Juliana S. Hello everyone and welcome to our webinar here hosted by Acutics. My name is Juliana and I'll be your host for today. I'm working as a senior account manager for Acutics. And we'll talk a little bit about who Acutics is also for those who don't know us. But I've had a huge focus on helping organizations turn data into clear strategy and insights. And so I'm really excited to have Ramaz joining us today on such a relevant topic that we see in 2026 especially. So welcome to our webinar. But first I will turn the camera over to Ramaz to do an introduction to himself and so that we can have a great cut next 45 minutes. Thanks, Juliana. I appreciate the opportunity in speaking with you today. Juliana S. I'm a marketing analytics director at the University of Phoenix and it's been a wonderful journey with Acutics and the foundational data that we have been constructing at the university. Juliana S. And I'm really happy to talk about how we're leveraging the platform and where we are today, where we've been with the construction of the platform, all of our media data, a little bit about taxonomy and metadata, etc. Yes, great. So just a bit about the plan for the day. And thank you again, Ramaz, for joining us and that you're so passionate about this topic as well. So we'll first talk about the need that we've seen in higher education with some other clients that we have, as well as a huge need that we've talked about with University of Phoenix. And then also hear more about the story that Ramaz and his team have gone through trying to make sure that they have a unified data language. Then we'll wrap up with some questions, but we'll also have more of a dialogue back and forth. And we have the opportunity to take questions from you as well, but I'll come back to that in just a moment. Because first, so who are we? Perhaps you're joining in for the first time and you've never heard of us before or met us at the Acutics team. We provide the data foundation for marketing impact. We are very passionate about enabling marketers to be able to showcase the business impact of their work, providing a platform that enforces a shared data language, validates the effect on an ongoing basis and allows you to take full data ownership by design. And we do so in three ways. So one is again with that shared marketing data vocabulary, making sure that you have aligned across your teams and channels that you can work as one or as that shared data language, as I mentioned. And enabling consistent data governance by design and ensuring accuracy and compliance to downstream analytics, which is especially important today with AI personalization to have that clean structured data. So that's really why we're starting the conversation today. Not only because we've worked on this so much with University of Phoenix, but also just because it is such an important, almost non negotiable skill to have in 2026, given the push for AI. And a bit of light housekeeping before we jump in. As you can see in the box on the right, there is a panel where you can see some notes that I've already put a note in as well. At the top of that, you can ask a question. These questions will come to us with your name, but we'll read them anonymously. So feel free to ask questions throughout the presentation and we'll be able to get those answered. And of course, any questions are open. We're very happy to have that engagement. So first, just looking at why this is a topic we even wanted to discuss today at all. We have to focus a lot on measurement. So in our work with marketing leaders, we have seen that this is where business risk shows up measurement without governance and without governance. And without governance, marketing measurement can look precise, but maybe it isn't consistent enough to guide your investments. And if we can't compare suddenly across platforms or programs or campaigns, high performing channels can suddenly become undervalued. Weaker areas can get funded and budget conversations, unfortunately, can become much more political because no one trusts the data. And Ramaz, I think that's something that you've seen as well in the business risk in your work, why this even is something that you've put so much of a focus on. Absolutely. I think it's important to just start off by talking about, you know, online education, education in general. You know, we support a working individual that's like trying to balance their career. Some individuals are maybe trying to raise a family, caring for loved ones. So unlike selling a commodity or manufacturing where I've been previously, it's almost like we take extra pride and care into what we're doing in terms of the data, because these students are working professionals. They want to earn a degree, improve their lives, they want to earn a degree, improve their lives. It could be a single parent that are studying late at night. So when we refer to this data, these are individuals at the end of the day. So just to level set that, you know, another good thing to start out with talking about is the foundational effort is maybe not always the most glamorous per se. But it is so important because if you have a strong foundation, then you have a better confidence in what you're producing. So my team, we work a lot with visualizations. We interpret the data. We establish KPIs. We work with so many different internal teams. So our taxonomy, you know, it refers to the hierarchical classifications of your data. So unlike, you know, most organizations have spreadsheets, Excel spreadsheets to manage this data. And there's nothing wrong with that. But when you have dozens and dozens and hundreds of campaigns running, it becomes kind of a little bit tricky. And then, you know, through our experience, we have to kind of take a step back, kind of evaluate what was working, what wasn't working. And I could share a little bit more about that. But just want to level set on just the industry in general for the University of Phoenix and how we handle our data. No, exactly. You made a really great point that on the one side, it is that you're looking at a critical journey for people. It's not just, you know, with retail where you might be buying something quickly. This is a critical decision and you need to make sure that you can also reach people across all of the touch points. But also when you bring in the complexity of several different team members of different channels, it becomes a lot more complicated. And that's where we really see governance being such a high priority. So I'm glad that that's also something that you had focused on as a key key area to review, because there is such a pressure to prove marketing impact as well to understand which channels drive applications or where to invest marketing budget. And the challenge that we see is that pressure to prove impact just keeps increasing. But the underlying data usually isn't built to answer those questions yet, which you've probably seen on your end as well. Oh, there's so much pressure to prove results and impact. That's a given. But if you don't have the data that's very reliable and you have a high confidence, then that scenario of data quality is such much more difficult. You know, I come across some evaluations every year. You might see like 20% around there of media budgets are wasted due to poor data quality. And I'm sure I've seen from a coup it's also like there's that evidence. And that's really kind of hard to swallow in a time where you're trying to prepare for more AI models and more optimization and everything's under a microscope. So that kind of really goes back to your point on the pressure and how do we measure everything? Oh, exactly. And and with AI is, you know, you need the foundation to be strong. And in today's day and age, we have more data than ever before. But if the environment isn't built to manage that, it becomes very complex. And we see that really with like, as you mentioned, with AI, but also with fragmented marketing data. You mentioned that across several teams, you can have different ways of doing things that make spreadsheets quite hard to scale, makes it difficult to see the full picture. Also, when you bring in other channels like CRM or your web analytics. And when you tag that into the different reporting structures that you have across teams as well. So not just the foundation, but the people in the process and merge that in with rising expectations for AI. With an increasing rise in the need for activation, skipping this governance layer makes it almost impossible to even need to take the next step. Absolutely. When you think about it, a lot of these platforms are not designed to speak to each other. When you think about, you know, meta versus anything, even Amazon, your OTT. So you need this connectivity, a unified language. Therefore, you can produce the actual analysis from all of that together, put together. So, yeah, there is rising expectations right now. So you have to have a process in place. And I know we'll talk about that in a little bit to kind of manage all this effort. Exactly. Because Facebook has different metrics also than Google ads and trying to tie that all together to show that the journey isn't always linear, especially in the student journey, because you have multiple touch points. It's a longer process. It could be several years, could be a year, depending on the student process. It becomes so much more complicated. Yeah. Another another good point, Juliana, is, you know, I consider your media optimization is like your bread and butter of your organization and your metadata is so critical. So when you think of the metadata, it's it's your campaigns, it could be your creative outline and then your hierarchy under each. It could be the different experiences. So when you gather all this metadata, that's that's your value. And in addition to working with that, you have to work with all of your internal teams who are optimizing day in and day out on those platforms. So it's like a well tuned machinery that has to happen. And I think we've gotten a good place at the University of Phoenix and obviously much more opportunity. But for organizations, I think we could we could go into some of the detail, but it's almost like you have to take an evaluation of where where you're at, where you would like to go and how to achieve that. Yeah. Yeah. Yeah. You really need to start with the strategy of where you want to go, because so frequently marketing is changing so fast, you might add the different building blocks in more sporadically when you do need to take that step back and look at the overall strategy a lot more. And also matching that to your customer journey or in this case, student recruitment journey. Absolutely. At the university, from my experience to this is OK, we'll go to this slide here. But like I said, the student right now has so many different channels where they could obviously learn more about the organization and how to sign and become a student and progress through the funnel and graduate. Here you have outlined. I'm sure you want to speak to this one. But it's it's grown, I think, over the last few years. It's so rapidly changing and there's different touch points. So to manage this in itself is really a feat in itself to kind of gather all these touch points together of the recruitment journey. And then we have Adobe in support of that, too, and other platforms. Oh, exactly. You covered that perfectly. So actually, actually, because it is the point that, you know, here you have different touch points during your consideration phase, during the decision phase, touch points that you can track online, touch points that are offline. And it makes it so much more complicated because then when when we look at what we think the student journey looks like frequently, at least in my work with those on this journey, we think it looks quite linear. So we're thinking, how can we track the touch point from an Instagram ad through to having that detail in our CRM system? Or how can we have make sure that the online journey is tracked in a certain way and assuming that maybe we can try to get this at its linear stage, which becomes even more complicated when you have offline examples. So when you add in recruitment fairs or QR codes and brochures and trying to tie in that whole journey and make it more clear, it becomes quite complicated. Also, given, as you mentioned, different metrics mean different things in different platforms. Right. Absolutely. You know. The linear approach seems a little archaic now. You know, sometimes it's this this is characteristic of an individual, but we're finding more and more that there's different portions of the journey that they'll enter. And how do you credit for each of these entry points and where do they actually produce value for us? And the journey is much more complex. And we take the time to kind of understand each portion. And if we were trying to replicate this, there's like you'll see in your subsequent slide. It's not as linear as you think. But there you go. This is the reality. Reality. Yeah, exactly. Kind of looks a little bit more like spaghetti, which is not what we want to hear when we're going to track this, really. It's is scattered across different systems that were never designed to speak the same language. This one platform is measuring clicks and other page views and other leads or applicants. So you have the platforms differentiating. Then you have people differentiating. And that means we're not comparing directly. We might have data everywhere, but not data that is standardized enough to connect this journey. And that's really what you've been working with is trying to not have the lack lack of data isn't an issue, but the lack of comparability in your marketing flows. Yeah, you know, you tend to think about we have a lot more options, too. So if I'm evaluating going to I might have three or four choices of online college, you know, I'm going to I'm going to try and exhaust different. You know, I might go to my Instagram. I might catch my attention there. I might have I might go to the website, which is a really a critical piece. You know, the website of the organization. You know, there's so many that the reality behind all of these platforms, it's it's pretty wild. But an organization has to grab all of this data to really understand that journey. And going back to the foundation, it's like you have to identify each of these pieces in your taxonomy and your in your unified language to understand where they're coming from. And then, you know, if you're trying to create a campaign to reach these individuals, that's going to that's going to be the key. You know, how are we going to tailor this message or what is the channel we're going to use to to reach this particular audience or whoever? Exactly, because you also will then differentiate by channel depending on how you want to reach them. And that has such an impact downstream. We've mentioned that a bit already, but when data is so fragmented, reporting can become inconsistent, which then leads to a lot of time spent not optimizing campaigns, but rather fixing the downstream reporting. And that is in part due to naming and taxonomy, like you mentioned, as you can see here, things are spelled differently. Maybe you have spring promo versus spring back to school with a two versus back to school spelled T.O. And you suddenly have all these different ways of naming things. And if you're working globally as well, that becomes a major problem. And then we can measure activity, but we still can't confidently answer the decisions that matter the most. And that also leads me to a question to you of what business questions were the hardest for you to answer when your data was looking like this? Oh, absolutely. You know, that brings me back up some flashbacks to when we first underwent this journey. You know, we're talking about the Excel spreadsheets and trying to manage all that data. The process was very manual in nature. So we had a lot of copy paste, misspellings. I found that we were spending so much time internally trying to figure out what went wrong, then trying to optimize and, you know, our time wasn't well spent. There wasn't that software connection or any other between them. So all that copying and pasting between different documents and templates. So let's be honest, there was minimal governance to that process. What we really wanted to answer is like what's working and what's not working at what juncture and how can we share that across the organization properly? So the answer, the questions that you want to answer is exactly that. Like what's working and what's not what what's most effective? Where can we spend our dollars a little bit better? And when you're spending time to, you know, figure out what you know, why we spent the spell that incorrectly, there's going to be proper ownership in the process. So individuals will know their role, you know, and like I think once they understand where we're trying to achieve, then you can quickly get there. So that all those things that you have to go through might be a short period of time, but it's well worth it in the end because you're trying to establish a new foundation of this governance. Oh, exactly. It is both the shared data language from a taxonomy perspective, but also just coming together as a team to understand the end goal of what you are trying to measure. And that's where we really start to think about what needs to change. How can you actually strengthen the skill internally to take your marketing to the next level? And that is, as Ram has mentioned it, data governance. So the missing layer between your application and downstream activation, because we do want to get to that point where we can do these more advanced projects. AI, if that's something that's on the roadmap for you or personalization, updating your customer data platform. And that really only comes when you take that application level of the campaigns and before it goes downstream to your infrastructure, to power BI reporting, for example, or to activation, that you have the governance needed to send the data properly. As we say, sometimes you're now trying to turn the narrative gold in gold out to say a little bit more positive and garbage in garbage out. That is the direction that we want to go. And we can only get there when we have this governance layer, which then you've worked with as well. But what really can be hard and another question I have for you is how do you make governance not just a boring process that you have to keep updated? Yeah, that's a great question. I think, you know, I feel like you need to be a collaborative individual and have a vision. And that vision can be shared. And what are you trying to achieve through this governance process is an ultimate goal. You have to take a step back and all these moving parts are happening with all this metadata. I think I've had some great support in my organization through the media teams that go to market teams to embrace this new path. You know, you don't have to do this whole thing. You know, you can just continue with whatever process you have. But I believe like there's going to be inaccuracy or something's unaccounted for. So my recommendation is like trying to work with other individuals. It could be the media team. It could be it. It could be finance. You get get get together, try to map out a clear path with a goal to achieve this unified language of shared data. And I think people will embrace that. I don't see why they wouldn't. It just takes some time just to share. No, of course it is. And you'll discuss this a bit later as well. The people element is so strong here. And that's also why we want to showcase the path that we've been working on. And that's, you know, we've been out in the market talking about is because it isn't just another milestone. It's the foundation for efficient marketing, marketing, especially in universities where you have so many touch points where you may have a longer decision making process. And that's really starting at the strategic discussion with the right team members. So understanding which channels drive applications, for example, and identifying the high performing programs or markets or channel. And then starting to build out that consistency before being able to be more confident about your budget allocation and scale the growth. And that all comes with data governance as an ongoing marketing skill rather than a step go, you know, you know, between steps two and three saying, OK, governance updated, done. It's an ongoing process. And that's what you've been working with so much as well, because you are trying to then move up the curve in a structured way so that it's scalable. Absolutely. I feel like there's such more opportunity. And once you start scratching the surface, you're going to find that, you know, there are other channels that you want to uplift. You want to integrate into the platform. You want to because it's been a success. It's been a success with your paid media. So it gets gets you thinking a little bit more. How can I apply some of these successful patterns? And you know who your eyes and ears are those individuals within the organization are optimizing every day within those platforms. So they're going to speak to those individuals on other teams and like, you know what, this is this is working out really great. This governance that we are establishing, there's they're spending less manual time and other efforts that they once did. So, yeah, this is a it's a growth. It's it and it's it's a commitment and it's evolving to it's not a one and done. But you said, Juliana. Yeah, exactly. Also, you made a great point. It is important about getting the team members buy in, especially early in the stage that you make sure that it is a setup that matches everybody's requirements. Absolutely. I want to showcase a couple of practical examples as well before we talk about the people process element and the downstream impact from a product perspective. But just to showcase some practical examples that governance is not just a reporting exercise, but something that you operationalize. And that's really the major focus point that we hope you take away and start thinking about is investigating that shared marketing data language and a structure that best fits it across teams and across platforms and making that usable for the downstream reporting for stronger attribution and confident activation. So just looking at three examples as well. The first one we've talked about a bit as well already, but that would be standardized campaign taxonomy. So taxonomy meaning that you have set the exact tagging structure that you would like to have. So making sure you have that governance for online and offline activities, but starting with a core naming structure aligned across the organization built out with a master list with definitions and aligning that structure across teams. And that builds out from any potential spreadsheets that you might have with the source and medium and conditions of what you can choose when. But really building that out to match exactly what you need across each team so that it's planned tagging, for example. And that's what you mentioned as well. You talked about that being a way to kind of fight the inconsistencies. Yeah, you know, there's a flexibility in the system to join the on and like we've gone through what we had as a standard in terms of our taxonomy, but as you as you go and your your framework gets developed, you're going to start thinking about, oh, I need a new field for a messaging pillar or what have you or a different subset. So that's a good thing to point out here, too. Like your taxonomy is not set in stone. It evolves with the business. So that's this this whole process has that flexibility. So I think that's important to know, because having that flexibility in your technology is key. Exactly. And that is really critical to both have that flex on the flexibility, but also to have that ability to make it dynamic. And that comes into our second example. So. So. Tagging every touch point. So if for those working with shortened URLs for brand experience or QR codes. Really time to tie that offline input into online attribution is key. But what makes it even more important is making sure that you both have the brand experience set by using a trackable link, but also that you have a dynamic setup so that you can change the output of that link, for example. So this is going a little bit more technical, but just saying if you're using a short URL or a QR code for a brand experience, making sure that you have a clean experience and that you can change the output at the end and have it tracked so that you can adjust for the different recruitment fairs, brochures, just about protecting the university's brand and enabling a trackable setup to tie into all of your analytics. Really connecting those touch points and trying to make that overview look a little bit more structured. Yeah, I think QR codes are really still a very good option. And we just started scratching the surface on QR codes, but there's so much opportunity, as you pointed out in the previous slide with events, you know, an individual just with a QR code can be can be tracked. And, you know, and events in person, that's a huge portion of how you recruit new individuals for university. So absolutely, this is a great feature that Acutex provides. And it's really easy for us to kind of construct a new QR code, let them scan it, and we could track them through the system. Yes, no, exactly. And it is especially within higher education. I remember the start of QR codes being on content I was receiving when I was looking at universities. And now it's even bigger and even more, even used more frequently with brochures. There's so many physical items when looking at recruitment events. And this is also something that's become such a passion of mine, specifically for QR codes, because I've landed somewhere that doesn't look like the site is part of the university I was looking at because the link was different or it was an old link or just some type of experience that has changed the way I've interacted. And that's why the touch points that you can have across even something so small as this are so important to me. And that's why I really wanted to list it as an example. Yeah, I think sometimes QR codes may not be used to its best ability, but when you're working with the proper creative team and you're utilizing the purpose of it, it really works really well. And like you said, events is really key for us. And there's so much more opportunity for QR codes. Yeah, exactly. And third example from our side as well as looking at the student journey or the if you're not working in higher education as well, your customer journey in general, but connecting the journey for budget reallocation, for example. So this example moves from measurement to action by mapping the major touch points using such as QR codes that just discussed, but also general tagging and to connect silo data and to unify your taxonomy. And that is so important because when you can start to map the journey across major touch points, you can understand more about prospective students, you can avoid silos, you can connect even data potentially to your CRM systems, and then avoid any wasted media spend. Make sure that you're allocating the right budget where it matters the most to use the money in the best way or defend strategic channels or optimize your media mix. So that's also where kind of tying together the naming and the touch points really looking across the whole student journey. And I know you've focused on that a lot as well, which we'll hear about in just a minute in more depth. Yeah, I believe Acutis has a really good integration with Adobe. We're on a path to really leverage Adobe CJA. But the whole concept of student journey or customer journey is really key right now. So, yeah, there are different silos, but at some point we have to understand from a holistic approach, where's everybody coming and how are these connecting and where's the proper touch points that we need to identify, as we mentioned earlier. So, how are you going to dedicate a significant amount of a budget just for one silo? That doesn't work anymore. Yeah. Oh, exactly. And that actually ties in well when you talk about focusing on one silo and how to approach that. We do have a question as well from the audience of how you even got this process going internally to start. I definitely didn't hand raise for it. It wasn't a willing participant, but it was kind of, it definitely made sense because I've worked with the media team and, you know, optimization on our campaigns. So, and I work with the taxonomy. So, you know, taking a step back, it was like we had different partner vendors that we were working with. It was almost like you're taking a step back, you're evaluating the whole thing from scratch. It took a little bit of time and through a little bit of error and identification, a lot of meetings, unfortunately, but it had to happen. You kind of find out what worked and what didn't work from the spreadsheet process through a SharePoint process, et cetera, whatever you have. But then you're speaking to those individuals like what happened here, what didn't happen, what needs to happen, I think, is the main purpose of that. So I feel like within analytics, it's so important to analyze everything because you got to see what technology you have available, what you could leverage. So you're evaluating all sorts of things. But again, I think it's the collaborative sense that it really has to happen in the offset because it's not a one person journey. I can't force a new governance effort. And actually, you know, you're working and you're trying to kind of figure out things along the way a little bit. You know, we went through our proof of concept was with Meta. We used we chose a platform and I believe we had it running. We saw the data run through maybe a month, a little over a month, and it worked really well. So therefore, you saw all the campaign data running through really efficiently. And then you saw like pre and post. If we were to do this in our old process, you could see the distinct differences of the classifications of your data. Yeah, that's a really key point as well as picking that one that you tested, which in your case was Meta. And then comparing the past and the current, the current and past dates, essentially, is really making sure that you can showcase kind of about building the business case by starting with a test channel that is important to you. Exactly. Then let's on that note, also, perhaps to provide more words as well to the process that you went through. I'll just move over to some content that you've prepared as well to showcase your journey in more depth. So I will just go to the next slide here and then just have you voice over a bit more about the target benefits you achieved in the journey as a whole. And of course, just your story. Sure. You know, I feel like you in evaluating where we are now, I feel the foundational aspect was quickly achieved. The team understood at the activation level through this new process, although, you know, there was a little some trial and error. So this, the complexity before has allowed us to kind of see big picture, why their activities and are tagged every day and these decisions are made based on this. So, um, there was a need to have these high level categories in our metadata and campaign and messaging. Um, and this attribution was, uh, and messaging was clear toward the end. So we've experienced the enhancements in data quality, increased process efficiency, and then our reporting through, um, we use Microsoft power. We use our RBI, we see that, uh, quite evident in our paid media data. So in, in, in the summary, really, um, that's the test. If you can, if you can see, um, enhancements in your data, improve the efficiency, you're not spending too much time in error. And then finally your reporting and the output is, is really key. Mm. Oh, exactly. And then it is the, the test, um, that you went for as well to showcase, you know, the actual benefits that you can get without just jumping into a certain solution. Yeah. We have more visibility now in our media campaigns because of that. Um, we, we now have a user friendly platform that we could, you know, give that level of detail to everyone. It's not just, you know, a few individuals. It's disseminated through the many individuals that can, uh, manage and monitor that. This slide right here is kind of like the, the, the proof is in the pudding and comp complements to, uh, the, the, the, our data enablement team. And they are, um, the architects and they help manage, um, our, our cloud, our data leg, et cetera. The, the integration of all these platforms. And what we found and maybe, maybe other organizations might experience this also, that there was, uh, a gap, um, in the classification, um, of our data. So what happened, there was inconsistent classification and OTT, um, paid social TV and audio. So with these discrepancies, we were able to fix them rather quickly. And once you eliminate those, um, errors, you're going to have better reporting and consistency. You're not going to have those issues anymore. So what I mean is like, if you're, if they're not mapped adequately, it limits accurate performance reporting and cross channel, um, comparisons. And that's really what we need because as we mentioned, you, you got all these channels, uh, taking place through your journey. Uh, if you're not having a better classification, you're not going to be quite accurate in the output. No, exactly. And, and this enables some more interesting projects downstream as well. And is, how is the journey for you with AI and machine learning readiness in general? Are you beginning the journey? Are you moving more into it now as we go into the year? I think, uh, we progressed and we're, we're in really good shape. I don't think we're, we've been early adopters at the organization. Um, but you know, you know, in analytics, uh, in, throughout my, my career, I feel like if you don't have the confidence in your, in your data, then none of this is going to make sense. So like, um, I think it, um, back to AI is like, we have everything in place now and that confidence is there. So therefore we can make that journey, you know, we could save a conversation for the future, but what's happening right now with a lot of organizations, there's, uh, AI hallucinations because your data is not stable. It's not, it's not, it's not, there's a lot of, uh, cracks and, um, the foundation isn't there because it wasn't really, uh, set up correctly. Um, I don't think we, we, we, we, we have that challenge, um, per se, but, uh, what we, in my organization, I think there's like, we need to think about better opportunities. Like with the QR codes, I think there's opportunity with other channels, but, um, I think we have, we have to be prepared for like AI readiness is the new thing now. And once you overcome all these, uh, challenges, you're going to be AI ready. And then I'm not the AI, uh, expert. This is all going to be handed off to those individuals and they'll be ready. Yeah. No, exactly. Just sending the data down to their teams in the most structured way. And we talked before the session as well, about just how that happens with the different, with the strategy, with people, with processes, and of course, with technology. And I do have a question from the audience when we get to the people element as well, but I'll just give you a moment to also just put some words behind how you've seen the strategy drive your business growth. Yeah. We, we kind of talked about our vision already, you know, you need to have some confidence and some, some courage sometime with the, your team, with yourself and just map out, uh, how you feel, where you, where you need to go. And what, what, what is defined as the success? Uh, yeah, here you go. Um, every, everyone wants greater efficiency. So I don't think this is going to, is too controversial here. So, you know, once, once you have the shared vision and you can, and you, and you speak to it, then, uh, it's quickly achieved, but it means it takes some collaboration and some, um, you know, some, some, just to talk it over a little bit. What are you, what are you trying to focus on? Um, yeah. Uh, the next slide about people. Yeah. Yeah. This is a real, uh, important, you know, your colleague, for example, you, you and I were, we're 4,000 miles away. You know, we are, uh, very collaborative in nature. I, I, I, I work from home. I have teams in, in, in various locations. We've worked with, uh, how do we collaborate with all these individuals at the end of the day? You know, you have to think about different individuals at different competencies coming together to, uh, you know, establish this, uh, unified language. Um, and then it drives the innovate and innovation eventually. How, how are you going to innovate, uh, further with your large language models, et cetera? Uh, if you don't have, if you have cracks in the foundation, then you're going to have issues, but the people, we haven't been replaced by AI yet. So people are the most important to me, uh, equate piece of the equation here. And that actually leads us to a question that we got from the audience as well as how, what advice can you offer? Um, when you're talking with internal stakeholders, but not yet focused on the internal politics. So how do you speak about this internally with users who might not be the end audience outside of their normal jargon? Yeah, I think, um, people are convinced by, um, improvements in productivity. So if you could, if you could, um, share, um, why, uh, embarking on this, um, journey of, uh, creating a unified language, um, really impacts, uh, saving of time, saving of, um, of resources. I think that, that gets across to a lot of people, especially, uh, leadership, um, and also, uh, the individuals doing the work too. Like you imagine you're saving hours in your, in your week and your day, you know, that's pretty convincing. Yeah. No, exactly. Um, one quick question that we had for the audience before I move forward is just, um, there was a question just about these channels, um, just about OLV, just to clarify, um, as online video marketing tracking as well. Um, just, uh, pull up the slide here for a second so you can see it, um, just to clarify that as well. Yes, that's correct. Online video. Yes. Then on to processes. Yeah. Now we've got the people in place. We have the vision. We've hopefully had a conversation where we have been able to discuss outside of the jargon, a convincing way to proceed. Tell us about the processes. Yeah. You know, what's key in the process is everyone has a clear role. And accountability. Um, once this is defined, like you're, you're responsible for entering this at this juncture, you're responsible for entering or clarifying this campaign or, or, um, or even you're responsible for a particular channel. So, um, there does need some time to kind of manage and communicate what the new process is. But, um, once everyone is aligned, then you can, um, definitely, uh, feel like everything's falling into place. So once a new process is falling into place and the platform makes it quite, uh, easy. So you're going to see within the short amount of time, the productivity will increase once this new process is dedicated. You know, it's a, it's a user-friendly new process. And it's streamlining the workflow. Are there any challenges that you and your team had with kind of adapting this new process, just kind of taking longer or learning about new opportunities that you then had to adjust for? I think the challenge was, you know, just as with any technology, taking a step back and learning it, you know, but it, it doesn't, it's, it's really, you're not, um, it's not that difficult to be honest with you. I think, uh, dedicating the time and effort after you understand the vision and you have the right people in place, then it's, it's not a, a challenge. I don't, I don't think there was too many challenges to be honest with you. I think it's just getting alignment with one another. Well, and, and of course, uh, leadership too. You have to be aligned with, um, your leadership. And I think my organization was, uh, quite, uh, not a challenge either to, to, to share that this is, uh, uh, to the benefit of the organization. So, um, I, I don't know if there, I don't think there was too much of a tough challenge. It was just overcoming maybe a one-on-one on why we should do this. Um, what the, the, the, the platform and what we kind of had in existence and how we're transforming it for the better. Mm-hmm. Oh, that, that makes complete sense. And of course it depends also on the marketing skill sets in the organization as well, both on the process and the people side. But, but if you, you know, if you look at, um, other types of colleges or universities as well, how are we simplifying this information for those who may be newer in the marketing, um, role as well? So not just, you know, throwing around these big words, but merely being able to simplify the, kind of the storytelling just to make it easier for those who are more new to kind of this type of marketing tech. Yeah. My recommendation is, um, you know, you have to put your shoes in, in a new perspective, uh, individuals trying to pursue an education. Uh, first of all, and once you're kind of realizing that they have so many touch points, they have so many options. What are those points of data and what are you going to do with it? Um, how are you going to organize that data? You have to have to have the starting point to kind of get to, to, to, uh, the end game. And my recommendation is take a, take an evaluation of where you're at, work with, work with your teams, work with your, um, with your, your, uh, data. What types of data are you actually putting? What types of metadata are you already putting? What do you need to pull? Um, technology is only one piece of the equation. Like we, we need to kind of look at everything holistically now. And once, once they start thinking about, they take a step back, work with other teams, then you're going to know, okay, we can execute so many wonderful campaigns that are tailored to these different audience of who we're trying to target. To recruit and eventually, hopefully graduate. Exactly. And you mentioned the title, the technology element as well in that conversation, tying this all together, but also just making sure you reach the touch points you need to get the right students in. Yeah. Technology rapidly changing as always. But if, if it, at the end of the day, it's not improving, um, your organization, then, then, then it's going to be a challenge. I feel bad that we put a red X on the Excel here, but you know, we still use Excel. There's nothing wrong with that. And maybe it's a stepping stone for other things, but what you're actually trying to achieve is data accuracy and better high quality data. It's pretty simple to me and how, how the steps to get there are probably a little bit more challenging than adopting the technology. Um, but if you're trying to get to the next level, as we have here with AI enabled data infrastructure. Um, I think it's almost a given that you have to have these strong foundations. So the technology will get you there. The people, the vision, the people, the processes, all in that, uh, stage. Um, you're going to reduce all these manual root workflows, as we mentioned, the time spent, and now it's going to be user friendly. And then you're going to have a microscope or a magnifying glass. I mean, to see what campaigns are clearly spelled out and what are, what are resonating a little bit better than others. And that's the ultimate goal and how you're going to optimize with those teams with your marketing budgets. Exactly. And it also is just about preparing for when things change. So for example, you know, you have new channels that come up, uh, TikTok was a new channel that came up as well. You have AI now potentially has, um, there might be, uh, advertisements in AI as well and different, um, GPTs, for example. So there is a lot of focus on just making sure that your governance is set so that you have the ability to change for all of the different things that might come from a technology perspective as we go forward. So that is really the, the focus. And I'm really glad you could outline those four different areas as such an important focus point. Oh, I totally agree, Juliana. You know, I think, uh, this is all going to change again. It's a given, you know, what are the new, I used to laugh at TikTok. Now we're spending, you know, organizations are spending millions of dollars on that way to reach, uh, individuals. So, uh, definitely things are going to change again, but how are you going to be prepared? And this is going to make you prepared while having everything structured like this in the unified language. So exactly. It is about just kind of getting the structure to be able to take on these changes as they come. And I'm really glad you were able to come online today and tell your story. And just for us to have some dialogue about this topic, because it is something we're so passionate about. You're very passionate about it because it isn't just about connecting touch points so we can really understand the full experience and show impact of marketing, which is really important. And so I just want to thank you so much for your time and for coming online. I know we have, we've gone a little over time, so we'll call it now, but I'm sure maybe we'll have a second session in the future. Or, um, for those online, you can always reach out to us and we're happy to talk more about this topic. I appreciate the opportunity. Yeah, this has been great. Thank you so much. Yeah, thank you so much, Rames. And thank you to everyone. And, um, we'll see you online. Thank you. Thank you. Thank you. Thank you.