Put Me In Coach featuring Jeff Toister

Speaker A: If you are unfamiliar with John Fogarty's center field, it was the opener to this episode, but for reasons it's been blocked.

Speaker B: And, uh, not just in a handful of countries.

Speaker A: It was blocked in most countries. So this episode opens without it here, but you can find the original recording over at YouTube. Many rock musicians have been honored as inductees to the Rock and Roll hall of fame, but John Fogarty's 1985 hit center field got him honored by the National Baseball hall of Fame. Today, it's a fixture at the Baseball hall of Fame in Cooperstown, New York, and just about every other ballpark across the country. Baseball and its heroes have been mythologized as a deeply American tradition. But like anything else, it has evolved with technology, even so far as to use an automated ball strike challenge system in the major leagues. As of 2026, while technology is continually being introduced in sports, humans are still at the center of the action. Sports are hardly the only domain where technology has continued to drive change. Customer service interactions have long evolved as new technologies have been introduced to contact centers. AI bots or virtual agents are simply the next evolution. But humans should still be at the center of the action, says Jeff Toister. Jeff's authored five books on customer service, and this year he was inducted into the ICMI hall of Fame. This week on NEXT inq, we discuss the human element in customer service, the impact of greetings on customer experience, AI and customer service opportunities, and concerns the evolution of AI and human interaction, creating human connections and customer service, the role of AI in routine transactions, skills unique to humans in customer service, and the future of AI and human collaboration. Let's get to it.

Speaker B: Jeff Toyster. Finally. Finally. You are next in queue, my friend. How are you?

Speaker C: You know, uh, that hold music was pretty awesome. Can I just finish the song and then we'll come right back? I'm. I'm kidding, Rob.

Speaker B: It's great. You cannot m Once. Once you are off hold, you remain off hold, and you have to talk to me instead. Unless I escalate. Okay, then you'll talk with someone else.

Speaker C: It'll be a different song by then. It won't be my jam anymore.

Speaker B: That's right. That is right. I. Listeners of this podcast will surely know who you are, but let's assume they don't. Folks. Jeff is a speaker, an author of many books and courses, a consultant, a, uh, customer service trainer, an ICMI M Hall of Fame famer.

Speaker C: That's a thing now?

Speaker B: Yeah, that is a thing. Congratulations on that. It was quite the honor. Like, you've done a lot of stuff over the course of your career and you actually earlier this year, another book, Human Service, the Skills that AI Can't Replace. Congratulations.

Speaker C: Thank you. I really appreciate that. I'm excited about the book.

Speaker B: Yeah. So let's start there. Why did you write this book?

Speaker C: I think two reasons. One is I've talked to so many customer service, contact center, customer experience leaders who are really struggling with AI, and the question is, where does it make sense to use and where is there still going to be space for humans, human employees? And so rather than tackle the technology side, which I think is well handled, I wanted to tackle that human side of the question. The other side. The other reason is I think there's this really dangerous middle ground that will hopefully start shrinking. So on, on one hand we have things that we're automating and when automation works, it's awesome. And on the other hand, we have these really human experiences where we can point to this particular person. Made my experience so much better. So there's human value. The middle ground is that that agent who. Or that person who acts like a robot, they're, they're living, they're breathing, but they add no human value. And I'm not sure why we're employing them. We. We should just automate that or ask them to be more human. And a big part of the book is how do we get rid of that middle ground and find those places where being human makes sense? And then what does that look like?

Speaker B: M. Yeah, yeah. I see this on a regular basis. And it's. It is apparent at the very beginning of a call, if it's a call. And let's be real, this can happen across other channels as well. But it is literally the moment they answer that phone and the greeting, you can tell they say that greeting 30 to 50 times a day. And it just, they roll through it so fast that you can barely tell even what was being said. And that really just sets the stage for the kind of interaction that is probably going to feel robotic.

Speaker C: I have some early data on greetings. I did some work in person because I wanted to see the impact of greetings on people. And a good human greeting, it turns out, has a significant impact on our customers demeanor. You could see that in person. I observed over 400 interactions. Now I'm working on phone greetings. And early data shows exactly what you're saying, that that robotic greeting, it leads to worse outcomes. But a good human greeting not only makes customers happier, the surprise is that it is shortening Calls. Hmm. And one of the reasons for that is a good greeting automatically makes you feel like this person's got you. They understand you. This is, this is going to be a good interaction. So customers give over control and they trust the other person faster than if we have a, uh, bad greeting and a bad greeting. I'm sure you've experienced this. I'm sure your listeners have. There's kind of two flavors. One is the person who, like you said, it's the 50th time they've delivered it today, their energy is gone. And the second is the corporate standard is either something ridiculous like, I, I've actually heard, uh, how every day is a great and wonderful day. How can I make your day great and wonderful today? Like, no one says that. No one talks that way. Don't make people. That's just soul crushing. But then the other corporate greeting is. Let's start with an interrogation. Hi, this is Jeff. I gotta get your name and phone number, please. You don't start normal conversations that way so that we're already starting off in the back on the wrong foot with that stuff.

Speaker B: Jeff, that's how we start every conversation. I don't, I don't know what you're talking about, but that's how I start conversation. In fact, I didn't get your account number, so I am probably out of compliance. So I'm going to need you to provide that to me right now before I can talk any further with you.

Speaker C: And you, you just sent me a text, so I, I have to read back the code so you can verify it is me. And you don't actually need to access my account on this call. I just wanted to ask you a question.

Speaker B: Yeah, no, that's cool. Yeah, it's, you know, there is certainly when it comes to compliance, there are things that we know. Hey, I have to get this as an agent, and I'm doing it to protect you, and that's fine. But I also think that there is an opportunity for us as an industry to provide that context to customers if in fact that's the case. Right. And so it's as simple as saying instead of, I need you to verify your account number, it could be to protect your personal data. I need you to verify your account number. That extra half second changes the narrative a little bit because it gives you my intention of why I'm asking for this.

Speaker C: Yeah. And let's, let's deliver it the way humans do. So as an example, I fly Alaska Airlines a lot. I travel a lot. And on the Rare occasion I have to call. For some reason, the way they answer the phone is, hi, this is Jeff from San Diego. Who do I have the pleasure of speaking with today?

Speaker B: And of course you would say, this is Rob Dwyer. How are you?

Speaker C: Hey, Rob. How may I help you? Like what? That's, that's like humans. And then if we need to validate something, then you're absolutely right. Let's say it like humans do. Hey, Rob, I just need to verify your account for security purposes. Can I get your account number or your mileage number or whatever it is? But now we're talking like humans, and there's a lot more cooperation, which is again, what leads to better outcomes, shorter phone calls, so it's more efficient, and we're all happier. The agent's happier, customer's happier. We don't feel like robots. It's such a better way to do it.

Speaker B: Now, I have to ask. I work for a company that provides AI services to contact and support centers. We do this across the spectrum. But I'm curious to hear your perspective. Like, number one, do we have something to worry about? And number two, are you concerned that humans are just going to go away when it comes to customer service?

Speaker C: So the second answer is no. Their roles are changing and there's going to be more complexity for the agent role. But that's not something that started with AI. I mean, that, that started with, with earlier forms of automation. As a very simple example, a password said that, uh, used to be a phone call. It hasn't been a phone call for a long, long time unless something went really, really wrong.

Speaker B: Right?

Speaker C: So I think that trend just continues now. Should companies that sell AI products be worried? Uh, no, not at all. I think AI is the wave of the future in many ways. What I've discovered is that AI, like everything else, is a set of tools, right tool for the right job. So if your. Works really well for specific use cases, you're going to do well. If it doesn't work well, or, uh, your customer base consistently uses it for the wrong use cases, that's more of a problem. And even I think, in the customer service space, we're consistently seeing customers push back against AI. Customer facing AI. And one of the reasons why customers dislike it so much is their early experiences have been miserable. You get an AI bot and you ask a question like, what time do you open on Saturday? And the bot's like, I do not understand that. Please try again. You're like, well, Saturday, open time. And they're like, I do not understand that how do I get a hold of customer service then? And no, I will help you. You're just like, ah, uh, so those types of experiences cause customers to say, I don't even want it deal with. Yeah, yeah, there's plenty of good use cases that are working quite well.

Speaker B: It reminds me, and this wasn't customer facing, but it reminds me, many years ago I explored automating quality in the contact center that I led training in quality for. And this was, you know, pre2020. Right. We're probably talking 2018, 18, 2017 somewhere in that neighborhood. Right. So good Lord, almost a decade ago. I can't believe I just said that. And there were solutions out there that were trying to accomplish this. And what I found was that the transcription was so bad at that time that I just could not rely on this to give a score because there was no way that I could trust, even at a basic level, that this transcript actually is a reflection of what happened on the call. Right. And so my early experience with this kind of technology was just like, this is awful. No way. And what we've seen is this acceleration of abilities in ASR. Transcription now is way better than it was back then. But the early adoption of a technology and kind of that infancy stage can definitely give you an attitude about it. And that was the attitude that I had about transcription. Like, no, it's horrible. I, and that attitude didn't change until probably, uh, 2022 maybe. And then I saw, oh, no, no, no, transcription is, is pretty good there. And we've seen the same thing with customer facing AI bots and, and in some cases even lawsuits associated with that. And I think there maybe some people hopped on that bandwagon a little too quickly.

Speaker C: It's, it's interesting you mentioned that because one of the, the things that really has caught press is like when AI hallucinates. And I, I have kind of thought, well, are we spending enough time talking about when human agents make stuff up? Because that happens too.

Speaker B: Yes, yes it does.

Speaker C: But to your point, the tools have gotten better with transcription. What's interesting about it is it's gotten a lot better. But there, there are, and there's there's kind of two things that really stand out for me. One is that even today I still needs training and calibration, just like your manual QA does. We need to make sure that is reading the call or the chat or the email the right way because there's a lot of nuance involved and, and that nuance can sometimes trip, uh, AI up If I say the same words, but one is sarcastic and the other is kind of straight, sometimes AI is like, whoa, what did you mean by that? But the, the other side of it, I just saw some data that shows when we are transcription is really, really good. And we're able to use that transcript to automate after call summaries. So the agents just have to review and maybe lightly edit. Not only does it cut down on the after call work that agents have to spend, talk time goes down. And talk time goes down. Because if agents no longer have to be listening and keeping up with notes during the course of the conversation, they can just focus on the conversation. So as the tool's gotten better, it's enabled humans to actually be more human in those moments when customers need them to listen.

Speaker B: Yeah, absolutely. And the insider in me knows that we have for years trained agents to type your notes while you're on the call so that you don't have after call work. And oh, by the way, maybe we're going to limit your after call work artificially, right? So maybe you only get 30 seconds or 60 seconds of after call work, no matter how long you need. Like you're gonna go back available and another interaction's going to come. And so when we put the artificial constraint at the end of an interaction, the agent of course is going to. Hey, Jeff, do you mind, uh, if I put you on a brief hold one moment? Because I need to, I need to talk with my supervisor.

Speaker A: What am I doing?

Speaker B: I'm, I'm typing up notes sometimes, right? I'm, I'm trying to make sure that by the time we end this call that I don't need extra time because I probably want some time to breathe, quite honestly. Because what we do to agents often is we just, we put them available again and if there is no wait in that queue, then bam, that next one is, is coming right through. And so it totally makes sense if you understand agent behavior and that agent behavior is learned because we want them to do that, to reduce that after call work, that talk time is going to go down. If all of a sudden I go, oh, I don't have to take notes anymore, it's great. I can actually just focus on conversation.

Speaker C: Uh, I think you've pointed out one of many things that contact centers have traditionally done that causes agents to dehumanize the service they provide. Starting with that greeting. We give them this clunky greeting that no one would ever say. We train them not to connect with customers right out of the gate. But here's the process. Here's the call flow or the contact flow. Here are all the seven or eight or 20 different tools and screens you're going to need to solve this one issue. And here are the parameters. Here's how much time you have to do it. Like all of these things point to. You are a factory worker and a customer service factory versus you are someone representing our brand in this critical moment for your customer. And your role is to probably rescue an experience that hasn't gone well and help it go a little bit better. We've taken that out of the equation. No wonder we get less than human results. And I think there's an opportunity for the contact centers that do it right and create more humanity. What I'm finding is you're actually getting revenue improvement, more loyalty and more efficiency if you are allowing humans to be humans in those moments of need.

Speaker B: Yeah, yeah, it's, it's fascinating and I think those of us in the, in the business need to always remind ourselves that there's ultimate conversation is a human to human conversation. Yes, there are things that we can, we can automate but when, when the really challenging issues get resolved, it's usually a human to human issue. And we should want the person representing our brand to sound like a human. Absolutely.

Speaker C: Wouldn't that be nice? Right. I know there's people in marketing freaking out because they're like. But they have to use the brand words and sure. But those things are, they're trainable. We can create good guidelines. Those things are all doable. But you're right when, when people sound human like there was one. This is a, I think just such an interesting example of. I talked to a company and I wrote about them in the book and they said it was okay. So I want to be clear about that. This company called Headset Advisor, which does exactly what it sounds like, they advise you on, uh, what headsets you need to get. I'm a customer, uh, so I'm a big fan. But, but they did something that a lot of small companies have done, which is they thought maybe we can be a little more efficient by using AI to handle pre sales chat. So I'm on the website, I'm not sure if I've made the right selection. I'm lacking a little confidence. Can I get some help making a final decision? And so they went all AI on that and in that moment they discovered that customers really hated it. They were really upset about it. The satisfaction rate was like 12% with, with that chat. So to their credit they said oh, this is a big problem. Let's put humans back into the mix. And they eventually went all human because they recognized in this particular moment, I need someone who's actually used a headset who can speak to those types of needs. And they found that satisfaction went up to 90 plus percent. But here was the most important part. Conversion rate doubled. And with an average order value of $300, if I'm doubling my conversion rate by paying human agents to be there in that critical moment of need, that's a good business decision.

Speaker B: Yeah, absolutely. The proof is in the pudding, right? And there are all kinds of variables. I'm wearing headphones, could be a headset, but does not have the boom mic. But it does have a mic. One of the things that I find about these in particular, and I've worn lots of different headsets over the years, is because I also wear glasses. Like, they push against the temples of my glasses and they can be uncomfortable for long periods of time. These are the kinds of little insights that sometimes, yes, you can get AI to go through these questions, but having someone who can say, I really like this headset because I happen to wear glasses and I don't get a lot of pressure on the glasses when I'm wearing this particular. Maybe it's a, uh, one ear style or whatever the case may be, I think there's a lot of value in that. I wonder, besides that, like the actual experience, are there skills that you think right now only humans can really bring to the table and AI just isn't cut out for it yet?

Speaker C: I think there's some skills where humans have an advantage and AI is doing a better job every day at emulating some of these skills. I think humans will always have this advantage if we're using them correctly. So three areas I looked at. One is connection, that ability to. From the moment you start a call or an email or a chat, it's that feeling like, I got you, I'm connected to you, and you feel as a customer, this, this person's looking out for me. That's something that, that AI can emulate by being a little peppier or the way it uses dialogue, that's getting better, but a real human connection, that's, that's a different level. The second area, I think is that understanding. And your example with the headphones and glasses is a really good example of understanding at a very different level. That's, that's empathy. That empathy comes from having a shared, relatable experience. AI doesn't wear glasses. It doesn't Know what it feels like to try to adjust headphones to fit just right so they're comfortable over a long period of time. So humans do a better job of that, especially of getting that understanding of intent. What is your goal? It's headphones that are going to be comfortable over a long period of time, given my circumstances. The third is advocacy. Advocacy really means I am actively working to help you have a better experience. AI doesn't want you to have a better experience. It just follows its programming. Humans are really, really good at identifying kind of nonlinear ways to get to places, or counterintuitive solutions or just kind of interesting shortcuts that might be hard to decipher. And this is especially true when systems break. So one of the things that I wrote about, uh, in the book is the experience I had where I, I left my jacket in the backseat of a rental car. And by the time I got home and I realized it, I tried to get my jacket back. I went through five humans who, ah, not, they weren't human. They were these transactional kind of robot people who just were completely unhelpful. But the whole system was run by AI and it was broken, it didn't work. And all I needed was one person to say, you know what, I'm going to contact the rental car facility and we'll get you your jacket back. Because I knew exactly where I left it, but because the system was broken, I just couldn't handle it. So I think we humans will always have an advantage in those skill areas, even as AI closes the ground, especially for the more routine stuff.

Speaker B: Yeah, yeah. I mean what I hear is edge cases are always going to be human led or, or should always be human led. And you even see this in like self driving cars. Right. There are great self driving cars that can handle most of the normal stuff. Right. 95% of what they need to do in say the Bay Area, like Wayos, they can get you where you need to go. But then there are these edge cases that crop up and all of a sudden they don't know what to do. And recently they had a power outage across the entire Bay Area and all the traffic lights were out and the waymos just stopped at intersections all four ways. They didn't know what to do. Right. And we know as humans, even though that this is a weird edge case that we would almost never run into. Like we would figure it out, we would go, okay, well the person to the right of me is going to go. And then once that clears, I'll go, we'll just treat it like it's a four way stop, even though it's not a four way stop. Like we, we can extrapolate those rules. And the Waymos hadn't learned that because

Speaker A: it was just such an edge case.

Speaker B: And I think that's a um, a really good illustration that you brought up. I wanna, yeah. Be.

Speaker C: And before you get the, in that example, I think you know, then the programming will be well now we'll program them what to do for that, but then the next edge case will come m up. And I think sometimes that's missing in the design is just an escape hatch to say, well, if we encounter something unusual, how do we get a human involved? Yeah, for those situations. We don't need a human for everything, just for the situations where AI can't handle it.

Speaker B: Yeah, it's time to escalate. Escalate to a human. You talked about making this connection and experiences that we can share and that leads me to talk to you about something that I'm a little jealous about and that is that you have visited all 30 major league parks. We need to talk about this for a little bit. I have not been to all 30, but I definitely keep track. What is your favorite baseball park in the US and, or Canada?

Speaker C: Okay, well, so I, I have to give you two answers for that because if I think of it from an experience perspective, the whole package, the facility, the fans, the food, it's, I'm probably going to a Giants game in San Francisco.

Speaker B: Okay.

Speaker C: And because there's everything involved, if I'm thinking just the ballpark itself, my hometown of San Diego, that's, that's the best ballpark. And in fact in recent years the fans mysteriously have gotten way better. Used to be if you went to a Padres game in San Diego, people would not be paying attention. That fans were kind of listless, they were not really into the moments of the game that mattered. And now it's changed significantly. So they're, they're closing ground quite a bit. But uh, for me that's the. Like an outlier is Fenway park in Boston. If I'm just judging the ballpark, it's, it's not very nice. It's very, very old. But if, if you told me I can only go to one baseball game, it would be Red Sox versus Yankees at Fenway. Because the experience with the atmosphere and the fans is just phenomenal. It's unbeatable. So experience is a weird thing, isn't it, that there's multiple things that you, you take into Consideration.

Speaker B: Yeah, I love that. So I have not been to a game in San Francisco, but I have been by the park, actually, very recently. What a setting with the water right there. Just a beautiful park. Been to a Padres game also. Amazing park. In fact, I still have a San Diego pullover, which is weird, but I needed to get one because it was unseasonably cool in the summer in San Diego. And I was like, it's. It's kind of cold out. I think I'm gonna have to get a pullover because I didn't back for this trip appropriately. But I love that you brought up Boston. Like, Boston has actually some of the worst seats in all of M. Like, you have obstructed view seats where you are literally sitting behind a support that is holding up the upper deck. And yet there's just something, uh, historic feeling about being there. And the way that that park is so unique, where it's situated inside of Boston is. You just can't replicate it.

Speaker C: It's. It's pretty amazing. And. And full disclosure, I used to live in that neighborhood and went to a lot of games at Fenway and will always have a fondness for it. But you're right. There's supports that are blocking seats. There's a lot of mysterious puddles in the stadium that I think there's some drainage issues from. It's built on a marsh, so we don't need to get into that. It's. Go to a game at Fenway if you get a chance. That's really what the bottom line. It's a good experience.

Speaker B: St. Louis used to have that actually on the field in the outfield in the old Bush Stadium. So, you know, some parks experience some. Some weird moisture issues in weird places,

Speaker C: but the new Bush Stadium's quite nice. I've enjoyed a ball game there.

Speaker A: It is.

Speaker B: It's beautiful. And, you know, the view of the arch is pretty amazing. I will tell you my favorite newish part is, uh, in Minneapolis, the new Twin Stadium is just, um. It's just a really great experience. They did an amazing job. I lived there when they played in the Dome, and I refused to go to a ball game the entire time I lived there because I was like, I am not going to that place. But once they built their new stadium, it is a fabulous place to see a ball game.

Speaker C: I agree. Target Field is. Is. Is well done. I had a good time there when I visited.

Speaker B: Yeah. Yeah. Okay. So we've talked a lot about when humans make more sense than AI or when they have an Advantage. But I'm curious to hear your perspective on where does AI have the advantage? Like, what situations do you see? Like, yeah, that's probably where AI fits better.

Speaker C: Well, there's a lot of places behind the scenes where AI is doing a lot of work. You know, just talking about the transcriptions, for example, or instead of sending a survey, we're going to do a sentiment analysis on 100% of contacts. With unstructured data, there's some huge advantages there. But specifically for customer facing AI, I think it works best when three conditions are met. One, confidence. Customer is confident using AI. Your example from earlier, like an early adopter having a bad experience, it makes you not want to try it. I think for a lot of customers, that's their experience with a bot or an AI voice assistant. And if they don't want to try it or they don't feel AI can help them, we shouldn't force them. There's been several studies that have said being forced to use AI without an escape hatch is a miserable experience. And I've seen data that shows that customers are more willing to try it if they know they can reach a human should they want to. So confidence is huge. Second, routine transactions are way better. I think a lot of operators who, uh, are just getting into AI are discovering you have to train AI, you have to monitor AI, you have to calibrate AI and routine transactions. It's easier to do that because I know this is what good looks like. This is what not so good looks like. The policy, the procedure, the workflow. So routine works a lot better. And the third is predictable. If I ask AI, what time do you open on Saturday, or what is your return policy, or any question, it should return a predictable result. And if, uh, it encounters the same scenario with exactly the same parameters, it should deliver a predictable level of service. And if it does, then it works quite nicely. If it doesn't, not so much. So if you think about confidence, routine, and predictability, that spells crap. Automate the crap that your customers don't want to wait around to get a human to help them with, and automate the crap that, frankly, it doesn't make sense to pay an employee to deal with over and over again. Just focus on automating the crap with AI and you'll be okay.

Speaker B: How long did it take you to come up with this acronym? Because I love it.

Speaker C: Not as long as you would think, because it kind of found itself. And I will tell you that AI played no role in creating that acronym. That was all human.

Speaker B: I love IT folks, automate the crap. And if you want to learn more about how you can automate the crap, call me. But if you want to learn more about empowering your agents to be more human, if you want to learn about how you can evoke that human connection for your brand and for your customers, like, Jeff is the man. He can help you with this. He's been doing it for decades, literally. I don't want to age you, Jeff, but I know it's been, it's been a minute. If someone wanted to talk to you about how you might be able to help them, what's the best way for them to get in contact with you?

Speaker C: Well, I'll, I'll give you three options. One is my customer service tip of the week. It's an email with one tip once per week just to keep you and your team skills sharp. All of those, it's of course automated but. But all of those emails, you could reply to any one of them. It goes right to me. And I put my personal phone number in the footer of every email. So that's@tolutions.com tips. The second place is I need to grab the COVID I'm gonna do the COVID shot here. I realize we're video. Here we go. In all of my books, including human service, I put my personal contact information. So this is the guide on the human skills that you need. If you want to check out the first chapter of the book and read about my miserable experience losing my jacket and how AI made it worse, uh, you could go to human servicebook.com and, uh, inside this book and on the website you can get my personal contact information. Probably the last place where I share a lot of the more cutting edge research and insights that I'm seeing is on LinkedIn. So it's, uh, you know, I'm Jeff Toyster, so that's nice. I have one ask though, for people reaching out via LinkedIn, and that is to please be human. And what I mean by that is, uh, you have no idea how many connection requests I get from strangers every day with no note, no context. I don't feel that's very human. What I think is human is when people interact with each other or anyone could message me. I've set up my messaging so it's open. My, my personal email is connected to my profile. Let's actually have a conversation or share some value with each other and be human that way. So you can reach me in all these ways. I just ask, please be human.

Speaker B: And I can personally vouch the first time that you and I connected, you actually held off on the connection acceptance.

Speaker A: I sent you a connection request and

Speaker B: you were like, hey, I will accept this, but only after we have a conversation. And you and I hopped on the phone, we set up time to talk and got to know each other. This was years ago. And once, once we did that, you were like, okay, now I'll accept this connection. So he's not lying, folks. He very much wants to have a real human connection, a real conversation, and is willing to do that old school thing where we actually have a phone call and talk to each other, which you and I also did recently. So just know that that is a, ah, that's a. It's a real thing.

Speaker C: He's.

Speaker B: He's real like that.

Speaker C: I'm a real human and I keep forgetting when we're on video, so I gotta stand up just a little bit. The T shirt proved that I am a certified human. And I can say I'm certified because I've, I've made that claim. So now it's true.

Speaker B: You get a hundred percent human quality score. So, folks, you know what to do. Down in the show notes, you'll find the links that Jeff just talked about. Reach out and connect, but be human about it. Don't just blindly send him a connection request. Go check out the website. He has not just this book, which this book is good, but he's got like four other books that you can check out. You can find ways to order those, uh, directly on the website. Jeff, thanks so much for joining me on NEXT inquest. This has been great.

Speaker C: Rob, it's been my pleasure. I appreciate you having me.

Speaker A: NEXT INQ is produced by me, Rob Dwyer. The music is courtesy of Red Horse. If you enjoyed this episode, please share with at least one person. Word of mouth is the best way for people to discover new content and thanks for listening.