Hire Calling
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Hire Calling
How Juicebox AI Is Redefining Talent Sourcing
Recruiting has always been a race between speed and quality. But what if you could have both?
In this episode, we’re joined by David Paffenholz, co-founder of Juicebox AI, to explore how AI is transforming talent sourcing as we know it. Born out of his frustration with traditional recruiting, Juicebox lets you search through 800 million profiles in minutes, surfacing candidates traditional keyword matching would miss entirely.
David breaks down how Juicebox uses large language models (like ChatGPT) to go beyond keywords and actually understand candidates' context, skills, and potential. We dive into the platform’s “Juicebox agent,” a sourcing assistant that never sleeps, soon able to launch searches automatically based on your ATS activity.
We also discuss market trends, including the BLS's job count correction, return-to-office dynamics, and how AI tools like Juicebox can provide staffing firms with a competitive edge without compromising on quality.
If you’re ready to spend less time sourcing and more time hiring, this is the episode for you.
🎧 Try Juicebox for free or book a demo at juiceboxai.com
Additional Resources:
1. Innovative Sourcing Techniques for Recruiters
2. Can You Trust AI to Handle Recruitment?
3. How Is Artificial Intelligence Changing the Recruiting Process?
🧠 WANT TO LEARN MORE? Be sure to subscribe and check out 4 Corner Resources at https://www.4cornerresources.com/
👋 FOLLOW PETE NEWSOME ONLINE:
LinkedIn: https://www.linkedin.com/in/petenewsome/
Blog Articles: https://www.4cornerresources.com/blog/
👋 FOLLOW DAVID PAFFENHOLZ ONLINE:
LinkedIn: https://www.linkedin.com/in/david-paffenholz/
You're listening to the Hire Calling Podcast, your source for all things hiring, staffing and recruiting. My guest today is David Paffenholz from Juicebox. David, how are you today? I'm doing well. Thanks for having me. It is great to have you. I've been trying for a while. You are a busy guy to get a hold of. That must mean business is going pretty well.
David Paffenholz:It's been an exciting time at the company, lots of new things happening.
Pete Newsome:Team is growing, customer base is growing and super excited to be on today Awesome Well.
David Paffenholz:I'm happy to have you just quickly set the stage and describe Juicebox in a nutshell, if you could. For sure, juicebox is an AI recruiting platform. We help our customers find the best talent by aggregating a bunch of different data sources and then using natural language search to surface the best talent. We then have some additional outreach workflows, including emailing, managing those contacts and more, and so I think of us as an all-in-one, top-of-funnel AI hiring solution.
Pete Newsome:Excellent. So, needless to say, ai a little bit of a hot topic these days, but we'll get into that in a minute too. First, tell me about your background a little bit. How did you get to where you are now?
David Paffenholz:For sure. So, as one might be able to tell by the last name, I'm originally from Germany. I came to the US first for college and then stuck around since I started the business, together with my co-founder, in 2022. And so this was shortly before ChatGPT came out and everyone started talking about AI, and our kind of initial vision, or what we wanted to focus on, is building tooling to make the recruiting process easier, particularly on the search side, and so that's where we started. The reason we were passionate or interested in that space is because both my co-founder and I had always found employment through kind of irregular methods. We were basically cold, reaching out to jobs or roles we thought were interesting or trying to create those roles for ourselves, and so it made us believe that there's still a lot of friction in that hiring process and still a lot that can be solved, which also made us interested in building the product.
Pete Newsome:I love that, and you know there's I think there's not many people who are young and coming out of school finding the job search process easy these days. So not a unique situation, but you chose to tackle it in a unique way, which I love Not just complaining about it, but doing something about it. So good for you for reaching that conclusion. Let's talk about the state of the market today a little bit. I don't know if you saw that the Bureau of Labor Statistics just happened to put out their employment report this morning. Did you see the numbers?
David Paffenholz:Yeah, so there was like a large correction shift.
Pete Newsome:Yeah, a massive one, right that almost 300,000 jobs were overreported over the past two months, and so a lot of us in this industry and a lot of job seekers are feeling that the market is not easy. Right, the government for the last couple of months, has told us that it's easier than we're feeling, and this told a pretty big story. I think that the job market is not growing as well as we'd like it to, and it's really hard to find a job. It's really competitive, recruiting is tough. So that's my perspective on the market right now. What are you seeing?
David Paffenholz:Yeah, I think there's kind of very different scenarios in different subsectors of the market, and so in some spaces we're seeing the market really heat up and kind of becoming very competitive, and other sectors we're seeing kind of a lot less of that. And I think the labor market correction is a good reflection of that too, where the statistics sometimes say one thing, the reality on the ground says another thing, and then the reality on the ground also changes depending on the role, the location and even that specific point in time. And so we've seen quite some drastic shifts amongst where our customers are hiring, where they're focusing on their searches, even what industries they're focusing on In that case, of course from the recruiting agency perspective as well.
Pete Newsome:You know, and I always feel like and I'm biased, of course, because I own a staffing agency but I feel like we have our finger on the pulse as an industry of what is happening at any given time and that's why, for me personally, some of the numbers were surprising. Right, you look on LinkedIn, it doesn't sound like it's a great job market right now and when I talk to my peers around the country, we've felt I've picked up on some struggles that a lot of companies are having these days. But I wanna know if you could share which sectors do you see they're doing well?
David Paffenholz:Yeah, I'd say the one where we've seen the strongest pull in is like the tech sector, especially here in San Francisco. We've seen like a lot of surge in hiring there, really across roles, but particularly for in-person roles here in the broader Bay Area, and so that part of the market seems to have really been accelerating and that's like roughly 20 market seems to have really been accelerating, whereas and that's like roughly 20 to 30% of our customers so it's a sizable chunk but it's not the majority of our customer base and so we've seen that acceleration there, and then in other parts of the market perhaps less so and perhaps less of that pull. I think it's interesting too, because it's almost like an inverse, where the tech sector almost has this opposite relationship to the broader hiring market and in times where the tech sector is doing well, the broader economy might not be, and vice versa, where we saw the opposite two years ago. And so for us as well, where we serve both customer groups, we always see some discrepancy in those as well.
Pete Newsome:What are you seeing locally out there with return to office? It's kind of subsided. I haven't heard as much as we have for the past couple of years here in Florida, where I am. I think it's business as usual. For the most part, those who are going back have already gone back and there's a lot of hybrid roles out there. But what are you seeing?
David Paffenholz:Yeah, I think most companies and most companies have kind of made their decision, like, either they are going to be, you know, fully in person they're hybrid or they're fully remote, and at least at this point they really should have made that decision too, because, you know, it's been a while since the world has started to normalize. In our case, our team is in person. We see a lot of companies that are kind of fully remote or have chosen that hybrid path as well. I will say that, from what we've seen, the in-person market has just become a lot harder to recruit for because it is a constraint on how many candidates can take on that role.
Pete Newsome:Yeah, and I think so much of that comes to supply and demand right Candidates who have a rare skillset, which has always been the case, but now it's in many ways targeted at. Are you going to work in the office or do you have the luxury of having that skillset that allow you to call your own shots more and work at home? Are you seeing that? Because I really think supply and demand is driving a lot of it.
David Paffenholz:Yes, yeah, definitely. I also think there's like some interesting parts where, like roles that used to we used to think are like in-person mandatory because of COVID, we're like forced to shift to remote, and then they've kind of just there's been this consensus of like, you know, some of these roles can completely be done remote, where if we had just asked people five, six years ago, is that even possible for these roles, a lot of people would have said no, and so I think there's kind of been that rethinking in the market which has really changed what people think about in terms of demand as well, of like what roles are really needed to be in person versus not.
Pete Newsome:So that's a perfect segue into what we're really talking about in the big shift is AI. We're really talking about in the big shift is AI. What wasn't possible in the very recent past is now a reality that we're having to figure out how to deal with right, not just in the staffing industry, but as a whole. So what's your general take on AI and how it's impacting the job market already, and then how it's going to impact it in the future?
David Paffenholz:Yeah, I think AI has had two big impacts on the industry. I'd say like one maybe on the labor market more generally and then the second specifically on like staffing and recruiting. And so I think in the labor market kind of more broadly, it means that the output of every single role I think the expectations have increased and the ceiling of what is possible has increased because people are starting to use AI tools, starting to be more efficient in parts of their workflow and achieving more. But that then also means that in some cases, the expectations for those roles have gone up because the kind of normal is now at a different rate. I think overall that's a great thing because productivity increases, the economy grows faster and we're able to do much more.
David Paffenholz:At the same time, it also makes it particularly tricky for roles where maybe that AI adoption is a bit slower or employees don't provide the opportunities to adopt AI or the tooling for it. I do think in most sectors there is now at least one AI tool that can really simplify workflow, if not multiple, I think, in recruiting. You know, despite us being in the AI recruiting space, there's also a lot of other good companies in the AI recruiting space and I'd say there's like there's a good amount of different solutions to evaluate and to test from, and so I think, yeah, there's there's a lot, right to say the least, and it's evolving rapidly.
Pete Newsome:That's one of the things that I struggle with. One of the reasons I wanted to speak with you today, quite frankly, is to share a message of what's even out there, Because when I speak to my peers around the country, they struggle to keep up. But I'm curious about adoption, how your perspective may differ than mine. Have you seen any trends among company size, you know being faster or slower to adopt, or is there generational differences that you see on? You know, if you had to put any categories in place, can you do that? Or is it just really all over the place?
David Paffenholz:Yeah, so what we've seen that gets me really excited and that I think is kind of unique to this time as well, is that individual users in many cases, or like individual team members, can find AI solutions and start adopting them for their own workflows.
David Paffenholz:If they find that it works for them, it can kind of spread within an organization without needing to be like centrally purchased solution, and so I think a lot of AI tools have started positioning themselves that way too. It's on like the simplest level, say a chat GPT where everyone can sign up, create their own account and start using it in different ways, but then even workflow specific tools where an individual user can sign up, try using it for free and then might spread adoption across their team. For us, almost all of our customers start off by having one or two users internally happen to come across the product or maybe have heard about the product, test it out and see if it works for their workflow before showing it to the wider team or looping in their manager to do a kind of more traditional evaluation, and that kind of bottoms up discovery I think is really powerful, because it also sets the bar a bit higher. For, you know, does this really work, or is this just a really good sales pitch?
Pete Newsome:I really like that and I hadn't thought of that before what you just said before. But as I'm listening to you, I understand exactly what you mean and I've seen that over and over and that is pretty unique in terms of technology adoption in my lifetime probably everyone else's where you really do have access at an individual level without having the company have to make the decision as a whole, and what a great thing I mean. As an employee. Over the years I've had lots of ideas where, when I was an employee which was early in my career I would often get frustrated by an inability to have the company adopt new things right. I've worked for two large employers prior to starting Four Corner and they've moved very slowly. I don't think you can do that anymore and I think companies have to listen to their employees and would want to listen to their employees who have the willingness to go and seek things out on their own.
David Paffenholz:Yup, yeah. And frankly, it's also a great way where you know if companies notice that, say, two employees are really outperforming or suddenly producing a lot more outcomes and output, and you know. Then one asks, hey, like what are you up to? Or what are you doing, has anything changed? And maybe they're using new tooling or they're trying new workflows. That can be a really cool evidence point as well, where it almost becomes a no brainer for the organization to at least consider those resources or think about what a wider adoption could look like too.
Pete Newsome:And yeah, so true, and I love it, and you know as well as I do as a business leader, there is nothing better than an employee coming to you with a solution to a problem you didn't even ask him to solve right.
David Paffenholz:I mean, how great is that it doesn't get me better? Yup yeah, Especially when it's like a problem that you know, it's always kind of being in the back of one's mind and like never really had the chance to tackle it or think about what one can do about it, and then just seeing that solution in front of you, it can be a pretty nice feeling.
Pete Newsome:A hundred percent, all right, man. Well, let's get into juice box specifically now. So I can tell you that the entirety of the time I've owned a staffing company which is we're in our 20th year we've always tried to find a better way to do things right, gain efficiency, gain speed, gain thoroughness, and there's been very little potential to do that up until recently. So I couldn't be more excited about solutions like yours, and I know that as an industry, we desperately need new solutions to improve. So just break it down from the beginning what is the premise in terms of what is the biggest problem Juicebox solves? And then let's get into some details For sure.
David Paffenholz:So I'll start off by kind of describing what we see as the status quo, or what our users typically do before switching to Juicebox. Then I'll contrast that with what Juicebox does. And so currently, what we see a lot of our customers do before adopting Juicebox is when doing a candidate search. They have a pretty manual process. There's usually two places they go. One is their existing ATS or database where they look through any candidates that they might already know that could be a good fit. Usually involves perhaps setting a filter, running a search depending on the software that they use, and then kind of manually reviewing those profiles In some cases pretty long lists, and ends up being fairly time intensive, Also usually not the best interface to do it with. And then the second thing that we see our customers do is going out and finding net new profiles for those roles, and so you know, be that sourcing externally through a channel like Indeed, LinkedIn or others, where we kind of manually also enter those filters and then start reviewing, and then finally we'll want to engage those candidates, be that through emailing, phone calls, etc. That whole process ends up being a large share of recruiter time spent.
David Paffenholz:That is exactly the workflow that Juicebox aims to solve, and so we do that in a few different ways. The main one is we combine your existing data with our larger data set, where we have over 800 million profiles globally. We've indexed them, added a bunch of additional data into them and provide one unified search. And so, rather than having to go into those different systems, describe who you might be looking for the role you're hiring for, you can just type that into Juicebox or put in the job description.
David Paffenholz:We'll automatically go out and search for both the best profiles who are already in your database as well as net new profiles that you should probably consider for the role. From there, we'll then rank them for you, and so we'll go skill by skill. Do they match what you're looking for, criteria by criteria, and present it to you very similar to how a human researcher or sourcer might. They'll go profile by profile and say you know, this criteria is met, but maybe not this one or this profile could be a good fit for this reason. We'll then present those top matches to you and let you reach out to them in one click, either through an email sequence or, if you prefer, to reach out by phone. We'll provide that data too, and so that whole process, instead of taking 10 plus hours, can go as fast as 15 minutes, going from initial search to having that output and then being able to take action from it.
Pete Newsome:And everything you described is for a human to do is what I consider to be low-quality time. It is necessary, but we want our recruiters engaged with candidates directly right, we want them connected and everything that leads up to that again necessary. But you'd like a better way to do it, a more efficient way. So tell me about the 800. I'm intrigued by that 800 million. Are those existing in your database, or do you have access to them in a database like LinkedIn? I mean, where do those candidate profiles reside?
David Paffenholz:Yep. So that's aggregated from public profile data. So, be that profiles that candidates may have on professional networking sites, be that profiles they may have on social media sites like a Facebook or Twitter, be that other information they might have on a company website or on a personal website, depending on what's available, it varies a bit from from role to role as well. So, for example, for the health care sector, there's some other data sources available, or even public licensing information that might not be available for other sectors, and so we kind of see what's out there, depending on the sector, aggregate that data and then put that into a more what we call unified profile, basically just combining those different data sources into one source of truth.
Pete Newsome:Okay, now is a tool, so do you have better can it profiles or more can it profiles in? Do you have a strength area in particular, or are you pretty agnostic when it comes to the position types?
David Paffenholz:We're pretty agnostic. I'd say, geographically we're strongest in North America and it's where the majority of our customers are, but then within that we're very role agnostic.
Pete Newsome:Okay, nice. So give me customer size typically. Do you have an ideal customer size? Do you have an ideal number of positions that you really see where juice box is most effective? Paint that picture for me.
David Paffenholz:Yeah, it's become quite broad. So we now work with over 2,500 customers, ranging from individual recruiters who maybe just set up their own agency or started freelance recruiting, all the way to some pretty large enterprises where they have, say, a 100-person recruiting team, or larger recruiting agencies where they have similarly sized recruiting teams. I'd say the sweet spot to get started is once there's at least five recruiters on the team, there's proper processes in place and the baseline of processes already exist. That baseline becomes even more important when adding in the AI layer on top, because if there's not a consistent internal workflow, then it's too early to add the AI or automation on top, because it might just lead to more confusion than benefit. And so that's usually what I recommend is that, like a baseline to get started is you know, are those workflows defined, are the processes defined, and then are we ready to automate those? And oftentimes we see that around like the five recruiter mark, though it can vary too.
Pete Newsome:So more effective if there's a certain level of maturity in the process and experience. More effective if there's a certain level of maturity in the process and experience, which makes sense. So I do my search right and I get to return profiles. Do I download them into my ATS? For the ones I want to contact? Do they stay within Juicebox? How does that process work?
David Paffenholz:Yeah, so that full process things with your ATS. So, as you've discovered those top profiles, let's say there's maybe top 50 that were matched for you and 20 of those already exist in your ATS. So we'll flag that for you and then the remaining 30 might be net new, and so you can then take the 30 net new ones, save those into your ATS as well and then reach out to all 50 of them and make sure that that data is logged there too, and so all of that data ends up living in your ATS2. So you still have that as your source of truth, while also having it available in Juicebox as you're doing new searches.
David Paffenholz:There is one additional element to the platform which I didn't mention earlier, which is the Juicebox agent. The Juicebox agent kind of works on its own and it starts doing its own searches and its own outreach without necessarily requiring you to review each profile. And the reason I'm bringing that up is because it can work in parallel with a human recruiter, where the agent goes out and does some of its work on the side and then just presents you those results along the way too. So while you say found those top 50 profiles, say the agent found an additional 10 or 20 that you might also want to consider.
Pete Newsome:Now, is that a longer process? Is that why it's an agent versus the automatic search, or what's it differentiate that for?
David Paffenholz:Yep, yeah, so it runs asynchronously. Usually it'll get you the first results after five minutes or so, but then every day it'll present you with some additional results, and so it'll send you an email saying hey, you know the search we started yesterday. Here's another batch of 30 profiles that either the agent has already reached out to or is pending a review to reach out.
Pete Newsome:Yeah, and I've noticed that that used to be a very prevalent tool in CareerBuilder and.
Pete Newsome:Monster back in their heydays. And those companies I think they've now declared bankruptcy and have been bought by someone else, which is wild. Right, because at one point each of those were the 800-pound gorilla in the space. I don't see that feature really existing anymore, what I would call an alert. Right, I want to see every resume that shows up or someone posts that's new with this specific skill set. Right, I define my criteria, whatever it is that's really powerful. I mean, is there anyone else doing that today that you know of?
David Paffenholz:Not that I directly know of.
David Paffenholz:I think the underlying reason it's now possible is because the way the instant search works is it basically matches or looks for the filtering, so this person matches the criteria or it clearly has what we're looking for.
David Paffenholz:But then what the agent does is it basically matches or looks for the filtering. So this person matches the criteria or it clearly has what we're looking for, but then what the agent does is it kind of goes out and it'll review, like tens of thousands, hundreds of thousands of additional profiles to look for potential signals or reasons they could be a good fit, and so that process. One, it takes some time and so it has to run. It's like it would be a bad user experience to have to wait for it in real time to happen. But then, two, it relies heavily on large language models similar to ChatGPT, to do that process and to take that time, and so it's really a kind of a new capability that we've had to do that in a really good way and present those profiles. And my prediction is that that's going to become more and more common again, where more platforms are going to offer that type of automation and reminder.
Pete Newsome:It's a really powerful tool to have and one that I miss. I wish my team had access to it today, and do you envision that that's something you just keep running indefinitely, if it's a position where you kind of want evergreen candidates to continue to be accessed?
David Paffenholz:That's right. Yeah, you can continue running the agent indefinitely if you need the evergreen candidates. And then the second part and this isn't live yet, but coming pretty soon is, as soon as we detect a new role or job description in your ATS, we're ready to go and launch an agent for you. And so as soon as that happens, it's already out there working and trying to find some initial candidates so that when you then start working on the role there's already a baseline that's happened for you and you can kind of hit the ground running rather than having to start from scratch. And so you know we're trying to be as proactive as possible with the agents to hopefully have that kind of user delight from the first minute that they're working on the role.
Pete Newsome:That's awesome. I love it. Where do you see the biggest time savings as a whole so far that recruiters are gaining from using Juicebox?
David Paffenholz:I think the profile review is probably the biggest one. We've set up the search. Now we have the list of profiles, but we still have to click through every single one of them. That part is where we've seen the most time used to be spent, and perhaps also the most time that the AI is able to add a lot of value in, because it can do a very similar process at a lot larger scale, and so there, I think, is where we're able to save the most hours per recruiter to this, but could you define why Juicebox is better at ranking those candidates?
Pete Newsome:The ranking systems existed in ATS for years, so is there something that Juicebox is able to do to take that to a greater level?
David Paffenholz:Yeah, so basically all platforms that have existed before 2022 used some form of machine learning or keyword predictions, essentially to rank those profiles. So how many keywords match what we're looking for, or how likely is that keyword to match what we're looking for? And then in some cases they would go a bit beyond that, but it would still be keyword based and maybe including, like similar keywords or things like that. That, for a long time, was like the best in class approach, but it's also inherently limited because you can't go further than that or like there's a pretty clearly defined ranking that you can do and there's not a ton of creativity that can go into it.
David Paffenholz:What changed in 2022 when ChatGPT launched is that we could do kind of fully language-based inferences and so we can look at the full profile, actually read the full context of these are the roles the person has worked in. This is what the company does that the person worked at, and then make a prediction of do we think they might have the skill that we're looking for? Do we think they might have experience in this role that we're looking for and that might mean that there's zero overlapping keywords or even zero similar keywords, and so they would never appear in that traditional ranking approach where it's like more similarity search based, but they would appear on a ranking powered by juice box or other large language model powered platforms. Because it's reading the full context, is truly trying to understand the profile and the requirement and then make that judgment. Could this person be a good fit?
Pete Newsome:And no one trusted those rankings previously anyway.
David Paffenholz:Yeah, they weren't good and they weren't explainable either. Right, it was like you know. Here's the word and that's why we think it's there, whereas now we can actually get a small paragraph from the AI saying you know, this profile spent four years working at this company, which seems pretty similar to the company you're recruiting for. Plus, they had a similar role.
Pete Newsome:We think they're a great fit.
David Paffenholz:That's awesome. What? What kind of feedback are you getting from the recruiters who've been using it for a while? The we've we've been fortunate to see a lot of growth in our customer base, so over 40 percent of customers have expanded their plans um to include additional team members or or kind of grow their usage even further, which has been really exciting to see. I think that's like the best way of getting validation is like do they they want to? You know, not only continue working with us, but grow their use of Juicebox too. There's also still areas we have to work on. You know, there's always limitations to what AI can do and how smart it gets and how fast it is, and so I think there's also still a lot of roadmap items that we're pretty excited about for the future.
Pete Newsome:I have no doubt about that Any, in particular that you say, hey, this is really going to be a game changer when we get there, but the technology is not quite ready.
David Paffenholz:One that we're kind of getting ready for is compensation data, so showing you person level predictions of their current compensation and then letting you filter based on that as well, and so that you can get very comprehensive but also specific compensation data on your talent pools and use that as a criteria in your searches, even for candidates that you've never interacted with previously. So that's been a really big lift, you know, one aggregating that data and then two making predictions for the cases where we don't have the data, and we think it's going to be the most accurate form that we've seen of it so far, but I don't want to make too many promises until it goes live.
Pete Newsome:No worries, I like it, we'll hold you to it, I'll get you back here and we'll talk about it. Well, what about contact info? I mean, that's always a challenge. You have sites like Indeed that won't give it to you, and LinkedIn doesn't have phone numbers. So is there a percentage you could assign to how frequently the candidate profile comes back with contact info?
David Paffenholz:Yep. So we're pretty transparent on how we do the contact info. So we essentially work with as many contact data providers as possible. We then compare them against each other for each profile, and we'll show you the one that has the highest verification rate. Because we do this at pretty massive scale, we're able to negotiate good rates with the contact data partners, and so we can do so in a way that's still economical, where it wouldn't be for each firm to get all those different contact data providers, but it does make sense for us to do it on behalf of our customers, and so that includes firms like ContactOut, RocketReach and more. In each of those cases, we'll pull the phone number and email, compare them, verify them and then show them to the user.
Pete Newsome:So that's great. So your customers get the benefits of your scale you have as a whole Makes perfect sense, because that's a constant challenge and I would expect that's a pretty common question you get asked coming in by anyone who's considering Juicebox.
David Paffenholz:Yeah, and it's also like I think it's a nice, it kind of almost makes it a no brainer on the contact data side because we can pretty confidently say like oftentimes our customers have one of those contact data providers or maybe two, and you know we can show you the list of contact data providers that we work with where we can be pretty confident that we'll get you better coverage and also that data continues to improve. So we learn from you, know any emails that may have bounced or when we know that a kind of contact data has changed and we try to dynamically update that data set as well that's great.
Pete Newsome:Um yeah, since you mentioned cost, I have to ask about that too. Are there? You know, we? We pay, we as a, as an industry, right staffing companies like mine pay way too much money, I think, to Indeed and LinkedIn, as we mentioned. It used to be CareerBuilder and Monster that continues to evolve. Job boards just eat into our profits in a major way. Do you see that as a potential savings? Do you think we still need to rely on those, even though Juicebox has efficiencies we gain? Can we gain some cost savings too?
David Paffenholz:Yeah. So, in short, yes, most of our customers find cost savings by using Juicebox. That being said, I think oftentimes the cost savings even get outweighed by the time savings and the additional productivity that comes from using Juicebox, where we're just closing more roles, placing more candidates, and the business has a better outcome because it's able to operate more efficiently. And so, while we often do provide cost savings compared to existing solutions, the benchmark we try to hold ourselves to is are we making the business operate more effectively because of our solution, and do they also see the ROI kind of on that pure basis too?
Pete Newsome:That makes sense. I'm not surprised that you answered that way. By the way, I would have loved it if you said, yes, you'll get be able to get rid of Indeed completely one day. One day. I look forward to that coming. But no, that makes sense. And that efficiency is everything right, Because it's not just in terms of internal resources and making the recruiter's lives easier. It's a competitive advantage if you can respond faster. But we know that, and that's always a balance With a company like mine. We're high touch, we are very thorough. That's one of the things we're known for. But my recruiters are constantly looking at Canada when it's a race, when it's competitive, like hey, we've got to do all these things when other companies are cutting corners. So I think you give the good guys an advantage by creating those efficiencies that the bad companies benefit from otherwise.
David Paffenholz:Yeah, it's interesting To me that's one of the most fascinating things about the recruiting industry is that it's one of the very few industries that is truly zero sum, where a candidate can only go to one company at a time and only one firm is going to be placing that candidate, and similarly for the open positions that a company has, and I think that results in these kind of very interesting competitive dynamics, which then in turn lead to some companies choosing a route of. You know, we're going to build our reputation, we're going to become long-term partners, which often is the most sustainable route, but then there's also always players that take a different route, that maybe played a bit fast and loose and get the temporary growth from that as well, and so I think that'll continue to be the case too.
Pete Newsome:And sometimes it's not even temporary, right? I mean, the world of MSPs have made, I would say put less value on quality and more on just volume and quantity, and no knock against companies who operate that way. Good for them, right? That industry exists, we know it. But if you are on the other side of that equation, you can't compete in that space, and it's one of the things I've looked for AI to potentially do for us and I've been excited about is how can we bridge that gap, right? How could we not be so disadvantaged by doing what I consider to be the right things, which everyone ultimately wants, right? But I think AI is going to close that gap a lot. So everything you're saying is a big piece of that.
David Paffenholz:Yep, yeah, and hopefully I like. The best part of the AI solutions is that the teams who adopt them kind of see themselves winning more too, because they're able to operate better and faster and keeping that bar of consistency too. So, yeah, we'll see how it plays out.
Pete Newsome:Now, before I let you go cause I'm watching the clock here I told you in advance because I'm watching the clock here, I told you in advance how long we'd talk, but that, as far as the candidate experience you mentioned, that's how you initially came to be here. Is there anything that you've been able to point to to say wow, it really is. I mean, it clearly benefit to recruiting firms and individual recruiters, but how about for the candidates themselves?
David Paffenholz:Yeah, I think the underlying thing that interests me the most is like do software solutions like ours actually help find candidates or match candidates that we're pretty certain wouldn't have been found otherwise?
David Paffenholz:And I think that's the most interesting part, even if the candidate isn't necessarily aware of that in that circumstance.
David Paffenholz:Because if we think of, like, the broader labor market even going back to what you mentioned in the beginning, of, like, um, the, the bro of labor statistics is are we helping make that entire job matching function actually be more efficient?
David Paffenholz:Are we creating more opportunities and more matches than than was possible otherwise? And so I think an individual candidate probably doesn't know that because they have no way of knowing, um, if they would have been reached out to otherwise. But on aggregate, there'll be more placements being made, there'll be more people being hired, which I think is the coolest kind of KPI behind all of this. Now, at the same time, there's also kind of more micro, individual things that I can make for a better candidate experience. That can be as simple as reminding a recruiter to respond to a candidate if we know that something has gone unanswered for, say, 24 hours, to just ensure that those best practices are easier kept because the software tries to be a little bit proactive about that too, and so we try to think about those little things to kind of encourage a good experience too.
Pete Newsome:Yeah, and those little things add up to, um, you know, making or breaking the experience as a whole. No, no doubt. And you know I have, um, you know, four kids. My youngest is, uh, is still in high school, but I have three others that are in the world of having to be involved in professional jobs and, and, and I see, through their friends and them, how difficult it is as a candidate. In addition, you know, cause I'm I'm kind of in the middle of being in staffing, but now that I'm seeing it through candidates eyes so that are so personal to me, um, I, I realized how awful it really is and I know what I'm doing. Right, I can give them good guidance, and it is a bad situation. So anything you can do to, um, to enhance that overall experience, man, it makes a big difference to the individuals out there.
David Paffenholz:Yeah, yeah, I agree, and it's also like it feels like it's clear to me that in like 10 years things will continue to get even better, but then it's also like it has to happen in the in the meantime.
Pete Newsome:Absolutely so. Anything else about juice box I didn't get to ask that you'd want to highlight because I know if what you've said and talked about before we started recording so many of my peers and staffing are looking for. You know better ways to do things and you're certainly offering that. I want to make sure we didn't miss anything obvious.
David Paffenholz:No, I think I think we covered most of it. The only thing that I'd emphasize or encourage is kind of what I tried to mention on like the you know, how do people discover AI software piece of allowing employees or team members to bring up things and test out new things, and so I think, even when evaluating a solution like ours, be that Juicebox itself or other companies in the space that would be my main word of encouragement is letting the people doing the work test it out and see what they think, and trialing that, because a lot of that software is meant to be trialed, meant to be used day to day, rather than just being, say, purchased top down and then implemented that way, and so that's the one thing I always like to encourage, because I think it ends up leading to better decisions too.
Pete Newsome:Perfect, and to that point, david, if someone wants to try Juicebox, what do they need to do next?
David Paffenholz:Just head to juiceboxai, and then you can either try it directly for free, or you can book a demo with our team, and we'd be happy to walk you through it too.
Pete Newsome:Perfect, awesome. All right, man. Well, thank you so much. I look forward to following everything Juicebox is doing. I look forward to trying it out as well, which we're going to do. I'm convinced that this is something my team absolutely needs to look at, and I'll get you on in another year and we'll see what's changed since then. Is that fair?
David Paffenholz:Sounds like a plan. Thanks so much for having me. This was fun.
Pete Newsome:Awesome. Thank you so much, David. Have a good rest of the day.
David Paffenholz:You too Bye.