due to the ... Basically they just don't want people crawling their site and repurposing the data.
Joel: So you guys settled out of court.
Joel: Terms not to be disclosed.
Jeremy: Due to the terms of our legal settlement I can't go into a lot of detail.
Jeremy: But one of my favorite things about Hiring Solved, this was before I worked there, they had to destroy the servers and they actually went to the desert, as a part of the settlement they had to destroy the servers and instead of just deleting the data-
Chad: Like office space.
Jeremy: They went to the desert and blew it up with military grade weapons.
Chad: Yeah. C-4, yeah that's cool.
Jeremy: It was pretty awesome. So that was a pretty neat way to do it.
Chad: Take that god damn fax machine out to the desert. Yeah.
Joel: So the birth of more sites like this come about. We have SeekOut, Hiretual. You could go on and on.
Jeremy: Yeah, no, it's gotten really popular.
Joel: And then there's a case with HiQ, a site that does that similarly, and then they currently won again against LinkedIn to basically have these profiles available to scrape and use. What's sort of your take on that legal decision, does LinkedIn give a shit? They're just going to keep whack-a-mole and make it harder and harder to scrape, we'll get to a point where the data is already there, so no one cares anyway. But talk about the case with HiQ, what LinkedIn's status is now, where are the other companies that are scraping data, how they feel about this decision.
Jeremy: Yeah. Well first off, can I go back and then if I don't answer the question?
Joel: You're our guest man, you can do whatever you want.
Jeremy: Okay, I want to go back a little bit. So 2013, it was pretty innocent. Everybody's just gathering this information, creating unified profiles, adding contact information and selling it. That was just, it was new, it was exciting and everybody was excited about whatever you could provide them. Fast forward, there are all kinds of data breaches on the internet and then wow, these Chrome extensions right after that big breach that was in the news, there are a bunch more email addresses on the Chrome extension out of Poland, or wherever. And so as this has happened, the data is becoming more and more commoditized. If you guys have been paying attention to the news, there's a file that was found on AWS with 400 million cell phone numbers from Facebook.
Chad: they tie to profiles, right?
Jeremy: Tied to profiles.
Chad: Tied directly.
Jeremy: Directly to profiles.
Chad: So they're not just numbers.
Jeremy: Not just phone numbers.
Joel: Let me repeat that, 400 million.
Jeremy: 400 so that means your cell phone numbers.
Joel: There's 325 million Americans.
Jeremy: Have been released.
Chad: Thanks, Facebook.
Jeremy: So not this guy's.
Jeremy: So, anyway, the point of this is, this was because of ... It was a bug in the system. Basically if you put a phone number in, it would say, yes, this phone number belongs to this profile and this person, it would show the person's face and then you can match that with the LinkedIn profile. So now you know the number associated with that profile, and there are about 600 million phone numbers in the US, so you could write a script and bring back every phone number and which profile it's associated with in a very short amount of time.
Jeremy: And so at Hiring Solved, we knew about that. Irina Shamaeva, if you guys know Irina made that knowledge ... She basically pointed it out to everybody that that was possible. So Hiring Solved knew how to automate that and we never did anything with it, just because ethically it's a little odd. There are kids in numbers in there and you can't control what people do with it.
Chad: Well taking stolen data-
Jeremy: That's not stolen.
Chad: It's just public.
Jeremy: It's public.
Chad: Just public.
Jeremy: But if it's kind of a gray area, I don't think there was anything illegal about it, it was a bug.
Chad: Wasn't illegal.
Chad: Man, that just doesn't feel right.
Jeremy: It doesn't feel right.
Jeremy: So situations like this have, in my opinion, made data, public information like this, it's very commoditized marketplace. At this point, we've got the early people to the game in 2013, the TalentBin, Intello, Hiring Solved. We were all kind of doing it on a more innocent level. At this point it's gotten a little bit shady, and the ones who win are going to be doing things that others might not feel comfortable with. The good news for the consumer is the price is going to go down. Everybody, imagine all the people who heard about that file and are hacking away building a Chrome extension right now in some little apartment.
Jeremy: In the Soviet Union.
Chad: Everybody's doing it.
Joel: I think that's an important message, is that developers, hackers, whatever you want to call them around the world now know how to create databases with this information of cell numbers, profiles, data, where you work, all that information.
Jeremy: Oh yeah, well there was a Business Insider article about it.
Joel: That's a mainstream publication. That's not some hacker black hat stuff.
Jeremy: And then on, I think it was Hacker News, there was a, how to crawl everything.
Joel: So are we going to see an influx of these tools of Chrome extensions
and sites that you can search all this data for whatever purpose you want?
Jeremy: Yeah, absolutely.
Jeremy: I would say there are a bunch, the price is going to go down.
Joel: Okay. So for the companies in this expo hall that make their living on that data, as that gets commoditized-
Chad: Where are you at?
Joel: Prices get cheaper, but so do profits, profits gets less, right?
Jeremy: Yeah, a lot less.
Joel: Not only your own company, I mean you're in this universe as well. Your decision of what to do about it is one thing, but as a whole, are we going to see more solutions here at HR Tech for finding data? Are we going to start seeing less because there's no money in it?
Jeremy: I think you'll see less. I think they're going to start to disappear. So the great thing about being an early entrant to this space, so our founders are, when they gathered, we had about 500 million profiles starting in about 2012, and so they connected those to neural networks. So our algorithms have been learning from that data since 2012. When I joined in 2016 we were complete, all of our revenues came from selling data. But the algorithms used to manage that data were getting smarter and smarter. And then so today, luckily we've transitioned our business model to where we're using the algorithms, the search and match and find me, you know, here's the job description, which person is best for this job based on all of these profiles? I mean it's trained on those 500 million profiles, but now our revenues, the majority of our revenues come from enterprise data, so large ATS and CRM systems and matching and managing that data.
Jeremy: So we're no longer dependent on data sales, so it's great to say as-
Chad: Big data is everywhere, everybody has big data.
Jeremy: Yeah, everybody has it now.
Chad: Again, you can't make money off of it. So therefore you guys are looking to make a smarter way, or you are making a smarter way to make that match against the job description versus all the candidates.
Jeremy: The job description using all of your ATS. So you've got 3 million in your ATS, 500,000 in your CRM and you've got a 2 million from a legacy ATS.
Chad: So it's your database. Gotcha, yeah.
Jeremy: So which is the best from all these candidates you already own. That's what we're using it for now.
Joel: Now, you guys have a really popular solution called Prophet that's a Chrome extension that a lot of people use. Are you guys going to keep that around? What's the future of that?
Jeremy: I think it's safe to say that we'll be moving on from that.