Rewiring CX: Bill Staikos on Human-Centered AI and the Future of Experience Leadership

Speaker A: For 20 years we've been creating innovation in the CX industry and now we're seeking out brilliant new perspectives on CX you just won't find anywhere else. I'm Richard Owen. Welcome to the CX Iconoclast. In this episode of the CX Iconoclast, we host Bill stakos, a uh, CX and ex leader with more than 20 years of experience helping organizations move well beyond dashboards and into delivering tangible business outcomes. Drawing on his unique perspective from both the vendor and buyer side of the industry, Bill shares why too many companies are still stuck in outdated models of customer experience focused on surveys and metrics rather than designing solutions with customers at the center. Our conversation covers the pitfalls of product led growth thinking, the impact of AI on both customer experience in the workforce and um, why the best companies are those that operationalize CX in partnership with technology, operations and employee experience. Bill argues that success will come from an action orientated, integrated approach rather than perhaps overcomplicated frameworks. We discussed the risks of short sighted cost cutting in the AI era, the importance of moral responsibility towards employees, and the opportunity for AI to help organizations finally break free of decades of CX mediocrity. I do hope you enjoy our conversation, but before we start, a quick word on the exciting new program we've been working on. The Customer AI Masterclass. As you know, I've spent my career helping companies grow through customer experience. Twenty years ago my team co created the Net Promoter score and in 2008 we launched the Net Promoter Masterclass which trained over 6,000 companies worldwide and became the gold standard for CX certification. Now we're taking the next step. The Customer AI Masterclass is built for CX success and revops leaders who want to harness artificial intelligence to predict customer loyalty and outcomes, reduce, churn and deliver measurable roi. It's the natural extension of everything we've learned about customer led growth and it's built for the next generation of leaders. Start your free trial today@customeraimasterclass.com and be part of the future of customer experience. Well Bill, thanks very much for joining us today and welcome to the uh, CX Iconoclast.

Speaker B: Well, it's wonderful to be here, um, and good to see you. Well, at least this time on video. Last time we saw each other we were in Lower Manhattan.

Speaker A: In Lower Manhattan in a very nice, uh, sitting on the street there, which there aren't that many street side restaurants in Manhattan I don't think where you can kind of sit out there. It was it's quite a remarkable thing to sort of catch the street atmosphere

Speaker B: in these cities and while drinking Manhattan's too. At least I was. Yeah.

Speaker A: Which was your hot tip for the restaurant? A good tip. But if you can't get a decent Manhattan in Manhattan, then we're talking, I don't know, what's the point?

Speaker B: Yeah, that's right. That's exactly right.

Speaker A: Um, well, and you know, your bio, you know, reads like again, industry veteran, you've worked on both the sell side and the buy side, if you like, of the whole CX industry, which I think is always a fascinating perspective. Right. And maybe we can stop there because poacher turned gamekeeper or gamekeeper turned poacher. When you think about your experiences from both sides of that, are there any sort of, um, things you've learned from going from both sides? I mean, obviously you become much more equipped to operate on either side of the table when you've had experience from the other side. But any observations that sort of spring to mind when you think about those two perspectives on our industry?

Speaker B: Yeah. So, uh, I love that question, by the way, Richard. So a couple of things. One is on the software side, no one knows what the hell is going on on the buyer side. Just sell the software, get it implemented and move on. Right. And I mean, I'm simplifying it or generalizing it, but the complexity of A, getting software approved, B, making sure the resources have what they need to actually go implement it. Getting the buy in from multiple stakeholders, getting your risk and compliance teams comfortable with the fact that you are going to pump sensitive data through these experience platforms, um, getting those approvals, getting budget approval, then making sure that the budget isn't locked up in some weird decision making process because the economy's not doing great, um, all while the salesperson's peppering you with questions all the time like, hey, where are we on this? Hey, you've got 30 days and I can't commit to this price anymore. I'm like, hey man, buzz off, I got shit to do. Sorry. I don't know if we can curse on this show or not, but, um, this is number 10 on my priority list of 10 things and I can't devote that much time to this. It's going to get done, it'll get done when it gets done and it'll be great for you, for us, but we need the space on the client side. Um, I think what's interesting is it depending on the company, um, because there are a lot of even enterprises frankly that are still in sort of a nascent state. Uh, uh, on the CX side they don't know what they don't know. So they kind of see this as like an expensive piece of software and do we really need it? And now unfortunately you get, well, just can't AI do this for us. And you're like, well, uh, not really, unless you want to go hire 20 engineers and we can go do this work. So I think the AI conversation has really changed the game in terms of do you need the software and what is this really for, who's going to use it, how are they going to use it? Um, but I think what I've learned at least on the enterprise side, that it's never. Technology is never the answer, it's always the question, right? Like what problem do we need to solve and does this piece of technology solve that problem? That's the question. And um, I think if you can help people understand the problem to be solved, get um, them sort of motivated around that kind of vision or shared understanding or shared purpose and help them see sort of the journey to get there and implement this software and how they're going to use it. Um, I think that there's a lot of success when that doesn't happen. And I've seen this on the seller side and the buyer side when that doesn't happen. Unfortunately you've got shelfware and you've just spent seven figures on something that nobody is using. And then three years later during renewal you're like, why the hell do we even have this?

Speaker A: It's funny you say that. There was an um, interesting piece published by Andreessen Horowitz recently in the context of artificial intelligence technology and they were talking about the role of services and bear with me, I think this connects back to what you're saying. Their basic thesis was that the venture community decided maybe as long ago now as 20 years ago that the best venture investment was a sort of product led growth strategy. The PLG strategy was basically find customers who will sign up for a piece of subscription software, switch on, ignore them, come back for the renewal. And the only sort of evolution of that was, well, we'll hire some success managers to check in on them, make sure if they're not using it, make sure that we understand why they're not using it, which is very infrequently a productive exercise, but it shows willing. And this whole PLG model became the dominant mindset for venture investors, which means the dominant mindset for how companies get performed. So almost all the technology companies for the last 10, 15, 20 years have been baked around the idea that number one, contact with the customer is an expense. Services are toxic to the P and L and a bad thing. Software needs to be hands free, touch free. Uh, and so we've trained a generation of technology innovators to think that way. And Horowitz to their credit, sort of said, well if you actually look back at the previous iteration of technology, cloud based, the sales forces and the work days, for example, they were extremely adept at hand holding their customers in the early days. Now ultimately that service footprint might have been outsourced to consulting firms, but there was no sense that you sort of topspin lobbed a piece of software over the wall and the customer was supposed to figure it out for themselves. And their argument was that artificial intelligence for a couple of reasons. First of all, any product in this cycle starts with requiring a lot of hand holding. And secondly, AI because of its fundamental nature where you're teaching a machine and the machine is like a seven year old when it starts and eventually it becomes an annoying teenager and then if you're lucky becomes a half decent adult. If a machine's going through this curve, you need to stick with it. You need to be mhm, driving them. So I wonder whether or not we're seeing sort of companies, given what you just said, uh, start to reevaluate what they're looking for in partners and technology almost back to the 70s where it was like look, we want companies that can help us get results, we want handholding, we want good service. This whole PLG thing's worked well for investors, but it hasn't really worked well for us.

Speaker B: I think that there is an interesting thing happening. So one, I think you're right. I think um, well first, uh, maybe not today, but let's just say in the next two to three years. I think the system integrator and the onboarding kind of work around software goes away. Onboarding, you can easily see that being an AI can do an hour is what would take people or team months to actually go implement a piece of software. Right? Um, number one, number two, I think the system integrator work kind of goes away for similar reasons. I think that what's really changed one and that I've seen uh, on the buyer side more recently is that one, the people involved and I mean I've never had more conversations with engineers in my career than over the last year plus and I was having a conversation just last week with someone and they're like, well, who's on Your team, how are you guys approaching this? And they were blown away that data science, data architecture, data engineers, front end visualization folks. I think that the people involved in the conversation are fundamentally different, number one. And the people that are involved are used to technology and having people sort of engaged in that conversation and helping them through. But I think it's a different conversation. I think it's about how do I make sure that, whether it's an AI, um, piece of technology or otherwise, how do I make sure that I get my value out of it. And the use cases, one, what do you think are the use cases? But then if these are the use cases, great. How do I make sure that they come to life in my organization? So I think that conversation is just different, um, today. And I think over time what you'll probably also find is the way that these, the software is implemented as well is going to fundamentally change. Because I just think about my time on the software side. We have teams of people sitting with our clients go implement this software. And I look back on that work now I'm just like m, that's going to be really different in three, four years. Right.

Speaker A: They were more like skilled artisans. Right?

Speaker B: Totally. Right.

Speaker A: It was just an art. And that in of itself is kind of counterintuitive why manufacturing had gone through this renaissance when we stopped building vehicles as if they were an art form. Because that was unreliable. The notable exception being the British auto manufacturing industry.

Speaker B: I can attest to that. By the way, Richard, I own one Jesus.

Speaker A: Which has managed to sustain a legacy of kind of handcrafted vehicles that rarely work. Uh, but everybody else kind of went the Japanese model which is, look, everything's Six Sigma, everything's within parameters. It's very proceduralized again to the software industry. And it still feels like this community of skilled artisans that sort of get around a table and do their thing and the results are extremely imperfect. Um, and high failure rates. Right. I mean they're quoting 80, 90% failure rates for AI, which sounds shocking, but you remember that CRM systems still have something like a 40% failure rate and they've been around for 30 years.

Speaker B: Yeah, no, I think that I'm not shocked by the AI failure rate yet. There's so much kind of still test and learn. Feel your way through the dark on this stuff. One, I think that sort of the talent isn't fully there. Um, number one, I think that certainly the capability is there, but I think people are really starting to still explore how do I even use this in my day to day Balance that with the fear from users like, oh my gosh, I just created a 20 page deck that I can send to my CEO within a matter of minutes. What does that mean for my job? I need to kind of make sure that I didn't tell them I built this with AI, otherwise they could look at me and say, well then you're replaceable. Right. So I think that I think talent. But then sort of this fear of what does this mean for me because it's super powerful and I need to hide the fact that I'm using it successfully. I'm not surprised by that. Although I do think it's lower, generally speaking. I just think people aren't admitting to the fact that they're using it successfully just yet.

Speaker A: Oh, there's a sort of, uh, under the table AI industry, people stealthily. It brings us to perhaps a bigger topic, which is, and I'm fascinated by how this has evolved. You have large company CEOs, most noticeably Andy Jassy at AWS and uh, the CEO of Ford Motor Company who for some reason thought it was a good idea to come out and say 50% of white collar jobs are going to be eliminated by AI. Which I suppose there's a lot of blue collar employees at Ford who might be cheering that on. It's like, finally, finally we get some revenge for this.

Speaker B: Yeah, happy hour at the pub is happy again, as they say. That's right.

Speaker A: We're starting this narrative that AI is going to be amazing because it's going to put all you people out of work. By the way. We're really looking for the company to adopt it and be innovative with it. Um, this seems like an exercise in absolute, uh, self fulfilling disaster. Tell your employees that they're going to lose their jobs to AI, but they better get going and figure out how to use it more effectively so that they can, what, self eliminate their own positions before the company gets around to thinking about it. I mean, is there a plan here? Are you spotting some cunning strategy that I'm missing?

Speaker B: I don't think there's a strategy. I think that these headlines are great. Clickbait. I think when it comes down to reality, I think it's a really, uh, dangerous narrative. Um, the company that let's go 50,000 people out of 350,000 and doesn't do anything with that just leaves the hole. There is a company that's run out of ideas. If you're an equity holder in Ford, I'm shorting Ford all day long because that company just needs to Cut costs at all costs. And it's like, well, you're not really creating better cars or you care. Go take the 50,000 people and go hire better engineers and designers to create the next great product. Right. Um, fill that hole with something productive. Um, more salespeople, whatever that might be. I think that the narrative is really dangerous. I also think that there's this weird thing happening in the marketplace. And I see this, um, colleagues of mine at other institutions, you've got this senior layer somewhat being. Yes, senior people, white collar are being let go. And then you have sort of the lower end or the younger just out of college, not finding jobs because of AI, particularly if you're in engineering. Gosh, it's like, forget it. Um, and there's this weird middle that is like, oh, what are we going to do with all this? And companies are like, the line has to come and meet somewhere. Right? And like, AI can't keep on pushing the bottom up and the top down because sooner or later you're not going to have anybody. And it's like a. I can't do this whole thing. I think where companies are going to realize they, um, have made a mistake is that AI needs institutional knowledge to go make good decisions. Like, it needs context. And if you get rid of the context, you just can't say, well, build me a great website for my new podcast. Like, okay, fine, it could probably do that on some level, but without, like, real context about, who are the listeners? What is your show about? Look, what is your background? What do you want to be talking about on the show, et cetera. I think that the AI just creates what it thinks is a good solution. Whether that is the right fit for your customer or not is irrelevant at that point. And I think what will happen is then the people that sit back and say, well, who has that context? And how do we motivate them and reward them in new and different ways to operate in this new environment? Um, and then put those things into place. Yeah, I think that there's going to be displacement, but the whole notion of AI is going to take 20% of the company's jobs. I just think that is a really. That is the wrong thing for the CEO to say, because your bad talent's going to just be worried, but not leave and probably not invest in their own learning and learn how to use AI. Your great talent's going to say, I'm, um, out of here. And then all of a sudden you got a company worth of just bad talent. And who does that serve?

Speaker A: I Don't see the upside. I'm a little bit lost. Now I understand why in a company like Microsoft, to some extent this is signaling to the market. You're on the sell side of AI, so to some degree you're eating your own dog food and you're basically trying to tell us narrative. That said, look at us, we're the guys creating a revolution in our own operations using AI. So we want to lead from the front. But you still have a lot of employees there, uh, who have to be looking around saying, wait a second, I'm supposed to sell this stuff and do myself out of a job. And on the flip side, I think you have this sort of natural Silicon Valley mentality, which by the way, I've been part of. If you'd have asked me 20 years ago, I'd have said yes, I'm absolutely ready to march in tune with this let them eat code mentality. This is good for society. Look, you can imagine lineups of people at TED talks saying world Economic Forum. What could possibly be bad about this? Societies migrate. Technology always creates new positions. And it's a wonderful, wonderful thing. Especially if, by the way, historically that position elimination has been blue collar jobs, which aren't us, and the wealth creation has been in white collar jobs, which is us. And so this has been a wonderful story. Um, now we're entering another era where the changes are likely to affect white collar employees. And I wonder whether or not have we learned anything from the sort of let them eat code last iteration that's going to arm us to do better this time, or we just doomed to repeat the same kind of set of mistakes, which is, look, it's all about cost reduction. Let's get humans out the loop. Humans are expensive, specially developed country humans. We couldn't find a way to get non developed country humans to do the job. Let's find an even cheaper version of humans which is non humans, and forget for a second whether it's good business. And I think you could make an argument, I'd love your view on whether it's good business. I suspect you're going to argue it's not. But also, it's not just bad economic policy. I mean, why do we want our society to evolve like that?

Speaker B: Well, I think if you look back in the last thousand, two thousand years, I think we're always doomed to repeat our mistakes from the past. I don't think I've, uh, I'm not sure of a scenario where we haven't just repeated, um, or haven't taken that Learning fully forward. I, um, think it's bad business and economic policy to suggest that an entire cohort of individuals will just be unemployed and not create a scenario where they have a path forward. Not everybody can see that for themselves. So I think that there does need to be someone that's going to come forward and say, and whether that's governing our other. Otherwise maybe it's the Silicon Valley folks to say, I'm going to create a path and a platform for people to educate, learn, build. I, um, think ultimately AI is going to create more jobs than it's going to take away. I think in the near term, yeah, we are losing jobs and that's clear. Um, but I think you've got to be on the side of technology progress to be part of that AI job creation too. And um, yeah, like if you were, you know, coal miner and, or steel manufacturer, like, yeah, like, you know, that's, that's kind of where you probably lost your job and that's very unfortunate. Um, but I think if you're a white collar today and you are worried that your job is going to go away, um, it very well likely may. I think you just have to lean into it and really learn it and understand how is this going to impact my role and how can I use this technology to create value, whether that's in the context of my role, in the context of a new role that I might be interested in, or in the context of what the company does and how they make money. And you need, uh, I mean, geez, ask AI. Had to figure that out for you too, for crying out loud. But like, you know, like you need

Speaker A: to be thinking my job to AI, you know, basically is your prompt.

Speaker B: Yeah, I mean I, look, I've asked that of AI before too. And they're like, well, this is exactly how you're going to lose your job. Right. It's pretty specific. And I'm like, well okay, well then help me think through. And that was actually part of my conversation yesterday with ChatGPT is like, how does this all go badly for me personally? Right. And professionally for that matter. Um, that's a really interesting exchange to have with ChatGPT, by the way.

Speaker A: Yeah. And it brought to mind we were talking before we started recording about the famous New York Times interview, which kind of kicked off in some ways a lot of the debate around AI, where the, the journalist had ended, uh, up going on a long, long, I think, you know, 18 hour narrative with what was uh, Microsoft's uh, early, uh, early version of copilot I suspect. And, and it went to some very dark places and the AI was convinced that the, that, that his wife in fact didn't love him. And they had a terrible Valentine's Day dinner. And it made for a great article. Um, but you know, as you said, if you, if you start to explore the way dialogues unfold, you come to some interesting places. But I want to sort of get back to the idea of a more positive image for what could be accomplished and in the context of customer experience. This industry hasn't substantially changed the narrative on customer experience in 30 years. Most companies, if you look at it from a numerical perspective, are as bad as they were 20, 30 years ago. And by bad, I mean there's a relatively small number of companies that seem to do an amazing job. Uh, and by the way, those companies seem to do incredibly well. They grow successfully, they command lion's share of the profits. Maybe the causality is the other way around. Maybe because they're so good at something else that customer experience becomes a byproduct of that. Or maybe customer experience is actually driving that. It doesn't really matter. If you've got a strong association between the two, you'd think that's a good reason to be concerned. And then you've got this 80, 90% of businesses that have been stuck in the doldrums for as long as I've been in this industry. And so maybe m. What we ought to be rethinking, like your reaction to this is that the opportunity here is to break out of that pattern. And whatever technologies come along, whatever format, can we finally sort of crack open the idea that companies can't do any better and actually start to get them to do better. And in doing better, achieve higher levels of growth, which is the currency everyone needs, and in doing so achieve higher levels of productivity and efficiency within their organization. Maybe you have the same number of employees today when you're twice as big, but people are twice as productive, making 1.5 to 1.7 times as much money, by the way.

Speaker B: Mhm.

Speaker A: Uh, which makes them successful in their lives and makes the shareholders successful and everyone's a winner. So there's the, there's the optimistic view. Possible. Achievable.

Speaker B: I think it's possible and achievable. Um, two things. Um, one, um. Or maybe not two, maybe more. Sorry. And if I'm going to go on a rant here, it's because I'm really passionate about this topic because we have been in the doldrums for far too Long Um, I think that their software, um, companies included really pushed the old way of thinking agenda because they made enormous amounts of money in that product led growth kind of space. Right. So number one, um, I think those companies um, and we don't need to name and shame but I think those companies are finally coming around to the fact that it just isn't about survey, survey, survey. Um, it's much more than that. Um, and they haven't necessarily built capabilities. Well they say they have um, built capabilities that really help you understand the customer from, from end to end, meaning across platforms and channels, um, um, structured and unstructured data etc. So that's number one and I think that narrative needs to really change from the vendors that are pushing sort of the industry so to speak. Um, number two, I think you know, consultants, you know, very large consultant who one um of their um, employees was one of the co founders of NPS are now saying hey it's not just about surveys. And that co founder actually even says now it's not just about surveys. Um, I think that narrative is starting to change. I just don't think that um, inside enterprises in particular, um, it's still the, you guys just, you're the survey team and you deliver your PowerPoint or your dashboard to me and I'm following my NPS trend tick up or down. I think organizations have moved on and they moved on three, four, five years ago. Meaning the companies and the brands that you referenced that are really great at what they do, yes they do surveys but more importantly they're bringing their customers and their clients into the development process in some way, shape or form. Whether you're in hospitality, technology, um, banking. It's not just about serving your customers and understanding, you know, understanding the voice of the customer. It's truly designing solutions with them at the forefront of your decision making process, truly integrated. So like I've been fortunate enough to work with some of those brands, they act like that is the big differentiator, there's action around the customer, not just this passive listening and sort of reporting paradigm which has really killed our discipline in a large way. And that I think is the 90% um, at least in my mind that uh, you're referring to. So I think it's possible, I think that there is going to have to be um, different players involved. Um, uh, I think the chief Experience Officer kind of role has to go away. I think that it really needs to be much more operationalized. I think that there needs to be a better partnership between the CIO and the COO around the customer to truly change this. Um, and for those really forward kind of thinking companies, even bringing the employee experience into it, um, large pharma, uh, company just consolidated into one role, their CIO and their chief, um, human resources officer role. I think rethinking the business model and old way of thinking is going to be paramount to being able to bring this forward from a customer perspective. And the same companies that are delivering those great experiences are the ones that are doing that, not the ones that are. Well, is my NPS ticking up or down? Because my bonus depends on it type thinking.

Speaker A: Yeah, well, uh, I share your optimism in the narrow sense. I think there will be another cohort of successful companies who sort of break with the past and innovate. And there's something about their DNA, their leadership, maybe it's as simple as that, or their corporate culture that says we can change how we're doing to get better outcomes. And then there's this kind of seemingly immutable law which says 67% of companies can't. They lack the motivation. There's a fundamental problem in leadership's approach. There's some sort of principal agent problem occurring where at the end of the day that they're so stuck in this model of how they're going to run companies. Um, or they just lack ambition at the end of the day. Right. People are sort of phoning it in, um, Some ways. The interesting question is what are the characteristics of that 20%? What are the characteristics of companies that are going to evolve? You have on one hand this emerging set of technologies with artificial intelligence. You have on the other hand this growth imperative which hasn't changed. It's still an imperative, it's still confoundedly hard to find solutions for. Um, and going back to almost the first thing you said in this interview on the buy side, it's absolute chaos. Right. Trying to do anything within a large company is excruciatingly difficult and requires an incredible act of both, almost like political acumen combined with uh, almost crusader like

Speaker B: take the great way to describe it, Richard. Right.

Speaker A: And so something's going to emerge from this where the next 20% of companies emerge. And um, our mutual friend Bruce Tempkins on his new mission around humanizing companies, which I think is uh, a genius and timely move. And I'm so impressed that he's taken that on. And you can take a few of his ideas or even just a high level idea and say ironically, in an era of artificial intelligence, the winners are going to be the Companies that actually figure out how to remain human. Maybe that's the North Star for all of this.

Speaker B: I think that's a fair comment. Um, at least in the near term. I think that there's a general look, I've got Gen Alpha kids. I think they could care less whether it's human or not, to be perfectly honest with you. Um, and on some level I don't even really care as long as you help me get to my solution as quickly as possible. I really don't care if it's a human in the other end of the line or if it's an AI or whatever it might be. And can I solve it in my platform or capability of choice? I think that we get so caught up in and no offense to Bruce, he's a great guy and I have a ton of respect for him and he's carving out a space which I think is a really important conversation to be had around that. But like, let's not like name stuff or let's not. We get so caught up in like all this like framework, like let's just go get shit done. Like think about how you going to use this capability and just go get it done. Like understand what your customers want and deliver against that. It's super simple stuff. Right. Um, but we tend to over complicate it. Super simple but not hard to deliver against. Yes, easy to say and it looks nice on like a board or like you know, in the lobby somewhere for sure. Um, in reality very difficult to actually implement and do. Um, I think that is going to change over the next three, four, five years. Um, the simplification of implementation. I think, um, I think that there's going to be a space where people are going to backlash and say oh gosh, like just I'm in AI chatbot hell and I can't get out. Right. It'll be the new version of the ivr. Um, and I just want to talk to a human being. I think that's fair. Um, I also think that humanization angle that Bruce is talking about is back to what you referenced. Don't start talking about just peanut butter. Approach efficiency by firing 50,000 people. Be a human company and understand that you have a moral responsibility as a public organization to do the right thing, not just by your shareholders, but by the people that have created value for those shareholders over the last 10, 15, 20, 30 years, whatever the time they've been in their seat. And I think too many organizations forget that, which I think is a, I mean just a God awful look.

Speaker A: I mean, even. Even the Roman army only knocked off 1 in 10.

Speaker B: Yeah.

Speaker A: I mean, Ford's going for a bigger percentage.

Speaker B: Yeah. Yeah. It's not. It's, uh.

Speaker A: Well, maybe. Maybe that's, uh, a. Maybe that's a good note for us to end on. We've. We've used up our allotted time, Bill. It's. It's. There's a conversation going for a lot longer. I really enjoyed the direction of the talk and we obviously got a lot more we could talk about, so I hope we pick this conversation up again in the near future. Um, and, uh, congratulations on seeing things from both perspectives. I think you're one of those rare individuals that will bring a different perspective based on being on the buy side and the sell side of this universe, and that's always going to be fascinating. Most of us live on one side of the fence and never really understand what's happening on the other side. So thanks again and we really appreciate your time.

Speaker B: Hey, it's been my pleasure. It's great to see you. Um, and, um, yeah, I'm looking forward to what's next on the horizon for me. And, um, I'm really glad that, um, our mutual friend has put us in touch. So, um, it's good to see you and thanks again for having me on the show.

Speaker A: Thanks for listening to the CX Iconoclast from OCX Cognition. Subscribe wherever you get your podcasts so you won't miss any of our thought provoking conversations. And please get in touch if you want to learn more about what OCX Cognition's predictive CX analytics platform can do for your business by providing complete insights into every account continuously updated and connected to operations. You'll find contact info in the show notes.