Hello. Good afternoon, everyone. My name is Devin Poole, senior product marketing manager, for financial services here at Coveo. We're gonna give folks time to get in, settle in. We won't kick off with with any, content until, you know, about, one or or two past here. So, if you're just joining us, feel free hop on, settle in, and, we'll get going in just a couple of minutes. Of course. Now is the singing portion of, the the show. Sandeep, I'm gonna turn it over to you for karaoke and, pick your favorite song. Right? Alright. And hello again. I can see a few more folks, just joining here. So we'll get going in about a minute or so. So you still have time to grab a last coffee if it's still morning time or you're an afternoon coffee person, or, grab a glass of water. Maybe those of you joining us from Europe, you might be into cocktail o'clock by now, and that's just fine as well. My my bad jokes are even better when you've got a cocktail on hand. So and we'll get going in just about a minute or so here. Alright. Too fast. Perfect time to to get going. Again, I see the trickle of folks, coming in, starting to to slow down a bit, and so seems like we've got our quorum. Welcome. Good afternoon, and official welcome to to everyone here. As I said, my name is Devin Poole, senior product marketing manager for financial services at Coveo. Really excited to be joined by, one of the best and brightest in this space from Accenture, Sandeep Pradhan. Sandeep, thanks for joining us. Yeah. Hi, everyone. Good morning. Good afternoon. And, glad to be here talking about the two interesting topics here. Yeah. I mean, really, really, exciting topic. We've got enough here to probably fill most of a a day, Sandeep. Right? But Yeah. What what what the, emphasis behind putting together this session for folks was, you know, one of the the biggest, most pressing topics for financial services leaders for the many, many years that, I've been covering this industry has, you know, not necessarily been how do we get more people to try self-service? How do we get our customers online? Because certainly, the the world has gone that way. We'll show you some data in a second there. But it's ultimately, how do I build more of a self-service dominant mindset, in the industry. Right? We've, always been an industry that holds on to our, our ways of doing business pretty closely. Right? I remember fifteen years ago when I was living in Australia, working with the banking sector down there. You know, it was, we we're never gonna get rid of the branch. Our branch footprint is the most important thing to us. And then you start to see that slowly chipping away. Right? So, our goals here for today are to, you know, one, share, interesting insight, data from, around the, world that's gonna show you, you know, how, or customers are reacting, what companies are doing about it. We're, of course, gonna talk about everyone's favorite topic, generative AI, who's not talking about that these days. And then leave you with some, you know, tactical, practical advice to building a more self-service dominant mindset. Right? What are actions that we can actually start to take action on today? So with that in mind, let me first just level set everyone with, you know, where we are today. Right? It is the the digital first or digital dominant or pick your, you know, terminology for this. But we live in a world where the majority of our customers interact with us primarily through digital channels. Right? And you can see, different industries represented here from, some data from Morning Consult, their financial services trends report, which is fantastic, right, where the the darker blue bars represent, you know, respondents interacting with their primary financial services provider, you know, mostly digitally. You know, for banks, little over half of people. Credit cards, it's up to nearly seventy percent. You know, credit unions, investment management firms, roundabout almost fifty percent. Wealth management coming in, at the the lowest end, but still forty percent of people say that's primarily how I interact with my financial organization. Of course, when it comes to, the the area that Suneet and I cover, most closely, it's customer support. Right? Whenever I have a problem, right, the first thing that the vast majority of us do is we Google it. Right? I search for information. I start in a digital means. So while this, data tells about the overarching relationship, what we often see, right, is that when it comes to support, customers primarily do choose digital channels first. Salesforce shared this about a year ago. Right? Eighty one percent of retail bank interactions start in a digital channel, start in some sort of self-service option. And so this is, great to say we're we're moving toward the the digital first era. Now, Sandeep, let me bring you in here because, in a lot of ways, you start to see this where the the rubber meets the road. What what are some of the things that you're hearing in your conversations with financial services leaders when it comes to, you know, making this push toward a digital first landscape toward, you know, a world where we interact primarily with our customers in a non, you know, one to one human to human conversation. Yeah. I mean, I think, one of the thing that, I hear most in the financial industry is I mean, as we are talking about, like, in the wealth management, right, or or in the banking, where you wanna you go into the digital and you wanna be able to self serve the customers, and they want they're all savvy, tech users. I mean, they're savvy at the Google. Right? Again, everybody can do the Google. So they wanna find out the answers quickly. So I think no different in here is, like, as you are as to from anybody, like, who's serving you in the bank or they wanna find the answers quickly, and they'd be able to do that, I think, by going on their own, which we are saying as a self-service. So to have a good self-service, you do need to give them answers that are we are more tuned to it, like seeing in the first three results or, like, first page. And that's where I think it kind of becomes, more important to get more relevant results on top, to answer their question. I would say be more active, like, actionable answers that could be sewn prominently on the top. Yeah. And that's it. Right? It's if you ask, what's changed in our lifetimes? What's the biggest thing that's changed? It's, of course, technology. However, at the same time, right, what technology has changed is the convenience factor. Yeah. Our world is so convenient these days. We can get any answer, any piece of information that we want at the touch of a few buttons with the super cute computer that lives in our pocket. Right? And sometimes it listens to us when we're not even using it. I'm sure we've all had those cool, creepy experiences. So this is what customers have come to expect. Of course, how is it going? Right? What what are customers saying, about their experiences digitally? Well, you know, we just, undertook a large, survey to talk to to customers about how it's going with their digital, interactions with us. And, you know, to me, to hear that the headline kinda says it all, patience is wearing thin from customers. Right? Take a look at this first stat, when Coveo went out and asked more than twenty five hundred customers around the world, fifty percent of them said that they would rather have no self-service option over bad self-service experiences. And a lot of what this speaks to are customers who are really tired of being, trapped in that chatbot whirlpool where it's like I go around in circles, and no one ever lets me out to a live human even though it can't solve my problem. Or it's like, don't give me that. Just give me something else, instead. Right? So what customers want self-service? If it's bad, they'd rather not have it. And then fewer than one in three customers said that they're satisfied with the the app or the web interface of their financial services providers. Right? So, we're starting to see customers, and this is why, on the last page, we probably still stubbornly see some of those numbers of people who will only or mostly wanna engage in person. And so it's not that they wouldn't do it. It's that we're not necessarily providing the the right resources here. Making it worse. Right? This is, sort of like the the death by a thousand duck bites is the the way we always talked about it when I was at CEB Research. Right. Fifty five percent of customers on the right say they rarely or never complain about it. So they might be having a bad experience, and some people on the line might be thinking, well, we're not hearing that in our VOC. Our customers aren't saying anything bad. Well, they're also just not saying anything. But that's the the sort of silent killer here. Right? Is that customers will just leave without telling you. We're facing tons of competition in the industry from neobanks, from digital and direct banks, and, I don't know. Sandeep, if you saw the announcement, Apple's getting into savings accounts Oh, yeah. Maybe partnering, you know, with, Goldman in that sense. But, man, what a big threat, especially when you look at how desperate we all are to scoop up deposits these days, and Apple can do it pretty quickly. It's it's gonna look like especially because they're answering, that they're offering fifteen x the the national average for savings, yields. Man, that's dangerous for us. Here's what we think about what we're doing in the financial services space, you know, as providers. Now all of the these three data points, scary enough, but here's something that, you know, we we think spur is gonna spur people into action. Right? Into driving, toward a different outcome. Because when you look at this chart, we're showing the tolerance that customers have, and how many, negative digital experiences it would take for them to abandon a brand, for them to leave. Of course, financial services products have become, you know, less and less sticky, over the last couple of decades. Right? It's easy to open up a new account somewhere else. It's easy to start just pulling, oh, first, maybe it was my credit card, and then now maybe it's my transaction account, and then maybe my savings go away. And all of a sudden, you're not the main provider anymore. And when you look at this, you know, three out of four customers, on the left hand side of this chart say it's gonna take three or fewer, negative digital customer service experiences before they are deciding I need to leave. I I I've got to go find something else out there. And so that that that's, tough, medicine for us to hear at times. But, you know, Sandeep, when you take a look at some of these negative digital experiences, what are some of the big drivers behind that? What what are some of those experiences that that customers are talking about these days that customers say, man, this is really driving me to consider my options? Yeah. I think, that's why I think it's very critical to measure these, like, implicit signals, right, rather than just I mean, I think if you're expecting them to provide the explicit feedback, it's not gonna happen. It's gonna have to be this implicit measures that has to be in place. So if if they can't find it, I mean, as you said, like, when three tries, they're out. So it's this becomes very important to, like, to meet that net need at the when you go when you do go live or, like, when you are launching to new system for this self-service. And it's critical that you have those implicit indicators and be able to tune to make sure that you're giving them the exact right answers, right, at the time that they're picking. So it's it's a very low tolerance, but I think that's also opportunity for, like, to have your have a, like, implicit measures to measure what's happening and to be able to tune and adjust adjust your system to fulfill the needs. I think that's what I've seen, like, in the system that we work with to with the clients to, I mean, to measure and then do have a pretty much, like, be able to fine tune that system as they go live. Yeah. And, of course, right, it is, as you're saying, relevance. Right? You've gotta have relevant information where I need it, enabling me to find it quickly and easily because when I don't, right, the first thing I do is I abandon the digital channel and say, that's way too frustrating for me. And then, I I pick up the phone. I I open up a chat. Right? And that is far, more costly, and it costs you on two sides of the equation. Right? Of course, it's a hundred and ten times more expensive to handle an assisted contact than than a self-service contact, but it's also costing you on the experience side. Customers, again, as we're seeing here, they have those experiences, and they they, you know, will decide at some point. Three is too many. I'm out. So this isn't to say that financial services organizations aren't doing anything about it, because, of course, we're doing something about it here. So let's take a look at that, over on the next page. Right? I call this slide sort of one step forward because while, we've been investing, you know, quite a bit in this space. We we've been looking, you can see a little over two thirds of banking executives say that their piece of digital transformation is accelerating. Right. We're we're moving into this world wholeheartedly, which is great to see. Right? I know financial services companies, it's sometimes pretty slow to change. Right? And so we're we're putting it in our strategic plans. And at the bottom left hand side here, you see that, eighty six percent of financial institutions say that they're, you know, assigned more than twenty five percent of their overall budget to the customer experience in some way, shape, or form. Right? So that that's fantastic. Right? We are putting our our money where our mouth is here. Now, Sandeep, over on the right hand side here, this, is some data that that came from Accenture and a study that you did looking at, you know, AI as a foundation, right, at least identifying the key drivers, you know, to, to push into, AI on the bottom and along the the top here, AI differentiation. Right? The capabilities identified to achieve the the growth that we're looking for here. But what we found is that while we're all making investments in this place in this space, very few companies are actually achieving a lot with AI. Right? There, only twelve percent that have a differentiated AI strategy and can operationalize their investments here for for value. So, when you're working with your clients, Sandeep, do you well, let me guess sort of a high level. When it comes to AI, do you see more people sort of building these things in house? Are they going out to the market? What are the the capabilities that they're looking for? So two part question. One, let's start with, are they trying to build this themselves, or are they going out to the market for it? I mean, it's I've seen mix of both. Right? I mean, some some are two people, they have to do a do a in house or they do a mix for certain parts of it. So we've seen mix of it. I don't have a data for the what's proposed in, but I think it's a mix of both. Yeah. Yeah. Fantastic. And then so what what are the the capabilities that that folks are looking to build in your experience, you know, when when they come when it comes to their investments in AI? What what are the most important capabilities that they're they're trying to achieve, and how's it going for them? So, like, for, I mean, wealth management, I think some of the, customers that I've worked with would like to apply, I mean, AI, like, cases like where you wanna have a self-service not only for the client, but also for the financial advisers. Like, if they're working with the clients, they would like to know, okay. Who who are my clients where I could, are approaching the retirement age, and I could tweak the plans or something that's gonna be important for him to talk to the him or her to talk to the, their clients to say, okay. This is a you're coming to the retirement place, and here are things five things that you should do about it. Right? So it would be some kind of, AI build system where they can, look at I mean, the system can warn the, the financial advisers about it and be able to be more, I think, proactive, than more, in in the system. So I think that kind of a kind of a personalized experience that everyone's expecting in the wealth management, and that's we can see, like, more personalization is gonna, be driven by the AI. Yeah. Exactly. When you can ingest and digest and analyze that amount of data to be able to say, you know, not just, you know, personalized because we know you so well, but rather, we know other people who share similar traits to to you. Right? Not just Yes. Necessarily, you you know, wealth demographics, not all mass affluent, folks or ultra high net worth folks act the same, but rather, you know, other personalization vectors, like, what what life stage are you in? If you, you know, wanna offer personalized content, personalized information to someone around retirement, say. Right? Like, whether you're just starting your retirement versus getting ready, to retire and start taking distributions, well, you're gonna offer much different, information to that person for, you know, a search or for, the the way that, you know, they're interacting with you, the way that you wanna personalize this. And so taking those into to play is gonna be critical. Of course, you don't wanna overdo it. That's one of the the keys. Like, you can get way too personalized way too quickly, with customers, and that crosses, you know, I've always called the cool creepy line where, sure, it's cool, but, man, it it's a little bit creepy. Now one thing, Sandeep, we've gotta talk about. Right? Since you and I started planning this session a couple of months ago, there there's been a few technological revolutions that that have happened in the world. Hasn't there? Right? So let's talk about generative AI for a a a moment here. Right? Because, we've seen some big announcements, OpenAI, and their partnership with Microsoft, Google with their Barca AI, You know, and the the the hype is real. So let's start with the hype. I'm gonna kick it to you in a second to hear, you know, what you're hearing about people are so excited about. But, some of the things that that I've heard, right, is that this technology, it's certainly is changing the the world the way that we, start to envision digital experiences. That that is a fundamental paradigm shift that has happened here. And at the same time, you know, I start to see a lot of companies that are thinking ahead and saying, what about a world where we never have to talk to our customers with a human? Right? The the bot can do all of that. So I've heard that the hype factors from all over the the spectrum, right from this is gonna replace our people entirely to this is gonna do everything for us. This is gonna build our products. This is gonna generate our content. You know, so the hype machine is is alive and well. What are you hearing from your corner of the world, Sandeep? I mean, rightfully. Right? I mean, it's a it's a very much, I think it's a new I think it's one of the revolution, I think, happening right now in front of us. And it's rightfully I mean, so because, it used to be the large language models were not something that was privy that you you needed to train a lot of sub data. Now I think because of the OpenAI, we we can use that and be able to kind of for the generative AI, be able to generate some of the summaries. Right? I think that's been pretty, apparent. And I think, most of the I think a is here, I think, and there's also been a myth about it. Like, oh, can it I mean, will it be able to, solve this? Or can he also would be, like, removing the replacing the jobs? I think it's gonna create more opportunities the way I I see it. And, also, I mean, I think we have to be, careful about this is that I mean, as we we'd be calling Accenture as, responsible AI. Right? As a part of the these generative AIs, we it's not gonna be something that we wanna replace, some of the things, but we wanna be able to put the human in the loop. Or I think that's what I think is a critical aspect as well because some of them are facts, but some of them could be ficticious. Right? And could be, I think what AI, generated by calls it hallucination. So Yeah. Thus. Yeah. Yeah. Exactly. It's, talking about, of course, the the hype. Right? Like, we we can envision this world, and it generative AI will do amazing things for businesses. Like, I I don't think that's in, debate at all. Right? But there there are risks to this. Right? That there are very real risks. You know, you mentioned that the hallucinations, you know, we've all seen stories about aggressive behavior toward users. You know, some of the these bots revealing company secrets, you know Yep. Who owns code when you've plugged it in there to build you a piece of code. There there's a lot, you know, to consider in this. But, I think we've also both, Sandeep, seen a lot of financial services organizations, in particular who are really gung ho about this technology, you know, which, I'll be honest, surprised me because we are typically a very risk averse industry. You know, when it came to things like chatbots, you saw a few people dip their toe in and said, we'll take a wait and see approach and and how other industries are doing it. You know, mobile apps, mobile banking, kind of the same. Now, of course, look how popular mobile banking is. Right? But we we were, keen to be, a fast follower in a lot of spaces, but I've heard a lot of financial organization services organizations who are chomping at the bit, you know, to to jump on to the the generative AI, train here. Why are people so excited about this from what you're hearing? And rather, why are they moving so fast toward it? Right? I get the excitement, but why are folks moving so fast? Well, I mean, in the financial industry, I think, they're moving fast, but, also, I think they're also cautious. Right? Because, it's a it's there's a lot of regulations, and I think, you don't wanna be the first one to be there. But also but you don't wanna miss the train as well. But I think it definitely, I think, sees the benefit, of of generating AI in terms of, like, I think, right, like, data stewards. Right? To be able to, from a governance perspective, to measure to see the quality of your data, I think that's one aspect I've seen, in the financials industry where they would wanna look at, understand their data, and how to reuse their data. So to to reuse the data, first of all, we need to understand the data. To understand the data, I think, how can we do that? I think generate AI, I mean, if you have the if you can search on the data and if you are able to kind of summarize that data through the large language model, then that kinda helps them, and see where where it is. And, also, like, I mean, from the users, like, even the if you think about the analytics, if there's a way to kind of summarize the dashboards, And if we already have so similar dashboards, it's kind of gives them an answer right there. So, also, I'm in from a finance industry where I've worked with, clients where they have large regulation data, like, their procedures and guidelines. There are some of the, things that looking into is, can you while they have to spend a lot of money to rewrite that content and it's a very regulatory content, it would it for the couldn't make it more user human friendly to read it, right, to get a good summary, quick summary of that. I think summary or or the quick description of the doc document from a purely from a user perspective rather than from a regulatory perspective. It kinda helps them, but, but it kind of, helps them what the document is about and also helps them rewrite, like, I mean, from their, if they have a existing process to review the document, it helps them review the document based on the summary. So I think it it it kind of, is, new areas. And, also, with the general AI, I mean, we could have, embedding vectors that could be taken advantage in the search so that we can find those, rather than just doing a keyword search now. I mean, we would be able to do a more searching on those embeddings, and that really gives them more of a finding those, concepts, right, in in a more aligned context of what you're searching for. And it's more different way up from a previously, I mean, would be to do it with the with the keyword search. It's a Yeah. A completely different landscape now. Yeah. Exactly. Right. It's the the shift from just purely search to wanting answers. Right? And that that's again, when it comes to service, customers aren't seeking a a contact. Right? They're seeking an answer, a solution, some sort of help to, you know, a problem I'm facing, to a decision that that I'm trying to make, right, to a a a plan. And so, on your side of you know, sometimes when it's a financial adviser, they wanna spend their time interacting with their client, talking savings plan for that vacation home. You know, we're working toward this. Here's how we're gonna build our investment strategy. They don't wanna or need to to talk about the the documentation that lives behind that, in order to to generate that plan, but they still do need to know it. Right? So it's almost when you think of a very high cost asset like a financial adviser, you want that person spending their time, thinking about the the client and advising and guiding them, not going through thick documentation. Right. So I think you're right. It's gonna be a very helpful way to do that. Of course, large language models have been in production for some time. Right? While, you know, GPT, allows us to make it much more conversational. Right, the the way that, we, at least, we at Coveo have been using large language models two ways here. On the left, using smart snippets. Right? And you can see that the technical description of this here. But, in in human terms, right, smart snippets are if you're asking a direct question, and that answer is contained within a document, like, at what age can I start withdrawing from a Roth IRA? Right? There's an answer to that. It's a named and known answer. Instead of saying, here's the document with eighty five, paragraphs that will tell you where that answer is, like, we'll just give you the answer and display that in the results of your search so that you don't have to go hunting for it. Right? So starting you know, that that's almost the, very simplified version of what you get from generative AI, right, of just give me the answer that I'm looking for when that answers in one thing and named unknown, and you don't need a summarization. It's just like, you know, when was the Battle of Hastings? It was in ten sixty six, in case anyone's a history nerd and wondering. Right. It's like, there's one answer to that. I don't need a a lot more information. And the other side is, you know, we call case classification. Right? So this is, most often deployed by our clients in the software industry. But if you wanted to, you know, allow your customers in preparation for a a more sort of advisory based conversation, you know, to submit something prior to to talking to someone. Hey. Here are the things that I'm looking for. This is what I'm trying to do. Right, you can apply a a large language model there to run that against your knowledge base and then start to classify, you know, here are the most appropriate things to answer that question to set us up for success. So this is a bit of what we're doing today. Of course, let me show you a bit of what we're planning to do here in the future because, you know, when it comes to generative AI, deploying that in the enterprise is certainly different. Right? And so the combination of large language models with, you know, mature and reliable AI search capabilities is what we believe to be the the key to creating these gen great generative experiences that organizations and enterprises can trust. Right? So it's a little bit of of best of both worlds situation here, right, happening on the back end here by taking where users already are, which is search. Right? Search isn't going away. Customers are, going to query, you know, your, your search box here. Instead of having two separate search boxes, one for generative AI, one for just regular old search, it's you sort of put them together here. So, you know, search will still provide the answers to simple questions that we have. Ones where you don't need to have a generative answer. It's I just need to see this documentation. I need to find this thing. Right? And so still utilizing, you know, search in order to do that on the back end is gonna be key. But at the same time, users may also want or need the ability to ask a question and get a long generated, answer. Right? So, it's possible, and what we're doing, right, is building a system that will process knowledge based content and organize it inside of VectorDB to then be combined with that large language model and generate an answer. So, you know, again, the the plan integrating both sides of these into one single system to, you know, start to give you search when and where you need it, and, then start to give you answers when and where you need it. Right? So it's gonna be a best of both worlds type of situation is what we're focusing on and what we're building here at Caveo. Now, of course, if you wanna go deeper on that, you wanna talk to our technical experts, you know, and go much, much deeper than than my knowledge, because I'll be the first to say I am not a technologist. Right then, let's set up some time for you. You can either let us know in the q and a here. You can let us know in the chat, and and we can reach out after the fact to set up some time to show you in much more detail exactly how we're going to be, starting to to build these capabilities. Now, of course, we we wanna talk about what can we start to do today. Right? As generative AI, those capabilities will take some time. I've heard a wide array of time frame investment, estimates for when generative AI is going to be in full production, and actually value adding for organizations, especially in financial services. I heard, you know, one analyst, from the space say, yeah. It won't be until at least ten years when when the regulations get in place. I've heard others say, you know, a couple of of years. So it's going to depend, ultimately, but there are things we can start to do today in order to meet our goals that you see along the bottom. Right? Cost, customer effort, and CSAT. If we wanna improve the digital experiences that we're having today, we'll talk through four things that you can see here. Right? It starts with trust. If people don't trust the the answer that they see online, the information, they don't trust that their path to get there, they're gonna abandon. You wanna simplify, for or or for your customers as well. Right? Make sure that we are not putting them through, some very, very long confusing process in order to just get an answer. We also want to make it continuous. Right. And on the back end, we we wanna be able to learn from what's been happening in that space. So let's start diving in here to, the the first component. How do we start to build digital trust? You know, and, Sandeep, I'll kick it to you in a second here to get your thoughts on sort of unifying an index and making sure that we have this single source of truth. But, you know, what's, starting to happen in, most industries, not just financial services, but particularly in financial services, is that content and information and insight lives everywhere. It's fractured. It's siloed. It's built by product lines. Right? And so what you wanna be able to do is create one single space where customers can, you know, query for an answer and start to get that that answer that they need. Hey. I know what I need. I know what I'm looking for. You know, help me to get that wherever I may be interacting with you, you know, from all of those different points. And not just what you have in your internal knowledge basis, but maybe it's something I saw, from your marketing team. Right? And there was this thing that that I needed to see. And, oh, how's that on YouTube? You know, if that's indexed, well, great. That becomes searchable on your website. You keep someone on your digital property to watch a a video, so that can give them the the information they need. So the you know, when when it comes to building a a unified index, when it comes to, creating that that single source of truth, what are some of the foundational actions that that organizations need to take care? Yeah. I think, from a foundational act actions, I think as we are thinking about, like, answering the questions, right, or returning in the search experience, so we have to think about, what is that user experience gonna look like, and how can we make sure, like, we answer the questions with, comes into it. So I think the the the details is that the metadata that's associated with that document, where's that knowledge. So I think some of the times the knowledge are is not even part of your, index or Mhmm. Which means, like, how do you pull that data? And then once you pull that data, how do you make sure, like, they are kind of conforming to the similar structure or something that we can extract the knowledge from there so that we can find the same experience when they're asking the question. Right? So it it I think one of the thing that's interesting that I've seen in, one of the clients of client that we worked with is that, we talk about these answers, and the this is was from the service associates. They had their own knowledge share that they created, which is like a like a cheat sheets that they had done. And they they shared the quick answers on those. And I think it was a great source for us to, like, put in and then build a q and a system from that. Right? So I think that so it kind of I think it's there's that knowledge already is there, but it's just the there are so much spread out in the in the organization. I think having to that pull in is, I think, is one of the, biggest hurdle. Once you pull in, I think the data, I think then I think it's question comes in as how do you make that come into the same experience so that we can give them the same kind of experience to answer the questions and be able to also return the results that makes kind of, helps them answer, like, what they're looking for, the insightful information that what would that experience be looking at. So I think that those are the hurdles I would say beginning to pull the content and making their share. Like, we have all the informations in a way that we can represent that in the user experience. Right? So those are the, I think, the few of the things. Yeah. Of course. Yeah. When I get consistent information, it starts to be a, a trust builder for me. I know that if I looked at it over here, right, you know, in the the mobile app, or I looked at it on your website, or I talked to one of the the CSRs right here. Idea, we said there, it rings so true. The amount of, you know, knowledge that's trapped in people's heads, that you hope that they will write down, and then you can have, you know, a SME look at that. You need to get it verified, of course. But then it becomes, again, that source of truth for organization. So this is reactively building trust. But, another way to build trust is, of course, to show your customers that you know them. Show them that we understand that the situation that you're in. So, making proactive recommendations. You you want to get out whether it is, you know, someone who has searched for something, and then based on on what they've searched for. Right? Oh, you're searching for, you know, a college savings plan, like a five two nine. Interesting. Right. Well, you also ought to be considering setting up a home budget. Right. And so proactively putting content in front of people when they've searched for something. Also, proactively putting content into customers' workflows. Right? And knowing who they are, what they're doing, your ability to, you know, put the right things just as I may have. Log in to, and again, just take a a retail banking environment. Right, I log in to make sure that, I've got enough money, coming up for the mortgage payment. Right? I've got the right amount of money in my, checking account. And maybe there's an article that helps me based on, you know, something nothing to do with what I'm trying to do, with with my transfer from savings to checking, but rather, something that will be helpful. So to do that, right, three, factors over on the left hand side here. Right? One is contextualized data. Using that information from the current session, from the system of record, right. What does this person have? What are their channel preferences, you know, to deliver that? You know, second is personalization factors. How do we start to, deliver that based on your life stage, wealth segment, areas of interest, and of course, what other people similar to them. I love the the Netflix, you know, of this, which is based on what you've watched, do you like this show, that show, and this other show? People who also like those shows like these three things. And when you're looking for something to watch, you don't even have to think about it. Right? But when I'm looking for something and content finds me, when it's helpful and valuable to me, I don't care that it feels kinda creepy you know this about me. Right? It's like, I'm so glad that I I've run into this, in a interesting thing. And, of course, feeding all of that, every single interaction that you have, feeding it back into machine learning models, in order to spot those patterns. So it's just becomes this continuous self learning system. Right? So, showing customers that you know them through personalization and, again, being proactive when it comes to to the data. Sunil, well, let's talk a bit here about, you know, how do we simplify the experience as well. And I'm gonna show everyone sort of two different factor or two different visuals here. Right? There's the world on the left of a fictitious, you know, credit card company that, we we created a a website for by just going out and looking at what most, websites for financial services organizations look like. And you can tell it's pretty crowded. Right? It's, you know, got lots of advertisements, lots of offers, lots of things there versus the right hand side, a box that we're all familiar with, the the Google search box. Right? And the the key question here is, of course, how do each of these make you feel? Right? Well, on the the left hand side, it's crowded. It feels kind of overwhelming. Right on the right, it's the the burden of participation is very, very low. Right? And so when you're thinking about simplification, think about the the emotive factors to that. Sandeep, when when it comes to, again, search as a category, just search as something that that organizations are prioritizing, do you find them building it as a front and center option for, their clients, their customers? Or do you think that that's an option to push this a little more to the the forefront so that if you need something, we're here to help you? Yeah. I mean, I always encourage the customers to put the search in the forefront because that's the way you can find the information. But I can understand, like, I mean, from a marketing perspective that you wanna have the information there, the what you see on the left, and the search becomes, one of the boxes on the top right or not the central piece. But I think, after they interact with that, the engagement would be called, like, I mean, the search box, then I think we do wanna as you said, like, be able to understand the context and be able to answer that. Like, whether it's now, I think, whether it's the top results or the if you understand that what they're asking, maybe provide them answers that you were saying. That that's, I think, would be the, what I've seen as being more successful. Yeah. And and, of course, you know, the the keys that that I'm pulling up here to, you know, building intelligent search. Right. It's not just, keyword search any longer. You need, you know, semantic search. Right? It needs to be connected, right, to to clear both structured and unstructured, you know, data from all sources into one customer interface. Right. Dynamic meaning that, it's continuing to learn. If I put in two or three searches or from, you know, my last logged in session, the the ability to, you know, apply, you know, some dynamism there to to help me to refine results, tailoring it, again, based on who that person is, you know, in order to, give them the the right contextual results. And then, of course, we we talked a little bit about something what we're already using called smart snippets, here. Right? Just display that. Be direct. Give me an answer when all I need is an answer. Sandeep, let me turn it to you on the question on the page. Right? Do we build these or do we, you know, buy these capabilities? But with, a question like, what are the big risks to building these on your own? Right? Of course, you you can go out and hire a bunch of people to build something like this. Like, what what are the big risks for organizations doing that? Yeah. I mean, I think search has been, like, more of a, I would say, commodity. Right? So building it becomes, like, you have to maintain it. Yeah. And I think the features that comes in, newer features, I think, to have that newer features and to catch up, I think, it's becoming harder and harder for the, to to do the actual build. Right? It's much easier when maybe, features that feature rich like Coveo, could be, could be the solution. But I think in some cases I mean, some I mean, there could be exceptions in cases where if you have the, developers that would, use the, like, open source and do it, I mean, that's a, could be another option. But, definitely, I think, what you need to think about is how can you add the value to find this I mean, con content, like, the connector piece that you have to connect it, and then be able to, add those AI features to find more personalized result, I think. If you can find the product that already does that, similar to COVID, I think that's, that's the answer. Yeah. I mean, for for my experience, right, often, you see when we have developers, when we have engineers, data scientists, they're not often applied to customer support problems and, you know, and functionalities. And so I agree with you. Right? Looking out to what what's been going on in the market is great. Of course, you also want to provide, you know, more continuous experiences for your customers as well. Right? So, two aspects to this, right, is the the first one is the the ability to sort of, pick up where you left off. If I've, been having an experience, and say I have to go away. This happened to me several times yesterday because I had a sick five year old at home with me. I'd start something. I'd start looking at something, and then she'd come in. And she I'd have to spend some time with her or, you know, she needed water or juice or a snack or or something like that. Right, like, the ability to get back into to something. Right? So providing some of these, you know, more what we call guided experiences. Using what I did in my last logged in session, to immediately display the the most relevant resources for a customer. Right? So, hey. Based on what you've done, here are the things that you need to, you know, continue with. Let let's keep going where we left off. You know, and then also, for financial well-being. Right? Using machine learning in order to say, here's what, what we know about this customer. Here's what we know what they've done. Here's what they ought to do next. Right? And I know that, I was actually sort of just reading this, you know, about organizations. And I remember in the financial crisis years ago, you would just get lists of customers that that banks would send people to call. This was a bank in New Zealand that that I used to work with, who would, you know, just every day have a whole team dedicated to making outbound calls when they knew people were heading toward a financial cliff. Say, hey. We we know. We wanna set up a conversation, with you to talk about, you know, your finances so that we can help you. And, of course, now we can do that digitally based on what you know about customers. You know, this is something that flashed that in front of them where it's gonna be a a great opportunity, for us to engage in those financial well-being activities. We we also want to, you know, provide continuous, you know, support across, the different channels that we have here. Right? So from, again, being proactive and prescriptive and, you know, in self-service, can proactively and reactively to allowing that that data to travel across to the assisted channels. Right? Where there's no world where you will have one hundred percent of, you know, your contacts happen in self-service. There there is always gonna be a world where we need to have people involved, and we need to have a conversation. But those are gonna be far more digitally enabled, interactions these days. And so when we can, take what's been going on, what did someone search for? Right. What were the last couple of documents that they accessed prior to picking up the phone and contacting us, or prior to coming into a branch? Right. If your people know that, then they can pick up the conversation right in the middle of what the the customer is going through. It doesn't feel like a fractured or, broken experience, for that customer. That feels like a a a much more, in a healthy way to to engage with them. So, Deep, when it comes to these, you know, continuous experiences, you know, and providing more of a, seamless approach to customers, How how important is it to start to break down the the silos that exist from the channels that that we manage, not just even the the data in the back end, but the way that we think about channels? I think it becomes important to identify where channels comes in so that we can understand if there's a channel specific behavior that you can, can give some insights. But I think the measuring that, I think you need to have some kind of a way to, see those different behavior. Right? How do you, find that out? And that based on that, I mean, that also helps us, like, what we're talking about, like, understanding the query, the user intent so that we can give them a more, contextual answers. Yeah. Absolutely. And so, we'll come to our last section here. And so, folks, if you've got questions, by the way, now is a good time to to start thinking about putting them, you know, into the the dashboard. Right? Or sorry. Into the dash into the I'm looking at an analytics title here. Putting them into the the q and a box. We'll we'll happily, answer what we can here. But, you know, when when it comes to, you know, analytics, right, starting to, you know, think about analytics and learn from customer activity across all of your interfaces. In fact, I was just this morning, having a conversation with one of our clients in the space who said that, you know, they use all of their, you know, analytics in the assisted channel space to inform what they're doing, in their, self-service channels. Right? So they are looking at what are the calls that are coming in? What are the topics that are being discussed there? You know, what are the searches that our our agents are performing, in order to close the those content gaps? Right? So reviewing that that activity across lines, and using that, again, to feed MLAs to provide that that better experience. If we know what customers are doing, what they've done in the past, and what's not working for them. Of course, that that's where we wanna start to, kind of close those blind spots. And then pulling that data into other, BI tools as well. Right? So getting that full three sixty. Often, self-service and search. Right? One of my favorite quotes I've ever heard from a a Coveo customer is that, customers don't lie to their search box. Right? So if you are able to feed customer, search terms, customer queries into, you know, other BI tools, that gives you a a full three sixty picture. And self-service has long been a blind spot for us. And then, of course, that data shouldn't just stay within, you know, service or CX and marketing. Right. We wanna be able to start to share, our data about customer behaviors across different, business lines so that we can improve things like product development, inform our stakeholders here. You know, with that, Sandeep, when when it comes to analytics, right, what are some of the the big things that you find, organizations are looking for, that you find that they're missing when it comes to their ability to view customer behaviors, in self-service channels? I think, one of the thing that's I mean, it's not missing. I think, apparently, I mean, everybody knows about, like, okay, for, which which zero hit queries, like, what are the queries that's not returning any Yeah. Any end results. Right? But I think also the part that which what type of queries are working, and I think what what is the what what is the machine learning tuning? Like, what are the click data that's affecting the which particular documents and which is high quality documents? Also, I mean, from other way around it, like, what documents are not being found? I think that's the outlier case. I mean, to to have those, I think, figured out, we could really identify as, like, is the what's the underlying issue with that? Is it because of the, the content, or is it there something that's missing to find those documents? I think that those are things I think to keep in mind, I would say, is not missing, but I think it's something to be aware of. Yeah. Yeah. No. I I think that's exactly right. Like, it's focused on what's working as much as what the the pain points are. I I love that insight. Right, that if we know something's working well, again, you can then put that into proactive recommendations. Right. Hey. We know a lot of people searched for this. You know, say it's, I mean, take, what what happened with, SBB recently. I'm sure a lot of companies are getting a lot of queries about that. And then really quickly, you can, if you see that query coming in, you you can say, man, we can pop that, results right on the the front page for everyone who may be thinking about this before they even need to to ask about it. Right? So seeing what's being accessed, and surmising other people in similar situations are probably gonna need to, look at that, document as well. With that, I'll I'll pause here. We'll we'll take a look for any, you know, questions in the the q and a box. I don't see any popping in right now. So if you've got a question, now is the time to ask. Otherwise, I'm sure, Sadiq, we can always put four minutes back on people's calendars. They can find something to do with them. Right? Yeah. Alright. Well, with that, don't see any active fingers going, on the the q and a box. So put some time, a couple of minutes back in everyone's calendar. Let me be the first. Sandeep, thank you for for joining us, for adding such great insight. Always, great as we partner with Accenture so closely here. For everyone that joined us, thanks so much, and look forward to talking to you again soon. Have a great day. Thank you. Bye.