Speaker 0: Alright. Let’s go ahead and get started. Hello, everyone, and welcome. My name is Andrew Lee, and I’m a product marketing manager here at Salesforce focusing on all things Salesforce Marketing Cloud and Customer Data Platform or CDP. Um, so excited to be joining you all here on day one of MAR Dreamin’. It’s my first time ever attending, so really happy, um, to be here with all of you. And, uh, today, we’ll be taking a look at how to supercharge all of your data driven experiences by unifying data to build a single source of truth with CDP that can then power personalization at scale across all of your customer interactions, increasing speed to value and reducing costs to maximize ROI. Um, but before we get started, if you’ve ever been to a Salesforce, um, talk or presentation before, you’ll recognize, um, this slide, everyone’s favorite slide, the forward looking statement. So just a friendly reminder to customers that, um, you should base all of your purchasing decisions based off products and services that are generally available in the market today. And with that, super excited to introduce my fellow speakers with me here today. We have Jenny Smith and Jill Katz, two of our incredible success architects who will be helping me demystify the CDP a little bit, um, today. And a quick peek at today’s agenda. We’ll kick things off by talking about some of the trends in the market that we’re seeing that are changing the way that people are thinking about data and personalization, um, and how Customer Data Platform can solve for some of the challenges that folks are facing. Um, We’ll take a look at some of our amazing trailblazing customers, look at some case studies, um, and take a look at how they’re using CDP to uplevel, um, their data capabilities, um, and personalize at scale. And then we’ll do, um, a deep dive kinda look under the hood of CDP and level set on some of the core product capabilities, and then we’ll bring some of these kit concepts to life with a product demo. So let’s go ahead and dive right in, and let’s talk about the importance of being data first and how CDP fits into all of this. Um, and I’ll start by saying, I think we can all agree that we’re in a new world. Right? Marketers need to make every single moment count, especially these days when we have tighter budgets and headcount shortages. Um, and we’ve been listening to you, our customers, and our trailblazers to really understand, um, you know, what’s top of mind for marketers today, and we’ve we’ve teased out three key themes. So the first one is that, um, you know, marketers wanna increase productivity and efficiency while still being able to engage with customers at the right time and on the right channel. They wanna reduce acquisition costs and make the most of every marketing dollar. Um, and lastly, um, marketers wanna know how to drive more business value using the data and resources that they already have. But easier said than done. Marketers are more disconnected than ever from customers today, um, for for a variety of reasons. So customer data is exploding and it’s everywhere, but that data often sits in silos and can be difficult to use. And, additionally, we’ve all heard about third party cookies going away, and cookies have historically been, you know, a primary tool for marketers. Um, and recently, we’ve seen Apple and now Google, you know, starting to allow users to opt out of, you know, app, email, and device tracking as well. Um, so all this being said, customer expectations are are increasing and are higher than ever. Um, but at the end of the day, um, customers really wanna be more than just ones and zeros. They wanna be more than bits and bytes. They wanna be more than just data points. They wanna engage on their terms, and they wanna engage in real time. So what does this mean for all of us as marketers? It really means, um, moving beyond transactions and prioritizing relationships and connecting with customers in new ways. Um, we recently did a study. Our Salesforce research shows that 86% of customers say that an emotional connection is key to winning their business and keeping their business. But on the flip side, only 33% of marketers are fully satisfied with their ability to create more relevant experiences with the data that they have on their customers. And we’re seeing that if brands can’t figure this out and provide the experiences that customers have come to expect, they can simply leave and they can switch to a competitor with just, you know, in a split second with one click. So we have to think about how, um, we’re delivering these customer experiences in completely new ways. Um, and that’s why if if any of you were able to attend, um, Dreamforce with us, uh, a couple months back, we’re thrilled to introduce Salesforce Genie, the real time platform for customer magic. And this is the most significant technology shift to our platform over the past twenty or so years, and we’ve integrated it natively into the Salesforce platform so you can treat your customers like people and not just those ones and zeros like we talked about before. Um, so Salesforce Genie really takes the customer 360 and adds real time data from the Customer Data Platform, allowing you to capture and ingest data from anywhere and at high scale. So let’s take a second to get acquainted with some of CDP’s main functions. So with Customer Data Platform or CDP powered by Genie, you can automatically automatically connect all of your data across any source to build unified customer profiles. So you can reduce your integration and maintenance costs by ingesting all of that customer data from both inside and outside of the Salesforce ecosystem to reconcile identity and gain a complete picture of your individuals and and your audiences. Um, the second pillar is really building intelligent audiences faster. Um, and what I mean by that is that, um, from a single user friendly interface, CDP allows you to own your audience building, analyze, and discover new segments, um, engage with all of your customers with relevancy and and in real time, right, all while remaining cost efficient, um, across all of your different channels, whether it be email, mobile, you know, ads, uh, or or across the web as well. Um, you can also act on real time data and insights. So with CDP, you can use those unified profiles that you create to derive what we like to call, um, calculated insights to understand key metrics like customer lifetime value, propensity to churn, uh, and much more. And you can also configure business rules that allow CDP to respond to, um, real time event data and triggers so that you can, you know, use these signals to kick off a journey or an email send or, you know, initiate a workflow in, uh, a platform that might be downstream of CDP. Um, and lastly, um, one of the more, uh, customer facing or visible pieces of of CDP is you can extend your data with an open ecosystem. So from within CDP, you can provision all of that rich first party data to, um, you know, different strategic advertising partners like Google or Meta, as well as trusted partners in the Salesforce App Exchange so that you can unlock, you know, additional or more powerful data use cases like profile enrichment, uh, and activation. So making it easier to really understand your customers and drive that personalization at scale. Um, and it’s also an especially exciting time in our CDP space, and you might have seen, um, some of these announcements coming out of Dreamforce as well. But we’re continuing to lay the groundwork for deeper connections and integrations from CDP to both B2C and B2B platforms. So I wanted to quickly highlight some of the new innovations coming out of the Marketing Cloud Account Engagement side of the house that will allow, um, B2B marketing and sales teams to work together to grow, uh, pipe pipeline and drive efficiency and reduce costs, um, while using, you know, flexible and scalable APIs. So our Account Engagement API enhancements are, um, enabling new integrations with CDP as well as external segmentation tools. Um, so now marketers can create and share segments with CDP, leverage a richer set of account attributes for personalization from, um, you know, key objects like prospect, visitor activity, list membership, prospect account, and more. And And then you’re able to activate, um, engagement across channels using Salesforce and third party platforms. So now that we’ve set the stage a little bit, um, we’re gonna go bring some of these concepts to life a little bit more and tell you about a few customers who have used and are using Customer Data Platform to solve their complex business challenges and drive impact across their org. So with that, I’ll hand the reins over to Jill.

Speaker 1: Great. Thanks, Andrew. We’re going to be telling you about a few different exciting customers today. The first one of those is Casey’s. Casey’s is the third largest chain of convenience stores in The United States. They have over 2,400 stores across 16 states. And most of them are located in the Southern And Midwestern US. One of Casey’s main goals when they were starting to work with the Customer Data Platform was to increase customer loyalty and drive repeat purchases in order to grow their top line revenue. In order to meet these goals, they needed to make a shift from mass marketing efforts to a more personalized experience for their guests. Using the Customer Data Platform, Casey’s combined large sets of customer and transactional data from Marketing Cloud and from Amazon S3. This gave Casey’s a much more holistic view of their guests and enabled them to create and activate more targeted audience segments. Here are just a few of the examples of how they were able to drive personalization at scale. First, they were able to use this combined dataset to create much more tailored product based segments. Rather than sending the same message to every guest, Casey’s was able to create segments based on specific products that their guests had purchased in the past. This was a big shift from what they had been doing previously, sending the same message to every guest. Now they were able to send much more personalized communication based on their previous purchase behavior. The Customer Data Platform also enabled Casey’s to target guests in order to drive repeat orders. For example, if a customer typically ordered a pizza on Thursday evenings and this week they didn’t, Casey’s was able to recognize that and send a reminder message via an app push message that included a promo code within an hour of the missed window encouraging that customer to place the order. So those are two great examples of how they were able to use data to drive personalized experience to their guests in order to drive the behavior that they were looking for. And in addition to these enhanced targeting capabilities, Casey’s also realized operational efficiencies that were great for their business. Using the robust segmentation tools in the CDP, Casey’s was able to create segments 30 times faster than their old manual processes. This was a huge win for their team and a huge time saver. So now that we’ve heard about Casey’s, let’s shift our focus a little bit to digital banking and talk about Inter, a digital banking company based in Brazil. Okay. Great. So Inter is one of the first fully digital banks in Brazil. Um, they offer many different financial products including checking, personal, um, and corporate accounts. Um, they offer loans and credit cards, investment and insurance services, and most recently, they’ve actually started to offer non financial products as well. Um, one of their main challenges before implementing the CDP was ensuring effectiveness at scale. As a growing company, it was imperative that they sent the right marketing message to the right customer to achieve the best ROI for their business. The way that their team was structured, they were structured into six different business units that had separate teams and separate resources. While this allowed them to grow quite fast within their individual business units, it also resulted in product silos and data silos, which led to them sending excessive communications to the same customer because they weren’t speaking to each other. They also relied on a lot of manual processes to manage data from each of the individual business units. With the Customer Data Platform, Inter is now able to ingest data from six consolidated data sources, including Sales Cloud, Service Cloud, Marketing Cloud, Amazon S3, and from their website and mobile app using the SDK. This allowed them to consume over 103 different data streams and unify that data based on match rules using identity resolution in the CDP. And we’ll talk more about how identity resolution works, um, later in the session. By unifying these individual datasets through identity resolution, Inter’s teams can now have a single customer view of their customers. Rather than each team looking at their customer data differently, they have one single view now that they could all use to drive, um, their efforts for for marketing. The CDP also enabled them to create engagement scores based on opens and clicks across the different business units to determine the best moment to have an impact on each unique customer. They’re now able to reach each customer with personalized product offers at the right time. Inter has also leveraged calculated insights extensively within the CDP to create product affinity scores so that it could use these calculated insights within segmentation. Again, we’ll talk more about this a little bit later. Once the segments are built and activated to marketing and journeys, Inter can use Journey Builder to send relevant communications to customers with the right product at the moment that matters most to each individual customer. Calculated insights provide the desired granularity and frequency that they need. And since it’s an algorithm built into the platform, it’s real time. They engage the customer with the subject that matters most at the specific moment. For example, if a customer’s interest changes, so will the algorithm, um, as that runs daily. This allowed them to migrate from more of a product centric approach to a customer and data driven approach, ensuring that the most relevant up to date information is used for every customer interaction. Since the initial pilot of, um, Customer Data Platform in April 2022, Inter has reported a 20x more return on investment on their campaigns, which is huge for their business. They’re now sending less communications and more relevant and targeted campaigns to their customers. This all also contributed to an impressive 35 times improvement on conversion rates. So as you can see, you know, the personalization had had a lot of impact on their their KPIs for marketing and their you know, this is just the beginning for them. The effectiveness also had, um, a positive impact on the team’s bandwidth. So it’s not just allowing them to be more effective in targeting, but their team is also able to be more efficient. The algorithms built into the CDP eliminated the need for daily meetings in which teams were meeting to analyze segment performance and usage across the business. This is now done automatically in the platform and the team has more time to focus on more strategic and creative work. Um, and it’s been reported that they’ve gotten back at least an hour and a half per week per individual. So finally, now that we’ve heard about Inter, let’s let’s shift our focus, uh, one more time to the education space and talk about, um, a company called School Specialty. Um, they’re a really interesting and a great example of a a customer using technology to approach both B2B and B2C business challenges. So if you’re not familiar with School Specialty, um, they’re the leading provider of educational products to educators across North America. Uh, they provide supplies to schools and teachers, and they have a portfolio of products that includes everything from learning environments to furniture and equipment, safety and security products, educational technology, school, and office supplies. So you can see it really you know, runs the gamut of of things that they offer to both schools and individual teachers. Um, they have, you know, stakeholders across the education system, including teachers, administrative assistants, um, administrators, and including, um, entire school district leaders. So, um, you know, it’s it’s really across the board and since they provide different solutions to all of these different customers with different needs, it’s especially important that they provide the right message to the right audience. So if you think about it, um, you know, for for a company like this, if they’re providing something to a district head of services, they should be getting a very different message than an art teacher in a school, um, as their needs are very different. Or a first grade teacher who is teaching all different subjects to their students should be getting, um, different messages and different product recommendations than a tenth grade algebra teacher. So there’s a lot of different ways to slice this, but as you can see, the needs are are very different across the board. Um, Adam Halfman, who’s their director of program management at School Specialty, is passionate about establishing a data driven culture at

Speaker 0: the

Speaker 1: company. Um, historically, School Specialty has been a print catalog business, but they were looking to shift to a more data driven approach to marketing. Um, Adam had said that they were sitting on a gold mine of first party data across 13 different sources, and Adam sought to unify this data and establish a unified customer profile, which we’ve talked about, um, with some of the other businesses, but it’s really interesting how they’ve taken that approach to to their business. So since implementing a Customer Data Platform, School Specialty has uploaded over 30,000,000 records into CDP and they’re using identity resolution to unify these, um, within the platform. They’re also seeing a 67% consolidation rate of their individual profiles into unified profiles in the platform. And now that all these customer profiles are all in one platform, Adam can activate the right message to the right audience in all of his marketing channels. More so with the combination of the Customer Data Platform and, um, Interaction Studio, he can see channel variations at a contact level and at the account level, allowing his sales reps to have much more strategic conversations with their accounts. Looking forward, um, this is really just the beginning for School Specialty. Um, Adam’s ultimate goal is to build personalized omnichannel experiences across Sales, Service, and Marketing Clouds. And delivering this experience to with our customers and students is at the heart of everything they do. Um, so it’s really exciting how much they’ve been able to do using the CDP, and and we can’t wait to see, um, what else they do within the platform. So now that we’ve heard about three very different types of customers who who are using the Customer Data Platform to drive business results, let’s dive a little bit deeper into the specific features of the platform as well as as a demo. So with that, I will pass it over.

Speaker 0: Awesome. Um, yeah. Like Jill said, uh, I know we introduced some of those, uh, high level CDP capabilities at the beginning of the session today, but, um, now I’m excited to hand things over to Jenny to do a little bit of a deeper dive. So take things away. Uh, take it away, Jenny.

Speaker 2: Thanks, Andrew. Um, so as Andrew mentioned earlier, our Customer Data Platform powered by Genie is designed to bring magic to every moment the single source of truth. Um, in today’s demo, we’re going to just really scratch the surface of CDP and and talk about connect, harmonize, and unify. Uh, there’s much more to this if we had more time. But, uh, to truly know your customer and develop that single source of truth, you must be able to connect your data across those multiple data sources. We saw that with all three of our customer stories. So today with our Customer Data Platform, you can connect your internal data within Salesforce from sales, service, commerce, marketing, and personalization, as well as external data through MuleSoft. You can also bring in data through Google Cloud Storage and Amazon S3, and you can leverage the unified SDKs for, um, for mobile apps and websites for faster time to value and to reduce time spent on custom development. Once all of your data is in CDP, we harmonize from all of those different data sources to a common business friendly data model to then resolve the identities to build unified profiles, allowing you to optimize your high value segments and power personalization. So let’s take a look at how Connect, Harmonize, and Unify actually look inside the CDP platform. We’re gonna do a quick transition here. Alright. So here we see our Customer Data Platform. Customer Data Platform is part of our, you know, overall Marketing Cloud umbrella, but you can see here it it looks a lot like our Salesforce CRM because it’s built on a Salesforce CRM platform. We are going to navigate to data streams and take a look at some of our our different streams that we have in here. So we can see we have our Salesforce connectors, the CRM, Marketing Cloud, and here, Interaction Studio, which is now known as personalization. We can also have Commerce in here. I don’t happen to have one in this particular list. And then we have our, um, ingestion API as well as Amazon S3 and Google Cloud Storage. So the API for Account Engagement that Andrew talked about at the top of the presentation would come in, uh, looking like this ingestion API here. And then finally, we have our SDKs for our web and mobile apps bringing in some behavioral events here. So let’s take a closer look at a couple of these. Um, first, we have this all subscribers data stream. This is coming from Marketing Cloud as a data extension table in Marketing Cloud. It could be a a file from S3 as well. It’s just a just a regular table, if you will. So this particular data stream is mapped to four standard data model objects over here. You can also see how many fields are mapped. We don’t have to map all of the fields that are coming in, um, many people do, uh, but if there’s something that doesn’t make sense for your particular use case, you can hold off on mapping that, come back and map it later. You can see we have a list of everything that’s being brought in. We have a field noted as the primary key for this table that we’re bringing in, and there are some formula fields that have been created either by the system or by creating an actual custom field when you are bringing in that data source. Typically, you’re able to go in and and add source fields. For example, if your table gets updated or add additional formula fields in this particular environment, I don’t have those permissions, but those are available to you. So let’s take a closer look at the mappings. This will take just a moment to load. It has a lot of thinking to do here. Alright. So what we see here as this continues to load is that we have our data stream on the left hand side that we’re bringing in, and then we have our data model objects on the right hand side. We can look and grab more objects to map to by clicking on this pencil button and searching through the available objects. But for now, we’re just gonna take a look at what we’ve already mapped to. So we’ve got contact point address, contact point email, contact point phone, and individual. Looking at some of these fields as part of this harmonization, we’re mapping DOB from our from our data stream to birth date on the individual record. And then here for email address, we have email, no spaces, no underscores, address to email address in our object as well. So here we have one data stream mapped to multiple data model objects. Let’s take a look at another data stream that has similar information about our individuals or customers coming from CRM. We have our contacts. So again, here, we will see that a list of all of the possible fields coming from CRM. There are scores of them, uh, available to us, and here we’re we’re mapping very few. In this case, we’re mapping to five different data model objects. Four of them are standard account contact, contact point email, individual and party identification. We do have a custom data model object that we’re mapping to as well. So you can customize the data model as you’d like and what makes sense for your business. So let’s take a look at the mappings here. And this one takes just a moment longer with all of those fields coming in from our contact object. Alright. So again, we see that we have on the right here or I’m sorry. On the left, we have our data stream coming in. We have a few of these mapped, but not all of them. We’re mapping to several different data objects here. We can see our custom data model object, and we’ve added custom fields here. Another option is to add a custom field just to a standard data model object. So maybe most of the information is covered by individual, for example, but there may be a few extra fields in there that that you want to add, and you can see there are some on individual that have been added as custom. Uh, so that is a possibility as well to customize the data model object to your business’s needs. Uh, let’s take a look at birth date again. So this time, our birth date field is birth date with no underscores or spaces. And, again, instead of DOB mapping the birth date, we’re mapping birth date to birth date. And then within our data model object, we’ll have just one field to grab to cover all of that and not have to remember the nuances of the different field names. And then for email address, here we have email mapping to email address instead of that email address as all one word mapping to email address. So this is what we really mean by harmonizing everything in our data model. What that allows us to do then is is take that look and and take these records, again, different data streams mapping to the same data model objects. Now we need to bring them together and and tie those records together. So that’s done with identity resolution. So we’ll slip switch over to identity resolution here. What you’ll see here is that we do have more than one identity resolution graph available to us. So in this particular environment, these identity resolution rule sets are very, very similar. So our consolidation rate is the same, but this allows you to play a little bit with the match rules to determine what’s going to work best for your business, what gives you the the consolidation rate that you’re looking for while balancing, you know, the not consolidating too much. Like, there there is a sweet spot that you wanna find, so having more than one helps you kind of play with that a little bit. So let’s take a closer look at this. As you are looking at this, again, I have to beg your pardon here as this is a demo environment. This particular set of match rules is one that I would actually never recommend for a business, um, because there are several here where we’re doing or statements. But I think it illustrates the flexibility of what you’re able to do. So let’s take a look at that. So here we’re saying if they have an exact email match or their phone number is an exact email match or their address is an exact match, then unify those profiles. Now in reality, we wouldn’t wanna do that because Jill and I could have the same address, for example, but we are definitely different people. Um, this rule here, the fourth one down is a little closer to what we typically see in a CDP implementation. So we’re matching on exact name and email. I say it’s it’s closer because this is, again, probably not something I’d actually do with a customer. Um, for example, on the first name, rather than an exact match, I would likely choose a fuzzy match so that whether my name shows up as Jenny or Jennifer, those records get matched. Exact normalized would just take care of capitalization. That’s not quite what I want for first name. For last name, we really just have one option here for exact match. And then for email address, I would likely choose exact normalized. Again, as people are entering email addresses, they may accidentally capitalize that first letter, particularly if you’re doing it on your phone and that autocorrect feature capitalizes your first, uh, letter of your email address. Um, but when you’re entering on the computer, it’s all lowercase. All of those would be taken care of with the exact normalized. So that would be what I would be looking to do. So this gives you that flexibility of of combining, you know, and, and, and within that match rule set or do the ors across the identity resolution rule set. Once that runs, you’ll see this graph over here on the right telling you about your consolidation rates, giving you some warnings. These warnings are probably telling me that I should match on more than just exact email, etcetera, some of the things we talked about. Once our profiles are unified, we can also take a look at those. So let’s jump over to profile explorer. And when you’re looking in profile explorer at individual records, this is really probably just sort of a gut check or a sanity check to see how your identity resolution rule sets are working out. Is it is it combining records that you expect? Probably not something where you’re gonna go and look at each individual. But I can look at both the unified individual from that first rule set or my second rule set. So as I’m comparing and contrasting my match rules, I can take a look at the same person in both rule sets to see how that data comes together. Uh, we’re gonna look at this first one, and I’m gonna grab a ID number from my, uh, all subscribers table that that I brought in, uh, that we were first looking at in individual streams. So, the difference here between attributes and related attributes, the top first name, individual ID, and last name are related to a unified individual here. So, this individual ID would actually be the unified individual ID. I’m gonna actually look at the related attributes because that’s the number I know from Marketing Cloud. So I’m gonna put in my individual ID here, and I have a unified profile, which is great. So I take a look at this, and it first pops up onto all of my related data because this is where we’re seeing what was actually unified. Right? So it’s bringing in all of the contact point addresses from different data sources. In this case, they’re all the same address. We actually have some discrepancies here in in the email address. There’s more than one email address that applies to this individual. Here we have a link table that tells us where those different data sources are coming from and all of the possible individual IDs that we’ve mapped to as part of our data stream mapping, what those IDs are. So this person has quite a few different IDs coming in from, uh, looks like Interaction Studio as well as Marketing Cloud. Um, I believe there are quite a few more records, um, when I click that view all link, which I’m not gonna do now because it takes a little bit of time to load. Um, this also gives a chance for us to look at engagement history. So here we have quite a bit of email engagement. This would also incorporate web engagement or mobile engagement if that was available. And then the calculated insights that that Jill mentioned, as you are building lifetime value, for example, you can take a look at what is this lifetime value calculated insight for this particular person. This particular person doesn’t have any data for that, uh, calculated insight, but this gives us a chance to look at it by person as well. Let’s take a look at one more profile, um, from our contact records. So, again, same thing. Looking at unified individual using that contact record ID that I know coming from CRM. So intuitively, I’m not going to know what the unified individual ID is. And take a look at Jimmy Caruso here. Jimmy actually has, uh, some updates to his address. He’s he’s changed cities here within Minnesota. Um, he also has some different email addresses associated with his unified profile and several different sources of data coming in and a contact point phone number. Um, one thing I didn’t show you on the last record was that if you go to details, you can see what is being mapped in on the individual data model objects. So we can see his interest and and some of those things that are coming over from mapping. Um, on the right here, again, we’re seeing some email engagement data. We do have some some information about his engagement count, um, and we can try to take a look at purchase insights too. I’m not sure if this will come up with with anything here. Um, but this allows us, nope, to see those calculated insights as well. So once you have all your data harmonized and unified in CDP, you can go in and start to build segments and, uh, calculated insights here within CDP. Unfortunately, we don’t have time, uh, today to dig into all of that. But, um, you can take those segments that you create and use those to activate those same segments consistently across your channels everywhere. And that’s really what we’re hoping to do with the, uh, with the CDP. Uh, next slide there. Thank you. Alright. So I appreciate, uh, your time and attention today with the demo. I hope you found it helpful to see inside the platform. I did wanna take this opportunity to review some key ongoing resources that are aimed at accelerating your CDP experience. As many of you know, Salesforce offers multiple ways for you and your organization to stay plugged into, uh, uh, the latest and greatest product information, uh, with expert led sessions. And as you can see on this slide, there are a few different ways to engage moving forward. I would definitely plug the CDP Trailhead module. These are a solid first step in understanding not only the need for CDP, but the possibilities it creates for businesses like yours or the ones you’re working with. It’s a great place to familiarize yourself with the new terms and concepts, um, which we definitely recommend for implementation. After that, you can see we have the Trailblazer community, which many of you are already a part of. Um, and the community is a great way to connect with other Salesforce customers to share knowledge, discuss use cases, and get ideas on how businesses like yours are solving today’s toughest questions about reaching customers. Um, we’ve also included a note here about our CDP Trailblazer program resource guide, where you can find all things related to progressing your CDP and data and personalization journey, including, um, introductory and technical webinars that this team has delivered previously, help document documentation, certification information, and many other resources. Um, for any customers out there on our premier signature success plans, there’s also one to one coaching and ask the expert sessions, which are amazing ways to engage in real time discussions with your own team or with our own team of trailblazers. And we have some additional resources on our professional services team for implementation assistance, specific release notes, and writing this plans. Um, and with that, I believe that’s it for me. Again, thank you.

Speaker 0: Awesome. Thanks, Jenny. And before we wrap up, wanted to just do a quick plug for the MarDreamin’ day three closing keynote this Friday from 02:20 to 03:30PM eastern. Some of our incredible Salesforce teammates will be talking about how Salesforce Genie allows marketers to meet, um, you know, increasingly changing customer demands and and privacy changes as well, um, as well as how do we kind of handle the questions when we’re asked to do more with less. So if you wanna learn more about Genie here at MAR Dreamin’, be sure to tune in. So I’ll pause here for a second, um, so folks can take a note, add it to your agenda, or maybe take a screenshot, but hoping to see all of you there on Friday. And that brings us to the end of our session today. Hope you enjoyed learning a little bit more about Genie and CDP, and our team is looking forward to keeping in touch with you as you continue on your data and personalization journey. So, um, with that, I’ll hand it over to Sarah now for some closing remarks. But, um, thank you so much for the time. Thanks for joining us. Enjoy the rest of MAR Dreamin’, and, um, look forward to speaking again soon. Thanks all.

Speaker 3: Awesome. Thank you so much, Andrew. Um, Jenny, that was an awesome demo to be able to get an inside look at just the the possibilities that is CDP. So thank you so much for doing that. Um, like promised, I have some swag to give away. So I asked a few of you guys to be active in the chat, say hi, participate. So our winners today are Angela Wolf, Terry Juncker, and Carla Mauricio. So we’ll be in contact after the event, um, with some logistics on how to grab those prizes. Um, so that is it for today. So I will see you guys all tomorrow morning, um, for day two. Thank you guys all again.