Episode 18 | Transcript

Aaron Beatty: Email Personalization, AI for SFMC, and Future of Data Cloud

Anthony Lamot: Hey, Aaron, welcome to the show.

Aaron Beatty: Hey, super happy to be here. Thanks for having.

Anthony Lamot: It’s absolutely a pleasure. It’s been a few months now, a few weeks now since we started or a Dreamforce. I was very happy to have been able to meet you face to face. And I’m very excited to have you here today. For our audience, can you tell us a bit about yourself, your background and ultimately what led you to found Engage Evolution?

Aaron Beatty: Sure. Yeah. So I’m gonna do my best to give the cliff notes otherwise, you know, I don’t know how much time we have, for the podcast, but I have a tendency to go in the way too much detail. So… I will give you, the quick background which is that I started in aerospace engineering. I worked for Northrop Grumman on the C-17 Globe Master 3 aircraft for a while then I switched into professional theater which you know, is a natural jump for most people to go from aerospace engineering to professional theater. But right doing that though I was a master sent Carpenter and a house manager. And then I did some time in retail. I worked for Apple for about eight years. And… once I was ready to start a family, it was time to find something that was a little more friendly to that. And that’s when I started learning about Exact Target and later Salesforce Marketing Cloud. And so that was, in 2012. And so over a decade now, I think I get to say I’ve been working on that and learning it and, you know, I kinda went through the ropes of that. So building emails, and testing, and campaign management, and support, and documentation, and all the other things that are part, of that ecosystem and just kinda been working my way up the ladder for a while. And my last position was as a director, of a group of a Salesforce Marketing Cloud practice. And, and ultimately, I would say frustrated that sometimes it feels like the larger an organization gets, the more it stops listening to their people start stops listening to their customers and it starts to feel like a herculean effort to try to get anything done or to try to get things changed from how they always were. And so ultimately, those frustrations, let me to feel like I had no other choice but to start my own Salesforce Marketing Cloud practice. And so that’s what happened in February of this year. And so I’ve been doing that ever since and, not a huge length of time there. But things seem to be going well, and I really enjoyed it.

Anthony Lamot: What a background I would ever explore what you’re currently doing, but there are a few things at that were interesting. So it continues to amaze me how much of a variation there is amongst marketing information professionals. In fact, a few interviews ago, I interviewed one of our own, Eduardo, who leads our customer success team, and he originally started his career programming satellites.

Aaron Beatty: Wow.

Anthony Lamot: Yeah. So the, I almost think also that having that variety for sure. The real life experience helps, I think for any marketing experience, sometimes just having worked in these very technical industries can definitely set you on the right track to deal with marketing automation because it’s so complex.

Aaron Beatty: Yeah. It, it is, and definitely can be. I think for me, my background, you know, I can look at every job that I’ve had and pick out little things you know, that I picked up, you know, while I was in engineering, little things I picked up when I was in retail, and sales, and a bunch of things while I was at apple. And that’s impacted, how I run my own company. It’s impacted how I treat customers and colleagues, and, it ultimately changes what I look for in a Salesforce Marketing Cloud employee too. Like, what am I looking for from people that I want to join my company as we grow? It’s all influenced by that background. But yeah, everybody’s there’s not a, I mean, there probably is now a digital marketing or marketing automation degree, but yeah, I didn’t go through anything even close to that.

Anthony Lamot: Are you ever able to tap into your experience as a master scenic Carpenter when you’re back working for?

Aaron Beatty: You know, I suppose, if I really wanted to, I, you know, my parents at one point wanted to me to be an architect and I was never really that interested in that. And then I got into building sets and stuff like that and being a master scenic Carpenter and, you know, what you do there? I’m not necessarily coming up with what the sets gonna look like. There’s a designer for that, but then they give you some crazy thing to build and you’ve got to figure out, you know, the structures that are maybe behind the scenes and, you know, how it’s all gonna fit together and still manage to support an actor’s weight or, you know, not hurt somebody when they’re on stage, you know, lost in their character, and not paying attention to how fragile that set piece may or may not be. So there’s I suppose some of that and that’s you know, in my job now it’s the same kind of thing, you know, a designer or a client will come and say here’s. The finished thing that I want, but we have no idea how to get there. And so much like an architect or a scenic, you know, Carpenter, you’re kind of figuring out the behind the scenes elements, and, the data architecture and the data structures that are supporting that end piece. So, and hopefully when you’re done, it’s not fragile and it’s sustainable and it’s scaleable. Just like you would want from, you know, a scenic piece in a theater.

Anthony Lamot: I love how you meticulously broke that down, and the abstraction layer, that provide some similarity between something as varied as being a carpenter in a theater industry marketing.

Aaron Beatty: Yeah. There’s I mean, the only difference is I’m not using any trig or anything like that that’s just reserved for when I’m helping my 13 year old with your homework, but everything else, you know, I haven’t had to touch that kind of stuff as part of the, there’s very little math although, you know, starting to get into AI, and language models. And, and there’s a ton of math and calculations involved in that. So who knows, I may have to start picking that up too.

Anthony Lamot: It’s it’s interesting that you mentioned that because I was gonna ask for Engage Evolution, the company you started relatively recently. Do you already have a sense of this is going to be our focus? Whether it’s functionally what you wanna do in Marketing Cloud, or maybe you focus in terms of types of customer you want to serve. Do you have an idea already what your ICP is and so on?

Aaron Beatty: So, yeah, I mean, we are founded as a Salesforce Marketing Cloud partner and really focused in, on that whole suite of software. So, you know, that will, I’m sure change and, you know, if we leave it up to Salesforce, I’m sure it will change names another three or four times just in the next year. But, but, you know, so that’s you know, what used to be Pardot, what used to be ExactTarget, you know, and Data Cloud and all the other pieces that are part of quote unquote Marketing Cloud is where we focus. And, and as far as verticals, I got a lot of advice when I started that I really needed to focus in on a vertical like, pick your lane, and I felt like that was good advice and also really difficult advice to follow because I have a lot of friends working in a lot of different industries and I’d like to be able to help them out kind of wherever they are. And if they’re using Marketing Cloud as are, I have some kind of insight or best practices and at least what I think they should be doing with their platform. And so, you know, right out of the gate I had, you know, financial services clients, I had nonprofit, I had some commercial and… you know, as long as you can speak the language of those different verticals, the solution and can have a lot of similarities. It’s just, the kind of code-switching you’re using in your language to discuss it. So are you talking about subscribers or are you talking about constituents? Are you talking about fundraising or you’re talking about development or you’re talking about sales. And there’s a ton of overlap on all those different kinds of code words that those different industries use. But at the end of the day, you know, the solutions in Marketing Cloud are going to be largely, you know, based on the same structures and platform capabilities that you have on any vertical. So… that’s a long winded way to say no. I haven’t really landed on a single vertical and, you know, as a start up, it’s you know, it’s gonna be hard for me to say no if somebody wants my help because they’re in, you know, not my core vertical or whatever. So that’s how it’s played out so far.

Anthony Lamot: And vertical could have been part of SEP, but I also know there are some who have an affinity for a certain segment like enterprise mid market. So that’s also…

Aaron Beatty: Yeah, that too. Yeah. And, and you know, it tends to be, I guess smaller, and more mid market, but, you know, we have a couple of, pretty large clients with some pretty complex setups… and, you know, a lot of times the solutions are still kinda the same. I mean, the focus, you know, is always going to be in terms of at least in terms of Marketing Cloud. Like how do you set this thing up in such a way that the, you know, perhaps just a marketer like a business user is able to get in there and get what they need without needing to be able to write SQL or, you know, do other things, that is not in most marketers bag of tricks. And so, you know, there’s as, you know, there’s a variety of products out there that help, with those kinds of things and services that help with that kind of thing. But it’s also from how you use structure in architect. The entire solution has to be, I think from that point of view first, how do you make it easy to use because of the inherent complexity, in the platform?

Anthony Lamot: Yeah, absolutely. Although I will say, I’m grateful for that complexity if not for it in our company will probably not exist, right? Yeah, it jokes aside, we have, I mean, I really resonated when you said there are code words for certain industries. So, for instance, when we talk with insurance companies, I’ll be more, you know, more likely to be talking about whether it’s a direct model across all of policies. Whereas if you talk with maybe higher education, we’re talking about advancement programs. But ultimately, what we do for instance, is a horizontal and it’s just finding those code words and relate into it. And I almost feel sometimes that and this might be interesting for those who are listening who are considering or already parting with Salesforce, when you’re parting with Salesforce, they’re all of guidance on being vertical specific. However, I feel that’s more because that suits Salesforce very well because they’re at this scale. If they want a significant capture time, they have to have that whole super vertical focus specific narrative. And that sometimes doesn’t make sense for other companies who are truly horizontal or, you know, aren’t even at a scale to have a strong vertical specific motion.

Aaron Beatty: Right. Yeah. It’s I mean, yeah, I think in some ways it’s partly due to just how Salesforce is structured. You know, their account execs and, you know, the people that work there. They have, you know, different verticals that they work in different size and scales that they work in and it’s helpful that way. And then, I think clients and customers also kind of force the conversation into that as well for better. And I think sometimes for worse because, you know, if I let’s say I work for a nonprofit and I’m looking for a tool to do forms, for example, I am in my, you know, looking at like seo type stuff and I’m looking for a product that does that. I’m not gonna look for the best form product out there. I’m gonna look for a nonprofit focused form. And so, I think that’s probably unnecessarily limiting in some ways because you’re looking, you know, specifically for your vertical under the assumption that it needs to be specific to your vertical or might have different tools or functionality. And, and I think too that clients want, they kinda want to know that you have a solution that’s just for them. And so saying well, you know, sales is pretty close to a nonprofit that’s trying to get donations, you know, or something like that. There, there is a lot of similarity in that. Just like there’s a lot of…

Anthony Lamot: The same idea that way.

Aaron Beatty: Well, exactly. No, they don’t, and higher-ed is the same like thinking of higher-ed and the context of sales. And in the context of trying to convince potential students to come to your college or university. I mean, that is, it is sales that, you know, they don’t want to think of it that way. But so there’s a lot of cross vertical and cross industry expertise that I think is going to waste maybe a little bit or not paid attention to just because it’s not specific to that vertical. And, and so, yeah, I mean, part of, you know, working on, the consulting side of it is learning to do the code switching so that when you speak to those things, you can translate it into their language. And then, they hear those code words and they go okay, they understand what we do. And then, and then you can have a meaningful conversation from there.

Anthony Lamot: Yeah, it certainly is a great way to build a report, Aaron, you’ve as we mentioned, have had about a decade of experience with Marketing Cloud. If you think back of the many projects you’ve done, can you think back of what was your favorite, or one of your favorite projects?

Aaron Beatty: Yeah. There’s a few that come to mind. I’m trying not to let like a recency effect here impact my answer because I just found some exciting solutions, for a client that was a lot of fun, but I think overall.


Well, I’ll go with, I worked with Teespring a while ago and they, they’ve kind of marked their business since I worked with them, but at the time they really were just kind of a custom teacher print shop. And, and now actually they’ve changed names. I think they’re just Spring now. But anyway, their request was they wanted an e-mail that could go out that would be personalized for people. And so what we ended up doing is writing a lot of AMPscript which is as, you know, the, you know, native one of the native languages for Marketing Cloud. And then I think there was some sequel involved behind the scenes. But basically it was an e-mail that sent each person their own unique e-mail and it would populate the e-mail with the top selling T-shirts of the different categories from which they had most often purchased. And so each person that received an e-mail was gonna get their own unique e-mail not even like based on a segment, it was really kind of a one to one thing just based on having access to the catalog and then having access to purchase data and then having access to the, you know, most popular shirts that were selling. So that was really that was a really fun one. And one of those that was like lots of late nights trying to get the e-mail to do the thing. And then finally like four in the morning, you get the thing, to populate correctly. And it’s just, you know, it’s amazing when you get to show the client the next day kind of a thing. So that was really fun. And really most of the really fun projects that I’ve had have been along those lines in kind of figuring out, how to increase segmentation and get closer to having a one to one experience on the e-mail versus saying you are one of, you know, 200,000 people in the segment to really treat each person as an individual based on their data. And that’s been kind of the holy grail, in e-mail marketing. And also something that’s been ridiculously difficult to do.

Anthony Lamot: I can imagine. And by the way I can confirm that that Teespring has been renamed Spring. I just looked it up but, it’s a cool brand, and it sounded like you’re really, you reached or at least approximated very closely at one to one communication. I suppose maybe people, who did similar, you know, purchases and similar product categories with that brand, they might have still gotten somewhat similar recommendations if not the same, but share with us like, why were the all mites necessary? So, what were the bottleneck in getting to that one on one communication?

Aaron Beatty: I think it’s probably part of that is just my, you know, I feel like there’s probably a bit of impostor syndrome there and that when I go to develop or build something, I feel like, well, you know, I’m like a junior developer, like a junior engineer, like, I can get by, I can make it work but it tends to be a lot of trial and error like, you know, you write the code, and it comes close, it almost does it or it just gives you error after error and you just can’t get to the point where it’s actually… you know, making it all the way through and displaying a preview properly. So, so I think it’s I think for me, it’s a lot of that, and who knows, you know, maybe your most experienced engineers and developers are exactly the same way. But, I envision somebody in my mind’s eye like a really experienced developer just sitting down and just from their brain directly, into the code. And they just write the exact code and then they hit, you know, send and it’s perfect. Like that’s. In my brain that’s how somebody that really knows what they’re doing would do it. And for me, it’s lots and lots of trial and error. And so, that ends up being late nights working on stuff.

And by the way, not working late because it’s there’s like a deadline that needs to be hit, but mostly because I’m like in the zone, you know, like I’m making progress. I’m really close to getting it and I’m having fun doing it. And so I lose track of time. And then I look up and I’m going, it’s time for my daughter to wake up and get on the bus or, you know, so, it’s more from that. Just like being like really focused in on something, until you crack it.

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Anthony Lamot: No, I definitely recognize that feeling. I don’t do any coding anymore these days.

But in the early days for DESelect, even I did and it, it’s definitely a good medium to enter that state of flow as psychologists would call it. And I do think by the way as it as a, you know, a little side, no, I do think even the best engineers have to do this kind of trial art or something to that works organic. I don’t think anyone can just, you know, A to Z type out a whole piece of functional code that will be probably like a freak of a person. Yes. But what I’ve always found helpful is to, rather than just starting to come up with a good architecture breakdown functionality into modules and then work my way through those modules. And, and when you de, structured like that, then… there’s a lot less frustration, and iterations afterwards.

Aaron Beatty: Yeah, yeah. I would agree with that. I, I’m not always as good at doing that, but I definitely have a smoother workflow, when I have a properly documented plan with requirements and, you know, goals and, you know, pseudo code prior to just kinda hopping in. And then, you know, saving early and often and saving iterations, of codes so that I can go back a step or two if I need to or if I break something, I’m just not always as good at being that organized. And sometimes I just want to hop in and get my hands dirty.

Anthony Lamot: Sure. Well, I still have to stay with this example of this project a little bit long because I’m kinda curious what kind of, what do the data architecture look like? Because I’m trying to sort of imagine what do you need to do a communication like that? So presumably, you need to store per customer their most favorite product categories. So that is based on purchase data, maybe with some sequel updates into a table. But then you want to personalize based on layer product. So do you load a product catalog and does that, is that linked to a content?

Aaron Beatty: Yeah. So I mean, I think you, I think you kinda talked it out there. So it’s largely that. So, the main thing that you need, is a product catalog and, you know, if that catalog has, you know, predefined categories. So like, in their implementation, I think they had like, you know, there’s like patriotic tee shirts, there are like music T-shirts. There are tee shirts by like keywords. So like, you know, if you search for teacher, you might get a, you know, a bunch of T-shirts for what it’s like to be a teacher. And if it’s if you search for engineer, then you might get a bunch of different kinds of funny shirts for engineer. So it was a lot of like keyword based products in a product catalog. And then they always had an image that they would show on their website for all the T-shirts. So I had access as to all of that. So between that and, the transactional data that’s really it. And then, and then the sequel is just looking for each person, their last X purchases and then looking at the categories of T-shirts that they purchased, and then trying to kind of discern their top, you know, however many categories based on whatever it is that we’re trying to do. So sometimes you can just use that… implicit preference based on what they’re purchasing. I have had some situations that are kinda similar to that where we’ve been able to combine the transactional… data along with the preference data from their like preference center, and then combine that with their viewing data based on like the things that they’re looking at on the website and then trying to kind of combine all of that through a series of SQL queries, or what have you to try to kinda guess the top things that somebody might be interested in. And usually, you know, the longer ago that they did that the less impact it’s going to have on your final scores and that kind of stuff. So you can make it as complicated as you want to. But it’s usually some semblance, of those pieces of data that you re-combine into an e-mail…

Anthony Lamot: It’s also interesting that you can combine implicit and explicit preferences. And I would wonder then what actually makes more impact if you would, afterwards, if you would like  AB test it and see if people respond more to their explicit or implicit preferences. I’m gonna guess implicit.

Aaron Beatty: Yeah, probably, yeah, because I think, you know, it’s hard to get really granular when you’re doing explicit because, you know, you can, you only want to show so many options on your page like you wouldn’t want, like if we go back to the Teespring example and let’s say they’ve got a 1,000 categories of T-shirts, you know, you’re not going to have them sift through all 1,000 categories and say, yeah, I like cowboy merchandise and my wife’s a teacher. So I like teacher stuff or, you know, like that’s gonna be really hard to find but you might be like, well, they like T-shirts versus hats. So like you might be able to combine the more broad categories with their implicit… either browsing behavior or abandoned shopping cart type stuff plus the stuff that they actually bought. And, and I think the thing that’s hard with that to really get right, which probably nobody does is like when is somebody gonna buy something one time for a specific use versus that’s the thing that they like to buy? You know, like if I’m on if I’m on the home shopping page and I bought a set of sheets or something like that, that’s probably not going to be something I’m gonna buy all the time. It doesn’t mean I just love buying sheets. It means I needed to set of sheets. I bought them. Now, I’m done with that. I don’t wanna keep getting emails about my next favorite sheets because I just bought them. So like it’s hard to, sometimes it’s hard, to square those edges and figure out… what’s actually gonna make sense in the ultimate e-mail and that’s it’s probably impossible to get right right now, but you can, you know, kinda take a stab at it.

Anthony Lamot: Now for Teespring, they probably constantly have new content available. So how do you make sure that you can actually show the last category winners, to those customers? Is it integrate with some kind of external CMS or is there like a process of constantly updating the latest image for the coolest new shirts? How does that work?

Aaron Beatty: Yeah. I think… this has been, it’s been a hot second. So I don’t remember all the details for them specifically, but generally speaking, you know, if we’re looking at top products, you know, it’s likely not going to include anything that’s brand new because there needs to be data to support that. It’s a hot product meaning enough purchase history or whatever to say. Okay, this is a thing that people like. And so it ends up just being, you know, in Marketing Cloud parlance, it ends up being a data extension that’s getting updated every, you know, probably a day or two with the current most popular items of the different categories. And then you take it from there. So that’s at least how that one worked to my recollection.

Anthony Lamot: All right. Thanks for sharing. We’ll talk about hot products. Let’s shift the conversation a bit to all the stuff we heard at Dreamforce. Salesforce has and continues to make major investments in their data cloud. That’s the name of their CDP, formerly known as genie, formerly known as Salesforce CDP, formerly known as Salesforce 360. But where do you ultimately see Data Cloud going? What do you think about that product category? And what do you see in the market?

Aaron Beatty: Yeah. I mean bringing it to specifically Data Cloud or Data Cloud for marketing. I think it’s definitely where they are wanting to bring the product. I mean, it certainly seems like they’re making a lot of investment into that tool and… I hate to say at the expense of, a, like marketing cloud engagement or something like that, but it does kinda seem like a lot of the energy and, you know, the new AI based tools and, you know, marketing GPT and all that it, you would expect it, I think to be in Marketing Cloud engagement or Marketing Cloud account engagement. And instead it’s in Data Cloud. So definitely they’re making a push to make that platform really attractive. And, you know, announcing that you can now get what amounts to a free trial, of the Data Cloud and kind of taking a look at it basically giving people, you know, their first taste is free for that. You know, the downside of that product right now is that it’s not an inexpensive license and it, it’s at current is really, it seems to me like it’s mostly a way, to solve for how difficult it can be in Marketing Cloud to get segments. And so, it’s a way for Salesforce to sell a product to make that part, of another one of their products a little easier to use. But they are, you know, rapidly advancing, the capability of that tool and I think, the kind of end user… the way that it’s being framed is more, you know, you’ve got your CRM data, but your CRM data is and everything you’ve also got data on the web and you’ve got data based on your social networks, and you’ve got data from all of your advertising. And so you’ve got all these pieces of data in addition to CRM and that, that’s a place where you can bring it all together and create profiles and kind of flatten the data and then activate it through journeys or through… let’s see what it’s called now Marketing Cloud personalization… or back into CRM and so… I don’t know. I’m really torn on it. I think it’s gonna grow into a thing that’s gonna be really attractive for folks, but it’s a little bit of a hard sell at the moment for at least most of the smaller organizations. It’s you know, it’s a pretty big lift.

Anthony Lamot: That’s fair. I think. And for those more well-versed in the Salesforce ecosystem, we all know that Salesforce platform really consist of often different infrastructure, different databases because of the acquisitions it has done over the years. What I do find exciting is that there’s going to be, well, hopefully you’ll become a common ground for all these platforms which will make integration a lot easier if not just completely unnecessary in case of certain capabilities. But I think there’s still some where, you know, there’s still some road to be travel before we get there.

Aaron Beatty: Yeah, yeah, I think so. I think, for those of us that rely on this ecosystem for our livelihood, it’s still an open question for where we should be investing our time and effort and, you know, training and, you know, certifications and all that kind of stuff like where are things headed? It definitely, you know, just based on the things that Salesforce has been saying, it definitely feels like data cloud is one of those areas where, you know, to your point, it’s a common ground for development and, you know, the newer stuff is all coming out of, that same platform. So, I think that’s where things are headed. But man, there’s just so much existing technical structure and depth in all of these other tools that for Salesforce as a company, I don’t know how they begin to bring all that stuff together… but yeah, I think that’s going to be an important part of, their strategy.

Anthony Lamot: Absolutely. Another thing we heard a little about a Dreamforce is AI, it was kinda hard to escape that phrase. You already alluded to the phrase earlier to start a conversation although maybe were you were rather referring to your personal use of AI, I’m not sure.

Aaron Beatty: I mean, it’s definitely right now, it’s definitely the buzz word dire, right? And, you know, my standing joke was walk around and go, who’s AI? Why does everybody keep talking about AI? But yeah, I mean, yeah, it’s inescapable, it’s definitely blown up obviously in the last year with chat GPT and then all the other tools, that have come around as a result. I am of the opinion, that it’s I think it will get us to a place where we can really do that one-to-one marketing engagement. And I think it’s really gonna expedite… that transition like I, you know, I referred earlier is the kind of, the holy grail of art marketing is to be able to have, a marketing segment of one and not have to group people together into these giant groups. And so the scale of data processing, and thinking and I use that term either in the, you know, the sense of a human doing it in the sense of an artificial intelligence doing it. But the, with all the tools and capability we’ve had so far, you just, you don’t have the time and resources, to have a segment of one. So it’s a short hand that you create segments and put people that are similar together under the assumption that they’re going to behave roughly similarly. And yeah, I think we’re just going to be able to get to the point where it’s literally, just this is marketing, for Aaron bad. And it’s based on what we know about Aaron bad and what we know triggers him. And whether he’s on his phone on TikTok or Facebook, or whether he’s on e-mail and we know he’s taken these steps in these actions and what’s gonna be the next action that’s going to be most likely to get him closer to our goal. And so, I think we’re gonna get there pretty quick and that’ll be, really great from a marketing perspective and as a consumer perspective, really scary because… as good as marketers are and as good as algorithms are at pushing our buttons, it’s just gonna get better or worse depending on how you.

So, yeah, that’s gonna be that’s gonna be really interesting, to see that happen. And, and from the marketing perspective be part of making that happen.

Anthony Lamot: Have you also personally doubled a lot with trying out AI tools or tricks with chat?

Aaron Beatty: I mean, I definitely, you know, I alluded earlier to being kind of like, you know, probably imposter syndrome, but just kind of feeling like a junior engineer in, some cases. And, and having a tool that can help me proof read that can help me write code faster than I can on my own or faster than I can with a quick stack exchange, search or Google search. It’s it’s really beneficial from that perspective. And then being, a very small company and then having all the responsibilities of, you know, building a website, having support tools, doing, you know, accounting and all the other things that are really just a function of owning a business. There’s a lot of help that I can get, from tools for copy, writing, for image creation, for writing outlines, for presentations. I mean, on and on, there’s a ton, of benefit to those tools. And then, you know, even on the project management side, we use internally a tool called motion that uses some AI tricks to basically manage and organize the tasks that you have do and putting them on, your calendar based on the time that you have available. So there’s some internal like uses of tools like that are really helpful for time management. And then I’m currently taking a class at MIT remote… for large language models and AI and kind of how to build your own. And, and one of the things that I’d like to do is to start to build some tools based on all of the documentation that I have, all of our kind of internal wiki, best practices and things like that and seeing if we can build something either for internal use or something we could share with, our client partners, and offer them something that can, where they can look at our kind of database of best practices and pull out the information that they need via one of those tools.

Anthony Lamot: Amazing! like some kind of marketing cloud knowledge base with which you can interact through natural language?

Aaron Beatty: Yes. Yeah. So I feel like that’s kind of, the first phase of that. I feel like longer term. I think there is going to be a need to have some tools that will do kind of what I was referring to with the one to one marketing. And, you know, if you take that thought out to its logical conclusion… where I have some kind of database data warehouse data, lake, I get lost in all the terminology, but you have a bunch of data somewhere and then you have some AI tools that sit on top of that to help you to figure out this cookie was when he went to this website. And this, you know, transaction was also Aaron because that’s tied to his credit card number. And, you know, some kind of AI that’s making sense of the data. And then maybe an additional layer of AI that sits on that to kinda analyze it from a, almost a psychological perspective like, a human behavior perspective, plus marketing. This is like they did these things. Now. They’re most likely, you know, kind of getting into generative or predictive AI like this is their next most likely thing that either we want them to do to increase profits or we want them to do to donate to our calls, or we want them to do to go to our university or, you know, whatever the use case is and then to send them a message through whatever channel makes the most sense to try to move them, you know, one step closer to that goal. And if you’ve got a system that can do that, then you don’t really need much in the way of an AI. You don’t really need much in the way of like a preplanned journey or automation. It’s really just the system kind of looking at each person and seeing if there’s any communication we can send to them that will increase the odds of them doing what we want them to do. So.

Anthony Lamot: It actually ties in to some stuff we do as well. We are already integrating a bunch of AI capabilities, you know, into our product. In fact, for this segment, we are already in alpha with people using natural language to create segments and not just that generates the SQL but it’s actually, you know, visible in our EDI. So also non technical users can really understand what’s going on. So it’s kinda cool because we just want to integrate speech to text so soon you’ll be able to just shout at your laptop to build a segment. I can, to do that.

Aaron Beatty: Right. I already do that. Actually, it just doesn’t listen. It’ll so that’ll be great. I’ll be like hang it, do this thing. It’ll be like, okay, it’s done. I’d be like great. That was.

Anthony Lamot: I can see, I can see you go“why don’t’ you listen?” and then it tries to explain very meticulously why it’s not listening.

But one one thing that, that’s also interesting to me is doing more campaign planning and optimization that’s what we’re doing with Engage two people using it now to plan their campaigns, making sure the segments are not being over-engaged with or over-saturated, right? Marketing frequency. But we’re now also introducing not generative but predictive either to allow people to still set rules but to also let the system come up with an ideal send volume per contact. And then even beyond that, thinking about maybe the marketer opens the platform and we can just go hey grade up on all those campaigns. But did you know this specific audience is under served? And then once this, these are the commonalities. And then two, these are recommendations, that we would give to you to do campaigns around like to do a campaign around this product category, probably have this kind of response. So we’re not there yet, but I do think that’s a really exciting vision to work towards. And I think that’s a bit the future of marketing. You wanna offer this… mission control center to marketing operations folks so they can much faster make decisions, and work out your planning. I think that’s really interesting.

Aaron Beatty: Yeah, yeah, no, I think we’re just at, the beginning, of what’s going to be available there. Because if you take, you know, what you just mentioned out as a kind of natural next step, you know, there’s already, you know, chat GPT, and other tools like, you know, Midjourney, and others that can start to create content given a specific tone. And so if you have, a brand tone or a language that your brand uses, but also you wanna make your language unique to the segment that you’re speaking with, you know, it’s almost like earlier when you’re talking about code-switching, for different verticals. It’s kinda the same idea you could do that, for your segments too and still maintain a brand voice, but have it match who you’re trying to talk to. And so you could certainly ask a copywriter to do that. And I’m sure the results would be fabulous. The challenges is the volume of requests and the quantity of segments that you might end up having. And so if you have a tool that can assist with that, even if it’s a first draft, to do that, and kind of go the rest of the way or maybe 80 percent of the way to generating the actual content and then rely on the human being for the last 20 percent to make sure that, you know, there’s not a crazy, you know, third arm or sixth finger… on image and you know, that kind of stuff. And that’ll get better with time too. So, yeah, I think it’s gonna be amazing.

Anthony Lamot: You mentioned that because what I recently did is so, in our team now, I’m still doing a little of enablement and a lot of product knowledge still sits with me. So one of the things, I enjoy doing too is sort of educating our own team. And since we also want to better speak to those codes, to use that same terminology, right? So to have more specific language, I started a little project where I was verticalizing some of our internal documentation. So we have very extensive internal documentation on our products, they use cases and then how that goes into benefits. And I CP, and all that good stuff. But I didn’t have any industry specific knowledge. So what I did was I opened a new session, I pay for the subscription have or significantly better point then I just, yeah, and I just went to our website and I did copy paste all dumped it into like, hey, this is what we do. Read the website and it just reads it. And then I said, okay, now try to think of typical use cases for marketing operations in insurance. And so then, okay, and I do a little bit of fact check like does it make sense? As I understand at I’m, trying to do, okay, now merge what we’re trying to do and explain me in insurance language, what we’re trying to achieve, right? And then I still edited a little bit, but I made that part of our internal documentation. And I’m just going through our, I started with insurance because that’s one of our typical verticals but there’s a number of verticals we serve. So now I’m doing that one by one. So I thought it was a really good use case to use something. Yeah.

Aaron Beatty: Yeah, that’s cool. I mean, and otherwise, it’s overwhelming with the amount of, you know, if you were gonna take that information and create like one pagers, for conferences or take that information and create an e-mail or have a, you know, a subsection or landing page of 

Aaron Beatty: And so if you have a tool that can help kind of, you know, I like the thought of maybe, you know, you put in the first 10 percent, the AI handles the middle 80 percent and then you handle the last 10 percent. Like I like that, it’s like a weird version of the Pareto principle, but, you’ve, got the chat GPT doing like the middle 80 percent of the work and that’s a huge time saver and it’s generally pretty good like, you know, with the proper questions and the right language and the right information the results, are pretty good and you can give it really detailed, you know, requests for what you wanna do.

Anthony Lamot: I did something similar for our page and kind of coming up with target personas and customer avatars and things like that for our business. And, you know, it was telling me that marketing Mike, is looking for help with XYZ and we call the persona “Marketing Mary”. I got Marketing Mary out of chat GPT, and, but like you can dig into, you know, what are, so for this personas, what’s there? What’s their greatest fear? What’s the, what are the things that they’re terrified about? Why? What are the things that they’re that are driving them to make decisions? And so you can start asking it some really interesting questions about what might be driving some of the psychological behavior and like motivations of somebody making a purchase. And, you know, it’s hard to know whether the results are accurate or whether they’re you know, true to somebody’s like psychological needs. But when I read it, I’m like, okay, yeah, I mean, that sounds right? Like I can see myself in that person’s shoes and think, yeah, I’m scared to fall behind in technology or I’m scared with joining with a partner that, that’s gonna just take my money and run or they’re gonna, you know, they’re not gonna give me the service that they promised upfront. And, and so, you know, it’ll lay all that stuff out which you can then turn into marketing and kind of target those behaviors and those thoughts with, you know, we’re gonna solve those problems and not just here’s our product here’s what it does because, you know, most people don’t buy stuff that way. So, yeah, it’s cool. It’s an amazing tool.

Anthony Lamot: You also mentioned Midjourney, I’ve heard several people mentioned I haven’t had looked at it yet, is it significantly better to write content? Because I do find GPT to content it generates can be a little bit generic and dry.

Aaron Beatty: Yeah. So mid journey is more of an image creation tool. It’s and it is, yeah.

Anthony Lamot: Yeah. You referred earlier to some other tool then? My mistake.

Aaron Beatty: Yeah, I can, I did refer to Midjourney but I’m thinking of it more in the context of, you know, if you’re going to build an e-mail or a blog or whatever, and you need both to generate an outline or some content. And then generally speaking, you’re going to have some kind of imagery to go with it. And so Midjourney is a really great tool for that. The weird thing about it though is that it runs through disco. And so it’s a little weird that you have to download like a effectively a chat client and discord, and then install the Midjourney bought. And then you can ask it to do things but, it does a phenomenal job and it, and it’s it craves details. So you can tell it. In fact, you can use ChatGPT to generate a prompt for Midjourney and in get it’s help to get exactly what you’re looking for it to create. So it’s great. But yeah, for me, those are the primary two tools that I use. I know there’s probably, you know, millions of other options out there at this point, but I’m like you, I paid, for, the fancy, your access and, you know, to have API access and I have ChatCPT for and it’s so good. I haven’t really needed, to try any of the other tools yet.

Anthony Lamot: Awesome. Well before we round up, I was wondering Aaron if you have any parting advice you worked with so many customers. You’re taking on new customers? What is something a new Salesforce Marketing Cloud customers should be aware of? Or something like what some good advice you can give to avoid some common pitfalls?

Aaron Beatty: I think, the thing that I see happen all the time… is that… a lot of times a client, a customer will be looking to replace their CRM and build out marketing cloud and do all that kind of all at the same time like they get a nice big budget or grant or whatever to go build this thing out. And what I see happen all the time that drives me a little bit crazy is a ton of time effort and resources will be put into the CRM side of that equation. And then the after thought is, well, what are we gonna do with that information? Once we get it all centralized? And so, you know, inevitably, you know, marketing cloud or some kind of outbound communication thing is one of the systems that will utilize that CRM data. And so as somebody that works in that space, it’s always frustrating when, you know, let’s say a company has a 1,000,000 dollar budget. You know, they’re gonna want to spend as close to a 1,000,000 dollars as they can on the CRM. And then they go, yeah, we also want to be able to send emails and so that ends up being the 10,000 dollar project to the 990,000 dollar CRM project. And it, you know, not to say they should be 50 50, but they’re definitely should be a lot more investment in the, what are you gonna do with the data? And in addition to that, I think it’s important to consider what are you gonna do with the data first? And, and for a lot of these setups it’s last, it’s, the initial investment and time and resources, is spent in what data do we have? Where is it? And how do we structure and organize it so that it’s all in the same place that’s effectively what you’re doing with the CRM, but they’re not thinking about what are we gonna do with it from there? How are we gonna use it? You know, what are our use cases? And, and so I feel like a lot of places get that backwards. They need to, they need to do that first, and then go work on.

Anthony Lamot: I think that’s very sound advice. I would also second that by saying that marketing cloud ultimately is a data driven product. And so you do have to start thinking about the data first. And then all the good stuff can follow. If you start with that, Aaron, it’s been a pleasure. It’s again a great pleasure, to speak with you. I feel there’s so much more we can explore but our time.

Aaron Beatty: Absolutely. Thanks so much for having me. It was great.

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