Boon is the world’s most agile referral hiring platform, empowering organizations to tap into their entire community to source top talent faster and more affordably. With AI-driven matching, seamless integrations, and gamified incentives, Boon transforms every connection into a recruiting advantage while reducing bias and boosting diversity.
In this episode, we speak with Dakota Younger, Founder and CEO of Boon, a referral hiring platform. Dakota shares insights into the evolution of Boon, highlighting the importance of leveraging community networks for efficient hiring. He discusses the challenges and benefits of using AI in recruitment, emphasizing a balanced approach that combines AI’s data processing capabilities with human judgment. Dakota also addresses common misconceptions about referral programs, advocating for their scalability and quality when implemented effectively. The conversation touches on the future of AI, legal considerations, and the need for responsible business practices.
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Show Notes
Takeaways
- Referrals are a powerful tool for sourcing talent.
- The best talent is often passive and not actively looking for jobs.
- AI can enhance the hiring process but should not replace human judgment.
- Engagement and communication are critical for successful referral programs.
- Companies often underestimate the importance of promoting their referral programs.
- Diversity in hiring can be improved by leveraging AI to tap into broader networks.
- The hiring process can be streamlined by focusing on accessibility and ease of use.
- Measuring success in hiring involves looking at time to hire and cost per hire.
- Businesses have a responsibility to consider the societal impact of their technology.
- Referrals can be scalable and maintain quality with the right approach.
Chapters
00:00 – Introduction to Boon and Dakota Younger
02:56 – The Evolution of Referral Hiring
06:00 – Transforming the Referral Ecosystem
09:11 – The Role of AI in Hiring
11:50 – Engagement and Accessibility in Referral Programs
14:56 – The Importance of Communication in Referrals
17:49 – Measuring Success: Time and Cost of Hire
20:42 – AI: A Double-Edged Sword
24:01 – Legal and Ethical Considerations in AI
26:54 – The Future of Hiring and AI Integration
29:43 – Addressing Diversity and Inclusion in Referrals
32:46 – Myths and Misconceptions in Referral Programs
35:47 – Conclusion and Future Directions for Boon
Transcript
Beau Hamilton (00:00.75)
Hello everyone. And welcome to the SourceForge Podcast. Thank you for joining us today. I’m your host, Beau Hamilton, senior editor and multimedia producer here at SourceForge, the world’s most visited software comparison site or B2B software buyers compare and find business software solutions. Today I’m joined by Dakota Younger, founder and CEO of Boon. The company claims to be the world’s most agile referral hiring platform. And what they’ve built is, a way to turn your entire community into a hiring engine of sorts. You got employees, you got partners, vendors, alumni, they’re all part of the process to make hiring better and faster. And Dakota’s been outspoken about the psychology of why people actually make referrals in the first place. And he spent many years figuring out how to automate rewards among other things and just keep people engaged and also just make the referral program, you know, ecosystem, something companies actually want to use, which is, you know, no easy feat given.
I think many of the frustrations that AI in particular has caused around the overwhelming volume of candidates for employers and the automated responses and algorithmic scoring candidates face, there’s a lot to impact there just in that topic alone. So without further ado, let’s bring in Dakota to talk more about the company and the current state of the industry. Dakota, welcome to the podcast. Glad you could join us.
Dakota (01:19.049)
Yeah, thanks for having me, Beau. I appreciate it.
Beau Hamilton (01:21.634)
Of course. So I want to get right into it. Now. I know you’ve worked at a number of tech companies throughout the years, but actually one profession or gig that really stood out to me was your time as a standup comedian and public speaker. I mean, I know getting out there and cracking jokes, engaging with, with audiences. don’t think there’s like a better way to really understand the psychology of people better than just performing live in front of them. At what point did in your career, did you realize like you were ready to put what you’ve learned to the test and kind of create the hiring platform known as Boon.
Dakota (01:57.155)
Well, I mean, so, you’re right about the, standup piece. I mean, it’s definitely, you get, I think you learn a lot about the psychology of people, but also you get to know a lot about yourself. and so I think that that’s, you know, obviously when you’re interacting with people, like a key part of that operation. but, so I was doing, doing standup and then I started doing recruitment kind of basically as a, as a side.
Beau Hamilton (02:08.558)
Hmm.
Beau Hamilton (02:14.604)
Yeah, yeah, totally.
Dakota (02:26.195)
gig because it allowed me, was able to do it remotely. And then really early on, like honestly, within the first week of doing like recruitment, I was just really surprised at how antiquated it was. it just seemed like there had to be a better way to do a lot of things, but I obviously, I was really only at that point. Understanding that getting understanding of the problem, which is not like the hum is the full solution. So, so going through that and starting different
Beau Hamilton (02:29.454)
Hmm.
Dakota (02:56.519)
recruitment agencies and tech enabled agencies, I started to get a little bit better feel for kind of not just like what wasn’t working, which was really obvious, but what might work. And that’s where like day one, realized almost like referrals, the best people know the best people. And that seemed to be consistently a great way to source talent, even as a recruiter. And there were other benefits, not just in terms of getting connected with that great talent, but
You could place them usually faster because they were more bought in and you could engage them more, rather than reaching out cold. Like if you have a, especially a really strong talent that was heavily pursued by other recruiters, if you can get in through a referral. So doing all that, it kind of, it was a pretty organic evolution of, wonder how far we could start taking this. And then it turned into certainly like, as you’re trying to scale things, you start to implement more technology to, kind of.
automate the things that you know that all right, that can be done without a person having to do that. And then that it’s kind of combined into Sabun. So it wasn’t necessarily like, there wasn’t a specific moment where it’s like, I’m going to, this will be a tech company. It started really more as like, all right, well, let’s start using more technology as we can and see where we can go with it. And then it evolved into something where it’s like, all right, well, this actually could be, you know, a product for other people to use, but we were the really the
one’s using it first. So there’s a pretty tight feedback loop when building it.
Beau Hamilton (04:24.354)
Gotcha. Yeah. I just love hearing the inception point or like the process behind the scenes of what led to where you are now and kind of your experience and how it led to that. What was the time frame? What year roughly was this culminated, your company?
Dakota (04:45.053)
Yeah. So we started the agency side of it in 2015. And so it took about three years to kind of evolve into what would become like the full like SaaS product. Over that, we were starting to get more more referrals. So eventually we were getting more than 80 % of our placements coming from referrals from candidates. And so that’s when that was more of the light bulb moment of, of, and it was consistent. So it wasn’t just like a spike, right? It was something that we were able to
Beau Hamilton (04:56.803)
Gotcha.
Dakota (05:13.491)
to achieve pretty consistently. So we realized like, look, this is something that a lot of companies struggle with is, is most companies have a referral program. They just don’t work the way they want to. There’s a lot of like, you know, accessibility issues and awareness issues, engagement issues and, you know, communication issues, all these other things that we had. We didn’t necessarily formally. Yeah. We didn’t lay out like a roadmap initially. We didn’t know what the problems were initially. We were just kind of like identified them over time. So it was more of like.
on a, on a case by case basis. well, we’re trying to get people to use this more. What can we do? All right. Well, let’s make it so they don’t have to go find it, you know, kind of, seemed like pretty obvious stuff, but when you start building it all together, it makes it. It’s kind of like incrementally, you know, impacted until until it’s yeah. Something that we realize like.
Beau Hamilton (05:55.939)
Yeah.
Beau Hamilton (06:00.526)
I think that makes sense. mean, you got to like refine, takes time to refine your craft and figure out what your niche is and then go from there, you know? And then also just recognizing, yeah, recognizing kind of the outdated system at the time, 2015 era, 2018. And then, I mean, it’s amazing to see how much it’s changed just in the last couple of years. So I know you’ve weathered a bunch of different technological, you know, changes and then just…
Dakota (06:08.159)
100%.
Beau Hamilton (06:27.732)
societal changes with COVID happening in between, you know, now and then. Maybe you can talk to like, how would you say Boon transforms the referral program ecosystem and how does it stand out from some of the other platforms you’re competing with or maybe saw at the time?
Dakota (06:47.471)
Well, so there wasn’t a lot of platforms at the time. mean, a lot of platforms, I think we’re trying to go more of the, like marketplace approach, but the problem with the challenge, not necessarily from the challenge with that is that you have with any marketplace, you have this kind of chicken and the egg situation where, you know, how do you, need the, the companies or whatever it is, you need both sides and how do you, you need both for it to be a marketplace, but how do you get one? Cause they both need the other, right? So
So like, do you get companies? you get, do you get candidates? How do you get all that? so they, that’s the, the ones that I remember seeing at the time we’re doing that, but they weren’t doing it well. there weren’t really any that were helping with employee referrals. and so, and the ones that the, any of the ones that were, doing, again, doing more broad and kind of spray and pray approach. And so one of the things that I was really focused on initially that I was actually not even just focused, I was concerned about, like for me, for
one of the answers that questions that needed to be answered before I got really excited about Boon was can we do this? Can we scale it and still maintain the quality of, and like the essence of what a referral is? Because just doing it to make more noise, know, scaling a broken process doesn’t really help anyone. Right? So it’s like, that’s what I wanted to validate. And so we put in a number of things to help with that. One of them being,
differentiating between what we call direct and social referral so that when a company when somebody sharing a job more broadly, that’s fine, but it’s technically not a referral. It’s it’s marketing, right? Like, how a joker on tonight’s is like posting it on like, Twitter, which is like just a smidge above complete anarchy is not the same as sharing with your friend, right? And so again, not necessarily a bad thing. But if I’m getting candidates as the recruiter, I’m going to want to know where the
Beau Hamilton (08:38.796)
Yeah.
Dakota (08:43.561)
how that was generated, because it’s going to impact how I prioritize those. And so that’s something that we do is we will help differentiate and say, okay, these came from social, this came from direct. So that way they can prioritize on those direct referrals and they can even using the reward automation, they can have different incentives for direct and social or other types of things. So, but that was like the big thing for me was wanting to make sure that we could scale it in a way that, that still provided value and didn’t just create an additional stream of kind of job board type of candidates.
Beau Hamilton (09:13.304)
Yeah, well, I can see that how that would be an issue just from a, basic understanding that like when you’re dealing with referrals, you’re dealing with relationships with people and, employers. And that’s something that you need really competent people involved. So when you, have to not only, you have to search for people you want on your team. So it’s kind of like, you’re, you’re part of, you’re really experiencing part of the process you’re trying to solve in a way. but yeah, that, that just opens up a bunch of, you know, difficulties, growing,
Dakota (09:40.905)
Yeah.
Beau Hamilton (09:42.062)
Because if you don’t write people involved, yeah, it’s just harder to execute on your.
Dakota (09:45.632)
What and the best talent is going to be passive. I think that’s one of the most compelling things for me about referrals just in general is like the best talents not going to be active like they’re not on job boards and actually most of the job like job the candidate network, you know, the employment market is most of those candidates are passive, right? So like give or take it’s around 30 % are active at any point in time. So that means you have 70 % that are inactive. So the majority of of that that job market that candidate mark, whatever you want to call it.
is not actively looking and the best talent tends to be passive. Now, to be clear, I’m not saying that people on job boards are not good, obviously, right? But when you’re talking about statistically, if you want the best talent, they tend to be less frequently looking, they tend to go from one job directly to the next because they get pulled into another one, right? So if you want to engage that top talent, you have to be proactive about it. It’s just, it’s, you know, and
Beau Hamilton (10:33.453)
Right.
Beau Hamilton (10:38.222)
Totally.
Dakota (10:40.052)
Yeah. So then, that ties into also some of the issues with job boards right now. I mean, there’s always been a volume issue with job boards, but I think that’s one of the, and I’m not trying to throw a ton of shade on job boards, but I don’t know how you could argue otherwise, but like there is an issue right now with job boards and not necessarily with job boards, but more on the AI side. But I don’t know if that’s something you wanted to get into, but like that’s to me is, a, yeah. Another big part of
Beau Hamilton (11:00.938)
I definitely want to get into that. I want to first kind of continue the setting, the groundwork of, be talking about some of the technology, the underlying technology behind your platform, because I know many, many platforms just kind of stop at like maybe tracking referrals, but you’ve obviously built something more robust, I would say. How, how would you say Boon moves from basic tracking to create those like secure automated hiring pipelines?
Dakota (11:08.009)
Yeah.
Dakota (11:25.524)
So we’re big into the psychology of like what motivates people because and so won’t never short answer is it’s a multi pronged approach. I rarely found that anything can be solved with like a silver bullet. Like that’s the ideal scenario, but maybe I’m just doing it wrong. But I just rarely find that like most problems are going to solve. here’s the cause most problems are driven by multiple issues. So
You know what mean? So like there, it’s going to take other multiple issues to kind of counter that. And it doesn’t always obviously have to be one for one, but when it’s, when you’re talking about generating a successful referral program, you really have a few key components. have how accessible and easy is it to submit referrals? So sometimes we combine those, but they’re really, there there’s two separate pieces. The accessibility is like, how easy is it to get to the process? Like, do I have to like log into things? Do I have to go find it? All of that.
Nobody’s looking to be on like a national treasure type of hunt for the referral program. Secondly, then once I get there, is it, yeah, is it like a, is it a code that I have to solve or is it, know, is a long form? Is it like this DMV form that I have to fill out or is it something quick and easy? Those are going to impact stuff and like how I convert. So, right. So you have your engagement and access your, your accessibility and your ease of use. Then you have your engagement and your promotion of it. So if.
It’s got to stay top of mind for people, you know, and this is going to be anyone that’s done marketing. This is going to be like, like, like truly probably marketing one-on-one, like day one type of obvious stuff. But like, it’s funny how that doesn’t always get transferred over to other, you know, that knowledge and that understanding doesn’t get transferred over and applied to other areas. So, but if you’re not promoting that referral program, keeping it top of mind, people forget we’re all doing a trillion things every day. And a lot of times they’ll mention it during like the onboarding of an employment, right?
Well, that first week, your brain’s just like absorbing an insane amount. like normally they’ll mention it like your first day, right? Well, you forget it by lunchtime because you’re trying to remember the password to your email, all these other things, right? And so you never remember that referral program again. And even if like, even if you remember there was one, you’re not about to go ask for it. Cause you’re like, crap, they told it to me. I don’t remember now. So yeah, there’s, there’s the accessibility you use. There’s a promotion of it, keeping people engaged, motivating them, helping to incentivize them. And then there’s the tracking piece.
Dakota (13:46.954)
But even that has a few different pieces. There’s the tracking and communication of the referrals, letting people know what happens. That’s probably one of the more overlooked pieces that I see with employers is that it doesn’t take a ton of like sitting down, thinking about it to figure out, okay, we should probably make it easy to get to and promote it. Right. Those are, those are pretty, I think quick jumps that people can make, but the, the, the, the feedback.
Beau Hamilton (14:08.184)
Yeah.
Dakota (14:15.028)
I think a lot of companies make the mistake of thinking that that is an option, like a bonus. And it’s not because if people don’t know what happens when they submit that referral, I don’t know why, but the default assumption is that nothing happened, right? That it just disappeared. Neither somebody saw it and shredded it. And I’ve yet to talk to an employer that yeah, that we were like, that they’re like, all right, so here’s some of our problems. We, we incinerate every referral before they come in. We don’t even look at them like that’s I’ve yet to hear. But that’s kind of the assumption. So
Beau Hamilton (14:33.464)
hehe
Dakota (14:44.062)
you have to let people know, hey, here’s what happened to that referral. It makes them feel appreciated too. So because if they’re opening their network, it’s not just about looking good to the employer, it’s about looking good to their connections, and sometimes even more so on that end. So if they feel like that makes them look bad, or even like kind of mid, they’re not going to be into it, right? So you really need to help them feel like this is a positive experience. And that they’re that’s they’re doing something even if it doesn’t generate a hire, but there’s some sort of traction with that, that helps them to want to do it again.
Beau Hamilton (15:01.965)
Yeah.
Beau Hamilton (15:13.134)
Hmm. So, yeah. Well, no, so many, so many great points. was just going to kind of talk about like the circling back to like the ease of use and sort of lowering the learning curve or just the adoption rate or increase in adoption rate by making it easier to pick up and use. Right. Is that something that I mean, some of these points you made, is this something that you’re still noticing is prevalent in the industry that, you know, is kind of considered maybe old school? Like, like, why do you think
Dakota (15:13.984)
So when we, yeah, go ahead.
Beau Hamilton (15:42.382)
Why do you think people aren’t maybe questioning the status quo and like, what’s, what’s at risk if they start rethinking the hiring process like you were doing, if that makes sense.
Dakota (15:51.296)
I think that when it comes to the hiring process, there’s this, you want to, especially sourcing talent, I guess not even the hiring process, let’s focus on like talent acquisition. the top of the funnel, I think there’s this compulsion to want to take action yourself. it’s perceived as risky to rely on somebody else, which is fair, which that is fair to a degree.
and I think that historically referrals have been looked at as like, they’re really great, but they’re one of these things that can be fickle in terms of the volume of it. Right. And so I think sometimes we’ve, I think what’s happened is, is sometimes we, we write that off as like, that’s like the price you pay for having such a great thing is that it has to be one of those things that’s kind of like catching lightning in a bottle. Right. But that’s, that’s really not the case. Cause again, if you, if you break down, why is it not more consistent or what are the issues you see that, and that’s what, again, that’s what we did.
is like, what are the things that are making that so that it’s not more consistent or whatever. But I think that’s what causes people to maybe go for more of like job boards and because they feel like they’re taking action, they feel like they’re making an impact because they are doing something rather than when you post a job and you’re waiting for those referrals, you’re not necessarily seeing that action taking place right away. And so it can feel like nothing’s happening even
Even if it’s only, I mean, you, you might post it and you might check, refresh your inbox every 10 minutes if you’re really looking for the right role. Right. So I think that sometimes can be part of, what holds companies back from wanting to maybe push the envelope when it comes to, talent acquisition.
Beau Hamilton (17:31.746)
Now, what about in terms of the numbers when you’re working with clients? What are some of the measurable results customers are seeing? I think of time to hire, cost for hire. How do those ROIs compare? I guess two questions, really. How would those measurable results compare to maybe some of the alternative solutions out there?
Dakota (17:54.57)
Well, I mean, yeah, the conversion rates for referrals is, is, doesn’t even compare to that of job boards. And it’s actually really hard to track right now. Again, I don’t want to go too far into that other, but like right now the application to hire rate for job boards is just is going up because, and that’s not the number you want to go up. is
You don’t want those to be a lot of applications, very few hires. That’s what I mean by going up is the rate is very far. You want it to be like one to one, right? Right now there’s a lot more volume there. So you’re going to see a lot higher conversion rate and a lot lower volume, which means more time can be put per hire and vetting those, which means stronger hires, but also usually reduced time to hire means lower cost per hire time is money at the very least. Right. And so you have significant savings there and then
Beau Hamilton (18:25.155)
Gotcha.
Dakota (18:46.942)
The velocity is also really important, especially in industries where talent is really, really competitive, right? If there’s a really competitive job market, within, especially healthcare, but you know, AI, anything, anything I, you know, on the tech side can be pretty competitive, but especially in the AI sector right now, you need to be able to move extremely quickly without compromising.
the hiring process as much as possible. Like you still wanna make sure you’re making quality hires. You don’t want to just like send out offers the minute you find someone’s resume. So like if you can make those, if you can still accelerate the hiring process and make them a little bit more favor to you as the company because you got referred in, any of those edges, again, they add up on their own. Each individual one might not be a game changer, but when you stack up one, two or three of those edges, can, you
cut a week out of the hiring process, that’s a week sooner offer you have to be able to get in and before any of the other competitors are making those offers.
Beau Hamilton (19:51.692)
Now I’m glad you briefly mentioned AI, I think that’s a natural segue for my next question. And I’m actually kind of surprised we haven’t, you know, we’ve made it this far without really singling it out, but I know we did allude to it. But obviously you’re, you’re, you have to, I’m sure you’re adopting AI into your platform. I mean, I know every company is at this point, you almost have to, and it’s, I know also know AI is a lot of ways of blessing and a curse for employees and employers. know, employees are using.
AI to bolster their job resumes to the point where there’s just, I don’t know, lot of like fluff and they’re all kind of structured the same. And then employers are using AI to try and whittle down the best applicants. And then as a result, there’s just less, there’s less humans in the loop, which actually do the hiring and do the overviews and checking that’s required. So how are you using AI in a productive way that doesn’t make the hiring process worse for everyone?
Dakota (20:47.936)
So I’ll try not to get on a soapbox too long about this, but I think this is like something that anyone in talent acquisition and HR even like was like immediately like it did. It didn’t take very long for to be like, this is, this could be real bad. because again, the volume is there and there is that compulsion to want to take action. and so yeah, like what’s, what’s happening right now yet. Tons of applicants coming in from, from, from, you know, AI.
tailoring the jobs, tailoring their, their, their resumes, the, application form, all that stuff that can be auto filled with this AI. And, then like you’re saying, like the employers are applying AI. it’s just AI kind of talking to AI and there’s not a lot of review. The problem is this is a really human process, you know, obviously people hiring other people, and there’s a lot more nuance to this than, then I think we even recognize and realize a lot of people. So.
The approach that I think is the most effective in what we apply is something called augmented intelligence, is using AI for its strengths and using people for their strengths. I think we have this tendency to want to make and compare the two, which comparing is not necessarily a bad thing, but I think we can call out some pretty obvious things that the AI can do that I can and vice versa. like, let’s let…
You know, an AI being AI and the people person. let’s look at, know, the kind of analogy I use is you don’t want to make a hammer or a screwdriver. Like they both serve us a purpose and that’s fine. Like they don’t need to be the same thing. So go ahead. So what I’m saying is so like the idea there is that like, look, people are great at nuance. Okay. So let’s let the AI crunch the data like it does, right? Let’s let AI do the heavy lifting and serve that up and then let people do that final, whatever you want to call it.
Beau Hamilton (22:23.074)
Yeah, well, sorry, go ahead. No, go ahead.
Dakota (22:40.576)
10 % box. mean, that last bit, that last bit volume wise may not seem significant, but it’s it is key. And like the analogy that I’ve used in the past that I think kind of helps to explain this really clearly. This kind of this logic is there was this this chess champion. I really need to get his name. But he played Watson the IBM computer, right? He was his grandmaster and Watson beat him and he was really upset about it at first. Understandably.
Then he teamed up with Watson. He decided, all right, well actually rather than getting Benashe about this, what if I worked with Watson? I wonder what we could do together. So he played a bunch of other grandmasters all at the same time. I it was like 30 something. And I think he’d be all of them or most of them, but basically playing them in a line, right? And he was able to do that though because Watson would queue up like the best three moves of that game, right? And then he…
the chess champion would choose which one to move. so neither of them could have done that independently and probably had the same results, right? Because that was the choice of which of those three moves was critical to winning those games, right? But being able to process that much data for that many games sequentially like that isn’t gonna work either, right? For for an average person. So by leveraging them for their strengths and focusing on that, you get a superior result than either of them could do on their own. And I think that kind of like highlights
how I think AI can be used when it comes to hiring and making sure that there’s a lot more efficiency, truly like ultimately efficiency, but then supervision and making sure that we’re not just having AI talk to AI. yes, cause scaling, like I mentioned, scaling a broken process or a bad process doesn’t do anyone good. And I think that’s what’s happening right now is it, it’s a classic scenario of like that we’ve done internally on accident, you know.
you get excited about being able to automate something and you don’t really stop to think, but do we really feel like what we’re automating here is the best approach?
Beau Hamilton (24:43.96)
Gotcha. Yeah. Is that Gary Kasparov? that sound right? Yeah. Okay. Cool. We’re, we’re doing some live fact checking here. no, that, Yeah. I’m just pulling this out of my hat. okay. So no, that’s, those are, those are great points. think that like the optimistic one way of, one optimistic kind of outcome, I think with, with utilizing AI that I’ve heard, obviously you, mentioned, for a number of different.
Dakota (24:46.526)
Yeah, yeah, that’s who it is. That is Gary Gasparov, absolutely. Yeah. You’re like, he was a bowling champion, nothing to with you.
Beau Hamilton (25:13.742)
platforms and whatnot is just the efficiency gain. So like if you’re using AI to kind of maybe filter out certain applicants and just apply it, like even at the most minimal filter, you’re still kind of freeing up the time and resources for maybe a human to have more time to look at the right candidates, right? Is that like one of the many, I mean, upsides, I suppose.
Dakota (25:34.72)
Yeah, well, yeah, so that’s correct. Yeah. So, but yes, exactly. but I think, yes. So then not to get too far in the weeds here, but like, think, yes, but in theory, and so that’s where I think queuing up and letting people though, I, if somebody told me that they have the perfect AI for doing that, for, for generating recommendations, I would say my, my reaction would be okay. But now give me 10 % less, less, less good. And you might think, well, why?
because I there’s, there’s, there’s what we know. And then there’s what we don’t know that we don’t know. Right. And there’s so what we know. And then we know we don’t know. And then there’s what we, there’s the part that we don’t know that we don’t know. And that’s the part that I find that is where there’s the most danger, but also the most opportunity for, for gains usually. And so by adding that, that additional layer of variability that doesn’t fit what we exactly, what we have, what we think we know now, because that’s based on the information we have at present.
By adding that variability there, you, think it doesn’t drag down the performance of, whatever the system in, but it allows for people that may not otherwise fit into it. The perfect criteria or whatever, the, the, the filtering that’s being done still to be able to get in that might still be actually a really great fit. just don’t perfectly fit because even again, how was that outline created? How were those requirements created? Probably using AI as well.
So, or at least with the assistance of AI. then again, like you had looking at how all that’s done and how that structure from the ground up, if it’s a lot of AI building it, it doesn’t necessarily make it bad, but it creates the potential for people not paying attention as much to those details. then assumptions being built on those assumptions on assumptions. And next thing you know, it’s, it’s a lot of artificial. So again, that’s where I think having some supervision of people, whether it’s queuing up with recommendations, you’re.
you have a lot lower volume when it comes to referrals as well.
Beau Hamilton (27:32.12)
think that’s a really good point. Yeah. And I think it makes me think of the flip side of the scenario where you look at. So obviously AI is trained on all sorts of different data and a lot of the data that it gets, you I think you can make the argument that it kind of reinforces a lot of maybe societal biases, which are unwanted and you want to filter out in the job hiring process. And one of the key kind of acronyms that is politically charged, it’s, you know, it’s the
diversity, equity, inclusion, DEI. It’s an important at its roots. It’s whether, know, ignoring the contention around it, I suppose. It’s a really important part of the hiring process. And I’m curious, like if you’re using AI, how do you kind of integrate these important aspects into the hiring process?
Dakota (28:20.928)
Yeah.
Well, let’s call it out though. Like if there’s an issue with referrals, because everything has, most everything has like a side effect or a drawback, right? And so having them isn’t bad. I mean, when you’re taking medicine that gets you better, right? There’s going to be side effects and it’s like, all right, well, is the risk versus the reward? Is the cost worth the benefit? That kind of thing. So on really any metric you look at, referrals will outperform other talent. But if there’s going to be an issue with referrals, it’s that they can be homogenous.
Beau Hamilton (28:32.003)
Mm-hmm.
Dakota (28:52.724)
Right. They can be closed network and that would be what I would call it. that’s that that is outside of the quality. That was my second. That is my second biggest concern with referrals is that you don’t want to, you don’t want to limit that, that variability. You don’t want to create closed networks, good old boys clubs that only allow certain people that specifically feed match your perspective. Right. Even as an organization, you want different perspectives and opinions. That’s how good ideas are. So to, to help with that.
What we found is that a lot of companies will find, Hey, when we’re asking our employees, there’s a point where they stop providing new candidates and they start going back to the same candidates. And we’ve tapped out their network. That’s they’re not wrong, but they’re not right. What they mean is they have tapped out the people that we can think of off the top of our head. we’re using, when we’re, when somebody asks us real quick, Hey, do you know a great sales?
engineer or whatever, you know, sales executive, they’re, they’re using the short-term memory, which, it doesn’t hold a lot of information. So when you’re using, and when you’re using your short-term memory, you’re obviously pulling from people you’ve recently interacted with. Well, those tend to be people like yourself. That’s how people tend to work is interacting with people that have common traits to them. and that doesn’t necessarily mean physically, but, but point is, is there going to be some more similar to you? So.
From my end, if somebody were to ask me statistically, I am more likely to come up with Caucasian males. That isn’t a filter factor that I’m actively applying, but it is ultimately going to probably be showing up in the data somewhere. Now, does that mean I’m unbiasedly racist? I don’t believe so. I think that that would be just because of this, what I call proximity bias. So what we can do is leveraging AI. That’s where I think AI helps to really have an impact is
Beau Hamilton (30:39.118)
Mm-hmm.
Dakota (30:46.368)
We use AI to help tap into the full network, right? So if you have, let’s say the average person, let’s say 5,000 contacts or something, right? They’re using maybe when they’re using their short-term memory, like one or 2 % of their network off the top of their head, right? There’s a huge portion of that network. So imagine just those numbers with 50 people, right? 1 % of 5,000 for 50 people versus let’s say 98 % of 5,000 across 50 people. Like that’s a dramatically larger number that you’re being able to tap into.
And it gives people then that you might not have thought of off the top of your head as a good fit, but you’re like, actually, yeah, that guy is great. I haven’t talked to him forever. I, know, maybe you worked at, you were in an accelerator with them a few years ago, or maybe, you know, it was at a mixture or something like that. you’re like, my goodness, that guy was, that was, that person was super interesting. Of course you wouldn’t have thought of them because again, you got everything else going on. And so that’s what, what, one of the ways we’re leveraging AI actively in the product and we’ve been using it for a while is, is to help.
leverage our networks more effectively. And again, tap into both AI’s ability to crunch and leverage all that data, but then people’s ability to determine that referral. Cause we’ve also gotten people saying, well, why not just have the AI recommended to the company? And it’s like, well, you’re kind of, you’re missing the point there then because then AI now, now we’ve lost the augmented element of it and we’re just relying on AI and that last 10 % is critical for the quality.
Beau Hamilton (32:08.045)
Right. No, that’s great point. And I’m glad that you’re super aware of it. And I think just translating that awareness into your product and making sure everybody is kind of aware of some of the areas to watch out for, I think that will translate into a positive kind of user experience. And that kind of gets to my next question really is just how do you, and I think it’s gonna be my last AI question, but it’s how do you balance that like,
some of the advanced automations that you’re using, maybe some of the AI functionality with that user friendliness aspect. Like how do you kind of foster maybe like foster the relationships with people who might be a little weary of some of these automations.
Dakota (32:53.952)
Well, so one thing we do is we, what’s the term I’m looking for is modular. We take a modular approach with the AI. So customers can choose whether they want to activate AI on the account and those recommendations and other components of AI. any even new AI that we’re looking at putting in, whether it’s providing agents for helping with leveraging different functionalities.
All of that, we’re still taking a very modular approach so that because we have customers that are in the security industry, right? That work with the government and, and, whatever, you know, government. So you have all these different requirements and every company is a little bit different. And so you don’t want to have a kind of a one size fits all. You want them to be able to say, okay, well, you know, maybe they’re still working through what they’re even their AI strategy is. That’s a lot of our customers right now. They’re not necessarily, they are weary of it, but, but it’s not like.
They’re not like spooked of technology. just want to. I think that’s honestly, I think that’s a smart approach is being mindful of what you’re doing, especially when it comes to hiring. Don’t just slap a bunch of technology, especially automation and hope that it, it crossed your fingers. Right? So when it comes to that, say, okay, if you’re still working on this, we don’t have to do this AI right now. We can pause this, wait till you guys vet this out.
Beau Hamilton (34:02.702)
Totally.
Dakota (34:10.398)
And then you can check. And that’s the other thing is maybe they test it out and they find that that’s not for them. We haven’t had anyone have that experience yet, but if that’s the case, we can also say, okay, well actually let’s pull that back then. Right. so I think that’s, that’s a good part of it.
Beau Hamilton (34:21.913)
It’s amazing to think of how many companies out there are, like, obviously every company, no matter the industry, seems like you’re going to be thinking about AI, being mindful of how to integrate it. But at the same time, there’s this huge bull run of AI advancements and feature drops that are using it. But it’s just how many companies out there are just still kind of in that stage of…
just considering how the best way to approach it. Because obviously you don’t want to rush something out that’s not ready and then upset your user base and your customers. We’re already kind of jaded with the whole process and sick of the term. It opens up a larger conversation. But I do want to ask, and I do apologize because I think this is going to be another AI question, but what’s next on the roadmap for…
for Boon, do you have any upcoming innovations maybe in AI, but also in engagement or analytics that you’re particularly excited about?
Dakota (35:24.478)
Yeah. So for this is one of the things that I think is really exciting about AI is, is, and I think that again, because it’s interacting with people, like this is where I feel like there’s, there’s lower risk, but not no risk. Let’s be clear. Like we still should keep, like we’re packaging AI with analytics, like, you know, almost on a two for one scale right now, like when we’re implementing this, cause we want to be able to see this from, from every angle. and again, kind of try to cover.
stuff that we don’t even know we don’t know. even if we’re like, we’re not sure where that will be relevant, still applying analytics so we can pull information from that. But one of the areas that we have is help agentifying or gentifying or whatever, I forget the exact term, but creating agents for onboarding and activation, right? So we…
The product has a lot of power, but we also recognize that people are very busy and we want to help give them greater access to the product in a way that matches their train of thought and where they’re at. So we’re really big on the whole product is coming to the user, both almost physically and or digitally, right? Like having product that can come to the individual and meet them where they are, whether it’s in Slack or Teams or their existing, you know,
workflows, but also coming to them where, their heads at. if their priorities are, are this. All right, let’s adjust the flow so that that, that, that’s, that’s, as long as it, as long as it doesn’t break something in terms of like, Hey, like if they wanted to create a reward without creating an account, well, we got to create an account to sign the rewards to, but you know, as long as that, that can be flexible, then that helps them to be able to kind of follow one and choose their own adventure. And that’s, think where I really.
we’re pushing the product to be able to work with people in that way and feel more conversational and feel more intuitive and tailored for them. So that not only does that create a thing, a more intuitive and lower cognitive load for people, which isn’t to say they can’t think that through. It just makes it easier for people. It’s essentially a nice way to say that. But also then you’re more confident in what you’re creating.
Dakota (37:40.99)
Right? When you’re understanding every little piece and then you’re not feeling like it’s flying over your head, when you’re like, all right, yeah, totally understand what that means. Okay, got it. Like what, at the end result, you don’t feel as shaky versus when you’re just throwing ingredients in and you’re like, I think that is right, right? Especially if you’re going to roll it across the entire organization.
Beau Hamilton (37:59.382)
Now, I think the safe answer, the default answer is AI is going to play a big role in the foreseeable future. I it’s hard to predict how it’s going to shake out even the next few months. But I do want to ask if there’s an emerging trend that you’re particularly watching outside of AI that will impact the industry. I know you mentioned the agentic capabilities and then this modular approach where you’re able to integrate it select areas for select industries.
But is there maybe a emerging trend that you’re watching? Again, it’s probably just AI and how it’s going to continue to evolve and make a splash. But anything else that comes to mind?
Dakota (38:40.81)
Well, like, again, for me, where I’m curious to see is, is one of the, the thing, and this doesn’t necessarily apply to hiring, but just in general is, like the legal, I’m curious how that will pan out because Sam Olmans pointed out something really interesting that like, there is no legal protection against, like whatever you share with, with GPT or, or caught or any of those things right now. And, not that anyone’s doing necessarily anything shady, but I think from a privacy perspective.
like the fact that, that somebody could just say, Hey, we want to see that information. Like we, there should be some sort of, I think deeper protections on that. And so that’s, I’m hoping that that becomes a greater talking point for, for us, because think about how much data is being given. And I think that with those conversations though, the cool thing that will come from that is because an initial reflex might be like, well, we don’t want to, you know, maybe people don’t aren’t keen to provide a ton of protection because they want to.
The idea though is when in order to create a rules like that, you’re going to have to think about it from a reverse engineering as well as like, where are the parameters? How are we going to track and manage and monitor? And so in order to apply those kinds of legal structures, you have to also build an infrastructure for it to kind of connect to. And I think that will hopefully help to create more guidance and more, you know, structure for how we’re going to monitor AI and how we’re going to access and tap into it. So I think that will actually have like kind of, it’ll cut both ways, both giving, you know, greater.
privacy and protection from a legal perspective for individuals, also maybe providing more accountability for those that are creating AI, hopefully.
Beau Hamilton (40:17.73)
Yeah, the legal issues and the lack of regulation currently is something that definitely is fascinating because there really are no, obviously, federal regulations around AI. It’s kind of a wild west. You have the Patchwork frameworks from California recently and some other states here and there. I think that, yeah, as this technology continues to impact the world, think the regulation will come.
so from business standpoint, yeah, you’ve to stay aware of it, right? And then not to date this podcast, but I mean, you have the like Sora too, just rolling out, yesterday, we were able to kind of deep fake your friends and, really whomever. and the, think that you’re seeing these, these features rolled out based off the capabilities we have, but without necessarily factoring the societal effects, which is not really the job of a business.
Dakota (41:11.732)
Well, but but not to go off on something but I do think that we like, this is where I’m sure there’s gonna people that don’t agree with this part. But like, I think as a business, we do have responsibilities to, like, to to to people in general, not just with our with what we’re doing as a product, but how we’re operating, it kind of sets a precedent. And and so yeah, like, it’s not our job to play sheriff or play lawman but but
Beau Hamilton (41:15.118)
Mm-hmm.
Dakota (41:40.256)
Just like as an individual, you’re responsible for your behavior and kind of how that reflects and how that speaks to your community and all that stuff. I don’t know why all of a sudden, like, you know, companies get, they get a pass on a lot of this stuff. I don’t think that that’s how should be. In fact, I think it should be held more accountable because it is a group of people. So I do think when we’re doing this, we, since we’re basically representing a large group of people, I mean, you would expect even with like, you know, like a, like a hobby group or, know,
Like they’re responsible for their behavior and how that reflects. But as a company, apparently when you’re making money and then it makes it a freebie. So I do think that we have to be mindful of what we’re doing and how we’re applying it and how that again impacts our employees, impacts our customers and be mindful of that. So when it comes to the trends, I do think that one of the things that will hopefully start picking up is validation of ways of authenticating information.
across the board, whether that’s, you know, like you said with videos, whether it’s with, you know, and that’s again, where I think referrals and stuff come in where you have some sort of validation, both official and, kind of through processes, which is really kind of with referrals, that may not be an official validation of, of like a, it’s gone through a screening process per se, but, there is a, a community, there is an individual type of validation that you get with referrals that are kind of baked into that process. That’s where I think that we’ll start to see an increasing
favoring is because, because everything will become increasingly less reliable from the sense of there’s a lot of opportunity to, to, create inaccurate information at scale, right? Then the, we favoring our, start looking for ways to be able to see stamps of approval or validation will become an increasing point of interest in a, in a sign of quality that we can rely on, you know, so that it’s, it’s not just a bunch of bad data, whether that’s news, whether that’s
talent, whatever it is.
Beau Hamilton (43:38.316)
Well, I respect that approach. Yeah. I think you definitely got to be mindful of the effects your product has on the people around you and society. mean, I think that there’s kind of that disillusioned right of between, you know, your immediate sort of circle and then the society at large. But when you start just stepping out one step at a time, think it’s, I don’t know. I think that people need to see if, like, for example, the Sora 2
deep fakes, if it affects my friends and my family negatively, just for some of the stuff I were to create and share with them on a personal level maybe or a local level, then you can just see the ramifications on a bigger scale. and I think when you’re working with, for Boon’s standpoint or for so many of the other companies we’ve talked to, they’re global and they affect so many people. And so yeah, you have to be mindful of how you’re…
the technology you incorporate and how it’s going to impact the world. I, yeah, I love that. and I have one more final question for you before we wrap it up. and it comes down to the myths in your industry. And I’m just curious, like what, what common, if there’s a common misconception about referral programs or your industry that you’d like to clear up and get straight, there’s anything that comes to mind.
Dakota (44:39.104)
for sure.
Dakota (44:59.968)
Yeah, the first one, like we kind of touched on it before, but I don’t think it could be talked about too much is that referrals don’t have to be clunky and cumbersome, right? Like it, they, they might have historically been that way, but it doesn’t mean that, that, that has to be the cost that you pay because they’re great. Um, they can be scalable and maintain quality. Um, so any company that has a referral program or maybe have been a part of a program and didn’t have the same success.
That doesn’t mean that you can’t now. It likely means the things you were running into, one or more of the issues we’ve already talked about, the accessibility in these use, right? The promotion of the referral program and how people are able to keep a top mind and the tracking and all that stuff is going to be critical. So if any of those things aren’t there or aren’t there well, it will impact how the referral program performs. So that’s one. The other piece I think that is important to talk about is that,
Well, like when it comes to referrals, obviously again, they don’t have to be a good old boys club. They can, if you’re using technology to open up and better tap into people’s networks, there’s a lot more opportunity to be able to tap into them and still tap into a broad network. So if you feel like you’ve tapped into your, you you’ve tapped out your employees networks, we get feedback constantly from customers. Like we thought we had, you know, tapped out our network and we were finding people down the street. I think that’s a big part.
to consider as well. then when it comes to launching that kind of ties into the accessibility piece, like it doesn’t launching these things. think sometimes with stigmas, they’re ATSs, HRSs can be a real pain to implement. And that’s not because they’re bad tools. That’s just because they’re, they cover a lot of processes. To tools like, yeah. So sorry. just, tools like, like.
Beau Hamilton (46:49.688)
So many great takeaways. Yeah. Yeah. I’m sure, I’m sure there’s a bunch more. Yeah.
Dakota (46:55.316)
Yeah. Talent acquisition tools are not as big of a deal. they’re a lot easier to fit into that, to that structure or that framework.
Beau Hamilton (47:01.656)
Gotcha.
Well, I hope some of the industry leaders are taking notes and some of the hiring agents, managers and whatnot are listening right now are taking notes because a lot of great takeaways. I appreciate all the insights you’ve shared with us. Honestly, it’s been one of my favorite conversations in quite some time. So I really appreciate sharing everything you have. there’s, for those interested in learning more about Boon and maybe getting in touch with you and your team, where’s the best place to go?
Dakota (47:31.678)
Yeah, go boon.co is our website. So check that out. You can obviously find us in Slack and in the team stores as well. yeah, go there and check it out.
Beau Hamilton (47:42.872)
Go boon.co. All right. Well, that’s Dakota Younger, founder and CEO of Boon. Thank you again for everything you shared. We appreciate it.
Dakota (47:49.598)
Yeah, thanks, Beau. Have a great day. See you.
Beau Hamilton (47:52.75)
Thank you all for listening to the SourceForge Podcast. I’m your host, Beau Hamilton. Make sure to subscribe to stay up to date with all of our upcoming D2B software related podcasts. I will talk to you in the next one.