Alright. Slide plans. Alright. Hopefully, you can see the right screen. We can. Nod. Alright. Good. Good. Hey. Welcome, everybody. My name is Mark Floyson from Coveo. I'm gonna be your host for the next, thirty, forty minutes. Firstly, welcome, everybody. Appreciate you joining the call. As I think everyone's probably familiar with Zoom, I'm not gonna go through all the gory details of how it works, but suffice to say that, if you wanna come off camera at any point, feel free to do so. We welcome the interaction. I'll take that as a cue that you want to say something. Alternatively, you can also raise your hand using the tools there as well. So we'll keep more than happy to have the lines open. With respect to the folks that that are on the call, or if you can stay on mute until you're ready to contribute, that would be great. Just so there's no background noise. Again, I think we we're probably all pretty familiar with the the ethics and protocols of these meetings having spent two years doing them collectively. What I would love to do is welcome today our respective panelists for the session on experience matters from static sites to personalized search. I'm joined by my co panelists, who are Brian McGlynn, Eric Immelman and Jay Jackson. I'm going to ask each of them in turn to give you just a quick minute of intro. Brian, let's start with you. Great. Thanks, Barca. And it's a great pleasure to be here with everybody this morning. We're broadcasting live from Montreal, Canada in our cold weather. And as we said, Mark, it's been two years as we go through almost the anniversary of that, being very, very fluent with Zoom. So I here at Coveo, I lead our ecommerce and our web line of business. So technologies that are focused on really bringing in new customers, existing customers, engaging with them, and providing the relevant content using AI and machine learning at the right times to really achieve a great business outcome. So really thrilled to be part of the the panel today as well. I'll, guess I'll pass it over next in line to, Eric Immerman from Perficient. Great. Thanks, Brian. So nice to meet everybody. My name is Eric I run our search practice within our data solutions group at Perficient. So Perficient is a a large system integrator. We've got about sixty five hundred people right now. We have, offices throughout the US as well as offshore and nearshore capabilities, be it in India or China or also all through Latin America, Argentina, Uruguay, Chile, Columbia, Mexico City, and so on. Really, my in my practice, I have a whole team of folks that works on how do we best use search to drive consumer experiences or employee experiences internally. How do we increase productivity conversion and those various pieces? I often find myself really working with customers on how do we blend that kind of mix of content and experience to make sure that we're essentially driving most relevant content for the experience at hand and and driving successes in that way. And I wanna pass it over to my colleague, Jay Jackson as well. Thank you, Eric. Jay Jackson here in sunny Atlanta. I am director of our Adobe practice, our digital marketing architects, to be exact. I also run our Adobe experience platform practice. So many of you who've had conversations with Adobe over the next over the last couple weeks and months, you may know their next generation, experience platform, if you will, and I run that portion of our business as well. So today, the four of us collectively are going to set the stage around a more conversational approach around how do we get value, as organizations out of the capabilities offered by sort of best in in breed and the solutions that we're talking about today, namely Coveo and the Adobe Experience Cloud, if you will. So, I think we have a nice segue to the next slide at this point, do we? We do indeed. And thanks for kicking this off, Jay. I think that, you know, we have a we have a couple of different topics that we're hoping to cover, and we thought it might be helpful to really just sort of set the stage, particularly given the fact that, you know, technology can seamlessly deliver these sort of personalized, highly targeted experiences and deliver content that, you know, in almost a holy grail fashion, we get to that notion of one to one personalization has been talked about forever, whether visitors are browsing or searching. It's about giving them exactly what they expect to see and and even anticipating what they need next. But, you know, the challenge, of course, is that, there's no shortage of, headwinds that customers face. So, let's open the kind of conversation with, you know, what challenges customers are facing when it comes to web personalization. And and, Jay, let me turn it back to you. Maybe you can give us some anecdotes from your experience. Absolutely. Thank you. And one other thing, just keep in mind, we would we'd love for this to be interactive and conversational. And so we'll start the conversation around for our best a little bit of feedback. Our our practices and things of your relative's time and still be successful within the past. But this is no by no means meant to be a presentation. Right? We don't expect to to speak at you until we'll start the conversation. We are absolutely looking for feedback, your personal experiences, questions, comments, concerns, any of those items as we walk through. To the point of the slide that's on the page, right, just to, you know, level set and make sure that we are waiting for the same sheet of music. From a challenges perspective, web personalization is fairly broad. Right? And so we're gonna narrow our conversation slightly today on the scope of of of search and getting answers to questions and how Coveo and Adobe really work together in some really complex, implementations that ultimately move the needle for clients. I can tell you that, two clients, that are shared between our two organizations that I wanna highlight today. There's more than two, but I wanna highlight today are one in health care. And so we know how to collectively, build experience in a in a PHI, kind of a compliant fashion. We're talking about AEM card analytics in Coveo, those working together properly in a in a highly regulated environment like health care in the spectrum of it seems like we have some feedback here. It's recruitment. Maybe you wanna check the the mutes. From a manufacturing active, we also have clients because it's saying, you know, excellent stat. Right? And, ultimately, it comes down to, leveraging the best of both worlds for each of the solutions. And so from a content perspective, AEM is frequently the mechanism which you build content. Right? Words on page, images, videos, happy smiling faces, those kinds of things. But content in and of itself is not the the execution layer of showcasing when and who we should show those build that content to, and that's where Adobe Barca comes in. And so AEM and Adobe and Adobe Target work really well with Coveo in terms of passing demographic information and other behavioral information that may have been may have been tapped other areas of of the web properties along to Coveo pre search so that it can return back the most, important and relevant results, not only from a, here's the list of x number results from a relevancy perspective, but also from a sorting perspective. Right? Putting the most important elements on top of the stack because they are most likely to be engaged with by the client. And, of course, all of this is wrapped in a nice form, breaking in Adobe Analytics. Right? So those two clients that I just spoke to, are ultimately trying to take from a sort of two steps, if you will. So one thing I would say that you could take away from this particular question is what we have seen drive the needle significantly is a, sort of, if you think about it at a crawl perspective is, I have a question. Right? I'm coming to the website. I have a question, and we want to respond with the most relevant, content, or a next best action, if you will, as required. And sort of the Nirvana from there or a step forward from that is, if you will walk, we know what your question is before you ask it. Right? Because of all of these data points that we can use across the two platforms that can work together to ultimately put forward that best, next best action. And so, Eric, I think you had a few examples as well of how the two solutions can work together or two two organizations, if you will, can work together? Yeah. Absolutely. And so to to drill into a little bit of what Jay was talking about, essentially, when we're looking at this from more of kind of a a search and a personalization and a a recommendation perspective, right, Essentially, what we're looking to do is gather as many signals as possible in order to have the most intelligence to kind of or the most information to provide the best recommendations, the best intelligence, the best results forward. Right? And so those signals are going to be, a, the user's intent. Right? What did a user type if they were searching, for example? Right? Could be the a very obvious intent, but it's also gonna be their context. And to Jay's point, Adobe Barca provides lots and lots of context in. Right? It might say, you know, this user is has this plan or is part of this membership or is looking at this part of the site. All of these pieces of information, right, are are things that we know about the user but that we're not asking them to explicitly tell us. Right? And if we we think about the big picture of of, you know, public search, right, everybody here I'm sure uses or has used Google. Right? This is how they do it. Right? They're fuzz fundamentally, they have so much context about you that they can drive, you know, you're searching for chicken. Let me show you a chicken place near your home because I know where you are at the current moment, where you live, and so on. Right? So we're bringing that concept back to an individual experience level and using target and other pieces to kind of provide that context accordingly. Right? Provide that additional information accordingly. Now once we've done that, right, then what we do with Coveo is we leverage AI models that are looking at what every user has ever done and what their context has been and using that to kind of match, okay. Johnny is like Sally and Larry is like Bob. We can drive their personalization experiences in real time in the same direction because we've seen this behavior before. Right? We know that someone who is looking at the employer's portion of a healthcare website has searched for diabetes and clicked on these documents. Right? And thus, we can now drive someone there, whereas somebody who's searching for diabetes on the provider's portion of a health care website might be looking for something different. Right? So that context is very, very important in that way. So, I mean, to talk about a couple of these scenarios. Right? One of these is is Poly, for example. Right? You know, they make, you know, probably microphones that people are using on this call today. Right? Webcams and a lot of those devices. Right? Their site has products. It also has support. It also has, you know, community and lots of different sources of content. Right? And depending your challenge, depending your journey, what products you own, where you've been, you want a very different result to be driven out of it. Right? So it's that context about what we know from Salesforce and CRM and e r and, you know, underlying systems on product information and warranties and ownership, right, that help drive that personalization down the line over time. Right? The challenge really becomes in how do we, a, get access to all that information and Barca helps a ton there because it's unifying a lot of things on the Adobe Experience Cloud already. Right? And, b, how do we have the appropriate intelligence of machine learning to be able to leverage that to drive a better experience in the long run? Yeah. Interesting points, Eric. You know? And it kinda I guess it leads us to that notion of, where you know, what people are connecting to and and and and where that content is coming into play. You know? I know that, for example, there are several folks on this call that are using, obviously, Adobe Experience Manager. Some are also running ecommerce stores, using things like Magento. Some are using both. Keeping it with you for a for a second here, Eric, how do you see customers approaching that kind of blend, if you like, of both, classic let's call it commerce content, product catalogs, and so on and so forth versus the the information that might be more valuable to helping them engage and and and and make a better shopping decision that might not live inside a hard product catalog. Right. Absolutely. And so I'll I'll give both how I see it done sometimes as well as how it probably should be done. Right? So how it's often done is based on, I'm gonna call it the limitations of the technology. Right? If you have a commerce system that is different than your content management system, they each have their own separate tools. Right? The the classical way that I'm sure everybody's kinda run into this is we put one search box and we have a little radio button that says, do you wanna search products or content? Raise your hand if you like that experience. I don't think there's anyone who does. Right? Because, quite simply, we're all spoiled at this point. Right? I have a search bar, I type in what I'm looking for and the magic, you know, Internet elves go off and they give me back the right information. Right? As such, the way that we kind of approach this a lot more these days is, okay, how do we unify both the product information and the content information into a single index and then develop an experience around it that allows that essentially content and product to work better. Right? So maybe I get back a product result that has a drop down to show me all of the the manuals or the documentations or the availability or the prices. Right? You know, I don't necessarily need to be looking purely in an ecommerce scenario. I might be looking more in a support. You know, I I'm maybe a researcher or a buyer in a b to b organization, for example. Right? And I wanna understand specs about some product. Right? The part that I'm interested in is not the buy now, the the, you know, how much is it going to cost me? It's let me understand all the various pieces of this and understand if it will hit my current beat or hit my current capability. Right? So being able to deliver an interface that mixes that content and and commerce is very important a lot of times because your audience is different. And as far as the personalization goes, right, we need to know who our customers are via all of those signals that we're talking about. Right? So I need to be able to tell via Barca, via other signals, and and honestly, just via usage and watching how somebody's interacting. Right? If somebody's looking at every product under the sun and they're never adding anything to cart, that's a pretty good signal that they're a researcher and not a buyer. Right? And so from those signals, can I then to have my interface be smart enough to dynamically boost and show product information first and the commerce portions first as opposed to the content portion so that even though it's the same interface, the same route somebody's going to to get to some experience, right, We can modify it on the fly for that user to make their experience better and ultimately convert more to our customers? Marcus, that's a feedback. I tell you what, Suzanne, if you can help me just there we go. Thank you. Just so following on from that, Brian, let me bring you in here. Obviously, this is something you've observed with with several of our customers, this blending of commerce and content. Do you wanna do you wanna add to it a little bit? Yeah. It's funny. Eric and I had a conversation this morning about this exact subject. We're talking about a client need, and it's the thing we see over and over again. Technologically, the problem is, is really the we look at technologically, there's a problem, and there is another gap in what the user's expectation. From a user's perspective, when you go in, what you're looking for is you really don't care about where it comes from, what source and that. You want information that's relevant to your intent. So if you're a b to b customer, you're going in and you're shopping for whether it's valve parts. You'd go in. You may be shopping or you may own valve parts, and you have a question about that. And or you may have a question about a product or even a problem about it. So you may say, hey. I need to stop, and how do I get a, ergonomic valve for a particular fire apparatus? Those are the questions that a rep would answer. Those are questions that a salesperson would answer and other parts around that because we have context. We understand the context. We understand what the user is. Translating that into the technology world, this it's a major challenge. It's an area that, certainly, COVID, we've been in business for seventeen years, and this and this has been really our whole view of what we've addressed. Take Adobe. You have maybe the Magento ecommerce system. Maybe you have an SAP PIM where you have product information. Maybe you have, content that's in Adobe AEM. You have the entire ecosystem that's out there. All these pieces living in silos. And, historically, people would go in well for answers, try answers dot whatever or questions dot whatever. Users don't want that. Users wanna ask a simple question, get a simple answer that's tailored for their need. And that's where AI and a unified index are really what we did. So we put together a lot of intellectual property and product to, first of all, unify the content, bring it into the index, grab videos from YouTube. We've done that with a client. Go in and grab manuals, grab all the items, and then understand intent based on the question that's asked, go through, and we use it using dynamic, navigation experience or DNE as we call it. So we'll look at the result set and then work with the user to better understand where they wanna be along those lines. The user at the end from a shopping experience, you think about it. I always go back to the analog standard. Take the best experiences, the best leaders in class from the analog world. And what do they do? Well, they understand what you're looking for. They understand what you own. They have a whole view of all the various content pieces and can present that to you with one click or zero in this case. So what we look at is that those particular parts have to come together built on AI, built on machine learning, built on strong personalization, built on a single set of index with multiple different connectors to bring that information, understand it, and and surface it. And as Eric and I talked about it this morning about a client, there's other clients we have along the lines as well that, are out there. So a big, big, big unlock if you're looking at any any technology stack that's facing front users. K. Eric, I see you nodding there as well. Yeah. I wanna kinda highlight on one point that that Brian brought up, and that's one of the biggest challenges in doing this is getting a a ground source of truth for what is most important to this person. Right? And typically when when you're operating in a siloed environment, it's almost every company is in at least some ways. Right? Unless you're building it all yourself. Right? It's you've got silos of of different pieces. Right? Each of them is going to come back and say, I'm most important, or this is my best piece of content, or this is my best best piece of of display. This is my best piece of content. And the challenge there becomes, okay. If I have systems a, b, and c all giving me their best stuff, which is actually best? Right? How do I rank those? How do I conjoin those? How do I order those? Right? And to be quite honest, that is a really, really hard problem to solve, essentially akin to building your own search platform or relevancy platform itself. Right? The hard part of search isn't, you know, rapidly finding information. That's been a pretty solved problem for years now. Right? You know, there are data structures you can use to load data in and very rapidly find large amounts of information. The challenge here is that relevancy model. Right? How do I determine when when given four different inputs, right, which is most important? And this becomes a challenge for a variety of reasons. Right? Reason one is I don't know who to trust more. Right? Reason two is it's not done in a bubble. Right? Your generally, your, business folks will have a say on that that is typically a very important say. Right? This is more important for this case. That is more important for this case, and so on. Right? Third, your customers will wanna have a say on that. Right? You know, just because the business dictates something doesn't mean the customer feels that way, and that's why we're having this conversation on personalization. So you need to look at doing this in a way, and this is on in a nutshell what Coveo really offers, right, of how do I unify all of these various silos, right, and provide experiences and business capable interfaces, right, for overlaying both the business users' rules, right, the act of them putting their hand on the scale for what should be most important. Right? This is our latest sale. This is a new product that came out we suspect is gonna need a lot of support. This is, you know, our our latest internal HR document, Right? Because we have a new policy around coming back to the office following COVID. Right? Those sorts of things where you may want your customers or your business users to be able to put their hand on the scale and push something higher, but you don't want to do that in an explicit way that completely overrides all of the end users. Right? Because at some point and at some level of scale, it becomes an impossibility to consider every end user's possible scenario. Right? You know, there's just too many permutations at scale. Right? You don't have time for those to pay or money to pay for the hundred business folks that just focus on manually optimizing every query, and thus machine learning and some of these broader techniques need to come in a little bit more broadly. Yeah. Perfectly fair. So I I'd like to switch gears a little bit and maybe just bring us back to a point, Jay, I think you raised earlier, which was that you're already seeing some customers, you know, unify both Coveo and Adobe. You touched on a couple. Do you do you wanna kinda give us a bit more color on on how these things are working together in practice? I do. But I I would love to give our our participants on the call an opportunity to respond. I think we've been talking, you know, nonstop for for a good bit here. I wanna make sure that, you know, some of the as I look at the the participants on the call, we have good representation from financial services and health care or these pharmaceuticals and and technology. I'm curious. If you go up a slide, I'm curious. Based on what you've heard so far, are you experiencing some of these challenges both from a connecting the dots of, potentially disparate solutions, or are you having questions around how to, make the investments that we've already made in the Adobe slash Coveo Coveo stacks work together or just any comments or thoughts so far from from some of the the industries and verticals that we have on the call today? Any takers? Chat is also fine. So, you know, if you are camera challenged, feel free to use the chat sessions as well. Alright. We'll give people a chance there. In the meantime, if there is anything that comes up, all well and good, feel free to open your line and comment directly or or contribute in the chat any questions you may have. Absolutely. And so to that point around your question or the slide, really, around how does, Coveo and Adobe, you know, how are they using it together? So I gave an example a little bit earlier, around the health care and manufacturing, how they use the very specific tools and Barca and and analytics and Cobayo, etcetera, etcetera. And those we certainly have many more of those kinds of success stories. What I will tell you, though, is that all of those sort of technology based actions are means to an end, right, for our customers. Right? That technology, in this case, at Coveo and and Barca and Analytics, etcetera, are meant to drive some kind of business result, whether that be orders. Right? If we're talking about commerce and revenue, whether it be call deflection, mark satisfaction, utilization, whatever those goals are, these are the solutions that we have seen move the needle to meet those goals. From a perspective, right, in order for us to sort of meet those goals, we found that there are really four key areas. There are many, many challenges across organizations, and certainly different big verticals have different challenges unique to those verticals, regulated, unregulated, those kinds of things. But overall, these are the kind the four kinds of things that we see coalesced across industries as we build together a solution that sort of works with each other, particularly on the on the Cobain, on the Adobe stack. The first of which is disparate results. Right? So many of our customers say that when leadership ask ask how many people did x, and you go to your disparate tools and all of them say five different things. Right? And so the first thing is making sure, that your technology ultimately is serving the business and working in the same direction. Not only just directionally, but ideally with some level of confidence so that solution a doesn't say, something that has a fifty percent variance of solution b. And that's one of the great things around that Adobe Coveo partnership is that we can leverage really fast insights in terms of what you search for and then correlate that search to some other action even if that action took place offline, say, in call center so that we can do correlation and causation ultimately, and maybe even attribution around those kinds of exercise. And if you want deep ingrained insight into the very specific search world, then we still have that that Coveo interface. And so a single source of of essentially reporting is one of the core benefits of of solving that challenge. On the second one is relevancy matters. Right? At the end of the day, when we're not at at Perficient and Coveo and some of the other partners, that we have on this call, we don't engage. Right? If something isn't relevant, we don't click on it. Right? And so relevancy matters. There is a survey going around on LinkedIn. You may have seen it around there who we asked customers. I think it was BCG, did a survey and asked customers what do they want, and they said that seventeen percent of them wanted personalization. The reality is is that personalization done well isn't noticed. You don't notice it. You only tend to notice personalization when it doesn't exist or it's not done well. Right? Think of, say, your cable company. So Comcast, for example, when you go to their website and they recognize that you come from a residential line in which they service, they change the entire home page. Right? It is all about service your account, pay your bill, those kinds of things, add new service, etcetera. It is not by contest. It's not why you should invest in this. You've already invested in this. Right? That is personalization, and it's not creepy. Right? It is ultimately, this is what's relevant to me in my journey. This is what's actionable to me. Don't show me things that I can't do, I can't buy. Right? The set the third thing is disconnect the user experiences. Right? And so that I go to one page and I have one experience, and I go to another page and I have a different experience that's not relevant to me and doesn't take into account what I've just told you. Right? A very simple use case that we do with Coveo and Target and AEM, etcetera. It's just, are you a customer or you're not a customer? Right? Prospect versus customer in a health care world that's a member. Right? And if you are a prospect, then we show why value proposition messaging, prospecting buy now. Right? But if you're already a customer, you've already taken, advantage of the value proposition, then it is maybe register for my account and or it is maybe, sign up for people's billing or etcetera etcetera. Right? It is utilization of the service. Right? And that's really straightforward kinds of exercises so that when we make that request to say a to search for a generic term like phones. Right? You get different results Barca. If you're a customer, it's noncustomer. Right? If you're not a customer, it's buying the phone. If you are a customer, it is servicing the phone. Again, it's about relevancy. And the last one is respecting privacy. Right? And that I'm going to, as as a nature or function of navigating this web experience, have some kind of bread trails across what I did. Right? My behavior. Respect that data. Right? If I if I have to authenticate or if I have to buy a product or subscribe to a service, respect that data. Outline exactly what you're gonna be doing with it. Hold to it, and then give me options in terms of obfuscating that data if I so chose. So those four things are things that really, we have seen drive the needle, in terms of success around those metrics that I talked about earlier. Not just implementing software without error, but it is aligning to your organizational goals. That was that revenue, that will average order value, that call inflection, market share, utilization, etcetera, etcetera, etcetera. Does that make sense to everyone? It does indeed. And and, we've actually got, some response from, one of the, folks online from Derek. Derek, appreciate that. Saying NetApp, we use Adobe primarily for analytics for our support site. It's our primary analytics tool for our entire website. But since Adobe began complying with GDPR, which, of course, we all have to comply with, we can no longer gather analytics for a sizable portion of our customers. We're wondering if there's any possible way to leverage Coveo's search analytics within Adobe. Do you have any experience of this? I can take this one if you want, Mark. Yeah. So there there are a couple ways to to leverage, Covey both Coveyos search analytics within Adobe and Adobe's analytics within Coveyos. We can go both ways on this. Right? So, option one and and the standard way here, right, is is in the UI that you have built that leverages Coveo, we can add tags in that are essentially via, generally, Adobe launch or Google Tag Manager, but considering Adobe, it's probably Adobe launch here. Right? We are adding tags in that are pushing information directly to Adobe from that system. Right? Now considering the GDPR piece here, right, there might be a a concern that we can't push it for the same exact reason. The other thing that Coveo offers that we've we've done a few times now that is a a more recent kind of capability of of the platform is with Coveo, all of the is with Coveo, all of the analytics data that is captured is yours. Right? It's all stored in the back end in a technology called Snowflake. Right? And I'm not sure if anybody here's used Snowflake, a big data tool. Right? But you have access to it and can essentially plug in your Snowflake reader account and and query it via JDBC or, you know, SQL or or standard kind of interactive data streams to merge it into your data warehouse, your Adobe Analytics, what have you. Right? So all of the data collected by Adobe, right, Coveo, you can essentially have a little tool or a script that you pull out of, Snowflake and push into Adobe Analytics as well or your data warehouse wherever it lives. It doesn't have to be purely Adobe Analytics. You can use that data for whatever purposes because it is your data from Coveo's perspective behind the scenes. Right? So that's for that piece in particular. The other direction, the other way place that Adobe Analytics and Adobe are particularly useful for Coveo, and we did this recently on a a very large ecommerce site, a top twenty five US ecommerce site. Right? So hundreds of millions of of searches per month, sort of scale here. Right? What we can do, because as Jay mentioned, many events that we care about on a commerce perspective are not limited to search. Right? I care about the first search, yes, but I also care about, okay, are you on a product page and are you clicking add to cart? Are you in your cart and are you increasing the number of items in the cart or removing it from your cart? Are you on the checkout page and are you actually checking out? Right? Because from a signal perspective, it's really useful to know if somebody's adding something to the cart or more importantly, are they buying it? Right? Just clicking and viewing is nice, but I care about the end result, which is are you buying this item? Okay? And so when we do commerce implementations way before we actually get Coveo integrated in live, we integrate Coveo's pixels as we'll call them. Right? Little JavaScript snippets into Adobe launch to start capturing events from your existing website to essentially I'll call it warm up Coveo, warm up the machine learning so it starts knowing how your users are interacting. Right? And so what this means is that we can start kind of pretraining the models or helping Coveo understand what products is our user looking at, how are they adding it to the cart, how are they going back and forth and interacting without Coveo even yet being in place so that when Coveo does come in place, not only does it have that additional information, but it also is then kind of building off of potentially months of of information that kind of was captured during that implementation of the platform to begin with. Right? The other way that that we tend to use it together in a little bit less of the analytics way, though, is it's very, very frequent to host Coveo on AEM. Right? There are out of the box components for this. You know, we've we've also built some on on Coveo's various UI frameworks, be it if you you have kind of the I'll call it the older style, standard individual pages that you're hosting out of AEM or a more modern, you know, single page application using React or Angular or Vue or some of the frameworks out there. Right? The idea is typically that Adobe is the Adobe AEM is the c c m s is hosting the page, is hosting the content that is essentially rendering a Coveo page, which is calling Coveo for all of the results. Right? So typically, you know, we're very tightly integrated between those two stacks. You know, Coveo is providing, I'll call it the intelligence API and maybe some of the out of the box components you can leverage to utilize that quicker. Adobe is providing the hosting, the analytics, the knowledge kind of collection upfront, to essentially enable Coveo to do what it it's able to do. Fair. Thank you. Appreciate it. Nice response, Eric. I know that, I I just realized that the clock is marching here. One of the other topics we did wanna touch on was, we talked in a brief about some folks actually using Target already, and and, obviously, there are some folks that maybe use Adobe Experience Manager without Target. Mhmm. But, clearly, how do those folks that are obviously, taking advantage of as much of the Adobe product as they can, how are they actually still taking advantage of Coveo as well? Yeah. So so typically, I'll bring up a a healthcare customer as an example. Right? Typically what's happening here is Adobe Barca is utilized to, you know, for everything from from personalization and AB testing and collecting various, information about customers, right, to grab that kind of context. Right? So first off, when we're using Coveo specifically for search cases to start, right, which is kind of the basic starting use case for Coveo, Adobe Barca is often leveraged very heavily to provide that context on the user. Right? So we talked before about the more signals I have, the smarter I can be. Right? A huge number of those signals are often coming from target in the various segments and personas and all the pieces that you've kind of captured in, you you've captured within the the target ecosystem. Right? To be quite honest, we don't need to re rebuild the wheel when we implement Coveo. We want to use the information you already have. And if you're already using Adobe Target, excellent. We've already got it there. Let's plug it in more directly. Right? Secondly, one thing that Target really does a a bit differently than Coveo, right, is Target is very much, a lot of times focused on the experience more. Right? Which components or widgets or pieces of the page are we showing? Whereas Coveo is more focused on the content. Right? What results are we showing or different other links or products are we recommending? Right? So there's a lot of times, I'll call it a nice integration and overlap there as your personalization might take multiple approaches. Right? Maybe in some segment, you just wanna recommend specific content. Right? I wanna recommend, you know, I'm on my support page. We might have training courses. Which training courses are most applicable to the support articles that you've been looking at? We think you should go and and take these three different training areas, for example. Right? Or, you know, you we saw you that you've purchased these products. Let us recommend accessories for those products. So that's I'm saying, okay. Give me the pieces of content that I wanna display. Okay? Now that's different than a different experience. Maybe I'm on a a Father's Day sale. Right? We wanna have a different layout and experience depending if you we detect that you are a father or a mother or a child or so on. Right? I'm I'm making this up off top of my head, so let's hope it goes somewhere good. Right? But, you know, essentially, we wanna have a different layout depending on that because we know that as a different type of buyer, you were more likely to, gravitate or, purchase via a different journey. Right? So what we can do there is we can use the combination of Barca to adjust the layout, adjust the the verbiage, the the chrome, the headers, you know, AB test all of it, make sure everything is looking appropriate. Right? And use Coveo to make sure that the content being displayed is also appropriate. Right? If we're giving back those lists of products. It's a it's a nice kind of dance between the two where each is providing their own part to drive a much essentially more capable overall personalized experience. Appreciate it, Eric. And I see, Marcus Salo has his hand up. Marcus, do you wanna chime in? Yeah. So so, from my experience, we actually I I I looked at the Lenovo before my position at the AP, and we did not use Coveo. We used Bluetooth Fusion. But regardless, question of target is what we did is, almost like you said, we used target to drive the layouts, but but we also did is we actually had target to drive the segment. So you would say use target to set an environment variables. Let's say, okay. We had a limited number of segments, maybe ten, twelve, fifteen. Yep. And that segment would be pushed to search on whatever given page you are. And based on that, you would actually favor or rank product saying, okay. This is a gaming person. We will favor gaming product and so on and so on. You say you could use target not just on display purposes or to drive the back end data. That's my experience. Absolutely. It's a it's a wonderful experience, and that that segment is essentially one of your signals you're bringing in. It's that's very common, hugely relevant, and and to be honest, it gives much better experiences because what happens when you have that signal is in Coveo, we can actually segment the machine learning model just seamlessly behind the scenes to say only learn from users in a single in a similar segment. So that when machine learning is kind of learning what to recommend, it's recommending gamer content to other gamers, right, and and productivity content to other productivity focused people, so that you're not kind of cross mixing and and sending, you know, your grandmother this LED light up, you know, laptop, right, that she's probably not gonna care about at the end of the day just because, you know, overall, we see this as a very popular product. Yeah. Right. So it's for further refunding the context. Yep. Exactly. Alright. We're down to the last five minutes, folks. So, I wanted to just maybe round this out a bit. Brian, if I can call on you, you know, clearly a large part of of why Coveo and Perficient are working so closely together, particularly around these the this Adobe ecosystem is the sense of the Coveo Relevance Cloud really underpinning a lot of what, our combined customers are doing. Do you wanna just talk a little bit about why we're able to kind of connect and and and help join the dots here? I think good point. Yeah. This Barca, absolutely. This is an Barca. Once again, Eric and I have had many conversations and working with clients on this part. This is an area where clients, at the end, bring us in. They solve the problem. They don't come to us, knock on the door, and say we have relevance problems. Say we have a problem where our customers can't find information, or our customers are are using a lot more calls at this point, and our our cost per serve customers are high, or our net promoter score is low. We're not giving customers what they want. So that or this ultimately, conversion gets to be a big part where customers want to focus on on really growing profit per customer, increasing conversions. Those are the things we'll go into. And what comes out of it is the ways that we we help an organization is really by going in and and looking holistically at a customer. So that entire three hundred and sixty degree view of where customer would consume content. So understanding that, mapping that, Coveo comes in, we we connect the dots. So if you're thinking it's AEM as a mechanism where we're delivering and they're really providing a capability to bring that content to the end user, we look at it as well where there's test interest, for example, Adobe Test and Target and other components that are going through and looking at the different parts. And realistically, in every organization, it's not a homogeneous stack. There's content. There's there's items about various different parts that come from it to be different locations. Really, the key part is that needle in the haystack where a customer doesn't wanna go in and see ten thousand pages of results. There's really the first three results and getting to that point where there's that one result of what's relevant at this point as well. And that's really what we've, at Coveo, spent our entire business on focusing is helping our customers deliver relevant content at the moments that matter. And that's once again understanding intent, understanding the content, understanding it from whatever source it may be, whether it's a product catalog that has call outs to a specific, PDF or making that match to understand here's the product content, and here's the related content that's out there. So this is where we work very closely with Perficient. Perficient brings immense skills to go in and understand where the content comes from, understand how the items interplay as well. We provide the technology that unifies that, and Perficient provides the capability to really understand it from a user perspective and integrate it from in there. So all across the board, this is where we work very closely with Perficient to go in. We have numerous customer examples where we've gone in and seen results where revenues have been lifted ten percent. Profit margins have gone up thirty percent in many cases where we've gone in and recommended the right product. Call volumes have gone down in cost per sale if we're looking at b two b metrics and we're looking at cost to serve metrics. All those key performance indicators working at Perficient, we've been able to work with the customer and help drive that. And, ultimately, whether it's payback, whether it's additional revenue that customers are looking at, whatever it may be, these are the key parts that we work together, very well, to to serve our clients. So a lot there, but absolutely something from a call to action. We talk with customers about hitting those. Excellent. Well, we are down to the final strokes here, folks. So I'm gonna put each of our panelists on the spot to kind of give you a a a minute of wisdom each, kind of last word lightning round. So, Jay, let me turn to you first. Final thoughts. I think, lightning round. Yeah. Thank you for joining. I think we've provided a lot of information. We're happy to follow-up on any of the kinds of topics or conversations that we've had today, in a direct or personal, mode with your organizations. Ultimately, I think what we what I'd like you to take away from all of our talk tracking conversation today is that, yes, these are best in breed tools, but our focus from a Coveo and a a and a proficient perspective is that these tools are means to an end. That at the end of the day, we want to make sure that we're driving to the results that matters to you, not just implementation of software without error. Eric. Thank you. Thank you, Jay. Eric. The old adage is the customer is always right. I'm gonna change that to be the customer is always right and the customer is impatient. Right? If you're not if you're not giving results right away or giving answers right away, they're either getting frustrated, right, and and that that's hurting the brand visibility or, you know, costs to serve and those sorts of piece for your business, or they're going elsewhere. Right? And quite simply, the the Internet and and computers have opened up everybody to have as much choice in the world as they want. Right? They can always find another site, another capability somewhere else to look, etcetera. So, from my perspective, where I spend most of my time is just repeating over and over again. The customer is impatient. How do we do this faster? And the big part of doing this faster is making sure we're giving somebody the right experience, the right piece at the right time, because they don't have to go looking that way. Right? You just put it in front of them, they move on, and and that's kinda where where they start buying and where success happens in the long run. Super. Eric, thank you. Brian? Great. Being third and last, I get to build upon what Jay and Eric had talked about. I mean, altogether, everything they said plus the fact that really the technology, it don't have to be it's AI is is absolutely essential. So going in connectivity, understanding where it is in this part and applying intelligent AI to make those decisions and to do that at scale. So everyone gets a personally bespoke experience that really understands intent, drives value, and really goes within the mission of what the organization is trying to do. We need this with partners like Perficient. We need to apply AI and technology and learn from every inaction that people have along the lines with her. And that's really the key part of not just checking a box with AI, but really committing to it and understanding it and bringing it in as part of modernization. Super. Well, I'd like to thank the panelists. More importantly, I'd like to thank everyone that attended. Thank you very much for for giving us forty five minutes of your time. We really appreciate it. This has been recorded, so we'll get a link out to you guys if you wanna share it, obviously, with your colleagues or anyone that wasn't able to make it. As always, if there's anything you'd like to do in terms of follow-up, please feel for feel free to get in touch. But, we thank you all very much for your time, and, wish you a pleasant day, pleasant afternoon, pleasant evening. Thanks, everybody. Thanks, everybody.