Speaker 0: Good afternoon, everyone. Hopefully, everyone’s had an amazing day one of MarDreamin. My, uh, panelists are just joining, um, as well. It looks like we’ve got a huge group on the call. No pressure, uh, fellas, and I’m gonna go ahead and share my screen, and we’re gonna get this party started. Hopefully, everyone is energized from day one, uh, and they’ve gotten some coffee. Um, I’d love to open up the, uh, chat with some maybe emojis of how you felt today was. If you had to pick one emoji, if you had to pick, uh, you know, one animated GIF, go for it. Uh, as we get started, and I’m trying to multitask on the screens. Oh, so fetch. I love it, Marcos. I did not wear my pink today for any of you mean girls out there. But without any further waiting, let’s go ahead and get this party started. So, um, again, welcome to day one, and we hope you were energized from day one and are excited for day two of my dream, which obviously is tomorrow. Uh, before we get started, we do have a few slides to review, uh, as we bring today’s, um, day to a close with today’s keynote on data cloud and marketing cloud. Hopefully, y’all have heard of data cloud before, but just in case. Um, of course, uh, we’ve got our our our awesome forward looking statements here. Um, I’m not going to read it. Hopefully, you have seen something like this before, but, basically, in a nutshell, anything that we’re sharing today, please don’t make any purchase decisions, plans, so on and so forth. And, of course, it would not be a Salesforce presentation without this thank you slide, thanking you all, uh, to, uh, for joining us, um, and also, um, thank you to our panelists for joining us from Salesforce as well. So what the heck are we going to be talking about today? So hopefully, you’ve heard about Data Cloud before. But if you haven’t or you want to learn a little bit more about what Data Cloud is about, you are in the right spot. We’re going to have a high level overview on what data cloud is about led by Arvin. We’re also gonna talk about how do marketing cloud and data cloud work together, which I think is super important for Us marketers here. Uh, we’re also gonna then talk through more of the nitty gritty around how do you ingest that marketing cloud data and then, of course, how do you act on it. Right? Um, being able to personalize, uh, being able to leverage that awesome data is gonna be critical, uh, I think to, uh, our communications now and into the future. We’re also gonna talk about consent considerations. So, again, beyond just the unsubscribe, what are the other things we need to do? And then what my favorite section is is gonna be around those recent innovations, ones that have come and are coming. And then we’re gonna switch things from presentation mode to, um, ask the panel. So we do have a few questions prepared, but also if you have questions, uh, that you wanna ask when we get to the panel section, do not be afraid to ask them on the q and a tab, and we’ll try to get to as many as possible. Uh, so without further ado, let’s go ahead and introduce you to the panel. Uh, for a a quick intro of myself, my name is Kirsten Schlau, and I lead the marketing cloud practice here at Circante. And I’m joined by Andrew, aka Kaz, from Salesforce, Adam Erstele from Circante, one of my great fellow dragons, and last but not least, Arvin, uh, Ramon, who is also at Salesforce, uh, that really owns the data cloud product. Um, and so with that, I’m gonna let things, uh, kick things over to Arvin. Thank you so much, Arvin.

Speaker 1: Thank thank you, Kirsten, and thanks to the group for, uh, joining. I’m willing to learn more about data cloud and marketing cloud. So why, uh, data cloud? So hopefully, some of you have heard about data cloud. Uh, next slide. Alright. So, uh, I mean, this is just as you know, your customers today, especially in this day of digital signals, are expecting more than, um, ever. They, you know, they want you to know who you are. They want you to sort of, uh, basically, um, interact with them and give them experiences across all channels and across all touch points. And in fact, 73% of customers sort of expect companies to kind of like for you to understand your unique needs and expectation. 70% of customers say that loyalty is more difficult than ever to maintain. Next slide. And in this day and age of fragmented data, you know, the average company has over 976 different applications. All of your customer data is sitting in different places, and there is more than ever higher acquisition cost. And with all the privacy regulations from GDPR, CCPA, and even other new ones coming, like, all of that is important to keep in mind, like, how do you sort of collect and act on your customer data, like, in a very privacy compliant manner? Um, but the truth is even though you may have data management at scale is, uh, complex. Uh, next slide, Kristen. Um, you know, um, just just think about your systems, you know, like the data that you are collecting about your customers from your CRM database to the your website, if you have mobile app, any of the transactions, you know, that you might be collecting your case and your service data. Um, by, you know, by, uh, last survey, they said that by 2025, there’ll be 100 zerabyte of data in the cloud. So I had to look up what is a zerabyte. So one zerabyte is 1,000,000,000 terabytes. Now granted, a lot of that may be TikTok and Instagram reels, but there’s still a lot of valuable customer data that you can use and harness. Um, so net, you know, in this day and age where data management is complex and you have to deal with all this for you to deliver that sort of customer experience, um, what you really need is, uh, next slide, is, you know in in order to sort of deliver relevance now, like, really knowing, um, you know, like, do you really understand who your customers are, especially as you as we move into this cookieless universe? Second, how do I unlock insights from all of my rich customer data to kinda deliver relevant moments and experiences? And third is, how do I really drive more value as well as efficient growth while meeting customer expectations? And that’s why Salesforce launched Data Cloud for Marketing. And what Data Cloud for Marketing really is is, uh, lets you next slide, Kristen. Alright. Um, so what is data cover marketing? Uh, so data cloud for marketing lets you unify your all of your data, especially your customer data into a single customer profile. So it lets you, one, connect data from all your sources, so across your marketing CRM, the Salesforce clouds, as well as any other in house systems that you may have and other systems we have. It lets you engage smarter with real time segments, with real time insights, and then also maximize those touch points and relevance with sort of AI powered ins insights and then personalizing those moments and your customer journey within their CRM flows. Uh, so that’s why Salesforce launched, uh, Data Cloud for marketing. And then, um, you know, and then you might be asking why Data Cloud for marketing. Um, and I think as the slide is slowly pulling up, you know, so one is it is natively integrated into the Salesforce ecosystem. It’s not a standalone product that sits. It’s natively integrated across the entire Salesforce three sixty, including marketing cloud. So it’s integrated to your marketing, commerce, sales, and service. It has advanced AI and workflows built right into it. So you can start building intelligent campaigns using no code AI builders, as well as you can bring your own ML models using any other ML provider like SageMaker, Google Vertex. And then really in a clicks no code, it’s gonna, uh, own your end to end data strategy in terms of how do you segment and act activate data. And then the data cloud for marketing was really sort of built for marketers. Right? So it’s how do I build scalable and flexible audiences with drag and drop segmentation? How do I democratize my customer data, um, and then, you know, be able to act on it with fast market differently tools to tie all this together using clicks no code. Um, and then here, the next slide has a few examples of our customers who are really sort of driving success with data cloud for marketing. And it really sort of straddles across different verticals. So we have Kia, which is a big, uh, car manufacturer, where they are using data cloud to ingest, uh, really billions of real time events. You know, they were able to get it implemented in a three month sort of time frame and, you know, to be able to collect all this data, um, telemetry data from their devices. Uh, Casey’s is a pizza chain in the Midwest, and, really, they are a heavy marketing cloud user, and they really adopted data cloud for building intelligent real time audiences faster. So in fact, they saw in their workflow that now their segmentation their segmentation needs, they are able to sort of, um, do the segmentation three times faster. And then Inter is a bank in South America. Well, really, they had a need to integrate multiple systems to kinda act on real time data insights. And, again, you know, they were using marketing cloud for campaign creation. But by integrating this real time data across their website and their financial system, they’ve had 20 x more ROI and 35 times uplift. Um, and then, really, like, we ask us, how does data cloud work? Right? I mean, I won’t go through this slide detail, but at a very nutshell, it lets you connect your data sources from across any of the Salesforce cloud. So from CRM, commerce, to any any of the hyperscalers like AWS, s three, Google Cloud Storage, as well as your website and mobile apps, uh, any of your APIs and, you know, website streaming. And then, um, we also have, uh, we also have a MuleSoft connector, which can be used to plug into any of your on premise system. And then once you’re able to connect it, you can do some transformations within data cloud both in a batch manner as well as through a streaming transform. And that’s when the power of data cloud comes in where we can harmonize it into a standard, what we call as a customer three sixty data model. And and what we mean by harmonization is, as you might know, your customer data that lives in different systems may have different naming syntaxes, different, you know, uh, like, even within the Salesforce clouds, I’m Arvind is a contact in my CRM. I’m I’m called a subscriber in marketing cloud. In my commerce system, I’m called a profile. Whereas in your ecommerce system, you might be called as a customer. So how do I bring data of these different shapes and different size and different naming syntax and really harmonize them into a standardized model. And once you harmonize it, then, you know, you can start to run what we call as unify them or to our identity resolution. That is, how do I get a single view of a customer even though I may be coming from different systems? How do I unify all that into a single place? And once you unify it, you can start to get some insights on it through our calculated insights framework, as well as using some of our AI predictions. And then you can start to an action on them, and actioning on them can take on different ways. You can segment and create audiences to activate them across marketing cloud through your ad networks, through any of the activation platform. You can also use real time data action triggers to kinda call out a web hook or to update in the system. But, basically, data cloud sort of is a hyperscale data platform that powers the entire customer three sixty. Um, and then I think next up, we’ll have Adam, like, kinda talk through some of the next steps in sort of logistic on how do we integrate marketing cloud and data cloud.

Speaker 2: Thanks, Harvand. Yeah. So now that we we have this platform, it’s really awesome and powerful. Right? How do we, really, how do we tie in the data that we already have in marketing cloud engagement, bring it into data cloud, and actually, like, start doing some pretty cool things with it? Now when you’re when you’re just starting off with data cloud and you’re looking to connect it to marketing cloud engagement, there’s some out of the box data bundles that you can use that make it easy to pull that data in. Right? And with data cloud and these prebuilt bundles, and there’s there’s three of them. We’ll touch on all of them. The probably the one that most people are gonna use is the email studio streams, and this is what’s gonna bring in a lot of the very familiar types of data points and objects from marketing cloud engagement into data cloud. Right? Some of these are only gonna be found in the email studio data bundle. Right? So if you’re if you’re looking to set up streams, it’s really easy inside of data cloud where you can when you’re looking to create a new data stream, right, you’ll first say I’m picking it from marketing cloud, and then it’ll walk you through being able to choose from email studio with the items we just saw a little bit earlier. You’ll have mobile connect and mobile push. Now with with mobile push and mobile connect streams, right, there’s a lot or there’s just a few objects that are gonna be included, again, because it’s relying on some of the common things that are found in the email studio stream. Now when you’re looking to pull all this together, what DataCloud’s kinda doing behind the scenes is it’s leveraging s three to take and house that data and help facilitate the ingestion. Um, there’s a there’s a few things that need to be considered when you’re when you’re doing it in that way, but it’s really one of the best ways to do this in a in a low impact and very performant way. Right? It’s read only activities, um, and there’s a couple of automations that are automatically created. One that runs hourly, another one that runs daily. Now a couple things to note is that these automations aren’t meant to be modified since they contain some very specific details on how to extract and transform that data to data cloud. Now there’s you know, with any technology, right, there’s always some considerations, and data cloud and marketing cloud is no exception to that. Bundles are all or nothing. Right? So you can unmap and remove some data sources in data cloud, but the Salesforce marketing cloud part will remain unaffected. Um, data from all business units are gonna get ingested. Right? So there’s some things you might need to do after the fact inside of data cloud to, you know, shape things the way that you want. And when you when you first get started, it’s only gonna pull in ninety days of historical data. And if you wanna pull in any more from that, there’s, uh, some custom things you might wanna do in order to be able to leverage all

Speaker 1: that data.

Speaker 2: Now once that data’s in the platform, Arvin’s gonna talk a little bit about how you can act on it.

Speaker 0: Thank you so much. Uh, Arvin, up for you on how do we go ahead and use this data in marketing cloud.

Speaker 1: Thank you. Sorry. Yes. Uh, thank you, Adam. Um, yeah. So, you know, it’s great. So you’ve been able to connect all your data from marketing cloud, CRM, other systems, harmonize them, unify them. But and now it’s really how do I get value from it? And as a marketer, how do I use data cloud in combination with marketing cloud? So there are two main, um, you know, patterns that we see. So there are two ways we’re gonna act in your data and really to kinda power the hyper personalized, uh, customer journeys. So one is what we call as our segmentation and activation. So you can create segments on the richness of data you have within data cloud all through a clicks, no code type approach. They are really, um, ideal for creating large, hyper targeted audiences. Um, and then at at that point, it creates basically a a data extension within marketing cloud that can then be used for journeys or used for your campaigns. The the other option is is more for event based journeys or, like, trigger based journeys. So what we call it data action. So that is reacting to any data change events. So be it, uh, data change event that happens in data cloud through, uh, any of the streaming insights that you might create. They can be used to kinda trigger one off either an email action or a journey entry event. So they’re really ideal for, you know, where you have a need to message in minutes, and it’s really for optimized for event or trigger based journeys. So segmentation and activation, like, that’s sort of the bread and butter and what we see a lot of clients who are using data cloud and marketing cloud together sort of leverage where now, you know, it’s really how do I, through clicks no code, create high value, you know, very targeted, segmented audience and then activate them at scale. Right? So within Direct Cloud, now you have access to all of our data, not just marketing, but across service, sales, and in this unified profile view, even any of your data warehouses and data lakes that you may have. Um, and then you can start to even, you know, create things like Einstein, you know, calculated attributes or calculated insights to model things like most common ones that we have seen are things like, you know, RFM score, lifetime value, propensity scores. Um, and then, you know, in a sort of in a very fast manner to be able to query on them or segment on them and then activate them through marketing cloud. And then so here’s an example across industry, not just, you know, where, you know, for example, a manufacturing client, you know, uh, where they’re right now, you know, everyone who has purchased a Ford Marquee and has outdated software, you know, and that can be then used in a journey to kinda, um, you know, like a a customer win back journey or to detailing where they need to do updates, know, based on their responsiveness. You we also have health clients with all patients, like, who’ve not had a, you know, uh, cleaning in six months. And then you can then use that just not for email, but even cross channel or SMS campaigns. And then, you know and integrate my clients, especially as you bring in the loyalty where your loyalty members of your, um, of your, um, you know, with the Top Gun as their favorite film. And then you can start to send them sort of push notifications for, you know, tickets and personalized offers and coupons based on the propensity to convert. Um, and then next up, we have data action. So this was the capability introduced early last year, which is really more of opposed to this batch based segmentation. Now how do I act on real time or streaming or moving data? So as data change events. So this is really meant for, right, if you’re capturing events from your website, if you’re if you’re doing any streaming insight, you know, to be able to enter into a journey, um, you know, to be able to send them a triggered email sent. So you can basically, uh, uh, send out a trigger using streaming insights, calculate insight, as well as any data change event that’s happening within Data Cloud. And then, um, uh, next up, I mean, here’s some, again, example for the same type of customers on what those, uh, trigger, uh, uh, in terms of how do you listen to them and, you know, send them into trigger? Uh, so in this same manufacturing client, where if you are collecting telemetry data and you see there’s a low tire pressure, you can send them an immediate SMS message with their, um, details on the nearest service center. Same with the health care client who just say has, like, has had a dental treatment. You can then send them a series of, uh, campaign or email messages on the recovery process. And then with the entertainment, what we also see in sort of using some sort of geofencing. So if you’re if you have especially a mobile app or you’re collecting geofencing data, you can start to act on it. And then this is just an example of how all this ties together of sort of showing you a sort of a use case. So, you know, if you’re a retailer, you’re launching a new product. At the same time, you’re getting overwhelmed by high demand in terms of delaying shipment. So this is where data cloud can kinda leverage the rich customer profile where you can both manage customer expectation as well as thank them for their, uh, thank them for the support. So the next slide will show you what the overall flow looks like when you are bringing across. So in this case, say you have a retailer website, you know, where you are collecting different data points from your, you know, purchase data to your product catalog, your pricing data, and then through using our Web SDK and our different connectors, that data is getting bought into data cloud. So, uh, an example of a campaign that you might create in data cloud is users that have purchased but have not been shipped to yet. Right? And you can put them into a journey through marketing cloud engagement. Uh, on a similar token, as soon as you get that shipment confirmation, you can put them into a trigger journey. Right? So, really, data cloud is sort of, um, powers, like, and just makes marketing cloud better and stronger by letting you leverage the richness of not just your marketing data, but across your entire data store. I think next up, we’ll have, uh, I’m talking some of our consent pieces.

Speaker 2: Uh, consent. This really could be its own entire session, but, uh, we’ll try to just touch on a couple brief things right now. Um, continuing on the theme of data bundles and things you can easily bring in from Marketing Cloud, there is a little bit that we can do with consent in bringing in some information from Marketing Cloud, but it’s actually just a very little amount. Right? For email, the only thing that Data Cloud will map for us is that they the unsubscribe engagement behaviors that you’d normally see in your unsubscribe data view inside of Marketing Cloud. Now if we’re looking at following that data flow into Data Cloud, right, when that subscriber opt out, that event is recorded in the unsubscribe data view along with the list where that preference was made, either it’s, you know, the publication list or the all subscriber list. And when that when that data passes to data cloud, it arrives in a data lake object noting the timestamp, subscriber, and the behavior. But as as we know, there’s a lot more to consent than just maybe opting out of a list. And what’s nice about what data cloud provides is it gives us a lot of capability for tracking different levels of consent. Right? At level one, we can store something like do not market, do not process my data, and and things like that. Right? There’s a bunch of other levels. I’m not gonna dig into them right now. Um, but because data cloud has all this capability, right, you need to figure out what pieces are you able to leverage, what pieces are you using in your marketing efforts, and then map them to what data cloud can model for you. Right? It’s really important to know that data cloud isn’t doing consent management, but it allows you to bring in your consent data so that you can leverage it in your segmentation or some of your actions or anything that you’re looking to do inside of data cloud. Now if we’re we’re thinking of a segment example, right, where we’re actually honoring that that consent, if you had all these various pieces of data inside data cloud mapped to all the right places, Right? This is the kind of segment that you could drive and and create within, you know, within your your campaign or however you’re trying to build your segment. Now some things to keep in mind is, you know, you need to understand how consent is currently being tracked in marketing cloud. Right? You need to understand those differences and then how are you gonna map them to the various levels within data cloud. Um, and it’s really important to know that, you know, not everyone needs to use all four levels. Right? Don’t don’t go through the extra effort of trying to collect it all if you’re not actually gonna use it in the near term. So with that, I’m gonna pass it off to Andrew who’s going to talk about some recent innovations and what’s coming up.

Speaker 3: Awesome. Thank you, Adam. Uh, Yeah. So I get the fun job of getting to tell you about some of the cool things that have come out and things that we’re thinking about coming out, uh, here on our road map. Now this isn’t an exhaustive list of features that have come out or what’s on the roadmap, but just sharing a couple different things about the integration between marketing cloud and we’re focused on marketing cloud engagement. Uh, so first up here, we have related attributes. Gonna level set because we’ve seen the the acronym DMO, uh, on this slide and on past slides. So a DMO stands for a data model object. Uh, think of it as a grouping of data made up of attributes about your subscribers. Those are created from data streams and insights and sources. So, uh, DMOs can be standard or custom based off of your customers or your business needs. Um, some common DMOs are things like sales order and account and party ID. So with related attributes, right, data cloud has two types of attributes, uh, direct attributes that only have one value. So things like first name or related attributes, which can have a bunch of different values that tie back to a user. Uh, we have policy information on the screenshot. So for example, um, whether it’s a policy or maybe even a past purchase, uh, I may have bought a bunch of different things. Um, with this new feature with related attributes, uh, you can go ahead and use different past purchases from me as personalized data points that can be activated into marketing cloud and then used in message content for personalization. So if you want to talk to me about the sweatshirt that I just purchased and try to upsell me on a coat, You’re gonna be able to do that as opposed to just grabbing, uh, any, uh, you know, singular attribute, uh, maybe like a t shirt that doesn’t exactly relate to that upsell opportunity. So that one is GA. That’s existing. So go out and feel free to use that now. The next feature that we have here is going to be related to rapid data publish. And we’ve got, uh, GA version, and we’ve got an, uh, a road map, uh, opportunity coming up. So, uh, in our summer twenty three release, uh, rapid data publish was, uh, became available. So, uh, this is related to the segmentation and activation process, and it’s a way to bring data from, uh, data cloud into marketing cloud. So you’re going to be able to now activate individuals who are added or removed from a segment in data cloud. Gonna be able to bring them in in either one or four hours. Uh, this is the option that you see on the right side of the screenshot compared to the standard option that you see on the left side of the screenshot, which gives you the options of bringing in data every twelve or twenty four hours. Uh, this really helps marketers accomplish those low latency or time sensitive use cases. And the rapid publishing is available because of how we’re sending the data between data cloud to marketing cloud. So instead of sending a full update of all the data each time, we’re just sending those incremental data up with updates with that rapid publish approach. Now the roadmap item related to rapid data publish is around updating attributes for existing subscribers. So what’s currently available is if you add or remove subscribers from a segment. But what we’re targeting, uh, for, uh, early twenty twenty four, you know, hopefully first quarter or so, is bringing down the time frame of passing updated attributes, uh, which is currently at every twelve hours, bringing that down to every one or four hours, uh, like we currently have for adding or removing people from a segment. So, um, again, that helps you to use the most up to date data from data cloud within marketing cloud. And, again, safe harbors subject to change, but we’re hoping to get that out 2024. Uh, the next feature that we have here, uh, again, another GA roadmap combo is all around real time journey orchestration. And Arvin touched on this a little bit earlier. So data actions are where you’re able to trigger entry into a journey. So it means that you’re going to, uh, be able to track behavior on the web or mobile SDK, maybe calculated insights, uh, and then pass that data from data cloud into marketing cloud and get a subscriber into a journey within minutes to help you kind of take action based off of what they did to be able to then market to them. Road map feature for this journey orchestration piece, uh, and we’re targeting this again for 2024 is a WhatsApp behavioral data ingestion, uh, and activation channel. So if you’re not familiar with WhatsApp, it is one of the premier global messaging mobile messaging channels out there. What this roadmap item will allow you to do is include fields that WhatsApp needs, uh, for activation within marketing cloud to be able to get that message out the door. Now if you’re not familiar with using WhatsApp and marketing cloud, we’ve got some, um, some documentation, some webinar series about using that feature. Uh, what I will call out is you will still need to, uh, create a WhatsApp message and a journey and make sure that your contacts are imported to that WhatsApp channel in marketing cloud. Once you have those kind of, uh, foundational building blocks steps done, this new feature is going to allow you then to go ahead and, uh, uh, more quickly in a more real time fashion, get those subscribers into a journey and start messaging to them. Next up is a feature that is GA Now. This is fresh off of our winter release, and this is our waterfall segmentation. So it’s kind of set the set the scene or paint the picture. Right? Overlapping segments is a massive pain point for many marketers, uh, when they’re working with their data. So it can cause them to oversaturate their subscribers with messages and kind of being looking as if they are not super precise with our outreach. Uh, so waterfall segmentation is going to help marketers avoid that by allowing them to create prioritization of mutually exclusive segments. So traditionally, uh, a segment is going to rely on attributes. So I’m gonna segment based off of age or interest or purchase or behavior, and that’s the qualifying criteria. Waterfall segmentation is going to allow users to set up, again, a prioritized list of those different segments, um, and maybe an individual is going to exist in one of them, um, or maybe they could exist in multiple. That prioritization is going to allow you to just have them exist one time. So if a data cloud user, uh, wants to create a new waterfall segmentation, they’ll go in, they’ll create a waterfall. They will look at all their existing segments that they currently have, click through prioritize it, uh, so that if customers are showing up in multiple segments, data clouds data cloud then knows which segment is most important to the marketer to pull that subscriber into. Uh, then the marketer gets to review the counts and the segments and publish the waterfall, uh, and they’re gonna be able to be a lot more precise, uh, with that outreach, uh, to their customers. So, uh, that was fresh off this, uh, winter release. Uh, the last roadmap item that I’m going to share gets into, uh, what Adam was just talking about around consent filtering. And, yes, this can be a session all on its own. Um, so, uh, you are going to, uh, so again, we have a pilot targeted for January. Now you are going to be bringing in your own consent mappings into data cloud from marketing cloud. That’s not going to change. What we are looking at launching though in that January pilot is the ability to take those consent signals and then create filters on l three and l four statuses during activation. Now, again, if you don’t have l three and l four consent statuses, it’s okay. Don’t make more work for yourself if you don’t want to. But if you are able to create filters on those l three and l four consent statuses, it means that, uh, marketers and data cloud users are going to get more accurate counts on segment sizes since you’re gonna be able to see who qualifies for a message and has agreed to receive those messages with their consent. Now depending on how you’re gonna use that segment, you could be good to go with a marketing cloud engagement send. So say if you’re going to, uh, use that segmented audience immediately for a send, you can activate that to marketing cloud and send it out. On the other hand, if you’ve got a long running journey, you are going to want to go ahead and continue those consent checks like Adam had called out on that last slide in Marketing Cloud as the journey progresses, uh, to make sure that those subscribers are still opted in and have given you given their consent to continue to, uh, receive messages from you. So those are just a couple of the things that we’ve released recently that we’re thinking about, uh, kind of building moving forward. I hope it goes without saying, but we are continually investing in that data cloud and marketing cloud integration. Uh, and we would love to hear more feedback from you, whether it’s this forum, uh, out on Slack partner community, what have you, uh, as we kind of continue to build that integration between data cloud and marketing cloud, uh, more into the future. So thanks for letting me have a little bit of time with y’all. And, uh, Kirsten, back over to you.

Speaker 0: Thank you so much, Kaz. Alright. So, um, now we’re gonna switch over to ask the panel. Hopefully, uh, as we were chatting about the latest and greatest related to data cloud, what does it mean, how does it work with marketing cloud and the future, you’ve been, uh, thinking of some good questions to ask. We are gonna go ahead, and we do have some planned questions. However, for anyone, um, that wants to ask a question, feel free to go ahead and, um, go to the q and a tab to enter your questions in there. Um, but to get things started, I’m gonna pass it over, uh, to you, Arvin, around this question. So when considering onboarding into data cloud, who do you see as the owner of this tech? Followed by and this is a two parter. Who is the typical end user of data cloud? We’re gonna start with Arvind. Um, and depending upon we we might kick over to you, uh, Kaz. Yeah.

Speaker 1: Great question. You know? And I think, you know, one thing we’ve seen is over the years is, uh, data cloud, you know, implementation use will really impact and need buy in from several departments, right, based on how you’re using it from your marketing to IT to CRM, if your e your ecomm team, your data teams, you know. But, really, if you wanna drive success, you still need you need a single owner to kinda own it and to drive its success. Like, in a bigger enterprise, it can be a COV, a center of excellence, but it doesn’t have to be. Like, data cloud is used across the board, so it can be a specific department. So even though it might interface with your across your entire organization, you need a single owner. It can be a group, a department to kinda drive it success. And it really comes down to what use cases that you’re driving. Um, and that really translates to the second part. Right? Like, how are you planning on using it? Like, what is the end user? You know, from a from a ingesting data, like, those are typically your IT users in terms of being able to set up those connectors. You might have data modelers to harmonize that. But from an end use in terms of segmentation and activation, that’s where we see more of that marketing persona, be the marketing specialist, uh, marketing manager, or even a data aware specialist who are creating those segments. Right? And then we also have a machine learning capability. So then we have some of our data scientists. So based on what capabilities you plan to unlock, it can really be used across the board. But I would say from a segmentation activation from a marketer’s perspective, that’s typically your marketing users.

Speaker 0: Thanks, Arvin. And what I heard was in true consultant fashion, it depends. Um, that was the easy one you had me walk into. Uh, Kaz, anything else that you might wanna add to that or any different POV here?

Speaker 3: No. I mean, you took my, uh, you you you took the tagline that I wanted to use. It really it really will depend on the customer and kind of what their focus area is to to Arvin’s point. Now I just wanna double down on it. Um, this is a tool that was built to try to help those data focused marketers have a little bit more control over kind of the world that they’re living and working in. So, um, biased because I I work with marketers all the time. Uh, I may lean a little bit more towards that as the the owner of the tech, but it truly is going to depend where on who who the, uh, true leader is, the person truly bought in, uh, with each of your customers. So I’ll just leave it at it depends.

Speaker 0: Thank you. Alright. And I have a question, uh, for you, Adam or Stell, around when should customers consider adopting data cloud? I think we had some, uh, comments from a few folks in the audience as we were going through this around, you know, what is the use cases, what are the ideal use cases, or those typical triggers or moments where we think data cloud could be a great solution.

Speaker 2: Yeah. And, you know, with data cloud being free, right, it can be really tempting to just jump in, get started with the trial. I can’t even count how many trials of software that I’ve, you know, used. You know, day two or three, I’m, you know, into it, and then either something shiny rolls by, and then, you know, my trial gets wasted. And, you know, with with data cloud, it’s really gonna be no different. Right? Don’t just jump into the trial without having a plan. Right? So what kind of moments would you have that might want you to, you know, think of a plan to use that free trial? And that usually will get kicked off by either just sheer volume of data. Right? Maybe you have a ridiculous amount of data, and whether you originally tried to throw it into the CRM or you tried to throw it into a data extension, and it’s just it’s not performing well at all. Right? That’s a really good moment of, hey. Maybe this new data cloud thing, you know, maybe this is the genesis of the of the free trial. Right? Um, you know, it can be queries running too long or the the SQL statements you have. Maybe they’re just getting so complex and no one can even read them anymore. Right? Those are all some key moments that might trigger that thought of, um, what’s this data cloud thing?

Speaker 0: Awesome. Thanks so much, Adam. And, Arvin, I realized I’ve got a bunch of a’s in here. I don’t know why it’s just taking me. Uh, but, Arvin, anything else that you would maybe think that you’ve seen as moments and maybe even just unexpected moments, taking that question slightly a little different?

Speaker 1: No. Sure. I think apart from what Adam added. Right? Like, if your data volume within marketing cloud is going long, your queries, I think those are, you know, definitely very legible, like, things. But what we’re also seeing is where customers who are using marketing cloud or even others, but they wanna sort of get that unified view of their customers, especially are are looking to integrate multiple, be it Salesforce clouds or others. So your maybe your commerce side, be it commerce cloud or some of the commerce side or your CRM in conjunction. Really trying to get that unified view of your customers and of that individual to be able to act on it. And, you know, and, you know, like, data cloud itself, just, you know, for the audience, sort of got its start in the marketing domain. It was called a customer data platform. But then as over the years, as Salesforce realized that it serves more than just the marketing use case, it has expanded. Right? So with that being said, like, some of the trigger words that we have seen, right, especially as your end users or customers are say, hey. You know what? I’m, like, I’m struggling with trying to get a free, like, a single view of my customer across all of my data sources, or I want access to all of my engagement data to kinda trigger very rich personalized experiences, or I wanna be able to combine my service data to kinda give my service agents and marketers a truly view of of all that. So I think those are some of the trigger words in terms of how, you know, you might benefit from adopting data cloud on top of your existing investments that you may have at Salesforce.

Speaker 0: Thank you so much. Alright. Kaz, you’re up. Uh, so this one is a little bit longer, so good thing we have it on the screen here for everyone. Um, I’m gonna read it out. Um, not that I don’t believe, uh, folks can’t read. Uh, but Marketing Cloud customers have had the flexibility of data extensions for a long time. As we shift our focus to data cloud, we noticed similar functionality within this tool. I think they’re talking about the segmentation. What guidance would you give to customers in regards to the data, uh, excuse me, when the data should reside in data cloud and when we should continue to use marketing cloud for some of this?

Speaker 3: Got it. Yeah. That is a a little bit of a mouthful for sure. Um, so my my take and my opinion on this is if we go back in time a little bit, and I’m saying maybe, like, five, ten years ago, uh, if you used marketing cloud, we would usually say, hey. Give us all your data. The amount of data that’s been created in the world, uh, just over the past year is absolutely ridiculous. So that that narrative has changed to, hey. Based on the use cases and your personalization and segmentation needs, that’s the data that we wanna see. And I would say that that statement, that, uh, kind of energy stays the same as we move forward. So if you have use cases specific to marketing cloud and you may not need that data within data cloud, okay. Fine. That can just stay in data cloud. I think you’re gonna find a lot of synergies. We’re passing data from marketing cloud into data cloud So that as Adam and Arvin have kind of alluded to, you can have that single view of your customer there and then activate it into marketing cloud. And then if you have marketing cloud specific data, you can then do some querying, uh, to supplement the MC specific data with data cloud data. So I I think from a, uh, just a use case perspective, the use case is going to fit the the the data into the tool that it needs to be in. I would say don’t be afraid of having data in both places because if if your marketers are living and breathing in marketing cloud, you wanna have that data there. Right? It’s no different than if you’re working with, uh, an account that has a sales or service cloud integration with marketing cloud. You wanna bring in the data that your marketers need. You wanna pass back data that those users are gonna need, Uh, the same kind of, um, spirit of where data needs to be is going to be the case for data cloud. At least that’s my take on it.

Speaker 0: Appreciate it. Uh, Yeah. And I think, you know, again, it’s gonna depend. It depends, uh, for each organization of of what makes sense, um, and it’s not necessarily a zero one type of answer. Right? Um, to talking about some coding things. So I definitely appreciate those insights for sure. Um, next question over to you, Arvind, around the trust layer. Uh, so could you share with us a little more about the trust layer and why it is so important for customers to understand this? And I think maybe also taking a step back of what trust layer actually means might be also good for folks that this might be a new terminology for them.

Speaker 1: Oh, that’s a that’s a tough one. Uh, let me look up chat JPT real quick. Hold on. No. Um, All jokes aside, so, uh, if you have seen any of the Salesforce, so Salesforce is investing heavily in sort of what we call our AI capabilities, and that’s grounded by our trust layer. So, you know, as you know, everyone is sort of talking about AI again, especially since, you know, um, since late last year and early this year, if you’ve been, you know, for news media, chat GPT, and sort of generative capabilities language has just taken over the world, like, almost every conversation we have with our customers across the board, just not marketers. Right? It’s like, what does my generative AI strategy look like? Right? So I think companies are also trying to figure out how they can make it useful for their businesses. Like, as a personal user, ChargeGPT is fun. You learn from it. You’re able to sort of tweak on it. But as a business, how do I so we wanna make sure that Salesforce, like, we do it in a very trusted way. And so we’ve been thinking about this pretty seriously, you know, because with AI, it’s only as good as what you give it based on the model that you train it. So one thing that you may have seen with AI is it tends to thalassinate. So it’s basically when these, uh, GPT, you know, make stuff up, right, um, thinking it’s 100% sure. Um, and in a business context, that’s just not something that can be tolerated. So what Salesforce is building is an an architecture layer on how do we address those issues with trust. Right? So and data cloud really sort of plays a key role in that architecture in terms of how do you ground your AI in reality. So, basically, grounding is a is a term that’s used that allows us to provide real data and context, uh, before we go out to these large language models to kinda get some generative assistance. Right? So they can be in the context of a marketing cloud for smarter segment creation using GPT type technologies or for, uh, for your sales cloud users, you know, using our Einstein prompt builder to be able to create those personalized emails. But, really, trust layer is the layer where Salesforce sort of guards that data and all of the data. Nothing is ever stays with your LLM model. So in case you do not know, anything that you might use, uh, tools like OpenAI for in their terms and conditions, it can be stored there forever, and the model is actually learning from it. With Salesforce, we strongly believe your data is your data, and, you know, so we don’t. So with our trust layer, you can be rest assured that your data sort of stays with you and is not being used for further model reinforcement, but just for giving it, uh, for context and for grounding.

Speaker 0: Awesome. Appreciate that. And, yeah, I think, uh, definitely ensuring we’re being, uh, responsible with data, um, is is super important. And, of course, making sure that it’s protected and used wisely, um, is is very much appreciated. I think for everyone of us that’s a consumer of some sort. Um, alright. We’re gonna wrap it up with one last question here, um, and this is over to you, Kaz, starting out first. And then, Arvin, um, would love your thoughts, and then Adam closing out, um, and, uh, then have a a few little announcements to close it. But, um, so this one last one. This is a fun one. Uh, rapid fire. What is the one thing that gets you most excited about the future of data cloud and marketing cloud working together? Uh, Kaz, over to you first.

Speaker 3: Uh, I I think I alluded to it a little earlier, but giving the marketer more power of the world that they live in. Uh, if you think of marketing cloud’s old legacy, big, big data segmentation tool, it required, you know, a professional services engagement to stand up and then, uh, include or make changes. So being able to give the marketer that ability to create their own adventure and and create the world that they’re living in as as it comes to their data, that’s what gets me most excited because that just makes speed to delivery faster, and it gives them more flexibility and creativity in what they can do.

Speaker 1: Um, Yeah. I mean, like, I’ll say this. Like, I just love the power of an integrated solution where we, as customers or as marketers now, you can bring in all of your data, just not your marketing data, harmonize and unify them, right, to get that single view and then activate that across Marketing Cloud. As a long time ex Marketing Cloud consultant, I’ve done many implementations and having to cobble together 10 different data extensions of their purchase data, their store data, their transaction data across, and trying to tie it all together through queries and then testing and validate it and still not fully confident that, yes, you have that single view. Now I think we put that power in the hands of a marketer. You know, like, once you have it set up, like, you don’t have to depend on a technical architect like myself and then to be able to use it on an ongoing process. I think that’s what gets me excited. And then since I did I’m gonna take second you know, like, I’m gonna say this the second thing that’s really you know, is I’m I’m excited is also some of the AI capabilities, like, since it’s grounded in data cloud. So we have things in pilot right now from a marketer for, like, segment GPT creation. So opposed to having to even create segments of click you know, through clicks, it’s more of your natural language GPT. So, you know, so I think those some of the investments we are making in the AI space and how that’ll manifest itself to our marketing cloud users as well.

Speaker 2: I’m glad that you brought up the, uh, GPT example so that I don’t have to use that as my one thing. Um, so I’m gonna go to my my next, which is, you know, I’m excited to see more of the marketing cloud account engagements data in the future coming into Data Cloud and really being able to power the marketer no no matter which of the Marketing Cloud flavor products you have and being able to do the the same things.

Speaker 0: Awesome. Thank you so much, uh, all of you for that. Um, as we’re closing up, just a couple reminders, uh, for folks, and we also have a survey that we’ve just launched as well, uh, that we’d love your feedback on. But quick announcements, um, as we head towards the rest of the week. Um, the marketing club road map session is coming up, but it’s not going to be recorded, um, tomorrow. So just make sure you attend that one. We’re also gonna have again, if you have any questions that have popped up through today or, again, you have some burning questions that you came in, uh, we’ve got some Genius Bar appointment slots available. Uh, so you can go ahead and chat with a Salesforce Salesforce, excuse me, expert. Um, we also have, uh, on the marketing resources tab, some free downloadables and other resources for your use. Um, again, don’t be afraid, as they probably said earlier in today’s, um, opening, um, notes to don’t be afraid to connect with people via chat, via LinkedIn, using the attendees tab. Um, and we hope, um, you know, again, the more you you join us live, we’re currently gonna have some additional prizes to win. So, um, I’m not sure exactly what the prizes were thus far, uh, but, hopefully, uh, there’ll be more to come in store since I missed out on those. Um, for those of you that are based here, um, in the Atlanta area, like myself and Adam Urstell and actually Arvind, um, go figure. Sorry, uh, Kaz. Oh, I shouldn’t tell that Arvind lives in Atlanta. Sorry. Um, Kaz lives in Atlanta. We can pretend that. Um, we have an AI and data cloud network and learn, um, really geared towards marketers. It’s gonna be an opportunity to learn a little bit more about AI, data cloud, see some demos, really focused on real talk. Um, so taking this presentation a step further. Also, some networking opportunities, that’s gonna be, um, November 14, um, the day before the actual, uh, Atlanta world tour, uh, which is gonna be at Cobb Galleria. So if you are, um, in a city close to Atlanta, um, Salesforce is coming your way. Of course, they’re gonna be also traveling to other cities as well. Um, but this is just selfish little plug for for us, for those of us that are are local to this area and wanted to make sure you were aware. Um, another great session, um, that you can check out, uh, tomorrow, I can’t believe we’re already in November, is around growing together and building the the future together and what the future of marketing looks like. We’ve got a really diverse, interesting panel. Uh, we also have a data cloud session, I believe, led by Adam Erstel, um, and some maybe other folks on Friday. Is that right, Adam?

Speaker 2: Yes. There’s gonna be a session on five tips for getting started with data cloud on Friday afternoon.

Speaker 0: Yeah. Perfect segue from today is, hopefully, you’re excited to to learn and you’re saying, okay. But now where do I get started? Uh, so that’s gonna be brought to you by by the one and only Adam Erstel. And last but not least, um, this would not be possible, um, without our incredible, uh, speakers, um, or speakers, number one, but also our sponsors, um, who are really, you know, our partners in driving growth. So I just wanted to take a moment to thank these sponsors for, uh, their support in making this event possible. Um, the folks that you see on the screen are definitely committed to the mission of helping marketers get more done on the Salesforce platform, which is what we at Circante are known for and love to partner with people that are like minded. Uh, so if you’re not familiar, uh, with any of these sponsors, please feel free to, uh, reach out to them. I know they would love to connect. Um, and with that said, thank you so much. I am shocked that we have so many people that stayed on for the very ending keynote. I feel like I should give you some, I don’t know, treats. Um, but hopefully, you got all of those tricks, uh, not tricks, excuse me, and more treats last last night, um, if you participated. Uh, we look forward to seeing the rest of the week, and thank you for sticking with us on day one. Have a great day, and, uh, uh, see you bright and early tomorrow morning. Take care.

Speaker 1: Thanks, everyone.