Latest / Recruiting Evolution / Why Most Staffing Firms Use AI Wrong and How to Get Better Results
Transcript
- Brad Smith [00:00:00]: Most staffing companies are using AI wrong right now for sales and marketing. And I know that sounds harsh, but I look at it as an opportunity. For the ones that are doing it right, you have the opportunity to own the answer. You have the opportunity to leverage and use the large language models to really position yourself as an expert and a leader in your areas of specialization. Kortney Harmon [00:00:24]: Welcome back to a special episode of Recruiting Evolution. If that name sounds new, that's because it is. The Full Desk experience is evolving, and as our audience, our conversations, and the recruiting industry have continued to grow, we knew it was time for the brand to grow with it. So welcome Recruiting Evolution, our new name and new brand built for the next chapter of conversations that you already know and trust. And while you see the new look and hear the new name, you can expect the same impactful topics, candid conversations, industry voices, and really practical insights designed to help you stay ahead of what's coming next in recruiting. The session you're about to hear was originally recorded as a part of the FDE+, our original event series under the Full Desk Experience. Going forward, those conversations will be live within the Recruiting Evolution brand. New name, new brand, same commitment to moving the industry forward. Kortney Harmon [00:01:25]: I'm your host, Kortney Harmon. Let's jump in with some fresh new ideas, future-ready, And creating relationships that fuel growth. I'm super excited. This is actually my first time getting to meet Brad as well at Haley Marketing. This is the other Brad. There's 2 Brads. Don't be confused. There's Brad Bialy and Brad Smith. Kortney Harmon [00:01:52]: So Brad Smith is the Chief Strategy Officer at Haley. That's According to your title here. Brad Smith [00:01:58]: Got it. Yep. Kortney Harmon [00:02:00]: Well, I love it. And he and his team have spent nearly 3 years in the trenches figuring out, and it's probably more in reality without AI, but where marketing actually delivers in staffing and recruiting firms and what's just noise. So his session today is saying you're using AI wrong and how to get more value out of AI in marketing. And honestly, this is a standalone title and you probably should sit up a little straighter, make sure you're Your bell tones are dialed in because I'm here ready to take notes. We're all talking about prompt engineering, GPT, real adoption lessons from working with hundreds of staffing firms. And if you're tired of guessing at AI and you want a clear path, Brad is going to lead us the way. So Brad, I'm super excited to join you in your talk today. Do you have any questions before this magic genie jumps off? Brad Smith [00:02:50]: No questions. I think we're all good, magic genie. Thank you so much. Kortney Harmon [00:02:54]: Awesome. I'm going to add this to the stage and I will be back. And if anyone has any questions, feel free to throw them in the chat and I'll make sure that we're answering those. So have a great session. Brad Smith [00:03:03]: Thank you so much. All right, Kortney, first I want to compliment you. I think that you've done a fantastic job putting on this event today. I think it's been absolutely wonderful. I had a chance to sit through some of the speakers earlier today, and I thought the content was just absolutely phenomenal. So, I am excited here to really jump in and showcase what we're doing, what we've been working on for the last few years here. So, just a little bit of background about me. Um, Brad Smith, Chief Strategy Officer at Haley Marketing. Brad Smith [00:03:39]: I've been working with the staffing and recruiting industry for, geez, going on 25 years now and have seen a lot of things change throughout the years, but I would say the last 5 have been monumental. There's been so much change in technology, so much change in buyer behavior, so much change in how people react to marketing, how people react to sales, how people are integrating staffing and recruiting more strategically in their business. So, I'm excited to share some of what we've learned over 20 years, but more importantly, probably what we've learned over the last And I have the chance to talk about AI and marketing and sales in the staffing industry, and I've done it for the last several years. And I just want to kind of talk about this journey here that we've seen over the last few years. And back in 2022, '23, we were giving talks and talking about this new thing coming to market, AI, and it was all built around curiosity. So Everyone was asking, what can AI do? What are the limitations? What should I be concerned about from a security perspective? And we had a lot of individuals kind of playing around with different things, testing things out, seeing what they could accomplish, what they could do, what they could streamline on a personal level. Then in 2024, when we were giving talks on AI, it was all about experimentation. So we're going from one-off individual curiosity to experimenting within the business. Brad Smith [00:05:18]: So we are trying to adapt and get our teams to try tools, to maybe pilot different projects and being very collaborative internally to learn what works and what doesn't work. And around this time between '23, '24, we brought in an AI consulting firm that focused on consulting for marketing. Agencies, one of the most reputable AI consultants in the space, Trust Insights, and went through this journey of really learning how to use the tools at their core more effectively. So in the presentation today, I'm going to share what we've learned over the last few years. I will walk through and show how we've taken that base-level learning and expanded that and integrated that in our systems and how that impacts the staffing and recruiting sales and marketing cycle. And then I'll jump into some very specific examples of how organizations are using it in driving revenue. And that kind of brings us up to '25, '26. So '25 was all about adoption. Brad Smith [00:06:26]: So we were talking about how to move from just piloting certain tests and moving them and embedding those in processes and how the AI tools that are available could really become a part of our daily work, our daily rituals, our daily process. And this year, the conversation has been all around how do we mix this into our operations? How can we build AI into our systems? How can we leverage and build it into workflows, into strategy? And how can we actually use that to create measurable business advantage? So that's kind of the trajectory that we've been on and that I'd like to see the staffing and recruiting industry in. So the good news here is that I think on the recruiting side, many staffing and recruiting firms, I think, have already moved into that operational phase. And I'd like to credit organizations like Crelate because they have built a lot of the AI systems, strategies, tactics right into workflows. And I think the technology partners here have really catapulted us from that curiosity phase a few years ago into operationalizing everything that we do on the recruiting front. So AI is built into many of our recruiting workflows. We're using automation in matching to be better at finding the right people and matching them the job quicker, faster. It's adding speed into our processes, it's helping us drive results. Brad Smith [00:08:06]: That's the good news. Again, we're sourcing smarter, we're engaging faster, we're placing more talent, and we're operationalizing AI on the recruiting side. Now, the not so good news, or the challenge that I see, is I don't see the same growth on the sales and marketing side right now. I think there's certain people and components that are doing some really amazing things on the sales and marketing side. But as organizations and as an industry as a whole, I think there's huge opportunity for us. So at Haley Marketing, we work with roughly 1,000 staffing and recruiting companies all across the world, mostly in North America. But what I find is the organizations that I talk with have done pretty well on the recruiting side, but 70, maybe even 75% Are still stuck in those first two stages on the sales and marketing side. So the adoption there, it's lagging. Brad Smith [00:09:09]: It's behind where we are on the recruiting front. So most of these firms are still in the phase of learning what AI can do. There's lots of questions. There's a little bit of implementation. But what I see is that implementation usually happens from. One or two rebels within the organization that have said to themselves, hey, I'm going to invest the time and resources to learn this myself because I want to be better at my individual job, or I want to make my job better, more effective, more efficient. They're testing out tools, they're creating content, they're creating case studies, but sometimes isolated. And I don't see that carrying over consistently across the industry. Brad Smith [00:09:54]: To other parts of their teams. So we might have a few programs or a few test cases here or there on the sales and marketing side, but we're not yet building this into consistent systems. We're not yet at a point where we can fully scale this across the market, across our company. We, in many cases, have not built AI into our strategy. Or our sales workflows, we're not creating and leveraging this growth engine that's available to us. And hopefully, after our talk today, you can think about some ways that you can move from the experimentation phase to operationalizing this across the entire organization because I think the opportunity is massive right now. I think the firms that are moving on to that. operations phase are going to own the market. Brad Smith [00:10:51]: And you're going to be so far ahead of those competitors that are still experimenting on a one-off basis or have a few individuals within their organization that are experts, but have not shared that knowledge and those resources and those processes across the entire organization. And one of the reasons that I think this is such a massive reset or a massive opportunity, especially for smaller and medium-sized staffing companies is because inherently how we find information has changed dramatically and continues to change. So in the chat, if you don't mind, share with me where you would start if you were looking for a new B2B vendor. So you were looking for a technology, you were looking for an insurance company, you were looking for some vendor for your business. Or if you can't think of that, maybe The last big purchase that you made, where did you start with your research? I'll wait here a second. Hopefully we still have some people that are awake and alert and ready. Oh, your own database. I love that one. Brad Smith [00:12:01]: Anybody else? Where do you start when you're going and you're starting and you're looking to do research? What I usually get, well, if I go back, what I used to get was, well, I Google it. And then I had some people that would talk about going to YouTube and doing some research. Then some would go to third-party websites out there. All right. They're coming in now. 100% Google search. Katie goes to ChatGPT. Kurt is going to peer reviews and referrals. Brad Smith [00:12:28]: Chat, referrals, YouTube. Yeah. Like we used to go and just Google things, or we used to go and just ask 1 or 2 people, or we used to go to an industry association and talk a little bit. But how we find information, how we search for services, how we pick vendors has changed dramatically. So when we look at how buyers used to find staffing companies or recruiting companies, it usually did start with a Google search, or maybe it started with a salesperson that did some direct outreach, maybe left some voicemails, maybe there was some level of direct outreach that got the prospect do a Google search about the company. Usually what would happen is that Google search would lead to a website visit. That prospect would visit your website, learn about your services, your markets, maybe some key points of differentiation, maybe learn about the people in your organization. Ideally, that would spark a sales conversation. Brad Smith [00:13:28]: They'd reach out, they'd have a conversation with your sales team to explore fit, look at capabilities, make sure you were the right vendor. Hopefully that led to an appointment or proposal, and then hopefully shortly thereafter there was a decision made. They selected the partner that they trusted, that they felt comfortable with, that could solve the workforce challenges. So it was kind of a predictable path. Some level of sales outreach or engagement created that initial Google search, and then they flowed through this process. Today, things have changed. So the modern buyer journey now Typically, especially B2B, is starting digital. It's not linear and it happens long before the salesperson even gets involved. Brad Smith [00:14:12]: So there's data out there that shows 80% of the B2B buying decision happens before a buyer ever talks with a sales rep. They're doing their due diligence just like all of you. They're going to Cloud Cowork, they're going to Google, they're looking at recommendations, they're going to Perplexity or Claude. And no longer are they just saying, hey, you know, who are the staffing companies in my area? They're doing deep research and long-tail searches around who is the best staffing provider for, you know, maybe logistics specialists in the middle of their careers with experience in X, Y, or Z. So they're getting extremely specific. And buyers are asking the AI for recommendations, shortlists, comparisons, pricing reviews, consumer reviews. So you're either being discovered or overlooked here. So in order to even get into the conversation, we need to own some level of answer and we need to own some level of visibility in the large language models. Brad Smith [00:15:19]: Even if they're Googling you still, they're getting Google AI overviews. Okay, so Gemini is serving up those AI overviews, and typically those AI overviews are not necessarily leading to a click to your website right then and there. So buyer's going to scan the AI, they're going to look at summaries, they're going to compare their different options. And this is all happening absent of your sales team and absent of, in many cases, your website right now. So visibility in the AI overviews is driving that early consideration that's determining whether or not they even get on to the next phase. We had some people that had mentioned that they're going out and doing the talking to peers. They're looking at review sites. They're looking for validation. Brad Smith [00:16:02]: That's typically the next step. So they're looking for proof. They're looking for feedback. They're looking at Glassdoor. They're looking at Google reviews. They're looking at other resources to validate and confirm that you're trusted by others. If you're not trusted by others or they can't find that information, They're not going to waste their time talking to you. Then they're going to look at LinkedIn and social validation. Brad Smith [00:16:26]: So they're going to check out your team, your leadership, what activity you've done. They're going to look at your individual level of experience. They're going to make sure that you're used to recruiting in their industry, that you've had a successful track record of placing the type of people that they really need to drive their business. And if you can display that in this phase, You're going to help build trust and people want to buy from others that they trust. Then once they've validated, they're gonna hopefully make it over to your website. They're going to hopefully find some great case studies. They're going to dig and dive deeper into your solutions, your experience, the results that you can prove, not just general information that says, hey, we're great at providing service. They want to see proof of those outcomes. Brad Smith [00:17:15]: They want to make sure that you should be on their shortlist. And then and only then, after they've done all that independent research, are they going to potentially strike up a sales conversation. So by the time they talk to sales, they've already been informed. They already have reviewed options. They already have other options in mind. They've already asked and hopefully gotten some level of answer on very specific questions. So that sales conversation is really validation, not just the introduction. They've already done all of that deep research, and then ideally they're going to make a decision. Brad Smith [00:17:50]: But I don't know about you, but I've seen and heard that the decision phase is a real challenge because no longer is it one person's decision. It's a buying committee. So you might be talking to the CEO or the COO or the floor manager, or maybe you're talking to HR or talent acquisition or procurement or the CFO. Most likely each one of those people has some level of decision on who gets picked and who gets chosen. So no longer are you able to deal with just one stakeholder. You need to deal with all of those different departments in order to win that. And it's become a real challenge because if you are just talking in generalities, there's no reason for that person to trust you. So As we get into the presentation more, we're going to talk about how to go from just general information to being extremely specific, extremely targeted, and I'll show how that's impacting revenue. Brad Smith [00:18:51]: Before we move on to that, though, I want to get across the concept of buyer enablement. So I mentioned earlier, 80% of that buying decision is made before they ever talk to you. Buyer enablement is no longer optional. So today's buyers, they want to learn, they want to evaluate, they want to build consensus before they even speak with sales. And here's some data that continues to be updated, but I think it points to the value of educating and providing that insight and that buyer enablement well before someone ever picks up the phone and talks to you. So 67% of buyers of B2B services don't want to talk to you. I know that sounds harsh and it can be challenging, but they want a rep-free buying experience until they're ready to make that final decision, until they're ready to validate. And I'm not saying that sales is not important. Brad Smith [00:19:46]: I think it's extremely important. It's never been more important. But before they even get to that point, we need to educate and provide buyer enablement content to get them comfortable To the point of talking with your sales team, because 70 to 80% of that journey is happening before they ever talk to you. In fact, only about 17% of their entire buying process is meeting with a supplier or talking with a sales rep. Now, it's a very important 17%, but it's been flip-flopped because in the past, I think it was 70 to 80% talking with a rep. It's completely the reverse now. We have way more stakeholders involved in the B2B buying committee and the decision-making process. So we can no longer have just one general message for everyone. Brad Smith [00:20:33]: Doesn't work. And 45% of buyers of B2B services report that they're already using AI during their purchasing process. The estimates are by the end of this year, early next year, it's probably going to be around 80%. I think this is probably a very underreported statistic. I bet you it's way higher than 45% now. So gets us to the meat of the presentation here that most staffing companies are using AI wrong right now for sales and marketing. And I know that sounds harsh, but I look at it as an opportunity for the ones that are doing it right. You have the opportunity to own the answer. Brad Smith [00:21:13]: You have the opportunity to leverage and use the large language models To really position yourself as an expert and a leader in your areas of specialization. So most staffing professionals right now, when they're using AI in sales or marketing, it's helpful to them, but it's not transformational. So most are using it to do things like, you know, write a blog. They're drafting a blog post or a newsletter faster. Some are using it for writing client outreach emails or nurture emails. Some are using it for proposals and follow-ups. Some are using it to write LinkedIn or social posts. Some summarize a meeting after they do some sales follow-up and they're done. Brad Smith [00:21:59]: They rinse, repeat. They feel comfortable in that they've used AI as a quicker, faster keyboard as opposed to a true transformational tool. So it's because of this that I think most AI output feels generic. In the chat, let me know if you've read something recently or looked at something recently or received an email and you said to yourself, oh, that was AI. I know that's completely AI. I'm sure some of you have seen that. Yep. 100%. Brad Smith [00:22:34]: Yes. So most people when they're starting and using AI for sales and marketing are using really basic inputs. So write me a sales email, write me a LinkedIn post, create a blog on XYZ topic. Some are maybe getting a little bit more advanced and saying, hey, I want a prospecting sequence that's going to be 10 steps and it's going to go out to hiring authorities in mid-level manufacturing facilities. Okay. And the output they're looking at, they're like, wow, this is pretty good. Some are using it just to summarize meetings. And in all of those scenarios, we're going to end up with generic output. Brad Smith [00:23:13]: It's going to be vague. It's going to be easily ignored. We're going to sound like everyone else. And why is that? Because the AI knows general sales principles. It knows general marketing principles. It's got generalized recruiting concepts. It's got public information that it's drawing from. Now, what happens if your competitor down the street is doing the same base level inputs that you are? You're going to end up with the same base level outputs. Brad Smith [00:23:48]: So garbage in is garbage out. And a lot of people assume that the problem is their prompt and they're looking at deeper, richer prompts. I'd like you to think a little bit differently and realize that the problem isn't necessarily the prompt. It could be the prompt, but the problem isn't necessarily the prompt. It's on what you're feeding into the AI that you're not teaching it all about the specialization, all about the differentiation that your team provides and offers that your company has. We're not giving it access to the information it needs to truly, really differentiate. And that's why all of the output feels generic. It feels the same. Brad Smith [00:24:31]: So we're going to use the rest of today to walk through how to get past that, how to get better outputs from a sales and marketing standpoint, and how to build some process around this. So the missing ingredient here in getting past just the generic content is context. So I think that the best AI users don't necessarily start with prompts. They're starting with knowledge. I know earlier today there were some great, great speakers. If you didn't see a chance or didn't have the chance to see them earlier, I would suggest watching the replays. But a lot of them talked about some amazing processes. They talked about using Claude Code, talked about different systems and tools and technology to automate, to simplify, to get a lot of the work done that you need to get done. Brad Smith [00:25:21]: And that was Absolutely fantastic. Just great key takeaways. I would caution you that in order to make that truly effective, we need to start with feeding those tools better context. Because if we don't start with the context and we just jump into the tool, the technology, the platform, the automation, you're going to streamline a lot of the work, but the message and output that you get is going to be too generic to have a huge impact on the organization. So in order to give the AI the context that we need, we have to do some homework. We have to give context about your company. What are your true key differentiators? What are you best in the world at? What industries do you target? What types of businesses and organizations do you really excel At serving. And don't say everyone, because you're going to end up with general content, but truly dig in, look at the data, look at your database, look at your financials, and determine what target accounts and what target industries are really driving revenue, are really driving long-term relationships, are really driving lifetime value. Brad Smith [00:26:40]: And let's feed that information into the AI tools that we're using. We need to get deeper into buyer personas. I mentioned earlier that the decision-making process on what vendor to bring in, you might have to convince 3 people, 5 people, 10 different people in 10 different seats within the organization on why you are the vendor that they should choose. Each one of those buyer personas has a different reason or a different thing that they're looking for. The rationale for a CFO is much different than the rationale for the COO, and that's much different than the rationale for the line manager who needs to get product out the door today. So in order for our outputs to be truly effective, we need to feed the AI and the tools with the proper inputs first so that it understands who we are, what we're great at, and who we're trying to get in front of. And that's going to go into your messaging, and that's going to help improve your sales process. So if we can feed this context, if we can give it rich context and a better understanding, we're going to get output that's more relevant, it's more personalized, it's differentiated from all of the other people that aren't doing this background. Brad Smith [00:27:57]: It's going to be actionable, it's going to be way more persuasive, and we're going to get way better business outcomes. So it's time to level up. So how do we help our sales and marketing teams do this? How do we use the AI more effectively? So I love the concept of knowledge blocks, and this isn't something that I came up with. This is something that our consulting company several years ago hit me with, but it makes so much sense. So knowledge blocks are really the foundational work that you can do to turn your AI tool, whether that's ChatGPT, Gemini, Claude, Perplexity, whatever tool that is, it's going to turn that into your best teammate. So the AI and the output's only going to be as good as the knowledge that it's able to get. Now, some of that knowledge it can get from other sources, but the secret sauce is what you need to give it, your secret sauce. So it organizes your most important information so the AI can think It can write and it can act like an expert on your business, on your industry, and your key target clients. Brad Smith [00:29:07]: So when you think about knowledge blocks, it's almost to me like a full business and marketing plan. So as a company, identify exactly who you are. What's your story? What's your mission? What are your very specific services and solutions and value that you offer to the market? What truly makes you different and unique? What is your secret sauce? What I like to do, a little exercise, I will go to our top clients and say, why do you work with us? Don't just guess. Ask them that information. What are your values and your culture? What proof points do you have? So as you're generating your knowledge block for your company, you're looking at overviews, you're looking at your service descriptions, you're looking at What makes you different? You're looking at awards and certifications. Okay, we need to feed the AI all of this information. So it's not just generalizing, it's not just guessing, it's not just saying, hey, okay, you're a staffing company. So a lot of staffing companies present themselves as having the best possible service and they screen and interview candidates and they have a great track record. Brad Smith [00:30:15]: Okay, that's what everybody does. What truly makes you unique? What truly makes you different? We need to feed and teach your AI, whatever AI you're using, what that actually is. Then number 2, the next knowledge block I want you to create. When I say knowledge blocks, these are just collections of information. So in my case, I put together a knowledge block in a document of our company. Now I'm going through and identifying our ICPs, our ideal client profiles. A lot of staffing companies that I talk to when I ask them, who's your ideal client? First response I get, and I always shake my head, is any business that hires. Well, if that's the case, then you really don't have an ideal client profile. Brad Smith [00:31:00]: So we need to get granular. We need to think about what target industries you're really going after. What's the ideal company profile that you're trying to reach? What different attributes make a client a good client versus a bad client? Maybe it's pay rates. Maybe it's geography, maybe it's ability for transportation, maybe it's split shifts, whatever that is. We need to identify what makes a great client. We need to streamline and identify what common business challenges you can help solve. We need to identify what success truly looks like. We need to look at what are the buying triggers within that company that would indicate that they need your service or they need to switch from a current vendor. Brad Smith [00:31:45]: So in this case, our knowledge block is digging into target industries, your company size, your locations, pain points, desired outcomes, what they want to accomplish. Then once you have your ideal client profile identified, we need to build out individual personas in those organizations. You could think of a persona as a job title. So who in those organizations are you targeting? What's their role? What's their title? And remember, there's probably anywhere from 3 to 10 people in that organization that are involved in that decision-making process. We need to know what their responsibilities are. We need to know what their goals and motivations are, their pain points, their objections, what interests them, what's their preferred type of content or outreach, what platforms are they on. If we can build out these buyer personas and role descriptions and, and what their individual KPIs are, Then our outputs can speak to those individual people. We can speak to them in a way that uses their language, uses their vernacular, details to them why they would want to work with us. Brad Smith [00:32:52]: And again, our message and our outreach to the CFO is very different than our message and our outreach to the line manager. So if we don't feed the AI with this information, what do we get? We get generic general outputs that combine all of those things together, and we're not a specialist to anyone. So once we have our ICPs, once we have our personas, then we can get into our messaging. So think about what your core value propositions are. Why would someone want to work with you? What problem or value do you add to the equation? What are those key messages we want to get across? What are proof points? So it's not good enough to say that You provide amazing service. We need to actually prove and have evidence as to why that's true. We need to make sure that we can cover objections or the AI knows what objections your sales team is constantly hearing. We need some strong calls to action. Brad Smith [00:33:46]: So as we're developing our messaging knowledge block, we want to look at value props. We want to look at key messages. We want to look at positioning statements. We want to look at taglines. And I also like to do a competitive assessment and look at what others that we're bumping into in the market are saying to make sure that our key messages, that our value props aren't just a rinse and repeat of theirs. We want to actually be different. And number 5, we need to show proof. So we need to put together knowledge blocks of case studies, client testimonials, metrics and results, awards, recognition, social proof. Brad Smith [00:34:22]: We want to look at client success stories. We want to feed the AI again, whatever AI we're using, whatever tools we're using, we want to feed it with all this information so it has the knowledge to create outputs that are really custom, that are really unique, that are really different, and that are really specific for our own business. So the knowledge blocks can help turn AI from a generalist to an expert in your business. And again, Before knowledge blocks, the AI is going to guess. It's going to give you some generic responses. It's going to give you some surface-level output. Once you feed it with all of this information, with all of this deep insight, it's going to better understand your business. It's going to better understand your buyers. Brad Smith [00:35:05]: And again, your buyers are people in all different seats within the organization. It's going to understand the industry that you're really targeting and it's going to understand your expertise. We're going to get way better outputs. So now, hopefully with those knowledge blocks, we're teaching the AI, we're sharing our secret sauce, we're sharing information about our organization. Now we need to direct the AI. This is another area where I see some staffing companies fall is they're not directing the AI. They're giving general guidance, they're providing general asks, and they're getting general information back. So I wanna introduce you to a framework called RAPPEL. Brad Smith [00:35:43]: And it stands for role, action. We're gonna prime, we're gonna prompt, we're gonna evaluate, we're gonna learn. So under role, we need to define what the AI's role and perspective should be. So if you're building agents, if you're using Claude Code, if you're just using a general ChatGPT or Gemini prompt, we need to start by defining what that role and what that perspective is. What mindset does the AI Does the agent, does the tool need to adopt? How does it need to think? So a very general example might be you're a strategic advisor, an expert in staffing sales and marketing. Now, I think that's a little too vague. I might get into geography and industry, company size, et cetera. After you've defined and taught the AI or the agent or the tool what role they should take on, then we need to clarify what you want it to do. Brad Smith [00:36:33]: What is the action you want it to take? This is where you're feeding in your ideal client profiles, your personas, those pain points, those goals and priorities. So you're speaking to the VP of engineering at a high-growth SaaS company. Some of their big challenges are X, Y, and Z. You're feeding it with that knowledge block. Then we're priming. So share what AI needs to know, that relevant background, those key insights, those constraints, challenges, maybe what you've tried in the past. Maybe what their big challenges are. If you've done all of the ICP and persona knowledge blocks, we can feed that right into our system. Brad Smith [00:37:12]: Then and only then do we create the prompt or provide the context or instructions and the data that we want it. So in this case, maybe it's simple. Maybe we'll want to write a value prop email. We want to keep it concise, confident, and we want it focused on ROI. Then comes evaluate. And this is where I think a lot of people don't take it to that next level. If you trust the first output from the AI, sometimes, especially if we've primed it and we've given it information, sometimes it's good, but sometimes it's just basic. Sometimes it's base level. Brad Smith [00:37:47]: Has anybody had the experience where one day they're using their preferred AI model and they get amazing output, And the next day they do the same thing and you get output and you're thinking, what did I do different today? Why am I not getting the output that I want? Well, sometimes it's just a little lazy. So what I encourage you to do is after you get a response, go back, request improvements, ask probing questions like, what am I not thinking of regarding this output? What other questions should I be asking? Related to this ask. So when we use AI and we've built a whole marketing system or agent, we don't rely on one language model. We might use 10 or 11 in any specific task. One might do ideation, one might do an outline, one might write the first content, one might evaluate content based on a rubric that we've created. One might go back in and be an expert in direct response. One might write better CTAs, and one might review and look at data to make meaningful recommendations for the next time. So we're not relying on one output. Brad Smith [00:39:00]: We are going in and continually using rubrics and continually evaluating to improve the output, make it more specific and more direct. And then we're learning from this. So capture what worked for future use. Save those successful prompts, document those processes, build reusable agents, continuously improve. So save it out as a template and have a framework in your organization where everyone can share these success stories. So when we follow this RAPPEL framework, and again, this is kind of a basis for what we've built, we get much better outputs and outputs that learn over time and evaluate And continually improve. So the knowledge blocks are teaching the AI who you are, who you help, what you do, why that should matter. And the framework, the RAPPEL framework, is teaching the AI or your agent or your Claude code how to think, what to create, who it's specifically for, and what success truly looks like. Brad Smith [00:40:03]: So first, teach the AI with your knowledge blocks, then direct the AI with your RAPPEL framework. So now let's get into this in action. I think all of this theory is interesting. Results are better. So let's look at how we've used this methodology to help staffing and recruiting companies, and I'll share some specific examples. So case study number 1 is a company that we worked with that reclaimed over $1 million in revenue. So in this particular case, this is a large national staffing company, and they had a lot of clients that they had done business with, but they were just dormant clients. So people that didn't have ongoing placements going, people that were in their database that were just kind of sitting there. Brad Smith [00:40:50]: They weren't unhappy clients, but they weren't people that were currently being billed. So what we did is realized that in the past They were doing one campaign, one message to a bunch of different industries. We went in and said, all right, well, there's a couple thousand people here. Not all of them are the same. They're different industries. They have different priorities. They've got different buying triggers, different pain points. Why are we sending them essentially the same message? Why are we creating one campaign and sending it out to the masses? Because that was getting poor engagement, very low response rates, low activation, no opportunity. Brad Smith [00:41:32]: We weren't regaining any of that revenue. So we went in and said, all right, we're going to use the AI to analyze and go through things. So we exported three years of revenue data out of their system, looked at existing client relationships. We looked at past relationships. We looked at recent patterns and behaviors. We looked at overall industry performance and trends. And originally, when we went into this. We said, all right, there's really 5 key verticals that this company focuses on. Brad Smith [00:42:02]: We're going to create messaging and do a deep dive in those 5. And I was surprised when the AI came back and analyzed this and told us that, yeah, there were 5, but there was one that we were missing. There was a huge overlooked opportunity over the last 18 months in property management. It was one of the highest potential segments And it's something that they weren't targeting. It just happened by chance. So the AI reviewed this entirely new opportunity and said, this is a high growth area for you. Let's put some focus and attention there. So right off the bat, fed the AI with the revenue data, did an analysis, came back, helped us refine who our ICPs were. Brad Smith [00:42:44]: From there, we went in and we built out buyer personas. So in each one of those 6 target verticals, We created detailed personas. So within each vertical, there were maybe 3 to 6 personas in each one of those organizations. So within each persona and within each industry, we went out and said, all right, what are the goals and responsibilities of that person that we're trying to sell into? What are their pain points? How do they make decisions? What's the best way to reach them? We identified what their common objections are so that we could overcome them before they came up. And then we identified how we could truly help them and how we could prove that we could help them. Once we did that, we built a 10-step automation campaign for each one of those ICPs and then each one of those personas. So this might sound a little overwhelming. There's 6 different industries. Brad Smith [00:43:40]: So we had 6 different versions of our campaign within each version of that campaign. We had different messaging for 3 to 5 people. So right off the bat, you know, you're looking at this, you've got 18 to 25 different campaigns that you're managing. So before it was one message, one campaign, one value proposition across all of these industries, across all of these different buyers by job title, didn't get much result. We used AI to scale this, so we fed it with the knowledge blocks of the ICPs. Of the personas. We created an initial campaign, the general theme for the campaign, and then we used the AI to write versions for all of these different personas. So we had custom messaging that was very specific. Brad Smith [00:44:29]: It was based on their individual pain points. It was based on their individual KPIs within the organization. All of them had very specific industry context. And the messaging was all buyer-focused. It was all about that buyer enablement. And then we mixed in email, LinkedIn calls, case studies. We handled objections. There were touchpoints throughout the campaign for phone calls. Brad Smith [00:44:56]: There were individual LinkedIn messages that we automated but made it look like they were coming from the individual. And then a final nudge. So before this, we had one message, one campaign, one value prop. Afterwards, we had 6 industries. 3 to 5 different variations per industry. We had persona-based messaging, industry-specific content, and very relevant and high engagement outreach. The send-to-appointment ratio was great. Even better was the appointment-to-reactivation ratio. Brad Smith [00:45:29]: They drove $1.1 million in reclaimed revenue off of this one campaign. And it looks like a lot, especially looking at this slide. But leveraging and using the AI and building out a process and a system was amazing. Our second case study I'll share, this one's a little simpler. This is a small 2-person recruiting firm and they focused in the insurance industry, so they knew their niche. They identified that they were experts in recruiting for insurance agencies and insurance companies. And they needed to scale their business. They couldn't scale it from one small brick and mortar outside of Chicago. Brad Smith [00:46:10]: They needed to expand nationally. So how does a 2-person recruiting firm become the answer across 50 markets across the country? So they had one location. They had a goal of being the top trusted resource for insurance recruitment in the top 50 US cities. And they wanted deep focus on insurance recruitment. So what we did is we scaled. We looked at and identified all of those top 50 markets. We realized that only 2 to 3 recruiters— we had to look for automation. They weren't going to be able to reach out and call, build relationships in all of these markets. Brad Smith [00:46:53]: We realized that there was no local presence in most of these markets. So there's no office, there's no recruiters, there's no footprint, there's no brick and mortar. There's no Google Business listings in any of these because they don't have physical locations. They had a very limited marketing budget, so every dollar had to deliver impact. And they were competing against national firms with national reach and national resources. They're going up against agencies with much bigger budgets. So what we did is we leveraged AI and scaled very specific content output So that we could own those top 50 US markets. We focused very specifically on SEO, AI optimization, and geo— GEO. Brad Smith [00:47:41]: So we looked at building topical authorities around everything tied to insurance recruitment. So we built the foundation and built their initial website and presence. All around insurance recruitment and everything that you could possibly think of tied to insurance recruitment. Then we went through and built out individual landing pages and sections on the site for each of those target markets that we were looking to get in front of. So people in Tampa were a little bit different than the people in Dallas, cared about different things, but we used the AI to scale and customize and create these pages and these geographic-focused sections to make sure that we ranked well. We coded everything properly and produced some great content so that we showed up in AI overviews. And now they not only own search in almost every of the top 50 markets, but they're referenced in the Google AI overviews in all of those markets. We made sure that we had some qualified traffic and now they're inbound traffic and inbound leads really drive their business. Brad Smith [00:48:53]: So they're no longer making a ton of dial-for-dollars calls. Most of their leads are coming inbound because of this strategy. So if you go and search for insurance recruiters in a specific market, you're more than likely going to find this particular company ranking either at the top or within the top 3 listings. And showing up in AI overviews and in the large language models. So we're creating that conversation ahead of time. So where should you go from here? I'll wrap this up here and then we'll open it up for questions. So the AI growth engine that I'd like you to think about, and this is a repeatable framework for sales and marketing, is really number one, building out those knowledge blocks. So looking at your company, your ICPs, your personas, case studies, and your industry experience. Brad Smith [00:49:43]: Build that out so that we can teach the AI what makes you special. We're gonna leverage the RAPPEL framework. So we're gonna make sure that as we're using any of these AI tools, we have the role define the action. We're priming it. We're prompting effectively. We're evaluating and using some rubric to get even better outputs. And we're learning from all of this. We're gonna create hyper-personalized content, stuff that's industry specific, that's persona specific, that's buyer focused, that's AI optimized. Brad Smith [00:50:14]: It seems Seems overwhelming to go from sending out one sales and marketing campaign to sending out 20 variations of that, but the AI makes this doable. And then we're going to look to build repeatable processes. So what can we do to build this into our recruiting, sales, marketing, buyer enablement, and automation processes? And with that, I'll leave it here. I don't think that AI is going to replace staffing firms. I don't think they're going to replace recruiters, but I think those that are using AI strategically are going to create a huge competitive advantage. If you can own the answer right now, if you can be the one that demonstrates that you understand the buyer better, then you're going to build authority. You're going to become visible where decisions are now made, where 80% of that decision happens. You're going to own that answer. Brad Smith [00:51:12]: And it's going to help prospects make better decisions before they even talk to you. Now, I know this probably all seems overwhelming, and creating all of these knowledge blocks and systems and processes can be overwhelming, and it is. But you can do it in your own AI models, or you can look for help too. And we've taken all of this and built this into our platform, RogIQ. So Starts by building out your company messaging and your brand and voice. We're looking at your target ICPs, buyer personas, competitor analysis. We're doing automated blogs, SEO, AIO, GEO, everything that I showed in those case studies. We're doing thought leadership content publications and building marketing analytics and marketing intelligence. Brad Smith [00:51:59]: So we've built this all into an agent to do all of this work for you. Now you can take all of these concepts, right, and build this into Your own agent. You can build this into your methodology. I think that's a great starting point. And then if you want to take that to the next level, you certainly can by leveraging a platform like this. So if you want to scan that QR code, it'll take you to a page with more information. You can even do a trial. But the key takeaway here is really that the more that you can do to educate the AI, whatever AI tools or agents that you're creating, around what makes you unique, the way better output you're going to get and the way more revenue you're going to drive. Brad Smith [00:52:40]: So with that, I'll open it back up. Any questions? And Kortney, I just want to thank you so much again for having us on and putting on this event. It's been amazing. Kortney Harmon [00:52:49]: Absolutely. Thank you so much for spending your time and being with us and such great information on your slides and your presentation today. I mean, heck, that's a question of a lot of people now. Like, How do I show up in the AI? How do I get my name to show up? It's just, it's funny the inputs that you're giving and what it's creating and how it's pulling it back out. Wonderful information. Love, love, love everything that you talked about today. So thank you so much for all of your information. Brad Smith [00:53:16]: Thank you. Kortney Harmon [00:53:17]: The question was, what is the best tool stack to enable this? Brad Smith [00:53:22]: Oh, great question. So I think there's several out there, right? I love Claude. I love to use that. If this is something that you're looking to build out across the entire organization, I think it It really depends on what platforms and what AI you've provided to your organization. I think you can accomplish a lot of this in various platforms. What we found internally though, is that each platform and each model does something really good. It's like staffing companies, right? Like not everybody's a generalist. Some specialize in a certain field. Brad Smith [00:53:57]: We find that same thing with LLMs and with different models. One's really good at ideation, one's really good at editing, one's really good at data analysis, one is really good at deep research. So I almost think you have to be somewhat agnostic. And like when we built our tool, RogIQ, we probably leverage no short of 100 different AI models. And I think that's part of the key. It's making sure that you're using feedback and information from different models to get a much better, deeper, richer, more unique response. Because anybody can use one model to get a response. Any competitor can do that. Brad Smith [00:54:41]: Very few are going to use multiple models and multiple rounds of revisions to get a very unique response. And I think that's where you really can dominate. And we've seen that, like in the examples that I shared, wasn't one model, it was multiple models. And that's why we built that in into our system. But I think you can do some of the same things if you're building out agents in different models. Kortney Harmon [00:55:03]: Love it. Well done. Overwhelming— or whelming, not overwhelming. Amazing. Brad, thank you so much for your time today, and I hope you have a wonderful afternoon. Thanks for joining us for this special Recruiting Evolution episode. As you heard, this session was originally recorded as a part of the FDE+ series, but going forward, you'll find these conversations under the new Recruiting Evolution brand. Make sure you're subscribed so you don't miss what's next, including new episodes, live sessions, industry spotlights, and Recruiting Evolution Expresses. Kortney Harmon [00:55:43]: I'm your host, Kortney Harmon. Thanks for being a part of this next chapter with us. Fresh ideas, future ready, and creating relationships that fuel growth.