Speaker 0: Hello, everyone, and welcome to our session. Um, today’s session that we’re gonna go over is called The Fifth Element. Um, you, data, AI, CRM, and marketing. My name is Brent Whitmer, and I’m a principal consultant at MRE Consulting. I’ve been a Salesforce consultant for the past about twelve years. And for the past eight of those years, I’ve been focusing on Salesforce marketing solutions. I’m excited to be here and to present with the amazing Jennifer Rivero.

Speaker 1: Hi, everyone. Uh, I’m Jennifer Rivero. I’m a director at Emera Consulting. I’ve been a customer experience and marketing strategy consultant for fourteen years, uh, and I’ve been working in Salesforce for about eight years. Uh, I’ve really enjoyed seeing how marketing has evolved with the power of technology to be more data driven, more personalized, and even more creative. And today, I’m looking forward to talking about data and AI.

Speaker 0: Great. And, um, if we have a few minutes into the session, you know, go ahead and throw questions to us in the chat and we can be able to answer those along the way or at at the end. We’re gonna go ahead and get started. But before we get started, we wanna thank our incredible sponsors at the event here. So I wanna thank Circonte, Salesforce, Stencil, The Spot, and Storylane. Without these companies, this event would not be possible. So our agenda for this session is outlined here on the slide. The first thing we’re going to talk about is how you are the fifth element and what that means. Then we’re going to go into data and data cloud. We’re going to talk a little bit about AI and Agent Force and then at the end we’ll wrap up with planning for the future and the key takeaways. So some of you may remember or can see the the images here on the screen the movie that came out called The Fifth Element. It debuted in 1997, so a couple years ago. Um, it did win 10 awards, was nominated for an Oscar. The movie takes place in the future when the universe is threatened by evil. The only hope for mankind is the Fifth Element, which comes to Earth every five thousand years to protect humans with the stones of the four elements. Now in the movie, of course, there’s a host of characters that are required to save the fifth element and protect the world while evil forces are trying to destroy it.

Speaker 1: So I want to comment about this because I’m a die hard fan of this movie, um, and I think it’s a perfect analogy, uh, Brent’s telling him a perfect analogy for what we wanna talk about today. So even centuries into the future, and I think this movie is set in, um, 2300, so just a few hundred years away, with all the technology that’s available then, the fifth element still ends up being a person. Um, so it still goes back to you as a person. Mhmm. Um, and then for a movie perspective, if we look at the visual effects, um, it’s visually interesting because the movie itself is grounded in reality with a lot of miniatures and practical effects. And I mean, that kind of, um, represents how you as a person need to ground, um, your strategy in reality. Sorry. Go ahead, Brent. I’m just gonna say we don’t have the movie.

Speaker 0: Um, the movie is is a great analogy for us, and we want to take that analogy and bring it to the you are the fifth element. You are the hero of your story. You are the one who can bring all the elements together, and we’re gonna call those elements data, AI, CRM, and marketing to save your company. Now fortunately for us, there’s no evil mercenaries out to stop us or to kill us. But at times, it can feel like there’s so much going on in our day to day jobs that it’s hard to know what to focus on or what’s the most important thing. So in our session today, we’re gonna focus on two of the main elements, data and AI, and how in this changing marketing landscape, we’re gonna give you some ideas hopefully they can help you succeed. So as I said, you are the fifth element. Um, just to set the stage a little bit for our session, this is not gonna be a technical session. We’re gearing it towards business, admins, business analysts, and product owners. So if you want to get technical, there’s a ton of videos out there that you can be able to read about or watch all the topics we’re gonna cover today. So we’re gonna highlight some of the things technically, but we’re really gonna focus on, the human element or you which in our opinion is the most important part of the equation for success. So what do I mean by that? You are the most important part. So, um, we all know that projects and companies would not be successful without people. Right? Running projects, making everything that we do. Um, we know that technology can change rapidly and it can kind of be scary to think about all the things that are coming up and how that may affect your job. So here’s some things to keep in mind with all this things that are going on in the world and all the technology that’s happening is that you are the most important part. You bring your unique background perspective to your job that nobody else has and that’s an important key of why you are successful. Also, you are the one who can get through your company’s data. Now this is going to come up a little bit later in a future slide about data and how important it is, but just keep in mind that you have control over that. You can know your company’s data. Um, remember that AI can’t replace you. Um, it’s here to help you, but it can’t replace you and that you are the one who can bring all four elements together for success. So with that in mind, let’s go ahead and dive into the the first thing we wanna talk about. Now it might seem like we’re talking about the end at the beginning, which we kind of are here, um, but is what do you want to accomplish? Thinking about the end in mind at the beginning. So the first thing that I want to think about or that I try to think about in my job are what are our top use cases? What are we trying to accomplish? And then once I know those use cases, it comes down to what data do I need to support those use cases? What do I need to know? What do I need to gather together to be able to make that successful? Is that data reliable? Is it available to me? How many sources of data are there? Um, another good question is how often do you need to refresh it? Do we need to get new data every hour, every day, every week to be able to have accurate data for those use cases? And the couple last questions is, is it structured or unstructured? We’re gonna go into more of what that means, but just keep in mind that there’s different types of data in your organization and how you get to it and how you use it is different depending on what what it is. And the last thing is looking at the systems you have in place today that you can use to accelerate, enhance, or transform what you’re trying to accomplish. We are not gonna be advocating for technology today just for technology’s sake. Right? We’re not saying everyone should go out and get data cloud and AI or agent force. It is looking at what do you have today, and does it make sense, or what do we need to look to the future to bring in to accomplish those use cases that we’ve talked about? Um, so with that in mind, I’m gonna turn it over to Jennifer, and she’s gonna talk about more about data and data cloud.

Speaker 1: Alright. Um, I think we have one more slide before this. Right?

Speaker 0: Uh, the only one I think was the title slide. Yes.

Speaker 1: Oh, no. Let’s talk about data. There we go.

Speaker 0: Sorry. There we go.

Speaker 1: Thank you. Alright. So let’s talk data. Um, every company has a ton of data. And today, the problem isn’t not having enough data, it’s having too much data and it being too difficult to figure out what data is good, relevant, uh, reliable, and ultimately usable in what you want to do.

Speaker 0: Um, the

Speaker 1: as Brent said, there are two types of data out there structured, which makes a lot of sense. It’s, um, really data that you can store in tables like, uh, like an Excel table or a SQL table, um, or unstructured data. And, really, there’s an estimate of, um, that unstructured data makes up 90% of, uh, data for most companies. That makes a lot of sense because unstructured data includes, um, things like images, videos, uh, meeting recordings like the ones that are gonna be available after this conference, PowerPoint presentations, PDFs. If you think about it, that’s, um, primarily the type of content, information, or data that you and I or others are creating on a day to day basis. Um, how bad is bad data? Well, you all know that it’s garbage in, garbage out. And if we want to be able to use new tools like AI, we need to have data that’s good and reliable. Um, but the truth of the matter is is that, um, 94% of businesses say that their data is inaccurate or unreliable. I’m sure based on your experience at your various companies, um, that you have experienced some of this. And then some other pieces of information. Right? 18 of all telephone numbers change. Now as a marketer, this kinda, like, hurts me to the core, um, seeing this because that means my SMS program is probably, uh, not as great as I believe it is. So what should we be doing? Um, we should really be looking at how we can measure and improve that data hygiene. So data accuracy, um, the proportion of correct data entries we have. Um, is it correct or not? Right? And then data completeness, the proportion of records which are complete versus those that have missing values. So there are so many companies, um, where go in and they want to do a particular use case, but they don’t end up having data. So I’m just reminded of a reminded of a story where, um, we spent weeks creating this very complex customer targeting model, uh, where the cost the client wanted to incorporate customer net promoter score. And we kept asking them, okay. Well, do you have an estimate of what percentage of customer records actually have this data? And we were assured, we have this data for everyone. Don’t worry about it. Well, finally, when we got into working with the production data, it turned out that this was only available for two to 3% of customers. So not very usable. Um, really, if you’ve ever considered cleaning up your data, now is the time to do it. We want to talk now about data cloud. Um, I know that, uh, you don’t have to utilize data cloud. We already, uh, talked about that, but, um, I feel like we can’t not talk about data cloud in this session about AI as it relates to Salesforce. So before you jump in, we wanted to highlight some things. Um, one, data cloud is a usage based product. This is very different from, um, Salesforce’s traditional models, like Sales Cloud, Service Cloud, Emerging Cloud, where it’s based on, um, license seats. Right? This is, uh, where it’s so important, um, to start with the use cases Brent was talking about and zero in on what kind of data you want to, um, utilize, how much of that data, and how often it’s refreshed. We’ve already had some clients who run into some issues here where they decided, well, we just wanna test out data cloud. Let’s plug in everything and refresh it as often as we can, and they ate up their credits really quickly. Again, this is where that human element comes in about, um, thinking through your what you want to accomplish and the minimum of what you need to get there. Next, data cloud isn’t a tool to, uh, merge all of your data. Um, all of your source systems are gonna stay there. It’s going to maintain that information, and what you’re really doing is it’s harmonizing the data. You still need, and it’s even more important to have, uh, data governance in place. Next, you want to have a basic understanding of data modeling, and we just highlighted one example of this with primary key versus foreign key. Um, for your structured data, I’m sure you have primary keys defined, um, but foreign keys in that understanding of how data relates to each other is gonna become more and more and more critical. Um, I had a client who wanted to do a very simple, uh, email campaign where they send a customer communication based on what that customer has purchased. Well, guess what? If they didn’t have their CRM system with foreign keys mapped to their their billing. So it was a little bit of jumping hoops, but that type of, uh, data modeling and data governance is going to become more critical so that, uh, more AI use cases can be enabled. Uh, four, data cloud is not a data lake. It’s data lake house, and we’ll talk about that more in the next slide. Um, but the takeaway is, again, don’t put all of your data here. It’s not a place to just dump data. You will have to pay for it if you do. Um, and finally, data cloud is not always the right answer. We said we don’t want to be, um, advocating for technology for technology’s sake. Um, there may be ways that you’re doing things already or traditional um, tools that you have access to that may be a smarter more, um, smarter, faster, more easily maintainable, and bottom line cheaper way to be able to do things. So explore all your options, focus on the use case and what you’re trying to do and not trying to figure out how to make this new, cool technology work for you. Okay. Um, so what you see here now is a a flow of how Data Cloud manages structured data. We said that this is not going to be a technical session. We’re not going to be diving deep into how data cloud works, um, but we did want to talk a little bit about the data. Um, so if you’d like to learn more, I would say go take a Trailhead, follow Danielle Laresley. She’s awesome. There’s a lot of functionality, new nomenclature, and concepts that are specific to data cloud that you should absolutely learn. If we keep going, um, we have a little more information about unstructured data, and this is where, um, you get all the benefits of data cloud being a data lake house, bringing together data warehouse and a data lake. Um, I did wanna highlight that data cloud uses that, uh, AI technologies like large language models to analyze structure and then chunk out, uh, that unstructured data into vector objects so that you can then query and search your unstructured data. This is critical and what is really going to unlock the value of your data and then make it available to functions like flow builder, prompt builder, Course Agent Force, Tableau, etcetera. Now that’s enough about Data Cloud, and I’ll turn it over to Brent to talk about

Speaker 0: AI. Alright. Thanks, Jennifer. Um, so we have talked a lot about data. You might be asking yourself, you know, why is that? Um, well, it’s because AI is only as good as the data that’s been it’s been given. So AI basically is moving very quickly. We’ve all heard about if you watch Dreamforce or saw any of the sections or the different sessions of Dreamforce, um, you know that if you talk to Salesforce five years ago about AI technologies and what they were doing, and today, it’d be very different anything about five years in the future. So things are moving very quickly. Um, today, we’re we’re hearing about 87% of companies that have already implemented some sort of AI are already, um, seeing, um, are saying that once they’ve implemented it, that the data management is a huge priority because, again, data is so important to feeding into their systems. Um and the last one at the bottom I’ll point out here is there was a study that asked there’s about 20% of companies that have implemented some sort of AI and of that 2097% are saying they’re already seeing reported benefits from it. So it is definitely here. Um, it’s it’s gonna be continuing. So one of the questions we might ask ourselves is, you know, is AI right for me or when is it right for my company? So our next slide is to talk a little bit about that. So what does it mean to be ready? How do we know if we’re ready for it or if it’s ready for us? Um, and again, we’re not advocating for technologies for technology’s sake. We’re here to to help guide you in how you decide and then once you decided how do you get ready for it. So the first thing you ask yourself, well, are we data ready? I’m I’m sure most companies are gonna say they’re not. So that means making a plan in place or talking about that. What does that mean? How do we get our data in a good state so that we can apply this? Uh, the next one down is have we identified goals and use cases that are suited for AI and for data cloud? Do we have use cases that we can support this? If not, maybe that’s next year or the year after that we’ll have those good use cases that we can apply to it. Um, and then once you’ve decided they’re gonna use it, do you have the right team in place, the right skill set in place to support that? And then the last thing to consider is the legal and ethical implications of AI. Now this changes depending on where you are at in the world. I know that the EU has very different rules than, say, we have in The US, and those will be changing over the next few years. I’m sure as more technology occurs, the governments wanna put in more things in place. So there’s gonna be more laws. So just keep up with that, making sure that you’re answering those questions and know if it makes sense for for your company. Now as we talk about AI, as Jennifer mentioned, that kinda leads right into Agent Force. Again, they’re they’re tied together, and you’ve seen the Dreamforce the last, uh, this last year. Um, so you might be asking yourself if you didn’t attend those sessions, what is AgentForce? So at a very high level, it represents the third wave of AI at Salesforce, um, after predictive AI and then copilots. So this is their third iteration, um, of AI, and it’s now called Agent Force. You can think of it as an AI powered platform that can help you, um, supercharge sales and customer service teams in different ways. Uh, maybe it’s, um, you can see different agents up there. So there’s, um, op agents, sales agents, support agents, marketing agents, different things you can put in place to help your staff do things easier or better or faster. So let’s talk about a couple of the key features. Again, not going too technical here, but just some of the highlighted things. Um, the first one is the AI powered assistance. Um, that’s where you can, you know, have AI agents handle a lot of repetitive or time consuming tasks to let your staff do the more important things, the more complicated items. Um, the next one down is real time data and insights. It really helps to analyze data very quickly and can be able to provide personalized recommendations, like, for marketing perhaps if you’re gonna have to do emails with personalized mark recommendations. Um, next one down on our list, number three, is the Atlas Reasoning Engine. Um, we could talk about this for a whole thirty minutes as well, all the things that it does. It really has all kinds of tools inside of it and different, um, pieces of it that helps to find, evaluate, refine, stitch together, and then validate the data before sending to the user. So it’s kind of the brain behind the behind the scenes of AgentForce. Um, low code customization number four. You can easily create agents for very low code or no code, um, depending on how you’re setting things up or what you’re wanting to do. Again, getting the technical details is another session, but just very low code customizations. And the last item here is it integrates with your existing Salesforce tools. We’re already using Sales Cloud, Service Cloud, other things that’s gonna integrate really easily with those and work seamlessly with them. Okay. Um, I just mentioned the Atlas reasoning engine. Again, this could be a whole thirty minute, um, talk or session here about that, going into all the details of it. Just know that there is a lot built into it for, like, that brain I was talking about of how it can retrieve information, plan, refine, evaluate, and really make sure that what’s happening is coming from all that data that you have and producing the right action. And the last item here we’re gonna talk about for AI is bringing those two things together. So keep keep in mind as we’re trying to associate, I should bring them back to you, um, the the human elements in all the things that are happening is that you can help define whatever agents are created at your company. You bring that human element. You’re gonna decide what those agents should do, what role they have, what data they can access, what capabilities they have. And a really important one is number four on this list, the guardrails. So part of agent force is the ability to set what it can and can’t do to make sure that it’s not going outside the boundaries and if it hits those limits it passes it on to a human agent so that it’s not processing outside of the boundaries that you’ve set up for it. Um so all those things are just really good things to remember that you will be influencing all those things. So learning about it, understanding it, um, will just help guide you to have the best solution for your company once this is, uh, an option for you. Um, and also the very end is you are helping to direct the personality and to represent your brand. So just keep that in mind, the voice, um, the tone, all the things that are happening are coming from humans and that’s that human element to that that that part of that success that is always needed, um, anything that happens with AI. So with that, I’m gonna now turn it back over to Jennifer and she’s gonna talk about the next couple of items.

Speaker 1: Thank you, Brent. Um, so as you plan for your future, we want you to walk away with a few key takeaways. First, always start with the use case. I know Brent talked about this at the beginning, but it’s zeroing in on, uh, what is it that your organization wants to achieve and letting that flow into everything else. Um, a good BA starts with requirements. Right? They don’t start with the technology even if a technology is a consideration. Um, and we’ll brainstorm some of these cases, uh, after this slide. Next, um, know your own perspective. I know the whole theme of the Fifth Element, and I hope you guys are also fans of the movie. I know that we didn’t have an orange wig. I I really did think about it. I’m sorry. But it’s about you leveraging your knowledge of your organizational goals and your department priorities, um, the people and the stakeholders. Anytime, um, you’re you’re trying to accomplish anything big in your organization, you know it’s so much about, um, getting, uh, the right people, right groups, and the right cadence out there. Uh, it’s also leveraging your knowledge of Salesforce’s capabilities and pricing model. I know I talked about it a bit with data cloud, um, but, you know, you you absolutely do need to start with that so you can understand what your total cost of ownership is gonna be and the maintainability of the solution that you’re trying to build. Next, get comfortable with data. I’ve met a lot of business analysts who skew more on the business side of things, and that is absolutely a superpower. Uh, but I’d say you wanna build stronger skills in data and logic. Um, data will power the future. It’s already powering, uh, the present. So the more comfortable you get with it, the better, um, you can set yourself up for success. Finally, know the technology and the resources that are available. Uh, we did highlight some of the, um, key sexy tools that we think that Salesforce is talking about today, whether that’s data cloud, AI, um, Agent Force, Atlas Reasoning Engine. But it’s it’s not technology for technology’s sake. It’s, again, going all the way back to your use case. Speaking of use cases, let’s talk about them. Um, we only have a few minutes here. So, uh, rather than reading off each of these use cases, um, let me actually ask Brent, is there one that you would highlight based on your experience working with clients?

Speaker 0: Um, yeah. I think the one at the bottom, the automatically triggering workflows and communications, that comes up with every client that I’ve worked with is how do we, um, um, know when to communicate with our customers? How do we send the right information to them? How do we make sure that we’re not over communicating with them? So all those things coming in with having that data, um, data cloud, and AI helping you to make those better decisions and to be able to trigger those communications at the right time, I think that’s gonna be super powerful even more so than what we’re already able to do with our clients today.

Speaker 1: Awesome. Thank you. And actually, I meant to remind folks, um, a few minutes left. If you have any questions, please drop them in the chat, and I’m so happy, Anthony, that you’re a big fan of the movie.

Speaker 0: Are there any on the list here, Jennifer, that you would, um, highlight for people that you’ve worked with?

Speaker 1: Yeah. There’s actually two. That first one, enable service agent visibility into net promoter score. So earlier in this session, I talked about a client who wanted to, um, create a customer segment utilizing net promoter score data, and they had defined it in a very narrow specific way. And that was many years ago before, I think, all of these AI tools were available. And, um, the ability today to be able to pump in all sorts of data and then ask the AI, uh, based on, like, large language models, like, how they would, um, characterize, uh, clients as positive, negative NPS, I think that would be hugely valuable. And then to be able to show that to a customer service agent, um, when they’re, uh, immediately there in the account, um, and because someone has called in, huge. Huge. Can’t wait to see more of that happening. And then the other use case I wanna highlight would be the ability to identify and engage customers who are likely to churn. Um, we work with a lot of clients who, uh, work on, um, on a, like, a contract relationship basis with clients, and that ability to figure out based on the customer’s engagement or usage history who we think is going to turn and being able to target them with marketing content or an offer, just, uh, highly valuable.

Speaker 0: Yeah. The other one I’d recommend or I would highlight here is the third one down. Um, I’ve worked with multiple clients in the past that struggled with this, that didn’t have the capability to be able to identify cross sell recommendations to their customers. They wanted to, but it just it wasn’t there. So I’m looking forward to, um, being able to build better solutions for customers to be able to say, hey. You’ve purchased this. Here’s some other recommendations. I know it’s out there. We see it from Amazon. Some of the big companies are able to do that, but some of the smaller companies aren’t don’t have that all set up yet. Um, so being able to tie those things together, build their dataset, and also to sell rec or to cross sell, um, good recommendations, I think will be very valuable to, um, some of my clients as well.

Speaker 1: Um, I see there’s a question around, you know, which of these do we use internally? Um, so I think it’s a for for us, um, the ones I would highlight are more the developer tools. Um, funny I’m saying that because I know that that is not necessarily, like, my, um, side of the house. Uh, but the ones that I’ve seen folks use are pretty amazing where they can go and have write out the the business analyst logic for a flow and have, um, Salesforce, you know, uh, draft a flow and provide that to you. It tools like that are incredibly helpful, not just for developers, but also, like, VAs and admins who want to expand their their, um, their deliveries skills. And that’s actually something that I wanted to grow more in as well.

Speaker 0: And and with it, like Jennifer mentioned, this is just a short list of use cases. There’s there’s hundreds of other ones. So you’re coming up with yours. Um, I’m sure you’re gonna find, um, either unique situations at your company or the ways that you’re doing things. That’d be a great use case as well, but there’s a bunch of different ones out there. And I’ll go on to the next slide.

Speaker 1: So we have to end with, uh, a picture of Leeloo and Turnbull Teapass to bring it all back to you and how you’re the one who’s, uh, essential to enabling AI at your organization. It’s just a reminder of, um, the messages that we’ve been saying about how it’s, uh, all about your perspective and your context and knowledge of, um, your company. We we really wanna bring this home because with all of the AI tools that we’ve, um, seen coming out and gaining traction this year, like Copilot, Agent Force, um, I hear a lot of rumblings like, are BAs even still needed? Is this going to replace my job? Answer the first one, yes. Answer the second one is no. And it’s about highlighting, um, those human elements that only you can bring and how it is critical for, um, for AI. So, uh, as he said, only you can identify what is the most valuable use case, um, helping create that benefits case for your company of the cost and benefits, the maintainability of that solution, um, and also how AI can be used responsibly. Brent talked about this earlier about how there is more There have been more, like, legal and ethical, um, guidelines that are coming out around AI, uh, which are definitely, um, important and needed, but it’s also about how we are building our own AIs for our companies to reflect our brands, our values, um, and our morals.

Speaker 0: I think we we ended

Speaker 1: Oh, okay.

Speaker 0: I think we’re on, uh, point two or three of the slide that it did for us.

Speaker 1: Okay. I probably should have just jumped to the questions or the the support resources. My bad. I saw something change and I wasn’t quite sure, so I just kept talking.

Speaker 0: Alright. Thank you.

Speaker 1: Thank you.