Hi, everyone. Thank you for coming today. I know you all have a lot of products you're also interested in seeing, so we're happy you're here during our road map session. So I'm Alex Pallotta. I'm a senior product marketing manager for SAP Engagement Cloud. I'm here with Dr. Stefan Wenzel, who's our chief product officer of SAP Engagement Cloud. So what we'll be covering today where we'll be spending our time. I'm going to give a little bit of an insight into our market opportunity. Then Stefan's going to walk you through our agentic revenue engine, some of our investment priorities. You'll get to see a demo, which is great. And then we're going to pull it back to the foundational elements that play into our product. So quick disclaimer. So we do talk about forward-looking road map items here. We're not formally or informally committing to those items exactly as you see them today. So just make sure that you make purchasing decisions based off what's available in the product. With that being said, I'm really excited about everything we have to share with you. So all of you chose the market-to-lead road map session. You're probably here because you have a hand in your market-to-lead business process. You may be in marketing, you could be in sales, you could be in IT, but regardless, we're all folding into this process that is driving revenue for our business. So for the marketers in the room, you probably recognize what's on the left. This is what we call our engagement layer. So you see the channels that you activate to reach your customers. It could be mobile, web, email, SMS. You also see some of the journeys or the automations you've built to engage your customers along the way. And then, of course, you have your customer data platform that's really the foundation behind it all. So when you look to the right, you've got the enterprise foundation. This is the side of the house that usually isn't talking to that engagement layer. So this is where you have your ERP data, so your transactional revenue, your order data, your finance data, your P&Ls, your budget, your supply chain data, where your inventory and fulfillment information lives. So because these two don't necessarily work together, it's created what we call the context gap. And this is a problem for marketers. Marketers are making decisions that are potentially stalling revenue or creating leaks in your revenue and business process because they don't have access to that critical business data that's on the other side of the house. Now, it's not just a problem for your teams, it's also inhibiting AI to function like it should be, because AI requires that cross-business context to drive impact. So you're probably saying, "Well, I've already invested AI. My teams are using it, maybe from the marketing sense. They're using it to edit copy," but they're doing it potentially in silos or in ways that aren't actually accelerating revenue. So what tends to happen when marketers are working with AI, but they don't have the ERP or the enterprise side of the house, is they're optimizing for the wrong things. So you're targeting accounts with out-of-stock items. You're personalizing with sale pricing. You're cross-selling to a customer with something they've already been sold. These instances not only create a bad experience, one-off experience for your customers, it depletes their loyalty and potentially is harmful for the reputation of your business. When you do connect the ERP side of the house, you're able to connect those engagements and make sure that you have that live pricing data, that live inventory data, all purchase history that's relevant to your customers, feeding into your marketing engagements so that marketers are driving more impactful revenue. Again, AI is only as intelligent as the data that it has access to. So ensuring that those two are connected allows your agents to work better for you. So how does this all apply to market to lead? This is essentially what we say good looks like, right? So the B2Cers in the room, you're looking at the market-to-convert side of the house. My B2Bers in the room, you're looking more at the market-to-lead process. Essentially, they're saying the same thing. You're going to identify the contacts that you want to target. You're going to nurture them. You're going to personalize your engagements with them, going to analyze, make sure that you're doing it the right way, all with the end goal of either handing over your lead to sales for them to close a deal or to convert that person to a paying customer. It's all the same, and the issue is present in both cycles. Marketing signals aren't the most impactful signals to be driving every step of these business processes. It's the ERP signals. It's the order signals. It's the sales and service indicators that are really impactful to get you to every step of this business process. So what does this look like when it's a little bit broken? We've kind of showed you what the different stages are of the process, but what does it look like in function? Where is that revenue actually leaking? So I'll just call out a couple examples, but when you look at the personalized stage, we saw that 73% of buyers actively avoid irrelevant outreach. I think everyone in this room probably has something sitting in their inbox that absolutely does not resonate with what you are or what you're interested in as an end consumer or even a buyer for your business. When we move to the score and qualify stage, 49% of CSOs report that they have no agreement on what actually qualifies a lead. That means that it's time wasted on figuring out what qualifies a lead and what doesn't, versus actually driving revenue. So again, these issues compound when we add AI and agents into the mix, because they're not able to stop these leaks across your business process. They're actually going to make them larger. So this is a little bit of what we are trying to get to, what we hope that our marketing, our CX teams can get to. Right now, we are sitting very much in the automation phase. We're going from reactive communication. We're building based off of rules. We're manually pulling in workflows that we've probably been doing for a while, right? And we're also focused on task execution. When you get to the point of autonomy, you have a team of agents that you can trust because they have access to every piece of the data that they need access to, to work autonomously in your favor. So that means outreach is proactive. You have intelligence at every step of the way. Decisions are much easier. They're informing you of the decisions you need to make across your teams, and you're really, truly optimizing for revenue at every stage. So this is a little bit of a preview of the agentic work that we have built, the groundwork we've laid, and I'm going to pass it over to Stefan to show you a little bit more. Thank you very much, Alex. Okay, you've seen basically the flywheel that Alex introduced. Now let's look at it, how it works the agentic way. So we've connected the workflows across the entire revenue pipeline with agents and assistants. So for B2C, it's primarily markets to convert, and we're starting here with the identify and enrich phase. So the Campaign Assistant here basically helps you really translate that brief into an executable campaign. It first identifies and helps you identify the opportunities. It helps you translate basically the brief in what you need to set. And then with the audience identification agent, it really taps into the rich data universe of SAP, looking at behavioral data, looking at CDP data, looking at loyalty data to define the right segment for the campaign. The content assistant then helps you craft the actual assets that are needed, from the copy you need, from optimizing and personalizing the visual assets, from placing the right products or the right product recommendation algorithms for your campaign, and making that then fit To the respective channel. In the analyze and convert phase then, we have the Campaign Assistant support you as the campaign runs, as the journey runs. It analyzes the journey as we go with the Campaign Insights Agent, always have an eye on what's happening, how the performance is going, and feeding that intelligence back so that we can optimize and close the loop. So if we look at the B2B motion, it's going similar, but it goes essentially further. So in B2B, where it often breaks is at the score and qualify phase. So there, the Campaign Orchestration Agent really helps to assess whether a contact or lead has progressed and is qualified enough, and then we're basically handing it over and seamlessly working together with an assistant on the sales side. In this case, this is the Deal Qualification Assistant, and there, these agents work together to make that revenue leak and that seamless handover fit. Sometimes it's about quality. Another time, it's about coverage in a pipeline. And this is where these agents between marketing and sales really can work together to make a difference. Let's look at that a little bit more in detail. So I talk about the Campaign Assistant. The Campaign Assistant is really the companion for the campaign manager. Very often, compiling a campaign requires a lot of specialized roles and tasks, even down to departments. The Campaign Assistant really helps you as a campaign manager make that task together with that companion and empowers you to take back control over that entire process. So it starts with the Campaign Orchestration Agent that translates your campaign strategy into basically a plan how you can make that happen in the system. The Campaign Insights Agent looks at existing campaigns and tells you what works and what doesn't work, which is an important information you can take in crafting a new campaign. The Audience Identification Agent basically creates segments, but it doesn't only create segments of marketing data, but again, working together with BDC, with CDP, and loyalty system really taps into the entire universe of SAP. And this is a true unique value that we can bring here because typically that would cost data analysts hours of pulling reports on and putting that together. The Campaign Configuration Agent then translates these elements into an executable program, essentially. And this can be as complex as having dozens and dozens of nodes and branches and something that in parts often is an IT project to set this up. And this agent can help you make that happen. And that's not only based on your input, but the Configuration Agent has access to what we call a tactic library in the back. So that's a library with proven patterns the agent has access and can compose to a real campaign in the end. Content is king for every campaign. So this is where the content assistant really comes into picture. The Copy Personalization Agent helps you generate and fine-tune the copy for all elements of a campaign, whether that's the body, whether that's a subject line or a preview text. But not only that, it also places the right tokens throughout basically your templates and connects these tokens obviously with the data. But it can even go further. It can introduce personalization aspects around showing an entire blog or removing an entire element of a template. The Visual Asset Personalization Agent can actually create entire assets, but what it can also do, it can take your product imagery, for example, and adjust and personalize those to this very specific campaign. The Product Recommendation Agent sits on top of an entire suite of recommendation algorithms. So depending on your campaign, this agent suggests to you which algorithm is the right one. And this might not even be one algorithm for an entire campaign, but even the algorithm can basically be a personalized element depending on the contact that actually receives this content. And then the channel coordination content asset translates this to the very specifics of every channel, whether that's an RCS message, SMS, or email campaign. Every campaign basically or every channel has their respective specifics we need to cater for and make ready. Now let's see some of that in action. That was a bit quick. We are at a company, Apex Athletics, producing running shoes, and I'm a B2B marketer in that case. And I start my day typically with crawling data, pulling reports, what I should do next to really improve the pipeline and drive revenue. Now that. Here we go. But this time, it's not really crawling data, it's basically simply a prompt that I can give. So I'm asking Joule, basically, I need the highest margin campaign opportunity available right now and asking what I should be running. So here, the assistant helps me and crawls through a lot of available data that this assistant has access to. So this includes looking at inventory data. It looks at Google Analytics data that we've connected to the Engagement Cloud. It also looks at loyalty signals. It looks at purchase intent that is coming from the Commerce Cloud and brings all of that together to recommend me basically, hey, we probably should promote our new shoe, which is called Lightning AC. We have 50,000 units ready to ship, and basically, I'm selling both through a direct-to-consumer channel as well as through a B2B channel and promoting me-- like telling me basically, I should ideally create two campaigns, one direct-to-consumer campaign and one B2B campaign. So let us start with the B2B campaign first. The next step is then translating this idea into a real brief, a brief that is structured, that I can review, that then can be implemented in my Engagement Cloud. So it's created that brief for me. I'm going through it. Okay, it's the product line, Lightning AC. It has my target audience identified. It's retail accounts that I want to target to. It has a campaign goal defined that I then can measure. Its leads that I want to create for sales to follow up. It has identified the channels. It's like an email campaign with a companion lead ad on LinkedIn and basically, a lot of other specifics that are relevant for execution. So this looks good. I want to have that also personalized. So I just don't want to have a blast campaign. I want to really have a tailored, personalized campaign and asking Joule basically to make proposals on how I could drive that personalization. So it comes up with three proposals here. The one is an on-behalf-sender personalization. What does that mean? So the campaign doesn't go out from a generic email address, but it basically goes out from the respective seller that is responsible for the retail account. How is that made possible? Because we are operating off that SAP data model where we have that assignment of a sales rep also accessible in the Engagement Cloud. And I want to include not only that, we are here in B2B, so I want to remind the customer what the customer's order history was, what the details were, maybe even down to the point that they see their own discount scheme that they've been on. And again, of course, we want to create some urgency, so that's why we always show the inventory that is left for the customer to order. And on top of that, we have a trade fund that we can add to that. And that trade fund basically is available to those retail stores who have a lot of loyal customers. Again, so here are multiple things coming together. Promotion, trade funds, loyalty data to make that campaign really personalized. So personalization in that sense, and this is the key message here, is not only about a token and an email replacing a text with the first name, but it's really making that entire experience truly personalized with the data that we have at hand. Okay, this looks great. And, yeah, the trade fund idea we definitely should include because I think this really makes an impact. So Joule then starts to build out that campaign. But of course, we want to look at it. So how does it look and what is the result? So we're jumping over into the Engagement Cloud. First look at the automation program. It's a relatively straightforward one. So we have our segment that defines who's going into it. We have that eligibility check for the trade fund. We have then two paths. We have our emails going out, and then we're basically landing on a page with a form that can capture the lead. Yeah. And then we create that lead on the Sales Cloud. Okay, that looks fine for now. Let's check out that email. Okay, that email is personalized. We have our running shoe here. We have all the data elements prepared that we want to have in there. But yeah, it's a little bit slim still, and I think we could give these retailers a little bit more flesh to the bone, so to speak. So what I'm missing here is that promotional kit to that new shoe that we should give that retailer. So I'm asking Joule to include that block. So this promotional kit, these are blocks that we have prepared, basically, but I'm asking Joule basically to simply include that here, and that's what it does. And this is another, I think, important aspect I want to double-click a little bit later on, on how we build these agents and make them truly work. So it's not just like a large language model that operates on top of APIs, but it's really deep capabilities that we've built into the platform throughout. So here, for example, this entire content creation, whether that's visuals or copy, is built on top of what we call the AI-assisted content composer. So that's available and that's a functionality and a set of tools that is available to the traditional UI. So you can go there as a marketer and use that tool to optimize, tweak your content in an interactive UI mode. But it's the same tools the agent is using basically to produce this content. And this is like tailor-made AI capabilities in the platform to ensure really, like as an example, if you create a visual with a person that has jewelry so that we have five fingers, so that the shading is right, so that people don't-- like when you have models that they are standing on the Earth and not flying. So this has been really hard work we've been doing together with Google, with our partnership with Google Gemini, especially on that visual asset generation, but also on other elements to make this content composer actually happen. So we have our promotional kit in here. So it looks great. I approve and basically I have my ready campaign now. And yeah, so this would be the landing page. Actually, just as a side note, we're reworking our entire landing page and forms capability in the platform. This will start rolling out Q4 onwards. I think super interesting for both B2B and B2C marketers, and we're making that omnichannel from the get-go. So we will also have these forms and capability available, for example, on mobile and other channels going forward. Okay. So far to the demo, around the market to lead. If we switch back to the presentation, I wanted to show you the next step as well. So we've created that lead now in the Sales Cloud, and what we're working on more towards 2027 to take engagement even one step further. So what we've seen now was the job of a marketer, but engagement is relevant for the entire process, for the entire lifecycle of the customer. And now we're here. I'm Sam, I'm a seller, I'm in the Sales Cloud, and what I'm seeing here are basically my leads. And I'm seeing exactly those leads for this Lightning AC launch campaign that we've just created. And imagine I simply want to qualify those leads further. I don't have the time to call them up. can't handle this load, so I want to further qualify them who's really interested to purchase. And I basically open Joule in my context as a seller. I have no idea about Engagement Cloud. I ask Joule basically to help me prepare an outreach to make an appointment with me as a seller. So Joule is preparing that email. It's basically identifying the contacts and sending out that outreach. And it even goes further. So if I go into that specific lead, I also see this outreach in my timeline. And maybe there's even beyond that one outreach, there are further journeys that might be interesting to help nurture that lead and qualify it further. So I can check with Joule, "Hey, is there some multistep journey available?" And I can look that up. I have a proposal. I have Joule recommend me, include the right contacts, and I have basically the full power of an Engagement Cloud available in the sales context to a totally different persona and help with my engagement process now to, yeah, to extend that into the sales process. And this is something that we're envisioning to roll out beginning of 2027, stepwise, and then from sales, also looking into bringing that into further scenarios, be it service, for example. Okay. So these have been some tangible examples on how we want to bring AI to life and how we're doing this this year and where we're heading into next year. Now let's look a little bit into the investment priorities. So what I've just shown you here basically have been the assistants around Campaign Assistant and Content Assistant. In 2027, we basically want to deepen and broaden it at the same time. So on that initial phase of creating a campaign, we want to grow the entire assistant scenario to not only help you create a campaign from an existing marketing strategy, but actually really help you create that entire strategy itself. That then also includes identifying the right goals that you need to set, identifying the right attribution models, and also having the ability to work across many campaigns and many automation programs attached to a single strategy. So very often in reality is, for example, you have the goal to increase your basket value, or you have a strategy to increase repeat purchases. So these are long-running strategies and cannot be expressed by a single campaign. You have many campaigns and many programs attached to that. So this will help you tie that together, build out that strategy, and then basically assign and create campaigns with it. We're further investing also into agents that help you to do these things smarter. So one element is the Conversational Messaging Agent. We truly believe this entire conversational approach, whether that's on WhatsApp or RCS or even email down the road, is really a very powerful pattern we should look at much more in marketing. So that's where we are building an agent to help you build these conversational experiences and help route consumers through that journey. The Channel Affinity Agent then helps you basically to identify the right channel, not for a campaign, but in that very specific moment of an individual contact in a specific journey. On the Personalization Agent, on the personalization side, one of the biggest requests we received is on brand governance. So many customers really struggle with having many brands introducing rebrandings and then creating content at scale that complies with the brand, with the brand voice of tone, but even down to the point, having then the right brand links being put into the campaign is a super cumbersome process. So that will be a big focus of our investment. And also we are looking to make the entire process of localization more powerful so that you can manage that. Quick side note there, we are also rolling out a new localization capability that scales better with a large number of languages, and then the agent helps you to create those. And then, on the analyze and convert side, where basically you've seen the Campaign Insights Agent, the next step for us to making that insight more powerful by giving it autonomy. So we'll roll out a Monitoring Agent that basically monitors the campaign autonomously and reaches out to the marketer when things are going out of thresholds or when there's, let's say, a 10% drop all of a sudden in clicks, so that you don't have to do that monitoring by yourself. On the B2B side, we're basically investing exactly in what you have seen, the entire scoring capability gets more agentic. So we don't want to rely on static rules and counting points, but really want to have that entire lifecycle management of a lead more intelligent. And then bringing what I've shown to you, the sales engagement, the capabilities, and the power of Engagement Cloud directly into the sales process so that we have a seamless engagement across the entire revenue pipeline also for B2B. Okay, switching gears to the foundational capabilities. So AI can only be as good, and I think I made that point on multiple occasions, basically, as the platform is underneath. So on our first column here in AI and analytics, we have invested this year a lot into making analytics and data available in the platform, and also to AI. For example, the AI-assisted report builder has been rolled out already in Q2. I think the majority of our customers is using it by now. The adoption really has been great. But we've also been pushing forward the recommendation center, which is really a super-powerful collection of recommendation capabilities, much more flexible now. And this only enables us to build these agents on top. The same is true for data and integrations. We're vastly expanding our reach into the entire SAP universe, whether that's connections into CDP, or even investing into capabilities like universal schema builder, which allows you basically to connect any database in a very scalable way. Content and channels. Again, agents are only as powerful as the surface area they can act on. We have already one of the most comprehensive channel portfolios in the market, and we are heavily investing into that, making that more broader. RCS is one of those investment areas. We also reworked our entire mobile portfolio with a brand-new SDK that makes it much more easier to build experiences across mobile apps and web. So we have one SDK that basically goes across both channels, which is great. And one of those channels that comes with this SDK is what we call embedded messaging. Think of it as an inbox solution that can live on your storefront or in your store app. It's basically a message channel that does not require consent because the user basically goes there to read the channel, so it's not intrusive in that sense. And more to come. Yeah, I already talked about the recommendation center, something that we have been rolling out in Q3, with our last release. If you haven't done so, please check it out. I think it's a very powerful capability that gives you a lot of new options. The AI-assisted report builder is now covering a lot of new channels with our last release, and also introduced charting capabilities, so you can create dashboards ad hoc, and have them even visualized now. And now we're looking into enhancements to our data ecosystem. Yeah. So I think the theme of the day has probably been that you need a strong data foundation to be able to do all these agentic things, right? So these innovations and priority areas is really how we're able to do that. So we have engagement events. So that is our engagement event service that helps you capture, manage, and action your external events all in one place. So we recently released, and what you see on the screen is our contact retry and our retention limit enforcement updates. Those were in our recent release, essentially letting you manage the number of contacts that come through, and then if contacts come through multiple times, it's able to capture them and not miss any of those interactions. So what's coming is our CRUD API integrator connector. So essentially it's supporting that programmatic creation and management of your external events. And then you also have attachment support. So when you do want to send email communication based off an event that comes in, you can have an attachment to really enrich that communication to your customers. Our SAP ecosystem is how we are connecting into the rest of SAP in the business. So we've had a lot of innovation here recently, and a lot of what you saw in the demo that Stefan just shared is around our SAP Sales and Service Cloud connector that just became available to early adopters in Q3. Within that, we have B2B lead handover and our master data integration. Both of those essentially ensure that your marketing and sales teams are working off of the same data. And when a lead goes through enough engagement on the marketing side to be handed over to sales, that happens automatically now, carrying all of that engagement information from Engagement Cloud into Sales Cloud. So your marketing, your sales, your service teams are all working off the same customer and account foundation. So when we look to what our updates related to business areas in Customer Data Cloud and then Customer CDP, when you look at CDC, that is ensuring that when your contact is assigned to multiple business areas, it carries over that consent information that is so essential. And then with CDP, you're now able to assign multiple business areas to a single contact. So if there's different brands or regions that your companies are managing, they can have multiple of those options assigned to the account or the contact. Then, of course, SAP Business Data Cloud, we're really excited to have that bidirectional, zero-copy data integration into SAP BDC with our data products to be able to pull in all of that operational context, that enterprise foundation that we were talking about earlier, all that coming from BDC directly into Engagement Cloud to drive those marketing engagements. So now that we've got the data, this is how your customers are going to see the result of it. So all of our channel innovations are really exciting, and we're excited about embedded messaging for both web and mobile. So this will essentially create an interface for your consumers to receive messages even when they're not online, so they can access it when they want to on the web and mobile apps. And then it also does not require opt-in necessarily, and then all of that data factors into campaign analytics, so you're able to grade the performance of that as a channel. And then we have Rich Communication Services or RCS. So this is really that modern text messaging experience that is powered by Google. So your customers, all within a text message, can get rich, brand-approved company cards. They can look through products. They can essentially search, browse, and even buy all within a text message conversation that looks like an experience you would have created on web or on your mobile app. So it's a really, really cool innovation. We're bringing it to Android and iOS, and that is now in early adopter. So that's it for our channel innovations. I think we've got a couple more things, then I'm going to pass it over to Stefan. Thank you, Alex. So lifecycle management is an interesting capability where we're introducing to Engagement Cloud. It basically allows you to create segments, not by the pure definition of individual characteristics, but basically a lifecycle with multiple stages, and it allows you to have a lot of flexibility with that. So you can create lifecycles, let's say, for product affinity, for multiple product affinities. So if you have multiple product groups, so if someone interested in a car, basically, and basically a totally separate group and have these lifecycles set up in parallel. But a lifecycle could equally be a basic lead management process that you reflect or maybe even more importantly, synchronize your lifecycle management with the loyalty solution in the background and have your tiering reflected here on the Engagement Cloud and synchronized with that. And you're very flexible around setting up these rules, and we'll add more capabilities as we move forward. And these individual stages in the lifecycle management are then available throughout the entire Engagement Cloud for further usage, whether that's in automation or personalization or even down in audience reporting. So you can analyze basically how basically different stages in your lifecycle are doing. So this is, I think, super interesting to support various different industry use cases. So then on our loyalty side, of course, we're super excited to introduce dynamic loyalty orchestration within SAP Customer Loyalty Management. So first of all, yeah, loyalty programs only work if customers feel rewarded at the right moment. So, rather than blanket discounts, you can deliver targeted, personalized promotions to specific customer segments based on their behavior and profile. That means higher redemption rates and campaigns that actually move the needle on engagement. The second piece is gamifying loyalty. So we're here introducing basically, capabilities like configurable stamp cards and challenges and quests, but also allowing you to integrate third-party game integrations that reward customers and that really drive repeat purchases. And the last one are loyalty engagements. Think of any loyalty event, like a tier upgrade or a redemption that can trigger an event and that helps you keep all your connected landscape in sync. So customer loyalty management then seamlessly works together with the Engagement Cloud or enriches your profile, basically on the CDP or triggers a further process down on the services side. So engagement event is that super flexible concept that helps you bring the power of loyalty management into your entire landscape. Thank you.