Unleashing the Power of Data with Radancy

Speaker A: In this digital first world, the old ways of recruiting are becoming obsolete.

Speaker B: Or are they?

Speaker A: The talent demands on every business has put TA squarely in the hot seat. Welcome to Talent Acquisition in the Trenches, a real dialogue podcast with talent acquisition pros closest to the front line. We want to talk to our peers who are actually doing the heavy lifting day in and day out. You're going to learn what their biggest challenges are and how they're being solved. I'm your host, Matt Reimer, and I'm

Speaker B: here to talk about TA.

Speaker A: I've been in TA for over 20 years, and what I know is that I don't know. I'm here to listen and learn, just like you. No scripts, just real dialogue. My friends call me Rhymer. So, friends, let's create some new riffs with Rhymer.

Speaker B: All right, let's, uh, trench in. So, uh, thanks, uh, for, uh, all of the folks that have joined us today for this live session and live recording, uh, of TA in the Trenches. I'm your host, Matt Reimer, uh, co founder and COO at a company called Rogue Hire, and, uh, also have the, uh, honor and privilege to, uh, be able to, uh, host this podcast. And so today, uh, on this live episode, and Ryan's going to talk a little bit more, uh, here in a second about, uh, some of our learning objectives we're tackling and continue to tackle, really one of the biggest challenges in our field, which is unleashing the power of data AI and then really advanced automation. Right. And so what we're trying to do here is to move, um, the conversation beyond just the vanity metrics that we all know and love and kind of get involved in some, uh, deeper, more complex, uh, ideas. Uh, and so we have, uh, today, uh, really the perfect guide for a data driven conversation. Our guest today is Ashley o'. Connor. She is the SVP of accounts and strategic partnerships at Radiancy, uh, who they leverage, uh, uh, agentic AI to offer really a whole host of solutions from, uh, EVP work to, uh, career sites to Programmatic, so on and so forth. Excuse me, Ashley. Um, in addition to her current role, uh, she founded a company by the name of Brazen. And she reminded me here, uh, before that we had met, uh, years ago, uh, as she was part of the founding team as they were working to scale and really bring that product, uh, to market.

Speaker C: So we.

Speaker B: So she has, uh, over 15 years of leadership experience in SAS and so we're super, uh, excited to have her here, uh, today on the show. Uh, one of the things that I'm really uh, interested in learning more about is uh, geo. Right. And so that's uh, Generative Engine Optimization. Right. And really I think uh, trying to understand what that means uh, for the candidate uh, experience. And so Ashley, it's great to have you on the show here today.

Speaker D: So glad to be here. Thanks Matt. Good to see you both. And Ryan, happy to be here.

Speaker B: Ryan is our uh, gracious co host here uh for these live episodes. Uh, and he uh, is here at uh, Rogue Hire, uh, working along the team and really focused on helping healthcare orgs, uh, ignite the top of the funnel with his deep expertise and candidate experience, employer, brand and uh, programmatic marketing as well. And so Ryan, what are we hoping to get into and learn uh here today on this live episode?

Speaker C: Yeah, thanks Matt. So glad to have Ashley and Raidency here. So yeah, you hit the nail on the head. We plan to kind of explore the topic of uh, Generative Engine Optimization or geo, which to me is really the idea of sweet talking the AI models into mentioning your brand when people ask for questions. So uh, GEO is uh, beyond kind of traditional SEO that ensures your career, site content, storytelling, job postings are all structured to be discovered and surfaced by AI powered search engines like the ChatGPT, Gemini, Perplexity. Uh, so we're seeing over the last six months natural language search and AI summaries have surged, uh, so incredibly this increasingly is steering candidates to jobs before they even reach a company's career site. So excited to dive more into this today.

Speaker B: Let's just pick up and get right to it. And so I guess Ashley, when you hear this, right, um, and again I know this is something that we were talking a lot about, uh, is this uh, a threat? Is this an opportunity? What is this uh, for uh, us and in health care. And I guess like when, when you think about it, um, you know, you're talking a lot about the impact to the candidates. So I would love to kind of get maybe the conversation started there and we can kind of work our way out.

Speaker D: Yeah, happy to. I mean I'm sure everyone on this call who's joined is thinking about AI, has been asked by their leader, you know, where are we automating? Where are we leveraging AI to build team efficiency? I think so much of the conversation has been around post application workflows and AI screening and scheduling, team efficiency in general. I think what, I wouldn't call this a threat as a, uh, so much as an opportunity. I think AI is going to touch every aspect of what we do. Both personally and professionally. We know that that's nothing new to everyone, but I think this piece of it has not gotten as much attention as kind of the in the weeds post application kind of time to process workflow. Thinking more about what is AI from like a time to source look like, like, how are we using AI to better attract talent? And really Geo is essentially, you know, SEO used to be the name of the game for how your career site has visibility on Google and how you have your job schema, uh, set up correctly. So Google pulls those in and Google for jobs, it's just a new dynamic now. We now have this concept of how our language models, how are AI search engines so things like Google AI summaries or ChatGPT, when you ask it what's it like to work at Rogue Hire, how is it summarizing the information it finds and what's the sentiment of that summary and are you as a business part of that narrative or not? And that's basically what it is. So I would always recommend everyone ask some of those questions, see where you are, kind of do a geo, uh, audit, if you will. I don't think you need to be an expert in Geo, frankly, I don't think anyone is today. It's moving very quickly. But you need to know what it is and you need to be able to have a conversation both around the power of AI as it relates to your time to process what workflow as well as how is AI infused in your attraction strategy.

Speaker B: So, uh, let's, let's maybe go a little bit deeper here, right? And so, you know, I think, you know, what I'm hearing is like, hey, you know, the reality is, is whether it's chatgpt or a piece of technology like Perplexity or list it, right? Um, you know, I'm going in there instead of Google to ask questions, right, and have things answered. And so I guess, you know, the, the first place it seems that you went was, uh, in and around this idea of like, you know, what's it like, right? And so like, what's the culture like? Um, do you believe that, you know, it's important to optimize or can you optimize for jobs? Like, I would imagine if they're asking what the culture's like, it's like, what jobs are open at Rogue Hire or I want to work at Rogue Hire, click. And then it produces, in theory, right, the jobs that, you know. And so is it that sophisticated or these learning models, um, develop, will they start to pull in, you know, what's on. Indeed. Or what's publicly available into their analysis. Can you, can you unpack that a little bit for us so that we can, can understand? Because I, I feel like anybody that's been interested in this has been always like, you know, taught that like SEO optimization is important and we have to optimize our search engines and so can we optimize our generative engines? I guess is like is a more broad question.

Speaker D: You can uh, the level of influence you have on the speed of that optimization has changed and some of the technical aspects for how you optimize it has also changed. So as a very granular example to like get in the weeds, which I don't imagine, uh, many people that are TA leaders are SEO experts and by nature, by design. So again you don't have to be a geo expert but things like backlinks, you know, making sure like oh, these 20 sites are also linking to rogue higher, that's going to give us authority on Google and Google is going to say we're the number one destination you should look at when someone types in healthcare data benchmarks. That type of backlinking strategy is no longer applicable in a geo world. So that's just one example of there's differences, there's are some things that will change. But in general, yes, you can influence and you can influence based on are you answering the question with expertise, with authority and with a balanced approach to it. So you'll ask, you know, go to Google, ask that question, look at the sites they're citing. Oftentimes it's Reddit. You know what, Reddit used to be kind of a third party source. You know, maybe we play there a little bit. But they're now scraping all of that Reddit content to produce an AI summaries. Indeed, Glassdoor reviews. But again it's really not that. How can we make sure that no third party content is influencing the narrative? That's a losing game. It's how can we make sure we're still part of the conversation and that yes, these other third party sites have content. AI search engines are going to look at that content. But are we also part of the conversation and sharing our own perspective on this as a business? Does that answer your question? I want to make sure.

Speaker B: No, no, no, it definitely does. And I think there's like a couple of interesting uh, paths that we could go down here. But I guess Ryan, I'm going to get you involved in the conversation. Like are you from your vantage point, um, as you're out and about, like Are you seeing organizations um, you know, maybe more aggressively invest in a ah, GEO strategy or is it too early on and this is just like nice conversation that we're having here today on a Thursday afternoon without coding, without coughing.

Speaker C: Organizations are starting to think about it, right? But uh, to Ashley's point, they, they may not know, you know, even where to start. I think one of the points, important things to look uh, at is the opportunity lies in converting kind of our uh, generic company statements, employer brand statements into more structure, structured citable fact sets that answer specific AI questions, right? Like what are the tuition reimbursement limits but also the opportunity to differentiate, right? If everyone has kind of the same generic, you know we have great culture, um, you know we have great pto, but don't back it with, with more factual um, things or, or, or, or synthesize that into something more, more structured or, or storytelling. They're going to be left behind in those answers like Ashley mentioned are going to come from third party sites, whether that's Reddit or maybe Glassdoor Reviews or indeed. So the opportunity here is really to kind of empower our own content or influence it if you will, I guess.

Speaker B: Um, you know, uh, Ashley, when you think about this, is there um, like, like so what? Right? And so that's kind of where I want to go is like sorry, this is cool, but so what? And so like is there early mover advantages here? Right? Like and so like if I'm listening to this podcast I was like all right, so what, like what should I do about it? Right? Should I do what Ryan is suggesting which is to you know, think about the content that I do have control over, get more specific, get more detailed. Um, is that an early mover advantage or. Right? Is this kind of like one of those things? Well like let's just like kind of like wait and see what happens and, and see where I need to invest my limited time, budget and energy.

Speaker D: Yeah, I think there definitely is an early adopter advantage here. What I pay attention to is one of the data points to look at is what percent of traffic to your career site today is coming from AI search engines and language models.

Speaker A: Mhm.

Speaker D: If you looked at that it's a small percent but if you looked at the trend line it's pretty amazing. So in the raidency career site Network it's up 500% year over year. So you, that just says the pace of which this is becoming more prominent is rapidly evolving. And if you build the content today that language models are looking at the other Piece of this is, you know, Google, I think there was like a, they peeled back some layers on their SEO in general they do look at um, quality of that content. So when people come there, is there a high bounce rate? Are they clicking um and leaving showing like it's a low quality source. So the sooner your content is in place, that's answering these questions, that has higher, higher engagement on that page, you're optimizing that based on the traffic that you're seeing, then yeah, your authority of that page is going to increase. And likely language models, we don't know for sure, a lot of this is like very quickly evolving but language models will likely use similar type of quality metrics of people when we this answer and when people click here, we know it's quality because of the engagement on that page.

Speaker B: Mhm.

Speaker D: So to me it's like I don't think we can ignore, you know, think about it. In the healthcare world, Gen Z is almost 30. They're your experienced clinical talent. 70% of Gen Z is using ChatGPT on a weekly basis. Not to mention like how AI is being fused in clinical care. So to not think your candidates are using language models to, in their personal life, let alone in their, you know, career journey, like I think that that is a question we don't need to answer. We know that's true. So how do you want to adapt to that to make sure that your career site, your brand is ready for that kind of journey? It's a new journey of candidates today.

Speaker B: We were talking a little bit about this just in prep and I think this is maybe a good spot to dig into this a little bit. But you know, when we talk about AI and talent acquisition right now we talk a lot about it from the recruiter's Persona, which there's a ton of um, really cool opportunities I think to give the recruiters the next generation of tools that really um, enable them to um, stay focused on what they do best, which is engage humans. Right. And so you know, whether that's from you know, things like the intake or you know, the hiring manager updates or you list them. Right. Like wherever there's opportunity to use these language models to help move along communication, um, it's ripe not only at the recruiter seat, it's ripe for the TA leaders, it's ripe for the sourcers and you go down the list. Right. But you had, you had said like hey, the candidates behavior, right. Um, you know, you believe and your data is suggesting it. Your site Traffic housewives up 500% from GEO, right over some period of time. So that sounds like a lot. So I'm assuming that's at least substantive, you know, in, in your, in your data set. How else will the candidates, right when we think about that Persona, how else will that Persona, um, you know, from Radiancy's point of view or your point of view begin to use AI in their search beyond just you know, asking um, chatgpt or Perplexity a question about the brand.

Speaker D: Mm, that's a great question. I think we have to, and I'd love your opinion on this too. I think we have to kind of look at what's the commercial side doing. So two things come to mind. I think it was Amazon early this week on a call said that they expect their, you know, Rufus personal shopping assistant to add 10 billion in revenue in sales. So that kind of personalization, not just like a chatbot. I think that's kind of a tactical way of calling this. We take all the content from the site and we're really having this like conversational complete end to end navigational experience with the end result of like the E Commerce conversion, like you've bought the product. I think that kind of experience will no doubt bleed into recruiting and should. It's just I think the commercial world is kind of leading as it usually does. Um, so yes we have chatbots in the market today in recruiting, but I don't think they do what the, you know, the full end to end personalization experience. You know, Raidency has one now we call it a career discovery agent. But I think things like that will become commonplace on any site of like this true conversational navigation. Um, the second thing I think we see outside of the career discovery agent is just the um, the kind of like proliferation of just what this content means from a candidate and also how they're searching for it. So another good example in the commercial world, Marriott. If you go to the Marriott site right now they have a uh, let's call it an old school search keyword I want to go to Dallas these dates. They also have an AI search of I want to bring my dog and go somewhere warm sometime after Christmas. And so it's more of a natural language search engine like experience. And the results are not just here's the hotel listing, it's here's inspiration and ideas for a warm place in December. Here's ways that Marriott infuses, you know, pet travel into its experience. So that again same thing on a career site. Right now we have job function, um, whatever it may be City, I think. And you know, again, Raidency is building a natural language search into its career sites and the comprehensive, not just jobs, but everything you offer from a career perspective. Content, skills, events. So I would say look at the commercial side, see what's leading and can you stay ahead of it? Because to me it's kind of the game of are you ahead or are you behind? And again depending on your risk profile. But these are pretty low risk things. Like AI ethics boards are going to review things that are like we're removing 20% of our candidate base who AI said doesn't meet this criteria. This is different. This is kind of widening the funnel and honing in on quality and engagement metric, which from an AI ethics board perspective is a pretty low risk profile. But to me it's like, why not play in this space and start to infuse AI not only in your recruiter journey, but in your candidate journey as well.

Speaker B: Yeah, no, I love that. Before I answer that one, Ryan, I'd like to know, kind of like your point of view, um, you know, kind of in that, in that similar thread from a candidate experience, um, perspective, are there obvious spots where the talent acquisition team need to be aware of that evolving um, you know, experience or expectation, um, anything in addition to kind of what, Ashley? Um, just uh, laid out there.

Speaker C: Yeah, I mean I agree the competition is no longer just for talent, it's for attention, it's for digital convenience. So if your user experience is a step behind in consumer grades like Amazon's one click checkout or Netflix's personalization might be a bit extreme for talent acquisition, but you're strategically disadvantaged. But opportunities using um, you know, 247 AI chatbot convenience and natural language search career sites, uh, uh, you know, are going to kind of help move the needle in that direction. Which is why I'm really interested in the things that Raidency and others are bringing to the industry.

Speaker B: I think maybe to take a stab, Ashley, at um, the two obvious spots I think, um, you know, that cause a lot of inefficiency and friction. And when you think about what's happening on the consumer side, um, two things. Number one is the overall application process in general and then how that application or resume, um, translates into a real like skills discussion. Right. And so like the thing that I think is very interesting and I'm not sure um, if in your product set you, you all are, are innovating in this area or not is um, uh, you know, we have obviously a couple of um, partners in the ecosystem that are really Starting to lean in heavy on this idea of as soon as the app hits the ats, right. Um, I'm deploying a uh, voice agent, right. Uh, on that app to a. Speed up the experience of that initial point of contact. Uh, but then more importantly to have a real um, ah, conversation if you will, uh, about some of the critical skills, um, behaviors, uh, you know, and, or examples of um, uh, you know, with in essence. Right. You know, an AI agent. Right. A human's not even touching that and then that session closing successfully. Right. And so, you know, I think back to um, you know, when this all started as it relates to, you know, video interviews and some of the work early on. But when that session closes, then loading the ATS with really, um, you know, call it a complete map, uh, you know, of that individual, that conversation, and then having that map ranked for the recruiter to then take action on with the hiring manager and pull that through. Right. And so like, I just, I feel like, um, you know, with the generation coming up, they're going to be very okay with that being their first point of contact. And that experience I think will be very, very important. Um, um, you know, and, and kind of how things evolve. The, the resume at times just in the application just doesn't give justice to what that human's um, you know, core competencies and their, their core capabilities are. If I can't write well, um, if I'm not a great resume writer, sometimes I don't end up where I need to end up. And so I think there's a little bit of a normalizing factor that'll probably take place, um, you know, as we uh, as we roll forward.

Speaker A: So.

Speaker D: Yeah, absolutely. I mean I, I'm, I'm actually in some ways surprised at some of the feedback on voice AI and the response rates that I hear of in the market. Um, at Raidency we have, it's not a voice AI, but it's an AI agent that can engage post application to do exactly what you just said. Screen the candidate. We always have the human. We call it like on the loop. You know, no loop is being complete without that human being engaged in some capacity. Capacity. Um, but building a template, saying based on the job requisition, here's kind of the framework for that screening and that AI agent goes out, screens that candidate and if they pass certain criteria, potentially even automating an interview with either the recruiter or the hiring manager. And I think you, you have like two points of view here. You have maybe someone that might say, um, well, Isn't that a bad candid experience or getting this AI agent? Or are candidates sick of AI agents? On the other hand, you have the resume black hole of like, what's better, actually getting this immediate connection and understanding immediately if you're a fit to move forward or not or, or nothing. And so we would lean more toward if that's part of your, you know, if that's a challenge of like that time to process, then candidates are very receptive to that AI engagement. And I think it's just again, going back to like our personal lives. We're all using AI summaries, we're all doing zero click searches, letting Google tell us what to think in some ways versus clicking and reading for yourself. So I just think the narrative of is it too much AI, not enough human right now is not there. There was a reception in the market already we're figuring out ways in everything we do, personally and professional, to spend more time on things that matter. And I think because of that we're willing to engage in these AI automated flows.

Speaker A: Yep.

Speaker B: Let's switch gears a little bit. Uh, I think that was really good and appreciate that education and that deep dive. You know, we've got about 15 minutes or so here. Um, you know, the, the, the challenge in healthcare talent acquisition today. And that's just the place that we, you know, play in. And you know, most folks listening in here, um, is I think a couple of things. And number one is just the industry as a whole. Right. Um, doesn't have a lot of money and so margins are pinched. Right. And there really is no team that we're talking to here right now that um, the senior leaders of the organization are not focused on cost reductions. They're not focused on, um, higher productivity per person. Person. Like those are the types of things that we're hearing. Um, you know, uh, as, as we're out and about talking to, you know, CHROs and CEOs across the healthcare landscape, uh, is like, how do you. Right. Help. Help in that, um, you know, with that particular problem. And so the, the one thing that, you know, we've been focused a lot on here and I'm, I'm just, uh, I'm curious on your point of view, is wasted marketing spend, um, specifically. Right. Kind, um, of in the programmatic world. And so as I understand it, and Ryan's much more educated, he's tried to probably educate me like 10 times on this and so he'll probably clean me up on this. But like, as I understand it. Right. Kind of like at the highest level the way this world works is, you know, I'm Matt, I'm over at upmc and I say like, hey, here's the jobs, here's the general bucket of jobs that you know, I would like to have dollars, um, invested to and then I'm like asking you to then optimize my dollars across all the various channels that exist, you know, for the, for that thing to be marketed to. And then you're pushing basically applicants my way. Right. Uh, just high, high, high level. Right. I guess my, my question is, is, you know, is that, is that an effective model? And I guess like as talent acquisition leaders are looking for costs to reallocate or to push back, um, knowing all the change that's going on in the market right now, is that model working today? Um, and I guess when you think about it from a radiancy perspective, um, what are some things that maybe the folks on this call can think about as they're trying to dial that spend in and make sure that, that in the end they're not wasting any money.

Speaker D: Absolutely. Um, love the question and I'll use a, ah, healthcare clinical example to have fun. So is programmatic as a paid media model effective? It's the most effective thing you can do in the paid media bucket. But paid media should not be the only source that you're attracting candidates with. And so here's the example I'll give you. If you're um, let's say your right leg is sore and you have a sprain so you're overcompensating on your left leg. Think of that same model of like when we diagnose a customer, when they come in, we look at what percent of your hires are coming in from paid media versus your other lovers. Those other levers, high level should be organic basically. Career site direct from Google referrals. Never sleep on those. One of the best sources of hire. You guys know that for a lot of reasons, um, sourcing efforts, CRM engagement and then hopefully agency very small percent. And I know so many healthcare orgs have done amazing work weaning off that over the past five years, but we were in a bad place five years ago. So we can tell right away if your paid media is at you know, a, uh, uh, beyond benchmark for what it should be. In a healthy hiring mixed model, you're overcompensating likely or bad organic traffic, no referrals, process little, you know, to no CRM kind of workflow automation. So that's my answer. I would give you and I can dive deeper, but I would say if you're you, you should have a paid media stream. It should be programmatic so that it's not, you know, job board spend all this budget and hope I get it, but optimizing it based on dollar for dollar. But you should have a healthy mix and happy to give anyone that mix one on one based on, you know, your, your sector and kind of your area of it shouldn't be the only source of hire. And so that's a great benchmark to say if you're at 30% paid media. Higher. Absolutely, that should be lower and raidency and uh, I, you know, we, we don't want you to spend more on paid media. We want you to have your infrastructure, your technology be doing that mainly work because it's a better cost per hire and in many ways better retained, higher, better quality hire.

Speaker B: Ryan, I know you have a lot of experience here. What's your point of view? Um, you know, kind of on this topic and again as these budgets are being pressurized, they're looking for the big line items and sometimes the reality is is the programmatic or the indeed line item is a big one. Um, you know, and it's something they've got to deal with. Um, you know, so just kind of curious uh, Ryan, on this and any tips and how to's maybe for the, for the team listening in.

Speaker C: Yeah, I 100% agree with Ashley that the paid media or you know, kind of what you're putting towards the active labor market if you will, like programmatic and indeed should be, you know, in an ideal state, limited to a healthy uh, amount. I think the bigger opportunity too, uh, you know, as you're obviously analyzing those other top of the funnel tactics like referrals or boomerangs and uh, analyzing your own candidate inventory and doing rediscovery types of campaigns too is take a more strategic look at that programmatic spend. So what decision intelligence are you using to put those dollars towards? Or is it based off of intuition or maybe, you know, you're fighting fires from, you know, feedback from hiring managers or facilities. So I think there's an opportunity to look at, you know, much more deeper and strategic data to determine where those dollars go, uh, traditionally and sometimes it's a challenge based on what you can track, uh, the decisions and logic and programmatics just based off of a surface level, uh, candidate flow. Right. But what if you looked a bit deeper and made buying decisions based on your existing candidate inventory or analyzing where you might have candidates already stuck in the process, maybe they're sitting with hiring managers or maybe you have a really healthy candidate database and you know, remarketing and rediscovery tactics should be kind of the primary lever there. So I'm a big fan of Programmatic. I just think with the, the algorithms at our fingertips, there's just an opportunity to maybe do it a little bit more strategically.

Speaker D: And Matt, can I just chime in on one thing? That I'll kind of bring it to the first part of our conversation. The so what? Like, why does this matter? Okay, so we're getting this percent from language models because that's your organic traffic. Though if you look at the hiring mix, you have paid, you have, you have organic, you have referrals, sourcing agency. If the name of the game for how we get healthy organic traffic, I.e. candidates on Google that are searching nurse job by me, coming to my site, applying, getting hired, if how that organic traffic has been captured is changing from SEO to increasingly Geo. That's why it matters, because you want to make sure you have a healthy organic traffic. And with geo those dynamics are changing. So you have to be geo optimized to ensure we're still getting, uh, as it goes from Google to, you know, AI search engines and language models, we're still getting that healthy amount of free traffic.

Speaker C: M. Ashley, if you don't mind me asking a question, how is this impacting kind uh, of this area of Google for Jobs, or is Google for jobs kind of obsolete with, with geo?

Speaker D: Yeah, that's a good question. I don't know if I have like a, a firm conclusion on that. Um, schema. I know, like job schema. How Google reads your jobs and knows that's a title, that's a description, that's a location. Like that type of setup is still important in Geo. You know, whether or not it, there's going to be a, uh, listing for jobs in search engines. I mean we heard OpenAI is going to get into kind of the jobs market, the skills market. So I think this, like Google did in Google for Jobs, I think there'll likely be some play from large language models into workforce in general. What that is, you know, I don't know yet. I don't think we've seen anything of like, oh, look at this. But we've heard rumblings and like OpenAI made that announcement maybe what, two months ago. Um, but I don't think anything's set to come out from what I've seen until next year.

Speaker B: Let me ask a really like basic question and I And I feel like this has been an ongoing challenge, right. In our industry. But how important is the job posting and the quality to which it is written?

Speaker D: So uh, uh, I feel like I give you a basic answer to a basic question. I think a lot of that's what

Speaker B: I'm trying to get at, right, Is that uh, job posting is typically what these shops have the most control over. Meaning that like I'm at the recruiter. And so I was a recruiter for whatever, five years, right. I sat in the seat and so I was basically the last person to touch the job posting before it hit the Internet. Right. So I was editor in chief of said job. Job posting. And so it's, it's an ongoing challenge I think to um, for, for many recruiters and, and I'm not a writer. Right. That's not what I do. Right.

Speaker D: Yeah.

Speaker B: And so uh, I guess just with how GEO SEO, you know, whatever EO works, how important is it for us to produce high quality postings for. Or is it not as big a factor as what, you know, maybe I've been led to believe?

Speaker D: Well, I think it is, but not in the way you've been led to believe. So your crappy job description that you wrote because you're not a good writer just because it's bad, it's, it's not. Well now there's that GPT. There's no excuse. Just um, like

Speaker B: when I recruiter where I had to rely on myself and then my buddy across the hall that had to spot check it or whatever.

Speaker C: So that's how that works.

Speaker D: You're already at that age is what you're saying, right?

Speaker C: Um, yeah, I'm old, let's say tomorrow, right.

Speaker B: I'm turning whatever I was born in 77. 1977.

Speaker C: So anyway.

Speaker B: Yeah.

Speaker D: Oh, so you're. So you know, you're, you could have a really crappy written job description that's not going to have an impact on whether or not you're in Google for jobs. That's more structural schema, uh set up kind of at the, you know the, the technical architecture of the site. M does have an impact on however is the conversion once they get there and also the quality. So uh, uh, job descriptions are important. There's no company that I work with today that's like our job descriptions are amazing, everyone wants to improve them. But it's not necessarily directly correlated to the conversation we're having here around geo. That's more okay. GEO and having good traffic and being, you know, having the content on our Career site pulls them in. Now when they're here, are, uh, our job descriptions good? Are they going to convert the right person to the job? So that's how they're connected. But not the same. If that makes sense.

Speaker B: It makes total sense. That's good. All right, I know we only have a few minutes left. Ryan, I'm going to ask one last question and maybe if you've got one, um, yeah, we can do that, um, too. And so. Right. Um, I think we started with this idea of um, we're trying to dig deep into, um, metrics that matter. Right. And so I guess Ashley, from your perspective across, um, your wide breadth of knowledge, really top of the funnel and probably down funnel, um, if I said to you like, hey, you gotta run this decent, ah, sized talent acquisition shop, right? Um, that's now your job. Um, and you could only have let's say three metrics that you could have access to to kind of understand. And let's stay focused on kind of like top of the funnel how marketing, you know, how that's performing. What would those three metrics be for you? Like, what would you say? Like, hey, Matt, I would need to have these three metrics to run an effective operation. And you only get three. No more than three.

Speaker D: Can I say one and then Ryan says one and then we go back and forth.

Speaker B: I think that's fair. So you guys can like brainstorm it here.

Speaker D: Yeah, I mean, you know, I would say, um, definitely my overall, uh, so can I. I'm going to use the my ideal hiring mix as my one metric.

Speaker B: Okay.

Speaker D: Um, because to me that's going to tell me from a top of funnel perspective where I focus. So if the I, it's for me to as a leader to build a cost effective hiring model. Um, if I have 45% of my hires coming from paid media, I immediately know I need. It's overcompensating for a weak leg somewhere in my next mix. What is that weak leg and how do I build that up? And so I would, my first KPI would be what's my current source of hire in broadly these five buckets. Where's my weak leg? Where's my leg? That's overcompensating and how do I. Right size.

Speaker B: I love that. Uh, all right, Ryan, follow that.

Speaker C: All right. For me, I think I see much too reliance on conditional metrics that are difficult to quantify based on variables outside of our control, like cost per hire. So mine would be focusing more on quality metrics we can control my number one is dispositioned waste. So if you can assume anything past like a screen is quality, look at optimizing your programmatic, your media mix based on what's producing the most noise. The dispositioned, uh, waste. My number two there would be. If you can create some sort of kind of cost per qualified type of metric.

Speaker B: It cost per, say, say that last one again, like give, give us some more detail on that one. Put some more meat on the back.

Speaker C: The cost per qualified. If you're able to, you know, get a full candidate report of all the candidate dispositions based off your media mix. Look at things that are based off the initial screen and beyond and not hyper focus on a, a vanity metric like hires only. Right. There's so many variables that come uh, into play and attribution models aren't perfect.

Speaker B: So it makes me think of one more question then Ashley, we, you got to answer. You got to give me two. So Ryan gave two. So you can give me one last one. But it makes me your point, um, of view, Ryan. And while we have Ashley, we need to ask her this question because she kind of said the same thing. So when I was at um, Workday Rising here, um, a month or so ago, I had a chance to talk to, uh, I don't know, dozens of TA leaders just interacting. Right. And uh, some are, um, you know, clients, some are ideally future clients or whatever. But we get into this conversation and I swear, like if I talk to 12 of them, 10 of them were asking me like, hey Matt, how is rogue hire addressing source of hire? Like identifying source of hire and getting to like a, at least a uh, true north or a directionally accurate true north of source of hire. So like Ashley here, like in a minute or less, like, do you have any like thoughts on that and like, um, truing up that so that you would actually have quality, um, information or data to do the analysis that you just had articulated?

Speaker D: Yeah, I mean, I think it's pretty. And I saw Angela ask the same question as you, like, what's the best source of truth? Truth or source of hire? Or what do you, what do you look at? I think you need to look at Last Touch conversion. Ultimately that was the moment that converted into an application.

Speaker B: Mhm.

Speaker D: But then I think you can bucket. You know what they say on average it's like seven touches a candidate sees, potentially starting with like prospecting ads. And then a recruiter reaches out and I see a job on LinkedIn. If you can get that data and if your CRM can kind of back into like cookies of did you visit the career site two months ago and then apply when you came back? Two months. And what did you look at then? A secondary metric of like bucketing most impactful touch points, um, you know, around how people interacted with your content, you know, what pages led to the most kind of apply clicks, even if they didn't convert. Those kinds of things are interesting as kind of secondary metrics. And then I'd look at your first, your primary metric of like, what was the last touch?

Speaker B: Because that's gonna touch conversion. Figure out how to get your hands on that one. Make that one nice and clean and work, work off of that. I love that. All right, what's your last metric? And then we gotta say goodbye.

Speaker D: Oh, I was so busy listening to Ryan and you that I didn't think of my second metric. But I would say top of funnel, um, you know, generally career site traffic and behaviors. So that tells me what, what am I. How big is my, like, how big is my brand and people interacting with it from a career site perspective? And then is it quality or not? Because if it's not quality, I don't care about someone giving me a big number. I care about what's the engagement look like, what's my apply click rate look like. Um, so I think in general, bucketing that into like my very top of funnel visibility, visitors engagement apply click, that tells me is that, you know, quality over quantity.

Speaker B: So, Ashley, if people want, uh, to learn more about you or engage, what's the best way. What's the best way to get in touch with Ashley O'?

Speaker A: Connor?

Speaker D: I'll type it and talk. Ashley O'connoraidency.com I'm on LinkedIn. Would, um, love to chat with anyone. So please feel free to reach out anytime. Healthcare is a passion. My Mom's been an ICU nurse for 40 years, so it runs in my blood. And so, um, I specifically love talking about anything in the healthcare space. So happy to help wherever I can.

Speaker B: Great job today and really appreciate, uh, obviously, you know, your education and your knowledge that you shared. Ryan, any final thoughts here as we close out?

Speaker C: Only, I mean, the last, uh, topic we were touching on, you can go go deep hours into the whole idea of attribution models and first click and last click and, uh, talent acquisition has always been kind of far behind the consumer, the commercial side in attribution. And it's just, it's, it's, it's messy. Uh, but Ashley, uh, gave some very, very good insights on how to, you know, at least start making making sense out of the best practices there. So I appreciate that, but thank you, Ashley. Thank you, Matt.

Speaker B: Cool. All right, everybody, we appreciate you joining us here today, and, uh, we, uh, especially thank the group that joined us here live, uh, uh, for this live show. And so, until we see you again, um, thanks for trenching in. We'll see you now.

Speaker D: Thanks, everyone. Bye, now.

Speaker C: Bye. Bye.

Speaker B: All right, we want to thank you

Speaker A: for listening to TA in the Trenches. We are produced by Iron Mike and his team at Ironbound Media. Keep up the great work, team. Please subscribe to the show on your favorite podcast platform. You also can find me out on LinkedIn where you'll find quick show riffs. Feel free to ping me. I always respond.

Speaker B: Bye for now.