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
Retailers Can Now Sense, Predict, And Act In Real Time
What happens when retail stops waiting for shoppers to arrive and starts responding to every signal in real time? We dive into a candid, practical look at how AI is reshaping the entire customer journey—from discovery sparked in chat interfaces to fulfillment choices optimized for margin and sustainability. With SAP Customer Experience leader Balaji Balasubramanian, we unpack the systems, data, and decisions required to turn conversations into commerce and curiosity into profitable growth.
We explore why unified data is the real unlock for AI in retail and how a business data cloud gives models the context they need: customer profiles, orders, invoices, inventory, pricing, and unstructured signals. Balaji explains Joule, SAP’s conversational co-pilot, and how it sits on top of business AI and knowledge graphs to answer questions, trigger actions, and summarize insights for teams in the flow of work. We also talk about WalkMe’s role in accelerating adoption and giving users context-aware guidance and shortcuts. The result is a stack that reduces friction, shortens cycles, and makes bold ideas operational—without replacing the people who bring judgment and brand sense to the table.
The conversation tackles big shifts many leaders feel but haven’t fully mapped: destination shopping becoming instant demand; personalization evolving into proactive orchestration; and loyalty moving from points to trust. We consider how to tie recommendations back to inventory location, margin, and sustainable delivery so that offers are both relevant and responsible. We also address tough realities like a five-point slide in true loyalty and the widening expectation gap, and why AI-driven pilots—margin-aware personalization, proactive service, dynamic bundling—are the fastest path to learning what works at scale. If you’re serious about real-time retail and want a playbook that blends strategy with execution, this conversation delivers clear steps and fresh energy.
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Real-time retail is now, and being able to experiment and to drive conversations in a multimodal format into a richer commerce, into an experience is just happening as we speak.
SPEAKER_00:Today in Adventures in Customer Land, I'm with Bology Bala Subermanian, who is president and chief product officer for SAP Customer Experience. And uh for many reasons, one of them being this is the only second podcast I've had with anybody with a longer last name than me. So um very happy about that. But seriously, uh Bology and I had a conversation some time ago that opened up and I would say peeled back many layers of the customer experience onion that SAP is solving for. And we promised each other at the end of that that we would pick this back up. And since then, there have been all kinds of new developments, new announcements from SAP, uh, especially at their more recent SAP Connect event. Um, but enough of me. I want to welcome Bology back to the conversation. Thanks for joining me.
SPEAKER_01:Thank you so much, Mike, for uh having me. It's um you know it's fantastic to be here. And I always uh love talking about customer experience and specifically in retail. So looking forward to this.
SPEAKER_00:As we said just a moment ago before we hit the record button, um, frankly, you have a huge a humongous remit, but um uh almost aside from that, the the fact that SAP is so deeply wired into these specific verticals and what's happening with um AI's uh I'm just gonna rewiring of everything we understand about about retail right now, and fashion and wholesale and CPG. There's an awful lot to talk about here. There's just an awful lot to understand. So um maybe just just to kind of reintroduce yourself, if you wouldn't mind, tell us what that division of SAP is all about and your role there, and then maybe we'll just jump in from there.
SPEAKER_01:Yeah, sounds great. So um the unit that I oversee, Mike, is um we call it SAP Customer Experience. So what that really means is we serve organizations around the world in um in over 70 plus markets um to serve what we call as customer facing function. So this is typically uh organizations who have their sales reps and sales leaders interact with their customers in order to develop their pipeline opportunities and all the way through to um closing deals and serving the customers post. So that's a sales function, if you will. Um, we also have uh customer facing functions that serve post-purchase experience. This is your service experience. So, what happens when customers really use the products and services, and how do you serve them if they have a question, if they have a problem, if they need some help. So this the service part of it is the second domain that we serve. You know, this is all those uh service and service operation leaders. Uh, we also serve uh marketing domain and marketing function. So this is typically uh your marketing leaders and CMOs of the world. How do they serve the customers appropriately to get them be aware of it, send the right messages in the right time to the right audience and personalize their uh information in a way that is meaningful to in order to orchestrate the journeys? So that's the marketing domain that we serve. Uh, and we also serve uh commerce. This is like your um omni-channel, unified commerce that is heart, you know, bread and butter of every customer, every organization that they want to serve. So, irrespective of first-party channels, third-party channels, uh, different business models, whether that's you know, buy ones, bundles, subscription. So everything to do with uh unified commerce is the fourth domain that we serve. And underneath all of that is obviously what we call as like your understanding of your customer, customer data, customer insights, and all the AI that goes along with it that cuts across sales, service, commerce, marketing domains, if you will. And in many ways, there are certain industries that we serve that requires much more higher fidelity and complexity as it pertains to, you know, um, you know, configured products, and how do you code and how do you get that process through? So that's just in general across all the domains that we serve, and that's customer experience. And then the second part of my unit um actually takes all of these very horizontal set of domains that applies to manufacturing companies, telco companies, utilities companies, and what have you. And then we pivot end to end on providing best in-class experiences for specific industries, which is where retail, wholesale, fashion, and consumer products come in. So that goes everything from not just the customer-facing domains, but inventory, order management, all the way through to back office financials as well.
SPEAKER_00:So you can see why uh the last conversation was such a big one and and sprawled. Um, but in this one, I think, you know, frankly, there is so much we can talk about, and and I've got a healthy outline of places we can go here. But I think what I'd like to do, if it's okay, is let's just start with AI, because it is it is such an important factor right now. And uh, I'd like to start there because uh SAP's got some really interesting AI tools that you're working with and building, but I think more so because by virtue of your role at SAP, which um sits on top of several fairly big and complex business units and the reach of those business units um vertically and horizontally, I think you're gonna have a unique perspective on what AI is starting to mean in retail. And I'd love to just kind of throw this out to you and and get your high-level impressions because uh, you know, you and I and our teams have been to NRF, we've heard all of the AI hype, and then it continues um at pace. But I think you're in a unique position to see beyond that. What's actually working? How is this being deployed and thought through? What are the current effective AI strategies? And so I'm this isn't looking like much of a question, more of a theme, and I'd love to just get your thoughts on it.
SPEAKER_01:Love it, Mike. Love it. So I'll I'll say this, Mike. I think you're right. I think this notion of what does it really mean from an AI standpoint? I mean, it's it's disrupting every industry, every job function that we know of, and um specifically in um in retail, it's even more pronounced in some ways uh because we're all consumers, we all shop, we all know what it really means, and uh and it's just uh changing the way that um you know we expect certain things these days and how retailers will have to adapt in order to drive to those outcomes, if you will. And the first part that I'll say, Mike, at least from my vantage standpoint, as we think about um the future of retail and what retailers need to do, I think you know, the notion that retail from from the lens of a consumer standpoint used to be thought of as like, hey, it's a it's a shopping destination, so to speak, right? It's it's where you think of uh what you want to buy and what you uh uh and where you want to buy it from. But that is shifting very, very quickly into from a retailer perspective, um, instead of it being a destination shopping into an instant demand. And this is shaping the nature of all the channels where the customers are coming in, not just what they buy, but what they intend to buy, what questions they ask, what information they post, what they share with their friends and family through that, it just becomes an instant demand because I think that when you assimilate through the power of AI, you can actually drive phenomenal outcomes from uh a retailer operation standpoint as opposed to it being just from a shopping standpoint as well. So the ability to sense, predict, and act uh through that demand signals that are coming in used to be a much harder to go do, it was time consuming to go do, and the accuracy was not as great as it used as we have the possibility now, and AI is changing that shape dramatically to be able to tighten that um flow and end-to-end process much more shorter, much more crisper, and to be able to do that. So I think that's the starting point of what I would say is where AI can drive phenomenal outcomes for retailers, especially being um being that that glue effectively and that operating model is being always on uh wherever your customers are in whatever channel, uh whatever time it might be. So being always on uh to being um you know personalized, if you will, which has always been a nirvana that all retailers have always been wanting to, but now with the power of AI, that that that's quite feasible. But more importantly, is being predictive. So you know, you anticipate the needs before and sense the the signals in a manner that you can you know pipe the way through all the way from just not the customer facing functions, but all the way through to intelligent operations. And that's what drives us, and that's what we look forward to delivering for our customers from an SAP standpoint.
SPEAKER_00:Couple of thoughts you've prompted here. One is um that you're what you're chasing is a much more holistic view of customer value beyond just purchase, basket size, frequency, and those kinds of things. Um, what are those other signals where they're providing value to the value to the sponsoring company? Which is really interesting. And I think that's a whole multi-conversation podcast in itself. Um, the other thing that that occurs to me as you're telling me about what this particular call it function set that AI is providing um through SAP is that you listen to the news today uh over the past couple of days, and there are uh large companies uh laying off large numbers of executives, middle and upper management, because AI is now taking their place or they're planning to. And yet, what I think you just described here doesn't, if I'm thinking about this correctly, doesn't displace anyone at all because these functions were never even possible before. You couldn't even get there. Therefore, this is all basically found money, if I'm not mistaken.
SPEAKER_01:Yeah, it's a really, really thoughtful and insightful observation there, Mike. So we don't think of it in terms of, you know, whether intelligence is there to replace uh a job function. We think of them in in two different pivots. One is for every job function in every company, retail in particular as well, there are, you know, if you think historically and most enterprise retailers have, it's not like they don't do it. They do it, but it's it's isolated, it's siloed data and it's sitting in different systems. And I think you and I will agree, Mike. I think, you know, the the benefit of AI and the value of AI is much, much, much more deeper when the context that is provided to that is as broad as possible. So when the breadth of the context is wide, the value is much, much more deeper. And that's a fundamental philosophy that we take here. And therefore, um, to your point, um, we think of you know any persona in an organization, whether I might be a category manager, a merchandising manager, a customer support um manager, if you will, I tend to do my jobs today, and we tend to create intelligence for them through what we call as assistance. And these assistants are AI-powered. It can be embedded in your workflow, in the line of work that you do, in the applications that you're using on a day-to-day basis, or it can be a gentic stuff that happens underneath that is autonomous, that can reason, that can act on behalf of you. So, ability to assist a human in the line of flow that they work on is a critical part of what we do. So that's point number one. And why we do that is oftentimes um many of these roles and personas in these organizations actually spend more time in doing, you know, like really grunt work, mundane work that actually takes time and effort from actually doing something that is meaningful for the business. And therefore, the more we do it, it relieves them of their duties in that regard, but then focus on what really matters in the in their line of duty and their line of job effectively. So persona-based AI assistance is one part. And you flip to the other side, which is these are things that um many organizations don't even know can be done. So we call them deep research. And how does deep research come in? Is because you have isolated pieces of data that are sitting in different places. You were never able to correlate and bring them together into a meaningful aha moment. Hey, did you know that this is what is going on? And it's fascinating because this was never even possible before the age of AI. Right. But now the power of the technology that we drive is just even phenomenal. But the underlying data, when you assimilate and bring them together, the deep research capabilities of this will provide retailers with immense value that then can convert from data to research into insights, and insights drive action. And those action feedback into the same personas that we just talked about, then it becomes a much healthier and much higher value cycle, so to speak. So that's how we classify set of assistance and set of deep research capabilities, all founded on the foundation of connecting data, semantically rich data from different parts of the system that is enterprise-wide.
SPEAKER_00:So I'm dying to get to this part of our conversation here, and I think you're you're uniquely positioned to have a view to it, but and I'll just frame it this way um AI isn't just an efficient, an efficiency creator, it is potentially a business remodeler. Um and and I think, in my view, it should be right now. I think the the people who sit uh in the C-suites should all be thinking about what their business shape, their business design will look like in a year or two, three, or five. And um, and I be frank with you, I speak with a lot of executives um who are at that level. And I think when I mention these kinds of ideas, I get a gentle nod, like, yes, of course. But my sense is that that work is really difficult. It takes it takes thinking that is not part of your normal business day-to-day task work to consider possibilities that you've never considered before because of of what AI can do, and I guess if I understood correctly, what deep research is designed to do. Do you see in your work and your work with uh clients and executives at that at that level, are they beginning to start to understand the magnitude of the reshaping of their own businesses and industries? Or is that still kind of hanging out there as uh we'll get to it when we need to get to it?
SPEAKER_01:Yeah, I I think so. From my my vantage standpoint, Mike, I think the the possibilities are becoming much, much more um obvious for many of these business decision makers in these companies, for sure. Um, and I think it's also becoming even more clearer the power of this technology that we have in our hands today and what you can do with it effectively. So, in many ways, what we believe and what we talk to our customers, um the age of real-time retail is now. And that's profound in the sense that we used to be thinking about what does real-time even mean? What is it? So to operationally pull it all together, and we know retailers have massive amounts of data already, and they gather even more data on an ongoing basis from core, backend, operational data to behavioral data, to engagement data to pull it all together, the age of real-time retail is now. Now you combine that with what the business outcome is, and we believe that at least the key part of where the technology can fit in, and what we aim to drive is to enable organizations at large, but definitely retail, is to drive what we call as profitable growth. And to drive profitable growth, you need to pull in this information that we just talked about, sense, um, you know, uh decide or predict and act. And in that model, you can actually try to make the demand and supply come together. Um, and to be able to say that I'm not even, I'm not just personalizing information for you, but personalization is a way that I can actually drive action. So connecting insights through that into data action is a key part of it. I'll give you, at least my view, uh Mike, like it's some examples, right? So, you know, the these AI capabilities and models around us in the world of real time retail, you can actually take, you know, your inventory feeds, your pricing feeds, your demand signals, what people are looking at, what they are searching, what they Are you know spending time like you know, uh not just structured data, but even unstructured uh data with all the semantic and context, you provide that, and not only now can I personalize just because what Mike was interested in or what a consumer was interested in, but now I can orchestrate this. I can orchestrate this almost in real time to be able to say what I'm personalizing for you, maybe an offer that you're looking at because it's interested, but now I can tie this all the way back into do I have the right inventory? Is it in the right place? If not, can I transfer the product so that it can be available when you want it? Is it even by the way, one of the key things that we look at is um is uh is it margin uh accretive? Because it's one thing to say that I'm personalizing it for you, but sometimes this type of real-time world, you don't get to optimize for the profitable growth that we talk about. So making sure that the profitability is taken into account. And last but not the least, is also sustainability. I mean, we we live in a world, especially the Gen Z uh customers, they care, they care about the brands that they buy it from, they care about not just the quality uh and the price point, they care about sustainability. So when I do that, I can take it back and saying, am I operating it in the most sustainable, environmentally conscious world? So by tying all these pieces, so that this personalized experience that I give to my customer has roots that tie it all the way back. So real-time retail now, with the ability to stitch data into insights into action that cuts across the entire enterprise, is what um we are talking to our customers about and what they are thinking about. Now, you bring up a really good question. Now, where are they in this journey? Are they implementing all of them now or are they like how are they facing it? And it really depends.
SPEAKER_00:You know, because I think there are people out there who are still scared of the idea.
SPEAKER_01:You know, it's it's also a journey, in my opinion, based on the maturity of their organization effectively, right? So some of them are far more mature than um in both in terms of data, their IT landscape, and also conceptually where they want to go effectively, and some of them are putting their pieces together. So I cannot say it's a one size fits all, but in my view, far more of these retailers and organizations are wanting to do more things than ever before because they now see the possibility. Yeah, they now see definitely the possibility. I'll give you another, maybe another example here, Mike, which is we believe, I think at least in this age right now, where we stand, um the the world of AI in general is enabling uh you know retailers in particular to turn conversations into commerce. Uh, and what I mean by that is in the past you have to like really take the action to go do something in order to uh you know, quote unquote do your shopping part. But now the idea that you are thinking about, the the concept that you might be kicking the tires with in your world, uh can actually turn into a much more richer discovery process, um, understanding of it. And this does not have to be in the traditional channels, if you will, either in a store or in an online uh web storefront or an app or even talking to a human. This can show up in different places now, increasingly in uh what we call as answer engines, like your chat GPTs of the world or perplexities of the world, this this notion that, hey, I'm I'm I'm having a Halloween party this weekend, starting from there, then I can immediately have uh ties into my personal my personal preferences, understanding who the customer is, understanding the uh the location where I might be in, all the way through to answering questions, asking uh relevant things around it, in order to drive a beautiful experience of discovery that I may not even have thought about. So AI and LLMs in particular, driving conversations into commerce, the richer commerce. And commerce I don't mean as a domain as a product or as a purchase, I mean as a domain, which ties everything from pre-purchase discovery all the way through to getting the right bundles, right offers, right way of delivering it to you, right way of even, you know, in some cases, um, you know, uh servicing installation experiences that might be needed. So that's a huge part of it. So, in our view, is real-time retail is now and being able to experiment and to drive conversations in a multimodal format into a richer commerce into an experience is just happening as we speak.
SPEAKER_00:Well, I'm sorry to say this, but we've just derailed the intent of this conversation badly, and we're we're now in danger of going off down many, many rabbit trails here. Um but but one thing that I think you might be pointing towards, and please correct me if I'm if I misinterpreted this, is that SAP is designing systems, these are my words, so you have to work with me here, um, of influence that touch on customer touch points, which may not be direct. And what I think I'm trying to say is that uh that you're devising ways of understanding individual customer ecosystems, the things that influence those customers beyond just they wear this size and they like this color, but what other what other influence mechanisms are in their worlds and how can those be leveraged? Did I get that close to right?
SPEAKER_01:No, no, you you got it exactly. So the idea of understanding, deeply understanding the customers, their preferences, their wishes and needs and wants, um, and tailoring that is one part, which is obviously feeds into a more personalized engagement, if you will. So there is that part of it. And I'm combining that, and this is what I'm calling um AI drives conversations into commerce, by combining that into a richer discovery process. Hey, did you mean this? Did you want this? How about this? And to being able to have as if I'm a human being that I know I'm an expert in it, so I can help assist in what you're looking for. Now the systems are designed and they are capable of assisting this in a self-serve, richer discovery process. That's the second part that I'm saying. And then the third part is proactive orchestration. So it's not just personalization because I know who Mike is and I know your preferences, I kind, but that's not enough. But we are trying to say, okay, you need to take that and make that better, but make that into a proactive orchestration that cuts across the entire enterprise so that your needs and wishes and wants get converted into a much better discovery experience and much better, you know, fulfillment, service, and after-purchase experiences as well. That's the three phases in which we think we do. And for us, the real-time retail being here, you combine that with conversations that are richer in discovery, turning into broader commerce is what we think is uh is needed for retailers to drive profitable growth overall.
SPEAKER_00:I so badly want to be on the uh fly on the wall when you're uh presenting these concepts to uh to your clients because um I think I understand where you're going with it. It makes an awful lot of sense and it's very exciting. But um watching the light bulbs go off above the heads of the executives as they're starting to see what's really possible that never has been possible before is really exciting. Um I'd like to to talk about two specific AI systems that SAP has. Uh, and I'm calling them systems because I'm just not sure what else to call them, but one is jewel, and the other one, which I'm just barely familiar with, is something called Walk Me, which um, you know, I believe they're both AI driven. But would you explain Joule? Let's start there, and then uh what is Walkme?
SPEAKER_01:Yeah great, great questions. Um, the best way, maybe the simplest way I can explain Joule, Mike, is think of it as like your your um co-pilot, if you will. So this is SAP's co-pilot. So this is there in um you know, in conversational interactions that you might want to have as a user, as a user of an application or a user of a system, if you will, uh that allows you to ask and interact with the system behind it. So this is like your conversational assistant. Behind Joule, Joule is not just the widget or the conversational assistant, but behind that, you always have our SAP business AI infrastructure. This allows you to actually have the right models, allow you to train those models, create knowledge graphs of it so that the information that you're asking for and what you're getting is far richer and far more deeper, because that's the intent of the so that it provides business AI capabilities that we bring to bear for our users. Behind that is uh data. So uh so this is not technically part of Joule per se, but what Joule feeds off and what we run on top of is what we call as business data cloud. So think of it as you know, you're a big organization, uh, you know, an enterprise retailer, you run some SAP applications, some non-SAP applications, maybe some custom ones. What SAP Business Data Cloud allows you to do is pull all of those information into a consistent, harmonized, semantically rich data model. So your customers, your orders, your invoices, all of them, along with some of the you know, uh non-transactional data all there. And that feeds business AI and the underlying model, and then Joule becomes the the thing that you interact with on a day-to-day basis in order to that's on Joule. Walk me um is a different uh, I mean, it's also obviously from an AI standpoint, it has lots and lots of good things in there, but it was also an acquisition that SAP made, I don't remember exactly, but in the last couple of years, I think. Um I don't remember the exact date on it. But the idea behind that is uh twofold. One is to allow is to enable users to discover and to adopt capabilities of the applications that they are in. So oftentimes, um, you know, if you're a user using one of the more uh comprehensive applications, if you will, uh to discover capabilities becomes a challenge. So walk me allows you to create content that allows you to users to navigate and get to know the capabilities in a much more easier manner. Uh that's why the term walk me, I'm walking you through the applications in a way that you can benefit from. So that's the first part. There is also another part, which is always on, always omnipresent layer, which means that if I'm, let's say, on a screen and I'm looking at something as a category manager to do, go do, I can invoke SAP walk me right there. It's it's on that action bar and it reads information from the screen and it gives you contextually rich aware uh rich actions that you can take right there without you having to leave and go do something else. So it brings that experience layer to it as well. So one is for AI and what you can use, the other one is for using the application, navigating, adoption, and quick actions that you can take. That's Walk Me.
SPEAKER_00:Gotcha. Okay, thank you for the clarification there. I'd like to jump to some of the uh the data points that your team's surfaced in some recent reports. Uh, one in particular, and we've spoken with other people at SAP about this trend, but it seems particularly salient right now. The loyalty index that you produce shows true loyalty, I'm putting this in air quotes, slipping five points year over year. And and I kind of just want to let that notion hang in the air because that's a that's that's a big deal. What's what's the outlook for the next two years? What what will and will AI-driven personalization be able to reverse that trend? Or are we facing some kind of a structural shift in the way loyalty is defined?
SPEAKER_01:Now I think it's a it's a fantastic data point that you're just uh outlining there. Um, because it is, you know, in our opinions, Mike, I think organizations have to you know deal with that reality where true loyalty air codes that you said, because the way we think of loyalty and what the the survey actually produces, this is not your typical loyalty program um of where I'm you know earning and burning points and buying. So that's obviously important uh for me, a number of reasons. But the way we think about um loyalty and what is critical is to earn the trust of that customer. Um, and because trust is that core fabric that stitches everything together and to earn the trust of that customer, because when that happens, then they become a lot more advocate of your brand, and then they um they become your fans and they bring in more. You know, the the notion of NPS that we all know of in the software world is criticality, and that is how we think about it. So true loyalty is exactly that, because the benefits are very real, because loyal customers, obviously, it's uh, you know, you can you can retain them, you can serve them better, they bring more business on by themselves, they're willing to pay a premium for your brand and for your experiences. So the business benefits is just extremely, extremely critical. And that is what we are focused on, and that's what we announced and talked about at SAP Connector as well, which is a loyalty management capability, not just purely for transactional purposes, but truly understanding your customers and truly serving them. And that ties into the operational mechanics of how the system operates, allows you as a retailer to have a more comprehensive multi-brand, multi-geography, both first-party, third-party channels in terms of how we do it, is how we believe that uh this needs to work. Now, to your point, will this shift uh continue to be there and can AI help? I personally, this is just my personal view, I fundamentally believe that in the world of retail, intelligent retail, real-time retail that we just talked about is here and AI is core foundation of it. And if retailers grasp the power of AI and what it can do, it can certainly change the mechanics of what we call as true loyalty. Um, in many ways, if they don't do it, this trend will accelerate. But I fundamentally believe that this is the only way that retailers can not just stop the trend of this, but actually turn this around in their own favor because when true loyalty index for their customers actually grows, their profitable growth uh happens as well.
SPEAKER_00:We've done research and we've done this for the past several years with uh another group that indicates that customer expectations in almost every category are rising at an increasing rate. And companies, brands, retailers' abilities to meet those expectations, while they're increasing, they're not keeping up with the increase that the consumers have, which creates this widening gap of unmet expectations. And um for a while, it was just one of those facts. Look, if you if you're a company or a brand, a retailer that wants to understand uh the drivers behind the those gaps, well, we can help you uncover that. Um but honest truth is uh a lot of those uh gaps are created by emotional expectations and emotional drivers. And up until very, very recently, companies didn't really have the mechanisms to address those at scale. So I'm I'm very interested, and I'm sorry if I set you up with a bit of a softball there, but the uh I'm very interested to see what those, what that gap starts to look like over the next few years, because we have AI-based tools now that can analyze what those drivers are and can point out um fixes, if you will, to them. And I think that's I think that's what you're talking about here.
SPEAKER_01:Okay, that's exactly right, Mike. I think that the the tools have been evolving to your point. AI is not something like in a relatively we've had the tools, but I think the power and the scale at which it is now working is far superior than what we have seen in our lifetime, number one. And two, bringing data together in order to serve that is far superior than um what we've seen uh in the past effectively. And three, I think the notion that uh the mindset of organizations and the decision makers in these organizations are much more um, you know, to invest and try to experiment and to try what might work is also far superior than what we have seen. And I know, you know, uh we're coming up to the holiday season uh here, right around the corner. And uh, especially for retail, especially in omnichannel and unified retail, so to speak, this is like the moment. This is a moment that uh all organizations, like you know, they've spent almost a good chunk of their year preparing to deliver their blockbuster uh uh uh season, if you will. And I think, you know, if uh we can leverage these tools and try in certain places, especially depending on their risk profile and what they want to do, I think they can learn a lot more from it and then they can adapt it in 2026 and beyond. I think that moment is right here, and we work with some of our retail customers in that regard as well, because there are some new avenues that did not even exist six, twelve uh months ago, and they can experiment with it than um than ever in the in the past, if you will. So I do look forward to seeing how this will play out uh in the in the next 12 to 12. 24 months.
SPEAKER_00:Yeah, it's going to be interesting. We we've got a longitudinal view of this those gaps that goes back, I want to say 25 years at this point. And it's just been widening with a few little blips in the curve that that show that certain industries or certain brands have started to close it. But overall, it's just a widening gap. Maybe it's maybe maybe we're turning the corner on that.
SPEAKER_01:So the only thing that they can do is there are things that they don't control, and then there are things that they do control, and they can make a big uh impression off it. And so by leveraging AI, turning into real-time retail with an end-to-end enterprise-wide to run intelligent retail, turning conversations into a richer discovery and richer commerce are things that they can control. And when they do that, and do that in an efficient manner, in a sustainable manner, they can turn the needle there on the true loyalty index that we just talked about.
SPEAKER_00:Um, so a cue to pay attention to the next edition of this conversation when Bology and I finally have a chance to reconnect on it. Um, Bology, I want to just thank you again for your time and your perspective. Um, not only is it fascinating, but I think it's really instructive. I think, you know, just by virtue of the fact that you see the world from where you do, um, gives the rest of us down here at street level a lot of perspective we we badly need. So thank you for that and very much looking forward to the next time we get to do this.
SPEAKER_01:Yeah, thank you so much, Mike, for the opportunity. It's always great to talk to you, and I look forward to the next uh next episode.
