Customerland
Customerland is a podcast about …. Customers. How to get more of them. How to keep them. What makes them tick. We talk to the experts, the technologies and occasionally, actual people – you know, customers – to find out what they’re all about.So if you’re a CX pro, a loyalty marketer, a brand owner, an agency planner … if you’re a CRM & personalization geek, if you’re a customer service / CSAT / NPS nerd – you finally have a home.
Customerland
Designing AI that Earns Trust and Relevance
What if doing “the right thing for this customer, right now” became the default? We sit down with Rob Walker, VP of Decisioning and Analytics at Pega, to unpack how empathy at scale, AI-driven decisioning, and strong governance can make customer engagement both more human and more effective. Rob explains why empathy isn’t charity; it’s a system for earning relevance and trust that compounds into mutual value. We dive into one-to-one decisioning that prioritizes a hierarchy of needs—solve hardship and service first, consider offers only when appropriate—and how real-time redecisioning keeps conversations useful as context shifts. The conversation gets candid on hype vs. reality: generative AI is expanding the content library needed for true personalization, even demonstrating better bedside manner in some settings. But trust requires more than sentiment; it needs policy. Rob breaks down the T‑Switch, a transparency and model-use framework that enforces explainability where stakes are high and speeds experimentation where stakes are low. Then comes the big horizon shift: customer advocacy agents. These AI agents will comparison-shop, negotiate, and handle service on our behalf, impervious to glossy ads and tuned to our preferences. That future could disintermediate brands and push competition toward price, reliability, and fit—raising the bar for authenticity and interoperability. Inside the enterprise, tools like Pega’s Customer Engagement Blueprint compress months of strategy design into hours, changing roles rather than eliminating them. Marketers and data scientists move from manual assembly to orchestration, governance, and measurement, while empathy and trust become operational standards, not slogans. If you’re ready to trade segments and batch campaigns for moment-level decisions and measurable trust, this conversation is your fast start. Subscribe, share with a teammate who needs to hear it, and tell us: what would you ask your customer advocacy agent to do first?
We all know that if we do our job even remotely the same way next year, we shouldn't be at that.
unknown:Right.
SPEAKER_00:And I think and I think that that's that I think that sentiment is really um um I think that will, if it's not landing now, that will land soon. And certainly when I talk to some of our clients, that's very sunk in, at least at sea level.
SPEAKER_01:Today on Customer Land, I have the honor and privilege of speaking with Rob Walker, who is among a series of titles, VP of Decisioning and Analytics at PEGA. He is general manager of one-to-one customer engagement and also has a PhD in AI. And I can just tell you from the sidelines, is a fascinating and and uh well, let me just leave it there. A fascinating person to listen to when he's presenting. So, with all that, thanks for joining me, Rob. Thank you, and thanks for the compliment.
SPEAKER_00:Um makes me blush a little, but uh but thanks.
SPEAKER_01:It's an audio medium, so it's okay. You can do it. I know, I know. So um, we were just talking a moment ago. One of my first introductions to Pega was uh several years ago. I'm gonna say five or six years ago, I was speaking with one of your colleagues, and the theme of the moment, and I don't know the I kind of approached this as maybe these are just talking points, but the theme of the moment at that point were was um we're building empathy at scale. And when I was able to kind of explore that with this person from Pega, um it was revealed as way more than talking points. This is actually appeared to be the theme around which most of Pega was operating at the time. And it seems to me, I'm I'm projecting wildly here, but that uh that's continued. So I'd love to see one if I if I did I come even close there, and what are your thoughts on all that?
SPEAKER_00:No, no, you got very, very close. Yes, we we really um um try to design the systems we build, but also the the philosophy with which to um implement it as really um leading with with empathy, empathy. And that's that's not, I will say, um, that it's the same as charity, right? I I will say that like what what we have found is that um empathy leads to relevance and trust, and that then eventually will also lead to just a very, very uh good and mutually valuable relationship, right, with customers. So it's not like um, but I think the the the the the main component of that are are are are there's a few points, I think, to make. One is like we have this approach, and that is central to how we deal with you know marketing and customer engagement in general, is this one-to-one approach, you know, that's all you know, Peppers and Rogers from the previous century, but now completely real. I'm going to assume a lot more real than they thought was possible at the time. Um, but that in itself is driving um um relevance. And then the other thing is that it never has have never been just about marketing. It's obviously a component, you know, the companies we we that use our software obviously uh want to make a profit, but it is it is like a hierarchy of needs almost, like, and that's where the empathy comes in. It is like, hey, listen, for instance, what what what some of the banks we work with do is like, are you in financial, you know, distress? Um, or is your, you know, like in Australia, is there a fire, or or is there like flooding, all these horrible things they have? Like that would it completely change whether that's outgoing or incoming, uh, the conversation immediately. So this is a hierarchy of needs. Do we need to address something first? Let's do that. Then secondly, is there a customer service need that we feel like this this customer is is is approaching us for? Let's handle, let's handle that. Um, and then there's a bunch of things, and sales typically is relatively low. I mean, it's still where a lot of the things will go in the end. And then you'd sort of decide, okay, like if we have no more pressing things to do, let's then use this moment to maybe, you know, put a proposal or an offer on the table. But that then too is one-to-one. So it's it's looking out of a thousand different things. This is the thing. So anyway, I think that's sort of, yeah, empathy is at the um at the heart of um at the heart of it.
SPEAKER_01:You know, um, just from a cultural anthropology standpoint, empathy is difficult. Empathy is complicated. You you can fake empathy really easily, but approaching authenticity, approaching something that's believable on the other end of that communication can be really difficult because, as you were just saying, you have to factor in so many different ideas, situation, contexts, uh, everything you can you can possibly know about their situation to um to do that. So I think that was the first, that was my first glimpse of of how Pega was approaching it at the time. But, you know, let's cut to more recently, I attended Pega World, which was a really eye-opening and great experience for me. But I got to see how Pega has modernized um the efforts there um with AI. And, you know, again, because of the space I cover, I see AI-based everything. It's it's it's an AI-based world out there, and you have to peel back the layers of marketing onion and being kind uh to see what's real there. And um, it became real evident again, really quickly, that uh uh the systems that that uh Pega is building out operate and are based on AI, but it's still it's still wrapped around this core idea of empathy. And you know, customer expectations have uh grown. Um our ideas of what empathy means with machinery like AI have gotten more complex. And you know, it's likely that this questioning will take us way deep into the weeds. But as someone who leads the the product side of all that at a at a giant company that has giant company clients, I'd love to hear your your kind of thought process for you know, where do you start thinking about developing these systems and what are your kind of end goals as you develop them out?
SPEAKER_00:Yeah, no, no, and I and I and I think you you you in in on on the previous topic when we talked about empathy, that that the fact that it is sort of really customer first, but not as lip surf as everybody's oh customer centricity, like it's like it's it's it's almost as nebulous as AI, right? Or agent. Um, but um but customer centricity does mean truly in our in our view, and also really in the technology, that you put the customer first and then trying to figure out for that particular customer in that particular context, um, what is the thing that is going to you know make this relationship uh more mutually valuable. And I think that sort of philosophy is is is I think um is is instrumental. But if you sort of look at like our roadmap, I do think because some people, and maybe we're we're going to discuss that later, it's like you know, AI is like it's it is everywhere, but it is everywhere, right? It's also not um, I said I think in my keynote, yeah, it's hype, but it's not overhyped. Right. It's it is it is pretty amazing. And one of the things talking about empathy and AI, I think one of sort of the bottlenecks we had a little bit, not really a bottleneck, yeah, maybe the maybe a bottleneck. It didn't hold us back too much, but it's still a bottleneck, is that we never had when we have this fabulous next best action approach, completely one-to-one. It's great if you want to be empathetic and you want to sort of make sure that you talk about relevant things that is really going to bring the relationship further. But if you don't have a sufficiently large uh library of topics you can talk about, like you know, so normally marketing campaigns are pitching one thing, and that's why they're not very empathetic, mostly, even if you use analytics. But but to sort of figure out this is the relevant thing to talk to Mike about right now, um, this is what he needs. Um, that library of content, that library of topics, that was uh that was a bottleneck. Companies have to build that, right? Especially if they're sort of you know more traditional marketers, they'll already make a lot of content, but it was always there is the campaign brief. We need to sell so many of these, create it, do the creative, do all of these, all of these things. And we would say, yeah, do all of those things for 1200 different things, because we're going in the moment, we're going to decide using AI and decisioning and all sorts of things. Um, this is the thing that we shouldn't be talking about now. And then we do that in real time, right? So if the customer is like, oh, I think that's a little bit much or a little too expensive, or we would redecision. Anyway, that's the bottleneck. And I think AI and Gen AI in particular is really helping us build that up, right? A lot more creative, you can do get a lot more personalization going on. And also, just on the empathy side, I I I read like, I think it's probably already a year ago, but the whole study on at that point, Chat GPT, I'm going to say three, I don't know, ancient, um, um, about like how it had a better bedside manner than than human doctors over email, right? I will say, possibly partly because it just had more time to think about it. But that still, it was a you know a blind test, and patients just appreciated that more. And that is because, to your point, these, I think these these Gen AI models just know more about people than our clients have in their customer profile. And therefore, we don't know about that, right? So that's, I think, is really going to uh to help here.
SPEAKER_01:So you've just opened us up to another line of of thought here that will that will absolutely derail the conversation. But um the the nature of customer relationships has been um debated for several decades, anyways. Um we've all seen the statistics on, as I mentioned earlier, customer expectations as they change and grow, the complexities around appearing to and actually being empathetic. But you know, in the age of AI, when so much is now possible and you can deliver relevancy and importance um to the customer instantaneously, it's it's going to change what the it's going to change how customer relationships work, I think, at its core. And I know as somebody who looks into the future, you're probably the one guy with the crystal ball on this. Um, look, look out five years from now and and how we're interacting with these technologies and with the brands behind them. How do you see the the customer relationship itself changing? Or am I off base here? Will it change at all?
SPEAKER_00:No, no, no. I think I think um no, I think you're not off base at all. Uh but I do think that a lot of it has already sort of changed on the inside. If I if the inside here is like a company, right, that is trying to to say things to people, um, um, you know, to figure out what that thing is, right? There obviously is have been very high levels of AI, sort of more what we call sort of left brain AI, right? Or or decisioning. So lots of analytics, lots of machine learning, but not the generative creative side of it, right? Which is sort of really nice, sort of add-on. Um, and I think uh, but that's early days. I think the the the cut the customers, the end customers will definitely feel like, oh yeah, it gets even more personal. Now, then you can have a whole argument, well, is that fake personal, is that real personal? Well, you know, we may discuss that in a in a in a in a in a in a moment, but certainly um there is more options to do the right thing, and I think that is important. But I think what will be a big shift if you say five years, which is which is honestly in this day and age, I always try to say, well, let's try two years, right? Because it's just crazy, honestly. I can only start when I'm preparing for my keynote. I used to be able to do that like sort of late the year before. Now I I can't even, if I started there, it would be like so stale and outdated. I can't it's it's completely impossible. Um, but uh five years from now, but I do think that like the agents are not just corporate agents, right? I I really feel pretty strongly that the likes, you know, the big brands like you know, like on the consumer side, Apple, Google, uh others um will have these, let's say, I think the term that I've read about it is like um um customer advocacy um agents, right, that will do the shopping and the talking and the customer service uh inquiries for you, right? And I think that will have a monumental change because, first of all, it will give a voice to people that may not be as eloquent or as determined, right? Or will not have enough time. So that will change. So the volume will go up massively. Um, but secondly, um it will peel away a whole level of marketing, right? Because that customer advocacy uh agent will not be persuaded by, you know, in booking travel to look at like, oh, there's a happy family on the beach, right? It's like meaningless, right? So just give me the price, give me customer reviews, and I know all the preferences for the for the person I'm um I'm um um you know standing in for here. So I think that's a monumental change that um is a little scary, but you know, ridiculous.
SPEAKER_01:I think it's inevitable too. Yeah, I was having a conversation around the very topic about a week, maybe two weeks ago, um, with a marketer who said, Look, we're preparing for it, we see it out there, but at some point the way the way they pursue marketing and the entire definition in their world um of marketing is gonna change because they're they've the the brands have to be really careful about being uh not being disintermediated from their customer entirely by these agents, you know, who don't care. They're the agent doesn't care, you know, if your customer services isn't isn't up to par, they don't care if your price is or you're like you said, the pretty picture is they don't care. Yeah, yeah, yeah, yeah, yeah, yeah.
SPEAKER_00:Now I think that is super interesting what that will do. So marketing sort of, I would not say as we know it, um, but maybe as we know it, that will really, that will really change. Um, but then it it will be really interesting if you really look at it from the human perspective, you know, how much um will that change if your if your your Google or your Siri of steroids or your you know your Alexa for all I care is like is like you know negotiating on your behalf, but really knowing a lot of private things that you would never even tell talk to you know, tell the company that you're negotiating with. Yeah, that's uh that's the I think uh yeah, there will be some magic there.
SPEAKER_01:Yeah, that's gonna be an interesting thing to do. So so I'm gonna start trying to get on your calendar for the next five years, right about now, because it'll probably be that much more difficult at that point. But but yeah, you know, just the idea that um all of that emotional exchange, if you will, between a brand and a customer is going to get it's just it's gonna become unimportant if these transactions are all agentic or mostly agentic or even partially agentic. So yeah while um one thing that's come up quite often in our world is the idea of um trust as it's uh as it's built in and baked into um AI components and machinery, um, but also how consumers are the users, let's say they're consumers or their businesses themselves, um are processing the idea of trust for themselves in its own utility, how they adopt it or don't, um, how these things get produced, what they do, and and how do you how do you how do you build trust into these into these mechanisms? And I could think of nobody better to ask that question to than you, because you know it has to be you know right there at the foundation of so much of what you're about. So I'd love to hear your thoughts on that, you know. Yeah, just I'll I'll open it up and and see where this takes us.
SPEAKER_00:Yes, yeah. So um it is very, very um dear to my heart. So you're not wrong in that. And I have been talking about like um uh trust. Um I would say before it was fashionable, and certainly before um, you know, the whole you know Gen AI um started, right? So when AI was not as as big a deal as it is uh as it is now, but I was always worried um that like um because I think trust there there's there's many factors to it, obviously, and we can talk about that for a long time. But I think one of the key aspects is is transparency, right? You have to be to be able to say, hey, why are you telling me this? Why do you think this is relevant and learn from it if it's not? Um, but that transparency is also something that we we built into the heart of things, but not to make it like you you can never use an algorithm that's not transparent, because honestly, the the well, I think the downside to doing that in practice, certainly on the real marketing side of things, is that um if you would be so restrictive and say, hey, listen, we need to understand every single thing um we um um we we we we we determine is relevant for somebody, then first of all, your human uh staff is not held to that same standard by any stretch, right? You have no idea, right? So that's one thing. So it would be a little unfair, but but um but secondly, I think what is really important is that if you um if you did that, the it's not always necessary, right? I think if you don't really understand why some AI said, oh, the best background color for this is this like bluish pink kind of thing, maybe that's okay if it works, right? It's a different thing, obviously, if it says, oh no, you cannot have this mortgage, right? That's a very different thing. So what we build in ages ago, really literally in AI time, centuries ago, but it was probably eight, nine years ago. Uh, we build in this thing that we call like a T-switch. Uh a T-Switch is for trust and transparency. And it is like a switch in the software that allows companies to sort of set their policies, their AI policies. So they can say, hey, I am um, this is the level of transparency I require for a decision like this, like offer or decline, a mortgage, for instance, or a loan or whatever, anything sensitive. But that's maybe the we need it to be a five, the most transparent, right? But for background color or the size of an ad, if we use AI to magic that up, that can be a that can be a one. So you can implement that policy, and then we would have uh guardrails in place that would say that would just if if if if a marketer or whoever in the company would build a next best action strategy, right, it would then say, Yeah, you can't use this algorithm here, right? You you'd like to, we understand, but you know, it's like your own policy. So we could not take it into production. It's not just a warning, it wouldn't run. So um, so that's kind of how how how how serious we take uh uh transparency. And as I said, I think that's a major ingredient of uh of trust.
SPEAKER_01:It's a huge thing. You know, we we see there, you know, every month, anyway, I'm sure more frequently you see a news item out there that talks about, you know, well, look what AI did this week, you know, look at the the horrible thing that that transpired. And there are loads of stories out there where technology's been misfired for one reason or another. But there's if it depends on who you talk to and which sector they operate in. But there is a kind of uh kind of, well, there's a few underlying fears there. One is like AI is going to take over my job, take over the world, um, but you know, a little closer to home, uh discomfort with the idea that so much of these major decisions are happening in a black box that um is completely opaque to the average person. And um, you know, for instance, if we're on Chat GPT, we have our chat bar, and then we have its responses, and it's very much um as great as ChatGPT and the rest of them are, it's very much just a binary exchange. You can't you can't get to a customer service agent or somebody behind the scenes to say, hey, this didn't work for me. Can we uh can we do something about it? It's literally like here it is, take it or leave it. And uh it seems to me that that kind of um those kinds of exchanges uh would erode trust over time, or maybe we just get used to it as consumers and say this is the de facto standard and and we better.
SPEAKER_00:Yeah, I'm not 100% in this case, Mike, that I fully agree with with with with with that one in this in this particular case, because I feel like um you said like it's it's opaque to um to an efforts person, it's actually a lot worse, obviously, because it's it's completely opaque to the designers of the whole system. There's truly no one who gets what they're doing, right? Um exactly, and and or even even approximately. It's very, very hard, right? So that's that is something I think to your point that we have to live with because the benefits are also clear, right? It's it would be if we met aliens that are a thousand times as intelligent as we are, and they're always right, and we don't know why, but it's always right, you know. People do love oracles, right? So um um, but um, but I think uh the the binary thing is what I was not certain about because I do feel like certainly in our vocabulary, we have a lot of things that we call, you know, like we call redecisioning, right? So the moment some customer in some channel would say, Well, I don't know, or can you do this differently, or even just hesitate or get upset, or any of these things will change the context of that conversation immediately, right? We pick up on all of these signals and then redecision instantly. And I think um the the the Gen AI algorithms would also do that. So they would say, so you know, either either the Gen AI algorithm or more traditional algorithms would say, oh, this customer is getting upset, then the tone of voice would change. Um, you know, and I think Gen AI can do that pretty well per that, you know, bedside manner that I uh that I uh mentioned earlier.
SPEAKER_01:Right. Yeah, and maybe I misspoke because I I think um that's one of the beautiful things about the the AI modules that I've worked with is that it will adjust on the fly. I think what I meant by the binary kind of opacity is just that all you get is the chat bar. That's the extent of the that's as deep as you're gonna go behind the scenes.
SPEAKER_00:Yes, no, that is true. We we have our own corporate agent that is using uh, you know, Gen AI. And uh well, you heard about her in the um in the in the in the keynote. And the fact that I call her her says a lot about how how effective that is. Um but uh but she also always gives, as a matter of course, she can't make if she can't give you any answer without explaining exactly how it got to that. But even that is not a hundred percent correct. It's like it's like just like humans are making decisions and then justify it afterwards. So there is a sense to it, but if it's really the actual cause of the decision, probably not. But you know, it's it's something.
SPEAKER_01:Interesting. So um I we sort of addressed this already, but you know, the five-year outlook to uh what these interactions look and feel like, there's there's gonna be a lot of um technology developed between here and there. But on the human side, you know, we're probably not going to evolve nearly as quickly. We're kind of slow evolutionary. You know, so uh the technology is gonna accelerate, we're gonna sit back here and figure out its best utility and trust. But to me, as someone who's looked at uh customer expectation gaps for the past, I've been you know looking at these uh kind of uh over uh you know, say a five-year period and how they've changed in different sectors, excuse me. It seems to me that if we if we switch the lens from customer expectations to sectors to uh customer uh engagement, customer trust over those five years, that um we as being the slow of evolvers that we are, um are really gonna have to be coddled. That's the wrong word, are really gonna have to be catered to to help us understand what's happening over there.
SPEAKER_00:Does that make any sense?
SPEAKER_01:Or is that um is that completely opposite?
SPEAKER_00:No, no, no, no, I like it. But I think we we did touch on it a little bit because I do think that these customer advocacy agents that I really think will be major. Uh, and there will be a lot of competition, and maybe there is even a marketplace where you hire an agent like uh like a like a movie star might have an agent, right, negotiating on uh on their behalf, right? So so who knows how you know, yeah. You asked me about five years, but I can totally see that that people are bidding for agents and say, oh, this is the best agent I can get, and I would pay pay for its services. Um, but anyway, uh but beyond that, I think they are the ones that will that will cater and that will also you know try to explain things, um, like, hey, listen, yeah, you you filed this complaint with this company, I've been talking to them, you know, like like like I I really think that will go pretty pretty fast, honestly. I think if you if you extrapolate um through you know these these these five years, I think because we have we've been focusing sort of on the on the on the the edge of the of the of the company and and it's and its customers, right? Which is that's a fascinating part, obviously, of engagement. It's also what I spent a lot of my time. But I think the other thing where that is going to radically change is the automation inside of those of those companies, right? I mean, when when we did this next best action decision, and it was like great, people had incredible returns, all good, much relevance, lots of empathy, everything worked. But it was like it was literally people inside the company working on this, on this, on this, on this canvas with like decision shapes, and they could have hundreds of predictive models, exception rules, and eligibility rules, and all of these things, and then they magic that together, and it was very powerful, but it was like sort of almost manual constructed and then very, very fastly executed. So that has changed completely already with things like now. Now we have the next best action designer, and soon we'll have like, or we actually already have you heard about this blueprint, right? That we that we have. So we have a customer engagement blueprint that just from your website and all sorts of briefing documents that you may upload to the thing, um, will come up with it with a with a strategy that will probably get you 80% there, if not more, including all of the content, right? So that part of it, we also shouldn't underestimate. I think the agility of customer engagement strategies will be massively better than they are than they are now. And and I think um, you know, you you you were joking earlier, or maybe not joking, but about like uh, you know, people taking the marketers that you spoke to said, well, when is this going to take my uh to take my job? Well, I think there will there will there will be there will be jobs, but it will definitely it will definitely change because these these agents, sort of the intra-company agents that are are getting very powerful. And I think blueprint, our blueprint is showing things that would take maybe even a year, right? And it is done in like you've seen the demos, but let's let's say that you do a few iterations, let's be an hour.
SPEAKER_01:Right, right.
SPEAKER_00:That's what we're talking about.
SPEAKER_01:Yes, you know, um, it brings up an a really interesting point. Um, just again, because of where I sit in this particular ecosystem, I talk to a lot of people who are marketers, and um you know, I I say this without um you Know, I I don't want to uh demean anybody here uh in any way because it's an exciting time, but accelerating marketers, CMOs, understanding of what's possible, even to the point where what's possible right now, I think is a big challenge. I know so many marketers, smart people, driven people, um, people who are very successful in their their own particular worlds, um aren't even aware of what AI-based tools like Pegas can do for them right here and now, much less in two years to be planning for it. So it seems to me that there's a there's a challenge and an opportunity there for somebody to come in and just start to kind of bridge those gaps, like here's where we are, here's where you could be very quickly just by deploying certain things in certain ways. Do you see that as well in your interaction with companies? Or do you see that that there's a readiness out there to deploy this, or is there an education that needs to needs to come along first?
SPEAKER_00:It's it's it's funny and it's it's a very, very good question because I I I've I I've I'm I'm I'm sort of leaning on that fence and sometimes leaning, depending, because I talk to a lot of our clients or or or companies that um fall into that uh fall into that category. And it depends a little bit. So historically, certainly in my space, like in the customer engagement space, I've dealt with a lot of people that are very traditional, right? With all due respect, right, but they're still using the same technology or the same vision on marketing or direct marketing that we've had since the 70s, right? It's basically querying a big database of people you think are going to be interested, and then you're going to put some subjective measures like let's wait two weeks. It's like, it's like that's not the world anymore, right? You don't have to, first of all, you don't have to do these queries and build like a segment, not for target, maybe to understand what you're doing in a particular segment of clients, but not for targeting, right? That was necessary when we were running things in COBOL, right? But now you don't have to do that. And and and so that's already, I think. So when I talk to people, sometimes that's already a paradigm shift that is a little hard. But that said, everybody is very aware of, you know, because they're also consumers of AI and they can see how fast this is. And this is the first time that I feel like uh like marketers, but also data scientists and a lot of other people, but those are the people I talk to the most, are really thinking, yes, my my professional life is going to change radically. And certainly, for instance, just at at at Pega, at my own company, that's very we all know that if we do our job even remotely the same way next year, we shouldn't be at Pega.
unknown:Right.
SPEAKER_00:And I think and I think that's that's that I think that sentiment is really um um, I think that will, if it's not landing now, that will land soon. And certainly when I talk to some of our clients, that's very sunk in, at least at sea level.
SPEAKER_01:And again, just to be really transparent here, I've been to a handful of Pega functions. Uh, there was one in New York here recently, and then of course Pega World. And um I've I've practiced and studied marketing for decades, and uh my eyes were opened um on both occasions to things that are possible right now. And and my job, my literal job description is to study and understand what's happening in the marketplace, and uh it took attending those kinds of things to to see new ways of doing things, and um, and I yet I think I'm one of the lucky ones who gets to attend these events and see behind the curtain, but there are hundreds of thousands of marketers out there without that same privilege and and uh need to deserve to see what's happening.
SPEAKER_00:Yeah, and and honestly, that's in part, that's also totally on us because what we are because we are very focused or sort of uh well human-infused uh technology, and and that's really our our our our our vision, but we do want to be the best possible in that in that space. And um, I think we haven't overspent, let me put it mildly, on marketing this, right? So I I won't say because it's trite and also not true that we're the best kept secret and everything, but it is definitely not our forte to um, you know, to to to to do these things. But that said, um now that we have this blueprint and everybody can go to pegat.com and try it, like it's it's free, right? So it's like that. We thousands are are created every week, I believe. Um and and and that is that makes it so much easier than for us to try to explain, you know, the tech and why empathy is so important and why customer engagement or the or workflow and the other uh uh uh parts of Pega. Um but now that you have this blueprint, you can just try it out and see it. And anyway, we'll see what happens. But it is at least it's very accessible.
SPEAKER_01:Yes, it is. And having played with it, I'm I'm blown away. I'm I'm a believer. Cool. Yeah. Well, Rob, I really appreciate this. Um, I can think of lots of ways to to spend more of your time today because it's fascinating and I think it's very useful, this conversation. But um, I'll let you get on to the rest of your day just to say thank you. Um, Rob and his team are doing some fascinating things at Pega. I've seen them firsthand, and um please pay attention, as we will, to what he and his team are doing over there. Thank you so much, Mike. It was uh very nice.
