The Breakthrough Hiring Show: Recruiting and Talent Acquisition Conversations
Welcome to The Breakthrough Hiring Show! We are on a mission to help leaders make hiring a competitive advantage.
Join our host, James Mackey, and guests as they discuss various topics, with episodes ranging from high-level thought leadership to the tactical implementation of process and technology.
You will learn how to:
- Shift your team’s culture to a talent-first organization.
- Develop a step-by-step guide to hiring and empowering top talent.
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The Breakthrough Hiring Show: Recruiting and Talent Acquisition Conversations
EP 172: AI, hiring, and the new talent equation with Steve Bartel, CEO of Gem
With markets reacting to global uncertainty and AI transforming the hiring landscape, both job seekers and recruiters are recalibrating their strategies.
Join host James Mackey and Steve Bartel, CEO of Gem, as they discuss how automation is changing resume screening, interview prep, and rediscovery of existing talent. As companies look to cut costs and boost efficiency, the challenge becomes clear: how do you hire smarter without losing the human signal in all the noise?
Thank you to our sponsor, SecureVision, for making this show possible!
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Hello, welcome to the Breakthrough Hiring Show. I'm your host, James Mackey. We got Steve Bartell back with us today. Steve, what's going on?
Speaker 2:Hey, good to be here.
Speaker 1:And for everybody tuning in that hasn't heard one of Steve's past episodes Steve, would you mind just doing a quick introduction on yourself?
Speaker 2:Yeah, sure, I'm Steve. I'm the co-founder and CEO at GEM. I've been building G Gem for about eight years. At Gem, we're building the only AI-first all-in-one recruiting platform. So what that means is we take your sourcing, your CRM, your ATS scheduling, plus full funnel analytics and a database of 650 million public profiles that you can source from and then thread AI through the entire product. But yeah, that's what we're up to Over to you, james.
Speaker 1:Cool. Today. We have, I think, a very action-packed episode. A lot of stuff to cover Before we get into some really cool things regarding AI how candidates are leveraging it in the interview process and what that's going to look like as candidates are, companies are leveraging it and then get into that. We also discussed talking a little bit about what you're up to at Jim, some of the more recent product and feature releases. We want to talk a little bit about candidate rediscovery, which I think would be really interesting as well, and making that whole process a lot more effective and valuable to organizations. I think there's a lot left on the table when it comes to rediscovery, so that'll be cool to dive into that as well.
Speaker 2:Sounds good, let's do it.
Speaker 1:Yeah, so let's just start out with the market. Last thing I checked, as of an hour ago, I think, trump's threatening it like an additional 50 percent tariff on China due to the fact that they put out reciprocal tariffs of 34, 36 percent or whatever it is. Of course we saw a massive market contraction and then within that like tech, of course, being one of the most volatile sectors, I think the whole market was down like five percent ish. Don't quote me, but it's like basically. And then I think tech was at least temporarily down closer to 12 last week or something crazy like that, if I remember correctly in the journal. So I'm sure hopefully, maybe some of that's just like temporary, just shock right to the market and tariffs.
Speaker 1:But it's definitely a really uncertain time right now. And I'm curious if you're hearing anything from customers. I know like we have early earnings call coming out, probably in a few weeks. Ceos are going to be talking, but just, is there any kind of word on the street, jim, customers, or your advisors or VCs, or what are you hearing out there?
Speaker 2:Yeah, totally so. First of all, I think it's really hard to know how this stuff shakes out. I do think that the market correction has probably been an overcorrection. When you think about the overall GDP of the US, interestingly, we're a very heavy services country as it relates to GDP. I think 70% of our GDP is from services industry and I think only 10%, 20% or something like that is from trade, and a lot of that is actually between Canada and Mexico and the US, and so when you take that factor out, it's even less. And so when you think about the market correction, that's happened. What did you say? 10, 12% or something like that In?
Speaker 1:tech. I think I saw that Like it was one of the hard graph things.
Speaker 2:I think the overall market lost like 5% and wiped out like 6 trillion ish or something in market value and so I think that's like an overcorrection, because when you just do the simple math on this stuff, tariffs aren't gonna reduce that gdp down to zero or even half of what it is.
Speaker 2:They're gonna add some friction. But so, first of all, I think it's, I think it's like an overcorrection. The second thing is it's really hard to know how this stuff is going to shake out, because a lot of people believe that the administration is doing this to set them up for like negotiations. Yeah, there's a lot of like imbalance in terms of how tariffs work when you look across different countries, and actually a lot of the tariffs out there are pretty unfair to the US, in the sense that the US has a much lower tariff on these countries than they have on us when they're importing our goods, and so a lot of people think these across-the-board tariffs are just to get people to the negotiating table to negotiate tariffs that are more reciprocal across the board. It's really hard to say how this stuff's going to shake out until another few weeks or a month or a few months pass and we can actually see what's the strategy behind this and does it work or does?
Speaker 1:it not? Yeah, it's interesting because you're right, like it could be temporary. But I'm wondering, like it is to some extent the we did this once before the united states. It was like in it was a really long time ago. The president called I think it was like mckinsey, I would have to or I'd have to go double check. But there was one time maybe not mckinsey I'll have to go back and double check and I'll put it in the notes of the episode. Cool, I forget his name, I think it was that.
Speaker 1:But he did a tariff strategy where essentially the United States was in a lot of debt and implemented a tariff strategy and back in the day before income tax, that's actually how the government collected. A lot of income was through tariffs and then, as essentially we implemented the income tax, tariffs went down, income tax went up and that is essentially modern day United States. That's how we collect, the government collects. The revenue is income tax. So this has been done before in the past and it actually did take the country from being in a significant amount of debt to a surplus and to a point where it's like almost like you don't necessarily want a country to be in too big of a surplus, because what are they doing with that money? Right, like the money should be, you should be taxing just enough to essentially provide what you need to. So you don't necessarily want a surplus, but you definitely don't want the debt that we have now, and so back in the day, when they did this, it did work, but then, essentially in the second term, this president did away with it. It was no longer working, but these things are so complicated. From what I was researching into it, it really wasn't clear if it wasn't working because they were at a surplus and it just changed the market dynamics and it just wasn't valuable anymore. It was just hurting them or something else. The thing is, though, again this happened. This was over 100 years ago.
Speaker 1:The economy is obviously completely different these days. There's a lot more trade occurring, even if it's a minority of our GDP, and then there's a connectivity of globalization and other industries or, excuse me, countries I don't know the percentage of GDP for them and then there's the whole. There's so much of the market on confidence, right, and if people pause spending even more, how that could impact things. And then, even short term, if Mexico, canada, prices are increased on, goods become more expensive for Americans if that heats up inflation. I'm not an economist, but I'm just wondering does that just stop when you lower the tariffs? You know what I mean. No, it's a really interesting question.
Speaker 2:I think these things are super complex and that's why there's not a clear-cut answer to foreign policy or tariffs and stuff like that, and something that happened 100 years ago might not play out the same way today, like you mentioned. And so I think all of this is to say people are feeling a lot of uncertainty right now to your original question, because it's really hard to know how this stuff shakes out and it's still early days. We're trying to keep a pulse on this with our customers and then also our prospects folks that are considering looking at JEM. Whenever we see uncertainty we think all right, how can we best serve our customers? How can we best serve prospective buyers who might be thinking about Gem? And the good news is we've been through a few of these cycles as an industry and so we've learned a lot.
Speaker 2:We've learned that when there's more uncertainty in the market or when companies are really slowing down down hiring, that there's a much stronger need for lower cost all-in-one consolidation. They can save companies money, also help unify their stack. There's a lot of benefits to having everything under one roof, and we've even come up with some pretty creative ways for companies that wanna embark on this longer term journey of moving towards all in one to get started today with a nominal amount of spend and then only start paying us as, like, their different renewals come up for the pieces that are on their current stack and in this way, people can benefit from having the all in one platformone platform out of the gate, but like never be double paying for the different line items that they already have. So that's not how we think about it. Internally is like how can we best serve our customers and the market when there's a lot of uncertainty, because no one wants to be the last thing somebody wants to be doing is double paying for tools when they're headed into a lot of uncertainty.
Speaker 1:Yeah, it's definitely for sure. By the way, I just fact-checked myself. I don't. I think I saw McKinsey. I was thinking the consulting firm was saying McKinley, ah yeah, 1890s, and he was a huge advocate of tariffs. So I recommend people look it up. It's really, it is fascinating. I've wrapped my head around it, I think, as much as I have time for interesting stuff and yeah, yeah, for sure. It's getting to terms like oh, that's like a simple thing, right, like it's pretty straightforward, and then it turns out no, not really, but but yeah, in terms of how I'm. I think people are thinking about the market right now is people are a lot of. I think a lot of folks are in a holding pattern, right, particularly in in the industries that are directly affected, in fact, like manufacturing, for instance but not just going out like, hey, let's open up plants.
Speaker 1:That's like a massive, multi, multi, multi million dollar endeavor that takes one to three years to even get them productive. So, yeah, but it's kind of okay, we just have to, we just have to wait. Nobody really knows, and I think it's just it. Just for me, it's like I run two, two companies I have a recruiting services company and I have the software company June for Secure Vision it's. I don't really know how it's going to impact us. I can say right now, our customers with different industries really nobody.
Speaker 1:The only customers of companies that are pausing and not making decisions are really manufacturing supply chain, like they're at a standstill, like any kind of deals and pipeline related to that they're not considering, they're just not moving forward. But you know, in other industries it's essentially it's weird, it's like business as usual, almost, despite all of this stuff happening in the background. So I guess that's good, right. And I think, though, like, in terms of customers thinking about, like spending all in one, that's still been the trend for the past few years, right, I think that in the markets going into that direction and consolidation, which is, I think, it's a good thing, so, from a for customers. I think that they still want companies still want that.
Speaker 1:When it comes to hiring and tech stacks consolidation, I think also this idea of being able to access gym, like different products, like just to get onboarded yeah, started to start adding value, pull up, give them help, help them where they need it and then transition them into a full stack or a full product suite customer yeah, definitely the way to go, because I think folks are like looking for all-in-one, they're looking for flexibility, but this is a macro trend, regardless of what happens right, even if autonomy gets hit mid to long term because of this, it really doesn't change. I don't think too much how companies are going to think about hiring or particularly the technology that they're going to be using. If anything, it's just further reinforcement that we need to optimize tech and be very lean as an organization. Now we think about talent acquisition.
Speaker 2:That's right. If anything, I think it just accelerates that trend.
Speaker 1:Yeah, it's just like the same thing, but it's not like pivoting. I don't think really.
Speaker 2:Yeah, that's right.
Speaker 1:Yeah, so that'll be really interesting to see what happens here. But I and I think just to it's interesting that all this market uncertainty and consolidation and cost scrutiny and all these types of things is taking place alongside a lot of innovation in the AI space, which actually enables companies to be a lot more effective with their spend. But I guess, before we get into the company side of AI, we wanted to talk about how candidates are leveraging it and the interview process.
Speaker 2:Yeah.
Speaker 1:So this isn't actually a side that I've done as much research into. I'm curious if you wouldn't mind just sharing with me and the audience, like what are the biggest use cases that candidates are leveraging for AI and they're for applying to jobs and things like that?
Speaker 2:Yeah. So the two biggest things that I'm hearing from like the market, from customers when I'm at conferences and things like that talking to folks in the industry are one some candidates are starting to adopt tools that make it really easy to apply to hundreds of roles all at the same time while still personalizing their cover letter and their resume to the opportunity, and so it's basically reducing the friction dramatically to apply to roles, and we can talk about that in a sec. The second is I was speaking on a panel at Transform and I think the moderator asked so what does everybody think about candidates using generative AI in the hiring process, like for actual interviews, and so I thought that was a fascinating question. But yeah, I'm really curious to get your take on that one too, james, in terms of yeah.
Speaker 1:So when they were talking about candidates using generative AI in the interview process, what were they? Did they give any more like? What specifically were you guys talking about there?
Speaker 2:Well, yeah, I think a lot of companies, so a lot of candidates. First of all, if they're on Zoom, they're realizing they can, like, use Gen AI to support themselves in the interview process and a lot of companies.
Speaker 1:Yeah, I guess they just sign ChatGPT at the same time.
Speaker 2:Yeah, how do you think about that? How do you feel about candidates using Cloud or ChatGPT or something like that? And my somewhat spicy take is we want candidates to be AI fluent.
Speaker 1:Yeah, you don't want somebody who doesn't know how to use it, right.
Speaker 2:Yeah, we want them to be using AI in their jobs, and so let's find a way for them to use AI in their interview process. In fact, maybe let's actually encourage it in certain ways. I actually heard of this really cool interview. I forget which company this was. It was one of the leading AI companies. A friend of mine was on BizOps. She's never coded in her life and this company said hey, use GenAI to code something up. It's like really simple, but like just do some pair programming with GenAI and we'll do it with you, and I thought that was the coolest interview ever. She actually realized that she could code when she had never actually tried coding before.
Speaker 1:Yeah, yeah, it's pretty wild, I think, frankly, if there is a, what comes to mind for me as an employer is okay. Are we going to be able to truly evaluate somebody's skillset or are they going to get past us? I just don't think that's the case. If you're interviewing correctly, like even if somebody's using, I think of so many of the questions that folks should be asking is really particularly if it's a role that requires experience dialing into past experience, like walking you through projects, specific problems, how they overcame them. For sales, it's talking in numbers, right, you have to be. You can't tell you your average deal size and sales length and quote attainment and can you get a reference from the previous direct manager to back that up? And that chat gpt is not going to help with those types of things too. Totally.
Speaker 1:I think, too, with behavioral questions, you could tie behavior into and personality attributes into, talking about examples in the past, right, just really dialing into their personal experiences, I think is like personal professional experiences, like you can still evaluate people. I don't think that. I think it would be a little bit like if somebody was using Chachi PT on an interview with me, like I would. It's not that I would be worried that I was going to hire somebody that's not actually qualified, but I it would still. Honestly, maybe for me, I don't know, but I feel like it's cheating, I don't know, I just would be like weird. It's how, like, I'm here to have a conversation with you. Yeah, I think that would definitely be something that I would consider a yellow flag, not because, like, I don't want people to leverage chat, gpt, but it's okay. Look, we both know that we're trying to have a human to human interaction here. I don't know, yeah, I think it's okay. Look, we both know that we're trying to have a human to human interaction here.
Speaker 1:I don't know yeah, I think it's weird I think it's weird if somebody really used chat gpt on an interview I get it.
Speaker 2:I get it. But on the flip side, if we want our employees, our people, to be using chat, gpt or claude when they get hired I don't know, it's almost tough should we allow candidates to use generative ai as an extension of their brain? Here's an interesting analogy I was thinking about the other day. How old are you, james?
Speaker 1:33.
Speaker 2:33. All right, so this might date me a little bit. I'm not sure if you had this experience growing up In grade school when you did research papers. Do you remember having to go to the library and get citations for your?
Speaker 1:book? Yeah, you remember that. And did your teachers ever say no, don't use Google, don't use Wikipedia? Yeah, yeah, a little bit.
Speaker 2:I remember that. Do you remember that? That memory stuck with me because I was like I can get this information so much more easily by going to Wikipedia or doing a Google search, yet I'm like being forced to go to the library, look in these cards, these physical cards, to find the book, then open the book and try to find the information I need, just so that I can have an actual citation from, like, a physical book, instead of using all the information at my fingertips on the internet. Oh, yeah, for sure. I think of it in a very similar way of hey, jenny, I was just going to be an extension of, so let's face that.
Speaker 1:Yeah, but, like also you, if you have somebody a question on an interview 10 years ago, you wouldn't want them to google an answer and try to find like an article. You just want to know, okay, what do you? And part of it's like hey, how do you leverage ai? How would you leverage ai?
Speaker 2:but I do think there should be some level of that's a good limit, says actually, if for the interview, depending on. So for the interview, if it's something where you'd want them not to Google, maybe you wouldn't want them to use Gen AI. But on the flip side, what is the rationale for that? Because on our jobs we can Google things.
Speaker 1:Yeah that's true, I think. For me, it's like the whole reason I'm talking to somebody is to get a better understanding of their experience and skill set. It's like everybody has access to the same GTP, chat, gpt. So it's like I want to learn about you, not.
Speaker 2:The thing I liked about this interview question that this company had designed for that candidate is they had actually got folks using generative AI and got them to show how they think and how they iterate. Oh, I like that. I like that a lot. I like the idea of bringing people in.
Speaker 1:Hey, can you leverage this tool to help think through this idea or to do this coding assessment? I think that would show how tech savvy somebody is, how well they can understand, like prompt engineering or creative, adaptable, general, maybe new intelligence tests. I think that kind of stuff is really helpful. That's a cool motion. I do like that.
Speaker 2:Here's maybe where I think I draw the line is yeah, I wouldn't want candidates using generative AI as a way to substitute for learning how they think, and then maybe we just need to reimagine the questions we're asking that understand really understand how candidates think about a problem. Maybe the difference between Googling something and generative AI is can actually spit out some pretty reasonable answers. You know, thinking through things in a way where a candidate could just parrot it back.
Speaker 1:Yeah, yeah, for sure Fascinating.
Speaker 1:Yeah, I don't really I don't mind. Yeah, I definitely want people who are leveraging gen ai, I guess, on the interview. I like the idea of it being some kind of like assignment or working session. I think that's really cool. Um, I think I definitely would want to know how they would think about leveraging it in their job, but again, more of like their thought process and how they think about leveraging it and using it as an extension, as you said, to like their brain and their thought process and behind the scenes they're just plugging that question into gen ai and it's parroting back here.
Speaker 2:Think about leveraging it and using it as an extension, as you said, to like their brain and their thought process. And behind the scenes, they're just plugging that question into Gen AI and it's parroting back here five ways you could use it on your job.
Speaker 1:Yeah, I know Exactly, it's just yeah. But yeah, I mean, I think, like the other thing with the applications is, I think that's just going to, that's just going to happen. I do think that's why there's a lot of value in a product like june, like with what I'm building right, because there are the markets going to be flooded with applications that help people apply really fast and the market's going to be flooded with a lot of applications that are reviewing resumes and applications and doing that motion as well. So it's like both. It's like an arms race of AI. Which system can outsmart the other?
Speaker 1:I think to the extent the recruiting industry can get away from keyword-based matching or searching for unqualified talent pools is really important. I think once you have some kind of evaluation step in place whether through a recruiter or through or like a tool like June I think then that kind of matching motion does become a lot more valuable because, like one of the issues it's like with inbounds is you can do everything right as a sourcer or a product could do everything right. But then my concern would just be like, like people have a lot of access to tools and resources to put together resumes, put together like the keywords tell the story, but it's again, it's, and I guess people could still even with an evaluation. I'll tell you what you want to hear, I just think. I think that the idea of having some kind of qualification step in place is really important to make those types of things valuable step in place is really important to make those types of things valuable.
Speaker 2:Yeah, totally yeah, and I could even see yeah, yeah. First of all, I agree the arms race was something I was just reflecting on and a lot of people are like, oh man, I wish folks wouldn't be using these AI tools, but the fact of the matter is they make it so easy to apply. Like, of course, over the next few years, like every single candidate is going to be using these tools if it helps them get more interviews and increases their chances even at all.
Speaker 1:I think I don't have an issue with that at all. The noise to signal ratio, like, though, is just what is the is clearly if it benefits companies, because maybe there's people that wouldn't have found you or didn't have time to apply.
Speaker 2:That's the really interesting thing is, I do actually think that if companies embrace AI as well so that they can get to the most qualified folks, then it benefits both sides, because it essentially enables a much more efficient marketplace of candidate job opportunities. Whereas previously, a candidate might be able to apply to I don't know five, 10 roles a day If they can apply to hundreds, but then the AI can bubble up the ones that are actually a fit. You remove all the human manual work from the process. Now you've got like an efficient marketplace.
Speaker 1:Yeah, I have no issue with it and I think it's just. I think it's just going to make the market, the economy, every company in it, just more efficient and effective and help companies move faster. It's I think, it's good. I'm looking for. These are the types of jobs I'm interested in. And then how they go out and do the applications like why should somebody have to do that manual motion of applying and applying when you know there's a good chance? You're not even going to hear back from the company. Yeah, you know what I mean, so I have zero issue with that.
Speaker 2:And maybe for candidates, they still the short list of companies that they know they're really excited about before interviewing. They still do themselves to put their best foot forward.
Speaker 2:Then they get like a longer tail of opportunities and interviews. Yeah, I think maybe the place where I do take issue is if any of these AI tools I'm not sure if this is the case but if they're actually misrepresenting a candidate's experience and background and just jamming keywords in there that aren't actually relevant to their experience, because then I think it's helping no one as soon as they go through June or like a actual recruiter interview, hiring manager interview, like it's going to be so easy to tell and it's just going to be a waste of time for both sides yeah, I think it's.
Speaker 1:that's why it's almost like if there's going to be automation and AI leverage on one side in order for the other side to actually absorb that and process, that requires AI and automation. Yeah, it wouldn't like, because if a company is getting a thousand more applicants every week, or more tens of thousands, or whatever, and they're not leveraging AI or automation, like how are they supposed to get through that? Yeah, totally it's like it has to be. You have to leverage it like a company.
Speaker 1:But the other thing like you need is you need, like the AI that's generating the applications, to be factual, yeah, I think so, and that's people will stack in keywords and I think one of the most common ways is oh, I did this once in a project or I watched a youtube video on it and there's that kind of stuff, and so that stuff's going to start to happen at scale. So you are going to have a lot more resumes of people that aren't qualified, but I don't know what it will actually do to the ratio. Maybe it's still okay if, for some kind of skilled knowledge worker role, if 3% of applicants, 5% of applicants are worth screening, if you, if folks, are using ai automation, will that ratio stay the same? It's just it's going to have a lot more volume. I don't know, but I don't know if it'll get better, if it'll get worse in terms of the ratio of like relevancy of the applications. Yeah, just don't know. But I think it's a good thing honestly. I think it's. I think it's good I think so too.
Speaker 2:I think once both sides of the market move towards using ai, we're actually going to end up in a more efficient place, surprisingly.
Speaker 1:Yeah, I just don't have any issue with it, and I think companies are obviously going to be doing everything to be efficient and effective with their process, and I would hope you want to hire people that think the same way. You know what I mean. As we said, you want people that know how to leverage technology typically, or in a lot of roles you do Not necessarily for every role, but at least in a lot of circles we run in right. You want people that are adaptable. Yeah, totally. I want to talk about Gem a little bit. So really just on where the product is today. What's coming up? Some new, possibly future releases? What do you have coming down? What are you currently doing and what do you have coming down the pipe right now with June, excuse me with Jim?
Speaker 2:Yeah, totally Happy to talk about a whole bunch of different products, but I think specifically on the AI front, given that we were just talking about that so we've built out like a really strong matching and ranking engine which takes in resumes on one side and then five to 10 criteria that the recruiter specifies on the other side for a job, and then uses generative AI to rank and match and score resumes based on those five to 10 criteria, and so we've applied that to AI sourcing on top of 650 million public profiles.
Speaker 2:We've also applied that to your inbound applicants. So to our point earlier around companies getting inundated with applicants, folks can find the ones that are most likely to be the best fit much, much faster, and then potentially they could advance those folks immediately to recruiter screen or even hiring manager screen if they score really high, and then they could use June for either the long tail or the mid tail to screen the rest. It's a cool tie back to what you guys are doing. Next up, though, we're applying that same matching and ranking foundation to candidate rediscovery.
Speaker 1:It's so funny, like how I was bringing that up earlier. It's like that's exactly what I'm hearing from customers and prospects is a use case they're really interested in.
Speaker 2:Yeah so it's cool.
Speaker 1:Sounds like you're hearing the same or thinking the same way about it.
Speaker 2:Just based on what I know about June, companies can only interview so many candidates, right, so they have to pick and choose. We help them identify the ones that are most likely to be worth a recruiter's time or a hiring manager's time. Past that you got to imagine that if June could do interviews for a much broader set, that more great people would be in the mix that maybe didn't know how to put their best foot forward with their resume, or who interview better than and actually have other skills that aren't easy to demonstrate just from a written resume. No, I think it was a really cool synergy between those two.
Speaker 1:Let's say, I was talking with the CEO of a company called Recruit CRM, which is oh yeah, you know them, okay.
Speaker 2:Yeah, oh, no, sorry, I was thinking about a different company, but yeah.
Speaker 1:Okay, yeah, recruitcrm Sean, their founder and CEO a pretty cool story. They actually bootstrapped and they have hundreds of customers, I think around a couple hundred employees. At this time they might even have a thousand customers, I'm not sure, but they do. It's an ATS, but it's like a recruiting automation solution for staffing companies, and that was essentially like the exact use case we talked about, potentially with a partnership with June and RecruitCRM was they already have? They have a kind of like an automation AI layer to identify profiles, right, that specifically for staffing of folks that are likely to be a fit, and then for June to be like the layer underneath that to shorten that. But that should make it a little bit smaller from what they so it's. I think that there's and then I think, just too, it just depends on, like the industry in the use case.
Speaker 2:We're just gonna have to see where it seems to fit the best but yeah, yeah, and I can see the same thing applying to candidate rediscovery stuff we're working on.
Speaker 2:In fact, there you have even more candidates or folks in your CRM that you've identified that could be a good fit for a role, because you're not just limited to the applications for a one or two week or three week period for this specific job that's been opened up, because you can actually look across all previous applicants, all previous folks in your CRM that the recruiting team has identified as a good fit, and so there the volume's even higher. So I think the idea that folks could use, like GEMS AI to identify, I don't know, maybe the 10, 20 GEMS, so to speak, that they want a recruiter to talk to immediately, and then they could use June to screen hundreds to see if they're a good fit for this new role that just opened up, to broaden the pool, maybe double the amount of qualified folks they can bring into the pipeline by seeing a much broader view of candidates, sounds really interesting.
Speaker 1:Yeah, tna Rediscovery is really cool. I think it's just traditionally an area that has been somewhat underserved in the from recruiting technology. I think that there's been. There's a lot of area for just providing a better experience there for recruiting tech and more value to customers. And it's interesting it's like for June. We actually have a customer that's starting with us and I guess a week from today, who they only want to use June for candidate rediscovery Cool. Actually, they're not to start. They're actually not going to be using us for inbound screening, screening inbound applicants. It's going to be what's that?
Speaker 2:Yeah, why not also use it for screening?
Speaker 1:Because they're.
Speaker 1:So this one is a it's a staffing company in the GovCon federal state and it's like cleared talent, and so it's a limited talent pool. It's still big, but it's like somewhat it's not infinite, and they're specifically they recruit for engineers, right, like a specific type of engineer, like data engineers in this case, and so what they're looking for is of course, things change over time, so they want June to be able to reach out after six months and say hey, in February you spoke with Debbie and expressed interest in X, y and Z, or had mentioned that you're currently doing this. How are things going? Are you actively looking at this point? Are you still looking for this type of role or whatever the kind of requalification is, because, of course, data in the system may not be current anymore. It's a way to re-engage with that talent, stay close to them, stay in front of them. So it's like an engagement and rediscovery kind of requalification motion which is like exactly that's the use case that they're going to be using at first. So they want to get that out first.
Speaker 2:And when the talent pool is more narrow, then you know, maybe they're actually able to interview most of the folks that come inbound that match that very narrow qualification. But then they've got this pool of people already in their system that they're just not engaging with because I think so and I think there's also like the relationship piece.
Speaker 1:I think specifically like they really want to speak with everyone, build that relationship off the bat and they're like they're willing to speak with people that aren't qualified, like they're just like it's worth it because they have to get to the select few that are. So I think that just their workflow, it makes sense for that. But, yeah, it was a little bit surprising because I got on the discovery and to do a demo and I was ready to. Of course, we bring up rediscovery, but I was also expecting to talk about inbound and the CEO's. Just no, I want to. This is what we need. We need rediscovery, we need to re-engage, we need to stay in front of them consistently. There's sometimes you speak to somebody we may not place them until two years later and I need a consistent way to engage with them, to stay up to date with what they're doing, what they're looking for and to remind them about us. Right, that's essentially what they're looking for.
Speaker 2:Cool good stuff.
Speaker 1:Yeah, yeah, I think Rediscovery is a really cool one. I think that's again.
Speaker 2:I think there's a lot of opportunity there for companies. Yeah, me too. That's just a goldmine If I can put some stats behind that. We definitely serve a decent number of staffing agencies. A lot of our customers are in-house. For in-house customers across the board, 30 to 50% of folks that are hired already existed in your CRM or ATS before you hire them. And then for enterprise customers, it's something like 60, 70% of the larger ones and, yeah, that's a goldmine. But when you think about, like, how folks are actually entering process, it's in really inefficient ways. It's people going out and cold sourcing them again, or companies running like Just so expensive. Right, yeah, you're building pipeline and 60, 70% of them, if you're an enterprise customer, are already people that you have relationships with, but you're paying all over again to build those pipes.
Speaker 1:Yeah, that's the whole thing. One of the reasons of many that I really like the idea of optimizing inbound and kind of rediscovery is because outbound motions can be very expensive from a headcount perspective and they're important and they're still like probably the most I would say for specifically for knowledge workers and specific profiles. I would say you need an outbound motion right like at secure vision. Most of the hires we help our customers with are still outbound outbound sourcing but nonetheless that's because we there hasn't been tech.
Speaker 1:I think that has really optimized inbound and rediscovery very well. There's just been gaps in the technology and I think that those things are now like more products are coming out to essentially increase contribution to hiring from inbound, increase contribution to hiring from rediscovery and make that a more significant ROI motion and that should help at least balance out the cost where the sourcing efforts it's going to cost more but you can be really dialed in and get those new profiles. And that's really, if you're paying a senior recruiter and a recruiting tech stack for outbound, which is expensive, more expensive, like you should have them laser focused on building those net new relationships, right.
Speaker 2:Yeah, exactly, you don't want them like exactly reinventing the wheel with folks that you already know about. Same for inbound like companies spend millions of dollars on like job advertising and 60 70% of the people they hire are people that are already in their database yeah, that's true no, I think it applies to both. It just across the board, like the top of the funnel, is quite expensive. So if you can augment that with people you already know about, no brainer yeah, yeah.
Speaker 1:Just one quick question on the rediscovery motion that you're building out. Essentially, it's going in and you're able to search for folks that match based on their screening interviews or their resumes, or is it like a combination? How is GEMS surfacing the candidates that are the best for a role?
Speaker 2:Yeah, so it's two things. One is, on top of the resume, we'll use that same ranking and matching engine and help you find folks that best match those five to 10 criteria that, like the recruiter or hiring manager, is defined for that job, and I'll look across your entire ATS and CRM database for folks that are the highest match. But then on top of that, you can also add some smart filters so you can filter out folks based on, like, how far they got in the interview process, what the blend of scorecards was.
Speaker 1:Oh, okay, yeah, that's really cool.
Speaker 2:Yeah, folks out based on have you had a touchpoint with them in the last three to six months or were they rejected within the last year? A lot of the really common rules of engagement that companies might have about, like when they want to re-interview folks. And because GEM is an all-in-one recruiting platform that covers sourcing, CRM, scheduling, even like talent marketing capabilities, ATS like we've got the most complete source of truth for all those different touch points that you can put on top of.
Speaker 1:Yeah, for sure it all, yeah, it's integrated, all tied together. Yeah, that's awesome, man. Yeah, I got to get my hands on more of the products that you have right now Still using. We're on the sourcing product of building cadences and outreach campaigns, which is, I think, you're running butter at least it was back in the day so it's the primary product and, of course, grown so much since then.
Speaker 2:Yeah, let's get you set up on it, James. I'd love to get you guys the full, the full power of Jam all in one.
Speaker 1:Yeah, we got to do it, man. I actually have been meaning to talk to you about that, because I'd rather, I just I do want to do everything through through Jam at this point, just based on what you're building. It's just. It would make things a lot easier for us too.
Speaker 2:You got it. I feel like we've had a really productive pod. We've we've figured out potential partnership opportunities between you and Jem. Yeah, yeah, we're going to get you on to Jem all in one. Let's do it, yeah.
Speaker 1:Hell yeah, man. Yeah, as always, it's a. It's been a lot of fun. Thank you for joining us today and sharing your insights, and I always enjoy these episodes a lot. I'm happy we get to do them on a regular basis.
