Programmatic advertising is nothing more than computers instead of people making decisions about what ads to run when and for how much money. Typically, humans used to (and often still do) decide that an ad for an engineer in Dallas should run on job boards A, B, and Z from a certain date until a certain date and with a cost-per-click (CPC) of $X. With programmatic, the machines make those decisions.
Today's guest, Kenny Wright of Advantage.ai, walks us through the accidental creation of the company and explains the benefits of programmatic advertising for employers who are hiring at scale. Spoiler alert: the benefits vary, just as the needs and wants of the employers vary.
Our cohosts, Steven Rothberg of College Recruiter and Jeanette Leeds are big fans of programmatic job ad buying, especially when used by employers with high-volume hiring needs.
Learn more about your ad choices. Visit megaphone.fm/adchoices
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[00:00:13] Welcome to episode 73 of the High Volume Hiring Podcast. I am one of your two co-hosts. I'm Stephen Rothberg with College of Couture, where we believe it every student, recent grad, deserves a great career.
[00:00:25] And then it should be easy and inexpensive for employers to hire them.
[00:00:28] Jeanette, my co-host, welcome again.
[00:00:32] Welcome, thanks to Kenny for being here today. I'm Jeanette Leads and we are here with the CEO of Advantage A&K,
[00:00:41] and Kenny Wright to talk about programmatic and High Volume Hiring.
[00:00:45] So, so happy that they could have you on today's so welcome, Kenny.
[00:00:49] Thanks for having me. Glad to be here.
[00:00:51] That's what, all we kick it off with the first question around like, what's like to give our listeners the context and like,
[00:01:00] advantage AI and sort of how you got to where you are. And just we feel like that would just be a good level set for our audience. So, that's my question. Tell us, tell us, tell us your journey.
[00:01:10] So after college, I went to work for a publishing company on a Birmingham, it was kind of the infancy stages of digital marketing.
[00:01:17] And then when the iPhone come out, I launched the first iPhone out for truck drivers to find jobs. So that was my first little dive into TA.
[00:01:28] So everybody thought I was crazy. The truck drivers don't use smartphones. They'll never plot through a mobile phone.
[00:01:34] And Chris, it was a very hard sale. But so the way that all of this evolved is a developed that product and then clients wanted more, more.
[00:01:44] And then so we started to develop a few other things, which basically evolved to hire master, which is basically a dashboard with all of our efforts.
[00:01:54] And I'm one of those OCD, 80 D guys and I get super obsess over things and I said, you know, there's gotta be a better way.
[00:02:03] How can we research this and find out if this is the perfect use case? And that's what we did.
[00:02:08] It started with a partnership with Auburn University hiring some of the students bringing it in, showing these case. Look, this is what we're trying to accomplish.
[00:02:16] There's all of these different ways to get integrated with all these different job boards and different mediums from Google and Facebook. And all that kind of gets stuff. You know, as it's CPC is it's CPA is it, you know, it's it is just a lot of moving pieces.
[00:02:29] And so when we laid it all out, it just looked like the perfect scenario to build a platform from the ground up just leveraging AI.
[00:02:37] So there's just a steady evolving process over client's wanting more, more and more.
[00:02:44] So it advantage AI, it sounds to me like it sort of its roots were in helping hire master become like a better digital recruitment advertising.
[00:02:56] Right. So you were kind of like building it for yourself and then realize hey, our clients might want this too.
[00:03:04] Absolutely. There's one of those things just like it's kind of the aha moment. It was like okay we're doing all this stuff internally. Why don't we just release this and let everybody share in this and so that's what we did.
[00:03:16] And you know, it's been a long journey and it's you know, it's you can have wonderful ideas on what to build.
[00:03:22] But if you don't have the right team to build it and a good plan to execute, it's it's not going to happen. So it's like all right we got this idea.
[00:03:30] We got this use case is problem that we're solving for is they're going to work. Let's try it and invest the money and hire the team and put it all together.
[00:03:40] And it's it's going to come very well. That is not easy right to have that idea and to get it out there. I love that the inception of your beginning was truck drivers with iPhone and applying because that sort of sets that level set foundation right of like where you mind just just goes thinking about that and you don't my view is and I you know for those who saw my post something to infer this is that like programmatic and high volume hiring anything gets
[00:04:09] like they it's just it's like a match made in heaven. It is BFFs like it just works like share with us whether it's from you know, turn all before you want to the world or like just like hey this is the kind of stuff.
[00:04:24] And the outcomes that you can get because I'm sure even though it's what you're returning for there are some listeners who aren't using this sort of.
[00:04:33] Yeah, now it's awesome.
[00:04:36] Yes, so we built this product kind of to be the support for our internal stuff and when we started working with all the university hard some students from Auburn and started building this platform we're looking all the different machine learning techniques and what we need to do to
[00:04:51] how are we integrated with all the different partners and so we had no idea if it was going to work you know we've we felt like it was the perfect use case for a but we had no idea if it was going to work.
[00:05:01] But we just started seeing it with with volumes with lower CPAs with quality it's just all of it was it was was firing on all cylinders and it just gets better.
[00:05:11] And that's the beauty of AI could because every single decision that's made in the platform is purely based on performance data.
[00:05:17] It's not a gut feeling it's not a look good in this spreadsheet it is isn't getting closer to our goal or is it not if it is let's evolve this solution to a better solution if it's scratch it you know and so it constantly evolves and learn from the patterns in the data and it just gets better.
[00:05:35] So so personally putting we it worked for us and it was like all right let's let's let's let this out into the wild and then and then we we started adding more people in our team that.
[00:05:46] Like Sean quickly he was at Symphony talent recruitics.
[00:05:50] He's our our vice president product design and.
[00:05:55] Fantastic he's took what we built and then we've added more to the team and just took into the next level.
[00:06:00] Yeah, I had the good fortune to meet Sean in person years ago it was at the ad agency that that was that later became Symphony talent.
[00:06:10] And yeah when I saw that you guys had hired him it was like okay that was wicked smart.
[00:06:14] So the listeners advantage I absolutely you need truck drivers great.
[00:06:21] You need warehouse you need retail you need hospitality customer service nurses whatever it's not a truck driver only platform right.
[00:06:29] Keep on in this is when we did this we're like let's build this and a master way to where it doesn't matter what the position is.
[00:06:37] Yeah because the ML models that were using it doesn't care what job it is.
[00:06:41] It's written out what's working and what's not working so it works for all industries you're calling.
[00:06:46] Say enterprise level company you know hiring at least dozens probably hundreds thousands they come to you when they say we've got you know a thousand wrecks.
[00:06:55] These are the hundred the fifty that are like actually have bought call center warehouse logistics whatever it is walk us through how you would explain to them what is programmatic.
[00:07:08] Because none of us are born knowing that how does advantage a I use that because it's not just on one side I know you're partnering with a lot including college recruiter.
[00:07:19] Infold disclosure as federal law may or may not require.
[00:07:24] There's a partnership there.
[00:07:26] And so having programmatic is just simply the automation of things and when we went to T.A. tech out of out of Austin we realized that a lot of people were still using rules based platforms and there's nothing wrong with rules based platforms we just felt like there was a better way to do it and that's where the machine learning came in to play and because when you're looking at you know build a platform like this you've got to have your partners you got to have all the proper integrations.
[00:07:51] You have some some integrations that you don't see P.A. some on your C.P.C. and when you're looking at managing all of these C.P.C.s and C.A.s for all of these different jobs and these different locations and these different industries.
[00:08:04] We're talking about fine taning and finding patterns in the data for every location for every job.
[00:08:10] I mean that's for every source.
[00:08:12] You can't hire enough people to do that and set small to tell and so that's what we were able to do with this platform.
[00:08:19] So I mean to explain it like the whole goal of this platform is for you just to feed the jobs or even create the jobs on a platform.
[00:08:29] And so because everything is weighted every click, every interaction is weighted and it's all put into the machine learning models to figure out exactly what's working.
[00:08:39] So it's really easy use and it's like using data at its best.
[00:08:45] For a client who's coming in bringing these on if they haven't used something like this before like how much better is it like how much you know are they save it like what any any good stats to share there.
[00:08:56] I mean we've got some companies that have lowered their C.P.A. by 35 to 60%.
[00:09:02] We have some clients that we're like, okay, we won't volume them.
[00:09:06] Then we have some that we optimize to the C.P.Q.A. so it's all about quality and they're like, look, we don't want as much volume.
[00:09:12] We just want to focus on what's actually down front on this going to bring the hearts of the people.
[00:09:16] So we have different ways of optimizing you know with the platform.
[00:09:19] But yeah, once what do you get in the platform and see how easy it is to use.
[00:09:25] It's like I mean of course I'm biased but I don't see using something else but as far as the advantage of like why do you want to do this it's like, you know, you go to all these different partners and no one.
[00:09:39] And so the public are going to have all the candidates.
[00:09:44] I mean, each of the largest one on the planet right now probably has what 40 to 57% maybe indeed it does.
[00:09:52] Great job.
[00:09:54] But there's a lot of candidates that's outside of that bubble that's not been utilized and that's what's so great about all the partners that we had this because we're able to get through and say, oh, here's a campaign of these jobs.
[00:10:06] These are the best performing job boards and sources for these jobs.
[00:10:11] Let's start allocating through CPC CPA budgets, slots, however the integrations are and then let them models work.
[00:10:19] It's because it's going to learn from all the other thousands of campaigns that we're running.
[00:10:24] So day one you've got the advantage of an efficient placement of jobs but once you run, start running and then it just gets better off of what your performance is.
[00:10:33] And that is the advantage and clearly advantage.
[00:10:36] I'm loving the branding and the name like it's so good.
[00:10:39] So if the listeners didn't pick up on that, I just said it like it was very cool.
[00:10:43] We are definitely connecting the dots here.
[00:10:45] I think we have time for one one more quick question in answer.
[00:10:49] I just kind of close the loop for the listeners who might never have used programmatic who might be using it but not really feeling like it's working as well as I think it should.
[00:11:00] Maybe they don't even know how they can measure it.
[00:11:04] And it kind of like going goes back to Janette's question on a couple minutes earlier when I think of programmatic and a college recruiter we've been using it heavily for a decade.
[00:11:14] I think of it for some employers, it's about efficiency.
[00:11:19] They can save money on postings and like you mentioned like the quality aspect.
[00:11:24] Other employers it's about quantity.
[00:11:27] We need to hire a thousand people. You're never going to get enough applicants from one job posting to hire a thousand people.
[00:11:35] Do you look at it the same way both something, something different?
[00:11:39] The biggest advantage of a programmatic for like a high volume employer.
[00:11:43] A efficiency effectiveness something else.
[00:11:46] I mean, it's just a common ace for them all of those and then it really just boils down to like how is your recruiting department laid out.
[00:11:52] It's really about the candidate journey. It's like how many can they handle, do they have 20 recruiters they have four and then how we're going to do this is going to be a hybrid model to where we want to get plenty of volume but we also want to focus on quality or is it you know what we need.
[00:12:07] So what's going to happen is that you have to go out through the door. So let's get it out there and so you've got that flexibility within the platform to opt to.
[00:12:14] Do you want that $7 CPA or do you want that $24 CPA and that candidate that has everything that you need as far as quality?
[00:12:24] And those numbers can get crazy, you know, being really low to really high but because every company is different but it's kind of a hyper pressure really just depends on on the client and what they're really really looking for.
[00:12:38] Cool.
[00:12:38] There's a nice amount of money.
[00:12:41] Thanks for joining us today. This is really helpful.
[00:12:44] Thank you for having me. First year.
[00:12:46] Cheers, Janet.
[00:12:48] Until the next one.
[00:12:49] Hi everyone.
[00:12:50] Good luck to you guys.