[Music] [Emily Wilhoit] All right. I see a few trickling in. Well, thank you everybody for joining us for the first session. I know it's after lunch, so please don't fall asleep. We'll try to keep it engaging. But really excited to have you guys here to talk about, Real-Time CDP and how enterprises are transforming their business. I'm Emily Wilhoit, Chief Marketing Officer of Blue Acorn iCi. We've been an Adobe partner for nearly 15 years, and I'm joined by Venkat from Infosys, our parent company. He's the DX Unit Technology Lead, and Gopi from Signet. Gopi, I'm not sure if everybody knows what Signet is. Sometimes it's known as other brands. Could you give a little background? [Gopikrishna Haripuram] Yeah. Thanks, Emily. Signet is the world's largest diamond jewelry, and we have subsidiaries in USA, UK, and Canada. If you visit any of the popular North American malls, we also go by Kay, Jared, Zales. Yeah. Yes. All the good shiny stuff. Awesome. Well, thank you again for joining. I wanted to, kind of, start by understanding who's in the audience, what industries we have represented here. So Gopi's obviously, a retail expert. Can we get a raise show of hands who's in retail or CPG? Okay, a few. Healthcare? All right. Good amount of that. Manufacturing, B2B? What am I missing? F, okay. Financial services. All right. A lot of healthcare and financial services. Did I miss anybody? - Maybe high-- - Oh, technology, communications? All right, a few. Great. Well, we're really excited to talk through how Real-Time CDP can help all of those industries get to that better one-to-one personalization. I think we all heard this morning the focus that Adobe is bringing to all of the solutions to help all of us get to more one-to-one personalization. But I wanted to start with a quick example, a retail example. It actually happens to be my husband. He was headed for a guy's golf trip and wanted some new shoes. So I've been in commerce a lot of my career, so I'm always fascinated with his commerce experience. And he started by, you know, browsing the site, and unfortunately, the size that he wanted in the pair of shoes he wanted was not available. So luckily, the site had an in-store availability checker, you know, inventory checker, which said, the store in Charleston, South Carolina where we live had his size. So he goes to the store, really excited to just get these shoes ASAP because his trip is of course in two days that he hadn't planned appropriately. So unfortunately, when he got to the store, his size wasn't there. I think we can all relate to these type of experiences, right? So he got to the store. There wasn't exactly a super helpful salesperson to help him understand what was going on. Towards the end of his engagement, he was asked, "Hey, did you find everything you needed?" He said, "No." Said you had size, you know, 11 here, and he didn't. So a salesperson took some notes, some data points, and he thought maybe they're going to help find it. They, kind of, semi-promised that. But ultimately, he left without any shoes. So I think we can all agree that that's a really bad consumer experience. And I bet, like I said, everybody has their examples of these. And, you know, really at the heart of it is inaccurate inventory data that took him to the store, out of his own home, and then disappointed him, right? Also, the lack of customer profile integration. You know, when he walked into that store, those sales people didn't know who he was. So a huge opportunity and ultimately, you know, it wasted his time and effort and caused a lot of frustration.

And so what we see what we all know here from-- Let's see.

Being in the Adobe ecosystem is many organizations are investing in this area. According to Forrester, 67% are investing in data solutions to help improve that customer experience. And what we want to talk about today is that solution, Adobe's Real-Time CDP. They can really help bring together all of that data and provide real-time customer profiles and audiences to help brands like yours deliver a better customer experience. So I want to turn to you, Gopi. You know, as a technology leader, what is a CDP? What are the benefits? We hear a lot about it, and Adobe announced it, you know, four to five years ago, but would love to hear from you, what are the benefits of a CDP? CDP means many things to many different folks, right? From a technologist, CDP is one place we aggregate all of the customer data. Customer datas can be streamed from many different segments, coming from ecommerce channels, POS stores, social media, among many different things. You need a standardized way of aggregating all of this information in a single place so that it's easily retrievable for many different organizations across the board, right? It's marketing, customer say, contact center, digital marketing, many companies use that data. One of the biggest things you need at CDP is to break down the data silos, right? One of the omnipresent problem across organizations these days is, data is fragmented across many different places. CDP provides you the concepts that are necessary to bring all of the information in one place. All of the customer information can be aggregated in one place with all of its attributes for easy retrieval. Previously, in the past, marketing teams, right, whenever they need to retrieve data, it really needed large data engineering teams to be able to retrieve the data, run any insights, building any campaigns, all of that, right, like, it used to be a laborious exercise. With the advent of CDP and some of the journey orchestration mechanisms, it's really easy for marketers to be able to get the unified view of the customers. It's really easy to correlate online and offline information.

That's great. So obviously, many of us are aware of the need for this. But Venkat, what's driving this need? What has changed in the ecosystem? Why are organizations now expected to deliver these great experiences? [Venkat G] Sure. Thanks for that, Emily, and good afternoon to all of you. As Emily said, hopefully, you all had a good lunch, and this will be an exciting conversation. So I think, you know, to add on to what Gopi said, if you'll really look at digital experience, I like to look at it in three phases in the recent past. There's what we call a pre-COVID digital experience era. There's a COVID era. And then there's a post-COVID era. And let's just touch upon what was the overall difference between these three, right? When you really look at the pre-digital, I mean, the pre-COVID era, you had organizations wanting to really get digital. And usually, you had the early adopters and so on. But I think COVID really changed all of that. Everybody went into it with doubling their investments on digital. Those who had already invested in digital, kind of, really disproportionate additional investments to increase revenues and so on. Those who were not really, you know, good in digital maturity, who were the slow followers, they really invested for first time, and they invested a little, I would say, you know, without focus on value and measurement. And all of that really hit, sort of, a glass ceiling when COVID ended. And now we are in what we call a post-COVID era. If you really look at it, businesses expect to date to focus on value and outcomes, right? And there's a lot of scrutiny in terms of the disproportionate investments that went on during COVID. So there's a lot of focus around how do I get more out of my customers. And in fact, a few organizations that we have spoken to sometimes, you know, are even focused around ensuring that they just retain their current customers, drive deeper engagement, and so on. Because for them, acquiring new customers, the ROI on that is much, much lower than what it is to just engage and go deeper with existing customers, right? So that's one big, you know, macro-change that we're seeing there. Now there are other trends that are obviously, you know, part of real life that all of us are accustomed to. You're seeing changing demographics, younger and, you know, different age profile of customers across all segments and industries. You're seeing behavioral patterns also change. You're starting to see channels that are different, right? In fact, the other day, we had gone to one of the retail stores, and we could not enter the store. It was not a sale or anything, right? It was just a good weekend during spring break in one of the Dallas outlet malls. It, kind of, gives an out, you know, view that today even returning to the store is happening. So channels are not just digital and social, but you're also starting to see customers come back. And if you take the example you were telling Emily, today, when customers engage with the brand and different touchpoints be digital and then in the store and then with the assisted care on call center or whatever, how is the brand or the organization being able to identify, yes, it's the same individual who's engaged with me the previous night browsing my product so that when you walk into the store, the assistant there is able to look at it and say, Emily actually looked at a profile of running shoes. And therefore, you know, quickly come in and say, "Hey, Emily, is it related to what you did in add to the cart?" So I think there's a whole bunch of these macrotrends going on. Also, in terms of, you know, the other stuff, I think it's really around focus on value and outcomes. And therefore, CDP and customer data platforms are being seen as that one solution to drive and to begin a journey towards driving better outcomes for customers. And that's where personalization at scale is the outcome. But I really think understanding the customer is the beginning of the journey, and CDP has really enabled us to get started out there. And you'd also see trends across different customers, right? So far, I was talking about macrotrends, but then if you bring in, you know, views of what's happening across the buying journey, you're seeing a lot of focus around marketing pre-buy for CDPs. You also see a lot of customers starting to use CDP in the post-buy journey, right? Some of which were not explicitly talked about in some of the conversations we saw today. One of our customers is looking at, you know, how do you drive-- And this is a high-end retailer, right? They're looking at how do you drive better engagement of the brand so that there's higher repurchase within a span of the next three years? So there's a post-buy engagement that they're focusing on, and CDPs help that. Second dimension to look at is B2B versus B2C, right? B2C obviously, is an early adopter of CDPs, but B2B is also slowly starting to pick up. And one of our customers, for example, is looking at B2B CDPs as a way to drive renewed subscriptions and also upsell their subscriptions, in terms of cloud provisioning for their customers. So that's the other dimension. Third, when it comes down to the different industry sectors, obviously, retail, kind of, is ahead of the pack, but you're starting to see, kind of, fast following happening from high-tech, telcos, and so on. And then I would say not left far behind are sectors around finance, insurance, and health care. In fact, one of the interesting examples is one of our pharma retail customers is actually using CDP to drive better, you know, prescription compliance, right? This is a very unique case, not something that we would have generally heard. And for them, this is the beginning of a journey because they feel a lot of the prescription orders that they get from the caregivers, around 15 to 20% of that is left unpicked at the store. So they want to begin this journey with that. It starts with understanding the customer, creating that profile. And this is all very secure and, you know, HIPAA-compliant solutions, right? So we should not lose the fact that as we try to drive better engagement, we are, kind of, ignoring some of the fundamentals of compliance and security. So I think, you know, you'd see different industries adopting it in different ways across journeys, across B2B, B2C, across different industry sectors. And finally, coming to the geo perspective, I think you'd see North America leading, closely followed by Western Europe. But you see digital natives in, you know, South Asia, Southeast Asia, and sometimes even in North America starting to adopt data-driven personalization way ahead of some of the others. Another trend that I see as a marketer myself is just doing more with less, and the need-- Yeah. We're all getting that pressure to deliver these great experiences, but, you know, reduce spending, reduce tech stack. So I think that's where we see a lot of opportunity with CDP, as well.

Gopi, from a technical standpoint, let's talk about CDP. What it is? What it isn't? Demystify it a little bit for us.

Yeah. I think we should start with what CDP is not, right? Like, it's not a data warehouse or a data where everything goes, right? It's not. It's very sophisticated and highly specialized customer master data platform, right, where you have all the attributes of a customer and all the information of the customer, right, all their, interactions prior. Maybe it's in a mall environment, in a store, and online impressions. It's aggregation of all the information you can get on a customer all-in-one place.

Oftentimes, right, like, there are other departments in an organization which do CRMs, DMP among other things. There has to be a clear demarcation and separation between what each thing is, right? The CRM helps with contact center and sales. CDP is a whole 360 customer view. So CDP from a technology standpoint, right, like, it's you briefly touched upon, it really enforces a lot of the data compliance and some of the good data hygiene that is needed, right? Like, before any of the data can be activated through campaigns, it's really important the preference and consent management is taken care of. CDP lets you do a lot of those things. It makes sure the marketers are complying with some of the rules around, right, industries. If you're operating in the UK, it could be GDPR, CCPA, among many different things.

CDP provides many opportunities, right, where you can tag the data appropriately, right? So it's easy for retrieval. And at the same time, it's easy to delete information if the customer chooses to.

To achieve all of this, right, it's really neat that you have a strong data engineering team in place to bring in all of the data from different disparate data sources, right? Never underestimate the complexity of legacy data, right? Like, at Signet, it took us 18 months to really go through and to build a data pipeline, which really worked for the marketers, right? Like, it's legacy systems, systems across many different places. So there are many constructs within CDP which helps you aggregate all of this information for easy retrieval.

It's great. I think, yeah. - You said it. Data is king, right? - Yep. So the importance of getting that data right before you begin this task-- Cleansing it, duplication, deduplication. Yeah. Venkat, anything to add about data? Yeah. I think Gopi's, kind of, covered most of it, but maybe a couple of points to just jump it and make it explicit. I think, you know, even though the question was one of the technical differences of CDP with others, I think, you know, one of the things is to work with business, right? It's really sits at the cusp of, you know, traditional marketers and the rest of the hard problems of the old enterprise, right? I think, therefore, you'd really see this as the bridge between unlocking value, but at the same time, keeping your feet on the ground and doing some of the dirty work that's sometimes very difficult. So I think that's a big, you know, reality of CDP. And the moment you dig deeper into it, some of the problems that Gopi said becomes relevant. Second, I think one of the points that, we'd like to deep dive is, if you looked at what was announced at CDP, RT-CDP today, RT-CDP is one of the big apps around the CDP foundation, right, so or the AEP foundation. So if you really look at it, I think as you go through that journey, you got to go through setting up that foundation, you know, getting your enterprise architecture team, you know, as part of the journey is very important. Getting them early on is very important, right? Getting your InfoSec, and your CSOs also aligned to that is very important. Your industry compliance, in the case of healthcare, it is HIPAA, so on, it's very important. In fact, one of our customers stumbled through their early first step, right? They were thinking, let's do a pilot. They had not even bought the license, and they wanted to just run some simple use case. And one of them really moved a little bit of customer profile data from their internal well-guarded wall into the cloud as part of the CDP pilot. And then that ran into a compliance violation, right? So I think you don't want to run into that because the moment that happens, then all breaks will be put into the organization. So, you know, be ambitious, be visionary, but, you know, be guarded also, right? Because CDP really is where you need to keep your feet on the ground while you aim for the sky. I think that's another important aspect on that. It's great. And obviously, it's an investment, right? You talked about IT and marketing, making sure everybody's on the same page. But let's talk about how you even measure the success of it. Gopi, we'd love to hear from you. You know, what are some ways that executives and internal business stakeholders are asking, you know, how have you seen progress? Yeah. Having good data is one thing, right? But it's really for business. It's all about the ROI, right? Like, how are the campaigns which you are executing impacting, like, is the ROI? Is the impressions, are they leading to conversions, right? It's all about, how many customer profiles are you able to mine through all that data signals you're getting through, right? Once you have the different numbers of customers, what kind of attributes and segments do you have on those customers? It's really important, right? Once you have the customers and all the attributes, you have to have a proper framework, a measurement framework in place which lets you determine, right? How many of these customers are reachable, right? Like, which is the extent of reach is what determines the journey. And the journey can be-- The people can be reached in multiple different ways, though, right? Like, if you segment users across email, SMS, web, and social channels, it's really important. You have a measurement tactic, right? Like, where you measure how many of these are actually flowing through. Yeah. That's great. And, you know, how often are you is your team looking at these, kind of, numbers, you know, is it talk about once you launch CDP, it's a continual process, right? Yeah. It's a continual process, right? Like, our development teams work in an agile fashion, though, right, where data is bought in, clients in every two weeks, sprint cycle, right? Our business units work in a four-week sprint cycle, right? So the units are always measured. We use Adobe CGA platform. I have my partner in crime, Michael here, who heads up our CX team, right? Like, they're constantly looking at the data, right? They're working with the engineering teams to identify gaps and fill where they are. That's great. So when I get into some learnings, but first, let's pull the audience again. This works-- I would love to understand where you guys are in your CDP journey. Some people come to Summit already having launched on CDP. Some people are just in the beginning. So by raise of hands, we're going to do these three segments, if you will. Anybody here still exploring CDP? A lot of that. Okay, what about beginners? Maybe you're in mid implementation, all right? And any practitioners? Nice. Okay, good mix. Well, Gopi, I think, you know, you've gone through this process, and you're continually improving your implementation, but what learnings could we share based on these three segments? For explorers, it really begins with the use cases, right? The technology comes later. It's really identifying what business gaps do you have, right, in your current, marketing campaigns among other things. It starts with having a forum, right, where you bring in marketers, contact center, digital teams among different teams, and try to identify what use cases you're trying to solve. Once you identify the use cases, data comes next, though, right? You scout through the existing data systems, right? Any data warehouses you have could be Hadoop, it could be POS and store systems. You work through a gradual strategy, right, where you incrementally start bringing in the datasets one at a time. You really don't want to boil the ocean all at once, right? Like, data is a beast, right? So once you identify the use cases, it's really important, you bring the data which is needed to bring the foundation, right? It's one of the things you will often notice as a beginner, right? It's one of the things which we had a little bit of trouble with is we're trying to bring all of the data at once. And it's not easy. Mastering the data, coming up with the customer identity is not an easy process. So you really need to have a test and learn strategy to how you are bringing the data in, right? Once you have all of the data, you want to scale it, right? Obviously, the demands, the more data, once the initial campaigns hit the ground and once business and other units start seeing the success, it's all about scale, right? How do you scale? How do you scale the data? How do you scale the campaigns? How do you scale the content? There are several different techniques and tactics that are used, right? And as everybody saw in the keynote, Firefly is of a big use, right, in terms of generating content at scale. Images, it's a commodity, which is really expensive, right? Like, but if you want to come up with a lot of variance, it's always going to be helpful to have AI utility like, Firefly in place, which can generate a lot of images at once. That's great. Venkat, anything else to add about, you know, you're working with customers across all industries. Any other learnings that you've seen of, what does it take to have a successful CDP rollout for a large enterprise? Yeah. Sure. Now thanks for that, Emily. See, I think, you know, on a lighter note, you know, we also want to be very cautious in what we look at the CDP for, right? Don't look at the CDP as a hammer and start finding nails. I think you're going to then start focusing on use cases and scenarios that don't really drive value. As Gopi was saying, you know, partner with business, that's very important. We're seeing many of our customers today being mature and starting to, you know, get business involved.

But one of the things we call is a CDP value canvas. So on one side, from an outcome perspective, it's the problems and the use cases and the value that we're trying to create. But really, what's going to drive effective outcomes in that journey is going to be the availability of data and the ability to integrate with the data and make sense of the data, right? So if you really see on one side, you have the bottom up view, which is, you know, what can you work with, which is data. But on the other side, there's vision and strategy, which is really what is that use case that you want to solve. And one of the things we are starting to see with many of our customers is this really a gap between the most important thing to do versus the availability of data and the right systems to be able to get that use case done as the first one, you know, in the first launch. Therefore, we have created what we call a fast launch framework, which really keeps your vision and the long-term roadmap in mind. But at the same time looks at what data is available that can then help you launch something at least even if it's a minimal value in the first 90 to, you know, 180 days. And therefore, you know, without ignoring your long-term priorities, it can help you show outcomes, you know, have engagement across with customers, as well as business come in, test and learn. And therefore, slowly over a period of time, you're able to merge the gap between what you want to do, what's the most important versus what can be done, which is the feasibility and the viability element. So I think that's important. Therefore, a canvas that, kind of, ties in and drives the road map is good. Therefore, it means from an implementation perspective, look at it in really two tracks. One is the value track, and second is the foundational readiness track. The foundational readiness, you know, as many of you are from the digital experience space, think of it like, what in the old world we would have as a UX track and a technical implementation track. And UX would ideally want to get their wireframes and visual designs at least three, four, you know, sprints ahead of implementation. Similarly, think of the foundation track as a track that in turn gets your enterprise integration and the data readiness for each of the data systems or channels available so that your value track can just focus on the use cases and look at optimizing that. And therefore, you can then look at activation and then measurement. So I think we really need to keep some of these in mind. And I'm sure Gopi will resonate with some of this, right? - Gopi? - Yep. That's great. So of course, we have to get out our buzzword bingo and talk about GenAI. It was the theme of the morning. So let's see. You know, if you guys are looking ahead, especially you, Gopi, how generative AI is already affecting your business and how it's going to help continually, you know, drive better personalized experiences. What would you share with the audience? Yeah. GenAI is no longer a buzzword, right? Like, it's well past its initial hype cycle, well on its way to the plateau of productivity. We at Signet see GenAI being utilized all across the board, right, both internal and external customer facing. AI chatbots are all over the place. Being able to summarize the chat summary's description is a big use for our contact center. That's one place where it's used really, right? Content generation at scale, I briefly touched upon earlier, right? Like, so content has to be scaled. And the way to do it is not manual, right? Automation at scale only happens when you apply AI. And GenAI and utilizing tools like Firefly is one of the fastest way to arrive at that.

Also, from a productivity angle, right, co-pilots are really helpful. For instance, developer productivity, like, Signet does a lot of work with Microsoft GitHub Copilot. That gives us the ability for our developers to be able to generate code utilizing many of the world-renowned repositories, right, like, automatically. We also extended the productivity to marketers as well. There is marketer productivity that can happen utilizing some of the Adobe's Journey Orchestration tools where you can generate marketing campaigns using natural language processing. A marketer can speak in plain English as to, right, what they want out of a campaign, and you have orchestrations that are built on top of that, right? There's segment builder opportunities which uses GenAI. Right. I think that's hugely important because if the CDP is giving you all of these new audiences and segments, then you have to have your team scale up to actually activate on that information and crank out a lot of content. - Yep. - Yes. - Think of anything else on. - Yeah. I think, you know, to add on to what Gopi said, a couple of points, right? I think, morning, we all heard one key, kind of, outcome, which is personalization at scale. I think, if you really look at what can help us achieve that besides using RT-CDP, I think, it's really the ability to mine customer intelligence at scale, right? And for us to be able to do that, today, most of the organizations have tons of data, right? It's just that in the way that you would look at the data is in terms of what we call logs or archivals, right? It's like, you know, a chat session, right? A call into a call center and a record of that or an email from a customer and so on. So I think one of the things generative AI is going to help, especially in a scenario for CDP is how do you mine all the tons of logs and information that's there unearthed in the past? Because doing it in the past was very expensive and sometimes even difficult to do. So today, LLMs and NLP capability at scale can help us mine that. And therefore, you can now, for example, one of our customers which, you know, who had around 500 plus attributes for customer profile, we're running a pilot where we are mining their logs from both call center, as well as emails and adding on almost 150 to 200 additional attributes for each of their profiles, right? And this is something in a pre-era. I mean, even just a couple of years back would have been prohibitively expensive to do. So I think, therefore, the ability to build intelligence and mine intelligence that is already, kind of, scattered and rusting in the organization is a big value lever. The second, I think, you know, I'd like to touch upon, which wasn't explicitly talked about in the Adobe Summit, but you saw that powering a lot of that capability again is semantic search. I think you're starting to see semantic search, kind of, play out in different customers in different forms, better NLP capability, both in the pre-buy and the post-buy journey. Visual search is starting to play out. So I think semantic search is, kind of, one of those less important or an area that's not given that, kind of, importance but can really drive huge outcomes. The third is in, I think, Gopi touched upon GitHub for software engineering, similar copilot model for each business function. One of our customers, we're helping them build accelerated marketplace launches both on the supply side and the demand side. So think of the copilot not from a software engineering perspective, but really as a business copilot for that merchandiser and the marketplace owner. Now we've all heard of copilots, and this example was just one example of a client. But I think them, you know, looking a little ahead is you take a bunch of these copilots, which are persona centric. And then if you look at it horizontally across a line of function, you can really drive end-to-end workflow automation, what we call using the chain of thought capability of LLMs, right? And we've heard of that. We've heard of LangChain. We've heard of various other capabilities. I'll give you an example of how running chain of thought and entire process automation and CDP becomes relevant. One of our B2B customers, they have around 7 to 10% of their client orders, which are not even responded to. Because typically, they have this measurement that if you don't respond to a client request because they deal with, you know, at least a million SKUs and these are low value products. And if you don't respond to that within two days, it's quite likely that the person or the customer who's asked that query is no longer interested because they would have found their way to the product. So therefore, today, they were not able to do it because that's a traditional way of selling. We are now working with them and building out what we call an entire B2B, you know, order lead to cash, kind of, workflow using, you know, LLMs, and LangChain, and the entire chain of thought capability where you are able to receive the request in a voice call or an email, understand the unstructured need, convert it to a structured below materials, use that to drive product search, get the availability and the price of products. Using the customer profile of CDP, you're able to drive personalized promotions on that specific query for that customer, create a draft quote, and then be ready to ship it off. And if it's low value, they're even starting to pilot low value, less than $100. Just go send it out, right, after a couple of beta tests. Only if it's high value customer or a high value order, then they would want a human to verify that. So if you really see you're enabling this organization and if things go well, almost 7% of leads which were unaddressed in the past are now going to be addressed, right? All of it combines CDP, customer intelligence, but more importantly, generative AI that can drive automation across multiple persona copilots. So I think that's just a teaser of the art of the possible, right, that we can look at. I think it's crazy to think a year ago, excuse me, we all learned about Firefly for the first time. And they said this morning we, kind of, were all in the playground stage. Yeah. And this time next year, I'm excited to see what some brands are doing with it to really drive the experiences.

Okay, for both of you, would love, you know, we saw that there's quite a few different attendees that are in the various stages. Exploring, implementing CDP, or actually using it. What are some final thoughts? Three words if you can, or three points of what they should take away as they are transforming their business. Yeah. It's truly, a business and IT exercise, right? Like, it has to be a proper collaboration between different units. It's really important, essential to identify the use cases across the board. As it comes to technology, right, never underestimate the complexities of legacy data, right? Like, it's really-- You need to have core engineering practice in place for bringing in a lot of the data streams across your POS, e-commerce among different channels. You have to be very deliberate about the use cases, right? Do you want the data to be activatable in a real-time fashion? That means a different, kind of, architecture setup, right? There is streaming information available, many SDKs out there. You have to determine what's from a marketer productivity perspective as well, though, right? Like, there are tools and places. You could write Adobe CDP extends, there is an entire AEP platform, right, where you can do journey orchestration among many other things. So lot of training, right? And understand, right, this is not an overnight exercise. Yeah. It can take organizations anywhere between 12 months, 18 months to 2 years to fully do this. So plan accordingly. Few more than three words. But, Venkat, now you're good. Yeah. I know. Now thanks for that, Gopi. I think, you know, all three of them are pretty relevant. Just to kind of deep dive into a couple of points that I want the audience to think about. I think the value map or the value canvas as we call it is very important. You know, I think it helps align, you know, really outcomes, and vision to really reality and feasibility. I think that's really the magic lever that can help accelerate the outcomes. That's one. Second, to go on to what Gopi was saying, it's going to be a long journey. And launching the CDP is in many ways, just the beginning of that marathon run. So in no way is it a outcome that you're doing, it's just the beginning of a learning journey, learning about customers, learning with, business, and so on. And the third, you know, I'd definitely not be doing justice if I don't say that, you know, many customers are very mature, very smart. You know your business more than us. But on CDPs, you do need a human copilot, and that's where, you know, partners like Infosys can come in and really help you navigate through those hurdles, right? So we can bring in learnings from other customers, ensure you don't repeat it, be contextual to what you want. I think that's really I'd like to summarize. Wonderful. Good tips for everybody.

- Sure. Thanks a lot, Emily. - Thank you. And I know you're not in the best of your mood today, but yeah-- Thank you.

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