Tackling face applicants using pricing

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[00:00:42] Welcome to Episode 97 of the Inside Job Boards and Recruitment Marketplaces Podcast. I am Steven Rothberg, one of your co-hosts. I'm the founder of College Recruiter. Episode 97 is a really great-ish episode because number 97 on the Edmonton Oilers is Connor McJesus, as he's known to those of us who grew up in Canada. And to the rest of the world, he's the best hockey player in the world. Not the best player ever, but today. Peter. Good to see you, my friend.

[00:01:12] Another hockey fan. Indeed. I'm going to the Solar Bears Saturday night. They're our local Orlando minor league team. They are terrible and they're inconsistent, but they're great fun. So I love going to the Solar Bears. Anyway, I'm Peter Zollman with the AIM Group. You didn't even do your Steven Rothberg who you are thing, but people know by now. And if they don't, tough. I'm Peter Zollman with the AIM Group.

[00:01:37] We sponsor RecBros, which is the recruitment marketplace and job board conference in Vienna in a few weeks. So come ahead. And we have with us today, Mark Chaffee, co-founder, in case you couldn't read it because maybe you're listening in audio, co-founder and CEO of Hack a Job, sitting somewhere in the UK. Mark, welcome. Steven, Peter, thank you so much for having me on.

[00:02:05] Just to get involved in the hockey chat slightly, I went to my first hockey game because I do actually live in New York now. I am in London today, but I do live in New York. And I went to the Rangers Bruins on January 2nd of this year. I mean, my friend actually made it onto the Megatron. You know, we were so enthusiastically cheering for the Rangers that we made it onto the big screen. And if you made it onto the big screen, you weren't sitting in the cheap seats. I guarantee it. It only took two minutes to call me out, Peter.

[00:02:35] Thank you so much. Anytime. Anytime. And we promised him this was going to be an upbeat and positive interview, but Peter's going off the rails. That's positive. So tell us about Hack a Job. Yeah. And we're going to talk about outcome-based pricing and recruitment and those kinds of things and about Alex Tchaikovsky's mad idea that's actually fabulous. Go ahead.

[00:03:00] So Hack a Job is an online marketplace that helps companies hire technical professionals. We founded the business 10 years ago. We now have a community of just over a million members on the candidate side. You know, these are software engineers, data scientists, product managers, designers, et cetera, based in the US, the UK and India. And we've built some really clever matching technology in order to be able to match them to opportunities using a skills-based approach. And we actually flipped the model.

[00:03:30] So rather than the JobSeeker applying to the job, the company is the one that applies to the JobSeeker, which is fascinating in this dynamic. As I mentioned, I'm now based in New York. We launched in the US about two and a half years ago, and that's been a very fun journey. And we now work with the likes of American Express, Disney, Comcast, some of the biggest brands in the country. So it's been a great 10 years. It's been a great run. And yeah, very, very excited to join you both today. Sounds good. Outcome-based pricing. What do you mean?

[00:04:00] It's not CPC. Is it CPA? Is it cost per qualified apply? What is the metric you use? Yeah. So I think all we've heard from customers over the last 18 months is I'm inundated with mostly completely irrelevant applications. And that nicely coincided when some of the biggest job boards in the world decided that they wanted to really lean into CPA. And so, you know, I think Charlie Munger said, show me the incentive and I'll show you the behavior. Well, if the big guys get paid for application they generate, they're going to generate you

[00:04:29] a lot of applications, regardless of they're only good or not. On HackerJob, companies only pay on a cost per qualified candidate basis. So how do we define a qualified candidate? This is somebody that signs up to HackerJob. So they go for our technical verification where we're actually validating their skills. They get matched to an opportunity. The company requests to interview that person. And the candidate accepts that interview. So you've confirmed that both sides want to interview with them. They've been technically screened and verified.

[00:04:59] And all of that kind of job fit aspect has been qualified as well. So we really mean qualified candidate when we use that phrase. And companies on HackerJob will only ever pay for a qualified candidate. This is William Tincup. And I'd like to talk to you a little bit about Indeed FutureWorks. Ryan and I attended the conference last year. And we created a limited series for Indeed where we talk to their customers.

[00:05:24] Great stories around TA and how they use Indeed to the max. So check it out. It's just Indeed FutureWorks 2024. You can search for it wherever you get your podcasts. Thanks. Question for you. You know, as an owner of a job board, I hear you absolutely loud and clear. And I completely agree with you. If you give an incentive to somebody, that's the behavior you're driving. So if you pay them per application, they're going to drive you more applications.

[00:05:54] That's what you're literally asking them to do. Quality is a different thing. So for the candidates, what Alex was writing about, what you and I were trading emails about before, is that if you basically put a price into that equation, then you get fewer people applying, maybe more. From a candidate perspective, APCAS says about 4% of applications will convert into a higher.

[00:06:19] So if you're just an average applicant, that means you've got to apply to hundreds of jobs, especially if you're like in fast food or something like that. So talk with us about sort of putting that pricing aspect in place. Like, how are you looking at that? How do you think that's going to be received by candidates? I think the key thing for us, if you're a great software engineer, and bear in mind, we operate in the tech space, so slightly different dynamic than a fast food worker.

[00:06:45] If you're a great software engineer, a great data scientist, your problem is noise. You get spammed about mostly completely irrelevant opportunities that don't meet your skill set, don't meet your location preferences, tech stack, comp expectations, whatever it may be. And so what we really obsess about on the candidate side is showing them relevant opportunities. And that's reflected. Candidates accept 70% of the requests they receive through HackerJob. So we crack that part there.

[00:07:13] So because in the economics of HackerJob, companies are only paying for a qualified candidate, and the candidate needs to be interested in the opportunity in order for that to count, actually it kind of further strengthens our candidate experience. Because if we show a candidate a load of jobs that they don't want to accept, well, then we don't get paid. We don't make our money. That wouldn't count as a qualified candidate. So I think we've done a good job of balancing the economics. So it incentivizes the right behaviors on both sides of the marketplace.

[00:07:41] One of the problems that employers are having now is that with AutoApply, similar tools, obviously this doesn't work with HackerJob. But, you know, employers get hundreds or thousands of resumes and CVs for every listing. In general, not HackerJob. How can the employers overcome that? Don't advertise on those platforms. God, I set him up and he took the bait. And that's a wrap, ladies and gentlemen.

[00:08:12] I was with one of our largest customers literally last week discussing this exact topic. And it's interesting because for a long time, we really advised customers, make the application process frictionless. You know, we'd go for a workday application form and we'd show them, you have 25 fields you're asking a candidate to fill out. This is crazy. And we've gone to this one-click apply and these AI AutoApply tools have just taken it way too far. And so what we were discussing with that customer is actually add some friction back into the process.

[00:08:41] It's not the worst idea to ask the candidate, well, why are you applying for this job? And now, look, an LLM can auto-apply and auto-complete that sort of stuff. But I like that mental model of actually let's add a little bit of friction back in. Let's not. Candidate experience isn't like doing everything by the candidate and making it maybe seamless. Actually add some friction back in. So that would be my actual tactical piece is where in the process can you add a bit of friction?

[00:09:04] Do you like Alex Trukosky's idea of adding friction by requiring candidates to spend a dollar or a quarter or a dime or something for each apply? Going to get me in trouble here, Peter. Oh, that's the whole point here. Before you answer, I know Alex well. Peter does as well. Maybe you do. He's one of those people who's like, I'm putting out an idea to brainstorm. And if somebody's got a better idea, bring it. So I don't think he's going to be, if you have a better one, he's going to be like, thank you.

[00:09:33] And to be clear, that's exactly what I was going to start with, which is I love people that challenge status quo, challenge norms, like let's see what we can do here. Inherently, the idea makes me kind of repulse because I'm like, well, hang on a minute. If you're a job seeker, you're probably in quite a tough spot. And do I have $10, $50, $100 to go and apply for jobs? Maybe, maybe I don't. And so I understand what Alex is trying to achieve. I don't think it's the right mechanism in order to do it. But what it does create in my mind is like the idea of a market. Okay.

[00:10:04] So what Alex is proposing is that both sides are now paying to find a job, which is happening. A lot of these auto-apply tools for candidates are now charging monthly subscriptions to candidates to do that. And so actually, is there an idea here where you're kind of setting like the market price to apply for a job or receive applications? So if I'm looking for a senior AI engineer, I'm not going to ask people to pay to apply.

[00:10:30] No, I'm going to go and spend a lot of money to go and get applications because it's really hard to fit a role. If I'm hiring for a job where maybe there are more workers than there are jobs available, okay, well, then maybe I should add some friction back into the process. Like I said, intuitively, I don't love this idea because I feel like if you're a job seeker, you know, you probably don't have a lot of disposable income. And we've never charged our users for that reason. We don't think it's ethically correct to charge job seekers. But some people do.

[00:10:58] So massive props to Alex for thinking outside the box. I'm eagerly following the thread and watching all the people bump on him. And I think that's not the right approach. So it will be interesting to see where that conversation goes. Yeah, thank you. And we've never charged job seekers either, I think, for the same reasons. The reality is if you're applying to a job that pays $120,000 a year and you're applying to 10 of them, you can well afford to spend a dollar.

[00:11:25] If you're a fast food worker and you're applying for a new job every six months, like most of them do, and you've got to apply to 100, 200 jobs, they don't have the money for that. And then how does that work in impoverished countries where it breaks down? But I agree with you. I think it's a really good idea. So walk me through the hack-a-job model. If I'm an employer, and I know that I personally have a college recruiter who has used hack-a-job when we're very happy.

[00:11:50] So if I'm an employer, is it kind of like I create an account and it's almost like resume searching, and then I see a profile, and it's like, ah, he or she looks good. I send a message. So it's kind of like one at a time? Or can I do it in bulk? Like if I need to hire 50 engineers, you know, how does that process work? Yeah, absolutely. So we describe it more as a matching platform than a search or database style product.

[00:12:20] So an employer creates an account, logs on. Let's say they've got a job description. Or you can just write a prompt and say, you know, I'm hiring for a senior machine learning engineer in New York with these skills, this compensation, etc. What is then going to happen is hack-a-job intelligence, which is our AI matching layer, is going to go through all of the candidates so they're interested in new opportunities in our community and surface the most relevant back to you using this quite advanced matching system that we've built.

[00:12:48] And your requirements can be completely unstructured. So it could be did a comp sci degree from these schools, maybe worked at a product-led organization and has experience with these technologies. Hack-a-job intelligence will surface the most relevant candidates, explain to you why they think it's a good fit, and you can take a decision. Yeah, that candidate looks relevant. I'm going to request an interview with them. No, that person doesn't look relevant. I'm going to dismiss them. From there, you kind of interview the candidate and run the process.

[00:13:17] We do have a service where we take care of all of the payroll and compliance. So if you want to bring somebody on a project basis rather than a W2 full-time employee, we can take care of all of that as well. And it's generally used by larger organizations. Like I said, the likes of American Express, Disney, Comcast, you know, these organizations are hiring hundreds, if not thousands, of technologists a year, and they're using our platform to do so. But ordinarily at this point, we say we have time for one more question.

[00:13:45] And thank you, you know, and I throw it to Stephen or vice versa. But in this case, we have used up our time. So unless you have anything real fast, Mark or Stephen, we're going to wrap it up and say thank you very much for joining us. Next time in New York, I'll do my best to try to catch up with you there. And Stephen, any last words? No, this is great.

[00:14:09] I think we need to have Mark on the High Volume Hiring Podcast, which Peter isn't a part of, so the conversation will be much better. Hey, yeah, yeah, yeah. That's all about watching hockey at some point. That's my ask of you guys. That's all about watching hockey. Cheers, guys. Well, we'll teach you about icing. Cheers. Cheers.