Speaker 0: Hello, everyone, and welcome to MarDreamin. We are so excited to have you all joining us today. My name is Kate Godley from Sercante, and I’m gonna be moderating today’s session. Before we get started, I do just have a couple housekeeping items for you all. Um, the first thing is that all of these sessions will be recorded and will be available on demand after the event. We’ll also be following up with links to the sessions via email. Um, if you’ve got a question throughout the presentation, be sure to post it in the q and a tab above. We’ll have time at the end, uh, to review some of those questions. Um, and then, uh, lastly, please use the chat. Uh, there’s emojis, GIFs, and more. We definitely want to hear from you. Um, and without further ado, let’s go ahead and get started. I wanna introduce you to our speaker today, Aaron Stamen. He’s got an amazing session ready for us all about Pardot, Butter, and Chocolate, bringing your Salesforce ecosystem data into marketing cloud intelligence. And with that, I’ll let Aaron take it away.

Speaker 1: Alright. Cool. Thank you, Kate. I’m gonna start my screen share. This is a presentation with a fun deck. Uh, we’re gonna be engaged both in looking at the presentation and, uh, also going into the marketing cloud intelligence platform. Uh, we’ll talk to you a little bit about that in a second. Um, but let’s do this screen share. Um, so what you’re looking at on your screen is our presentation. And first and foremost, in that presentation, of course, how can we not thank our sponsors? Um, you know, really making the the dream come together, another year of March even. So thank you

Speaker 0: to our incredible sponsors for for making this happen.

Speaker 1: Um, the next thing that we’ll talk to just really quick, uh, we talked to a little bit about this at the top, uh, but we wanted to let folks know about just what’s ahead for this week. Uh, so the Genius Bar is back. If you’re not familiar with what this is, these are one on one consultations with an expert. Basically, you can consider it free consulting. If you take a peek at your navigation bar on Goldcast, uh, you can see, uh, the sponsors and resources up at the top. Uh, this is where you’ll go to find the Genius Bar booth and book an appointment. If you’d like to take advantage of this free support, you should do so soon. Uh, we are seeing that appointments are limited. We’ve seen a number come in already. We heard people loud and clear last year about not wanting to miss our sessions to go to these events, um, but you can now see that you’ve opened these across, uh, the week to start earlier and go later and really just extended through the course of this week of March. Um, the other things that we’ll just note, workshop day, it’s not too late for this to sign up. Uh, our workshops are happening on Thursday. So if you haven’t purchased your pass, there is still time to do that. Uh, your pass will get you access to all 13 workshops to attend live and or watch on demand. Uh, and last but most importantly, as Kate alluded to, all of these sessions are gonna be recorded with the exception of one, uh, which is our product road map happening this afternoon. That won’t be recorded, so be sure to check that out live. Otherwise, you’ll be able to access recordings of this session and others starting twenty four hours after Marjorie concludes. And with that, we’ll get the the other items out of the way and get you your unique your unique content. Uh, if you are here for product butter and chocolate, bringing your Salesforce ecosystem data in your marketing cloud intelligence, you are in fact in the right place. Uh, so I’m Aaron Stamen, as Kate mentioned at the top. I am our marketing pro analytics program manager here at Circante. Before we dive into talking about me, uh, we would love to hear about you. So Kate is gonna put two poll questions in the chat, and we will see those as they are live. Okay, folks. Just a minute to answer these. First question is, are you using Marketing Cloud Intelligence? Uh, the reason we’re asking this question is just to make sure we know our audience and, uh, understand where you’re coming from in in regards to knowledge of that tool. And, um, let me just verify with Kate. Uh, as we close down that poll, we can get you some results here. And Kate has now put our second poll question in of what Salesforce tools would you want to bring into an analytics tool like marketing cloud intelligence? Whether you’re using it or not, uh, what are the the pieces that you would like to to construct your data out of? So those are a number of Salesforce products. Um, as many of you on this session probably know, there’s a lot of Salesforce tools. Uh, so choose which of these are useful to you. And, uh, you may need to choose other if it’s not represented. But, hopefully, this can give us a start we want to look at.

Speaker 0: And, Aaron, if you want, uh, for me to share the results of these polls, you’ll have to stop sharing your screen, and then we can share them.

Speaker 1: Yep. Let’s do it. Alright. So these are the votes. Uh, so out of what looks to be kinda ten years, this this cuts pretty cleanly as round numbers go. Uh, about 20% of you, two people, are using marketing cloud intelligence. 80% of you are not, which makes me very happy for the way that I’ve laid out this presentation that I I planned for that outcome of people not using this tool. Um, so that’s great information to know. And what tools would you like to bring in? We’ve got zero votes across a lot of these, a lot of abstention. Uh, if we if we scroll kit, do we have any any votes on this poll, or did people choose to sit out this election? Oh, I can scroll through it. Sorry. Yep. Yep. Yep. Yep. Okay. 15 votes on on account engagement. Well, boy, do I know my audience then. Uh, it’s in the name. So I guess that’s why a lot of you are probably here. Uh, again, glad to to have some of that validation. Um, I’m gonna click the stop sharing poll button, and we’re gonna go back to the deck and get you into a world of fun with, uh, marketing cloud intelligence and talking especially to carve out data. So we’ll we’ll try to center this presentation as much as possible on that. So that’s the poll. Uh, the next thing we’re gonna look through is just to talk about what we’re gonna go over today with, uh, that poll data in mind. Uh, as noted, only two of you are using intelligence. So we’re gonna talk about what marketing cloud intelligence is, what the value is that you can get out of that. We’ll talk through some of the interactions of different tools with marketing cloud intelligence as well as best practices for that data. Uh, as much as possible, I I heard my audience loud and clear. I think a 100% of people agreeing on anything in this day and age is is shocking, uh, but it sounds like you wanna know about how to bring Pardot and account engagement data, uh, using those names interchangeably here, uh, into analytics. Uh, so just a brief bit about me. Kate gave a very nice intro earlier, uh, but I have been in the ecosystem of what is known alternately as Datorama or Marketing Cloud Intelligence since 2018. I was part of the team when it was known as Datorama formally. Uh, as part of that acquisition, worked with Salesforce as part of the Salesforce organization, uh, until about 2023 when I came over to Circante and became a certified MCI partner, uh, last year. Uh, just a last fun fact is that I am also a Salesforce marketing champion advocating on behalf of, uh, marketing cloud intelligence, especially, and doing thought leadership there. Uh, not a a relation to marketing cloud intelligence or Danorama, but I’m also based out of Newmark, which is a little bit about me as a person. Um, so to talk about what brings us here, I just wanna first talk about marketing cloud intelligence, understanding that this may be new for some people, not so new for a few of you. But as far as analytics tools go, it is a tool completely built by marketers for marketers. It’s got, as you can see on the screen and we’ll we’ll dive into, uh, in real life in a little bit here, it’s got over a 125 different connections to data sources, uh, most of those being marketing centric, uh, whereas the screen scrolls here, you might see Amazon ads, you might see Facebook ads, you might see Google ads. Um, the platform, uh, formerly known as Twitter comes up here a few times, Google Analytics. Basically, a number of different data sources that you can natively connect without having to do a lot of technical lift to get data on your marketing analytics. One of the really neat things about this platform is that out of the box, it models your data in a very clean-cut way. We’re gonna go through that in a little bit. It really makes it easy for especially for nontechnical people to have really an an on ramp of being able to bring your data in and not have to think about, you know, what is my my querying language and things like that as you use the platform. Uh, it’s built around the idea of ingestion, reporting, and visualizing. Uh, basically, the screen that is scrolling through endlessly here is your data ingestion where you’re choosing your different datasets that you want to bring into the platform, and then there’s built in reporting and visualization tools that come into this also. Uh, and the reason, again, that a lot of y’all are presumably here for this session is that marketing cloud intelligence interacts pretty smoothly with the Salesforce ecosystem. So just a little bit more about that platform. Why do we call this session, um, Pardot Butter and Chocolate? Right? If we’re talking about marketing cloud intelligence, the idea is when I when I was still DataRama as an organization, we used to talk about peanut butter and chocolate all the time. Uh, the combination of different data sources being able to tell one coherent data story. Um, it’s a compressed image on the screen, but being able to see data across all of your datasets, being able to see what’s happening on your website, what’s happening with your ads, what’s happening with your leads and opportunities, being able to see all of that together. Um, I think for a lot of you on this call, you’re not necessarily marketing cloud intelligence customers right now. Um, but so often the selling point of this platform is being able to look at, like, Google Ads and Facebook together and all of these different media channels where you’re having clicks and impressions and engagement information, uh, that are effectively being brought into the platform. Uh, not so often do we see the full funnel, uh, fully realized with Salesforce data. So that’s what we’re here to help you tap into potential wise today. And really just going with the name, we think it’s a delicious set of possibilities to bring all of this data together. And, Kate, I’m gonna have you share as as I think we talked about, and I I just, uh, have my slide deck up. We’ll be sharing out just a little bit more information about this, uh, accessible for any of you. Uh, it’s a public link. But just to to learn a little bit more, uh, on the side if this is something you’re interested in, very brief, uh, walk through of what Marketing Cloud Intelligence does so well is that it has what’s called data models built into the platform. Uh, so it uses AI to grab any of your datasets. Uh, for any of the APIs that you’re bringing in, like Google Ads, it automatically does some of this work. Uh, but, effectively, you have things like ads data that’s built around MediaVise. We’ll go over that in just a moment. Uh, web analytics data, search data, email marketing, CRM data, all kinds of different marketing centric datasets that rather than you having to manually define are built out of the box, uh, for your utilization. Um, typically, I see ads and conversion are the most frequently used. I mentioned a moment ago that a lot of the time, the platform is really used to aggregate data across, uh, multiple paid media sources. And so that’s the the datasets that we tend to see the most frequently, uh, used to to optimize your media performance and the spend therein. Um, in addition to that typical model and any of these other typical models, there’s also a data type called generic data. So if you’re using your your platform for nonmarketing data or data that doesn’t fit into any of these buckets, You can also bring in data through what’s called a generic dataset and effectively build kinda your own database out of this platform as well. Um, so just to walk through the most common thing that we see, we see data reported on about media buy data. So that’s anything that you’re you’re buying, potentially an ad on a website, let’s say, just to make it very concrete, uh, for in case this is jargon for any capacity. You’re buying an ad on a website. Sometimes you have multiple ads or media buys that you’re you’re putting on that website. So you can see one website, multiple media buys, and same thing with the campaign. You’re running a campaign media buys within there. The platform accounts for all of this. You optionally have creative exchange and strategy data that you’re using as well. Um, but really the platform just out of the box plans for you to have a built in data model that you don’t have to think about. It knows, hey. You’re you’re trying to advertise on a website. We’re gonna build in the elements here and just make this as straightforward as possible. Uh, within those datasets, you also have different values that you can associate that are quantitative data points. Uh, those tend to be clicks, impressions, and costs when it comes to ad data. And all of that comes together in the platform, um, effectively through two screens. You have data come in, uh, this is just sample Twitter data from when that platform is still called Twitter, uh, where you’ve got data coming in across campaigns, across different days, across impressions and clicks, things like that. And the platform, all through AI automation, knows that these are the things that you’re trying to bring in. It’s campaign data, it’s media by data, it’s impressions, it’s clicks, it’s media cost, and effectively just names these in plain language that are easy to understand and allow for a really easy dashboard build out, uh, to come out of that where you’re able to report on these things, again, without having to do multiple different joins and, you know, different programming pieces, effectively just able to put this out in plain English. Um, so just some other things about these Salesforce connectors, the the core piece of why we are in this session today. Um, so what we’re looking at in terms of these connectors, we’ll start just by listing out what we’re talking about here. So different Salesforce connectors are available, uh, out of the box, and those include marketing cloud engagement, marketing cloud account engagement, knowing my my audience here, you know, uh, sales cloud reporting, commerce cloud, marketing cloud advertising. Uh, there’s just a lot of possibilities of what you can bring in, and there’s a lot of customization even beyond that, which we’ll we’ll touch in a moment in terms of just the technical vendors you can utilize. Uh, so we’ll talk about that as we go forward. This is a a basic overview and, uh, just a picture in the screen of what you see when you search Salesforce in Marketing Cloud Intelligence. So we’ll start with the out of the box connectors. Uh, there’s really two categories that I just like to note. So out of the box would be anything like the Pardot or account engagement connector, um, and Salesforce reports, different things like that. And then we’ll talk through as a separate section, just the more technical connectors. Those will be your SOQL where you’re doing any kind of queries, where you have, uh, data cloud, any of these more technical pieces where you need to query in some form or fashion that’s not standardized. So, again, knowing that we had the poll at the top, I just wanna be mindful of the pieces that people are most interested in and try to go through these other ones probably a little quicker. Uh, as you have questions, feel free to add them to the chat. Kate will raise these, and we’ll we’ll dive more in-depth as desired. But marketing cloud engagement, just to give this a brief summary if this is something you’re thinking about, uh, one of the easiest connectors to bring into marketing cloud intelligence. Out of the box, it has a connector built in and effectively allows you to just bring in, uh, messaging data and effectively customize what that looks like with not so much in the way of, uh, effort and certainly not much in the way of coding. Um, but effectively allows you to add in Mobile Connect, Mobile Push, any of these other data views that you wanna bring in just by clicking a few checkboxes. Um, it’s mapped by default into this messaging data model. Uh, you can’t change what data model you’re using for marketing cloud data. That is one of the things that we’re gonna go over as we talk about the difference between the out of the box and the custom connectors is that you don’t really have a lot of control as to how your data joins together when you’re using the out of the box Salesforce connectors, um, but with the the technical ones, you do. One thing that I’ll also note, if you’re using data extensions, if if marketing cloud engagement was to you, um, there is a separate connector to bring those in as well. There is also an email application. There’s not a ton of these in the platform, but one really cool one they have is this prebuilt email, uh, dashboard effectively that all you have to do is set up your credentials from this marketplace that they have. Uh, it’s completely free, but marketplace is just the name they have for extraneous pieces that are not defaulting. And effectively, you can bring in this pre built email connector, um, to visualize your data really quickly as like an out of the box just setup. One of the reasons that I also bring this up, and this is not a common thing, is that sometimes if you’re using the Marketing Cloud engagement connector, that it doesn’t retrieve data properly. I’ve only seen this once or twice, uh, but this app is a really good workaround also to be able to grab that data. For some reason, it has an even more direct connection to the the Marketing Cloud platform. Um, so I just leave this in here as a note. Again, we’re recording these sessions, so if you’re looking to go back and perhaps you’re a Marketing Cloud intelligence user who’s looking to to bring some of this data in, Hopefully, this is helpful information for you to refer back to. And now the thing everybody has been waiting for, try not to keep you too long to to get to the good stuff, uh, but there is an account engagement connector out of the box in the platform. It still has the legacy name. You’re gonna find this a lot. Uh, so if you’re a person who likes what Salesforce used to call products, uh, you’re gonna be really happy with Marketing Cloud Intelligence’s options. Uh, there is a connector for Pardot, as I mentioned, as the name, and it’s really robust. It can provide, uh, all kinds of different data, but there are some catches with that, namely that it’s broken out, as you can see on the screen, uh, into messaging, CRM, CRM lead, and conversion tag models. Uh, those with too much to dive into for the sake of this session, uh, those are prebuilt connectors that exist in the platform or rather prebuilt data models that you really don’t have full control over. Um, there’s really just not a lot of customization of what you can bring in, uh, in terms of the data model when you’re using this Pardot out of the box connector. So we do have other ways that we recommend going forward with that data. If you don’t have a lot of customization from what is pretty cookie cutter and built into account engagement, if you don’t wanna customize the way your email is being read, if you feel fine with the way the forms are reported, uh, There’s no real cost in setting that up up that extra data connection, but when you get to the the opportunities, the prospects, and any of your other CRM data, it works very differently than other data does in the platform, and we’ll we’ll talk about this later on. Uh, but that is just something to be really cautious about. If you’re a marketing cloud account engagement user who’s looking to add that data to marketing cloud intelligence, we do tend to give the guidance that this is not the best connector to utilize. Um, so what is that? Uh, we do recommend Salesforce reports. Anything that you can query as a user, um, for any of your CRM data, that tends to be a really valuable way to bring the data in instead. Uh, any report that you’re able to access as a user is available through the, um, Sales Cloud connector or the Salesforce report connector rather. Um, so you can also modify if you’re trying to figure out how do I customize the data that I’m bringing in. One great thing about the Salesforce reports connector is you can choose different data model types also to bring in. Um, the one caveat that I would express, and for those of you not using intelligence, just a caveat in general of Salesforce reports if you’re trying to bring to other systems, is that you can’t use more than 2,000 rows per export. So you really have to be particular about the kinds of data that you’re trying to draw. Uh, so that’s just one possible way. We’re gonna talk a little bit more as we get into the technical later about some other options. Um, but some of the other Salesforce, uh, connectors that we have are Marketing Cloud Advertising. Uh, this used to be known as Advertising Studio. That’s what it’s still brought into the platform as. And it brings in a small set of data from Marketing cloud advertising. Um, it’s not one of our most used connectors, uh, but if you need the data from it, it’s useful. You can also customize the way that it’s brought in. Uh, I would like to take this opportunity to kind of shake up things a little bit and have a presenting our data to you, um, which is to show you how we look for for these connectors. So as you may have seen on the screen just a moment ago, we were looking to see what options were available to us in terms of the fields brought in to these connectors. So when I look at my data sources across our Marjorie Mint instance here, this is just a very small sample snippet. If I was to go to click create new, and I was to search for a Salesforce data source, I can come in here and the same way that I had shown on the screen before with Advertising Studio, um, effectively, I can click this little learn more button that I was just hovering over, and it’ll tell me about the different types of data that’s coming into the platform that I can bring in what it deems as Advertising Studio, bring that data into Marketing Cloud Intelligence. There’s a help article here. I’m interested in that. And most importantly, it shows me the different datasets. So as you’re thinking about if you are somebody who came to this session thinking about an analytics tool, thinking about how as a marketer you can better report on your data, I really like that this platform allows you to see these different datasets. Uh, you can export the dataset, uh, showcase of of what fields are available to be brought in, you share with your team members. You know, if you’re trying to figure out what data sources to use, it just really makes it straightforward that you don’t have to go through building it out without a blueprint. Instead, you’re able to kind of see at step one what’s available in this platform. And that exists across any of these tools. So just something to note that I I think makes for a really great, uh, process as you’re you’re thinking about analytics. I’m gonna take us back to our deck here, and we’ll go to the next slide. Um, the next one, Commerce Cloud. Uh, two different types of connectors exist for this just very briefly. Uh, both have their own datasets and tied to an ecommerce model in the platform, uh, and require some extra permissioning if you’re trying to use that. And, unfortunately, like a lot of different datasets that we’ve talked about, um, you can’t really change the data model type. Um, so I’ll go forward, and I see some great questions coming into the chat. So I appreciate all the engagement here, and we will we’ll definitely move into those questions as we go forward here too. Uh, we’ve built in some time for that. So the technical connectors, which tie to to the data cloud question that I see in the chat as well as to to some of the account engagement piece, uh, these are a little more free form. And, frankly, if you have the the bandwidth and the knowledge the way that we kind of recommend, I will caveat this as the Kate sends out a lot of articles section because there is a lot to learn. This is how you’re using the platform. So, uh, Kate is at the ready, and I just want to make folks knowledgeable that if any of this seems overwhelming, we’re sharing out, uh, resources to think about for later also. So without further ado, uh, thinking about how you bring in marketing cloud account engagement data and how you bring in sales cloud data, We also strongly recommend using Salesforce object query language (SOQL). Uh, this is something that in addition to being very knowledgeable about intelligence, I feel like I’ve become very into the space of Salesforce, uh, object query language usage. So it’s a technical vendor in the platform. There’s not any kind of preset we were talking about before where when you’re bringing in account engagement data from what is deemed the Pardot connector, then it’ll do a lot of that work for you. It’ll bring in your message send names. It’ll bring in your message subjects, um, you know, the date that something was sent, things like that, your bounce rate. Uh, but with SOQL, you’re basically starting from a blank canvas. Uh, it is easier than it sounds, and I’ve actually provided here just some skeletons. So if you are not somebody who’s using intelligence but you’re using SOQL, hopefully, this could be a helpful piece, uh, for those of you attending today also. Um, but you can get the same kind of things that you get out of the Marketing Cloud account engagement connector and the Salesforce report connector, but with a lot more flexibility. One of the things that I just recommend, uh, if you’re ever testing this either in intelligence or in the workbench in Salesforce, um, I tend to set the the the SOQL version to the most recent version, in this case, ’59. And I use a query that I’m just leaving on screen. Again, just a helpful reference point for for those of you looking to do this later. Um, I do a select statement where I say select fields all. I I tell the platform, bring me from whatever object I’m looking at. So in in some cases, that might be from leads, it might be from contacts, whatever the back end name is of that, uh, object. And then I have the platform limited to 10 rows so that I can just get a quick file to take a look at. And just this is my my general tip for quick setup, uh, to be able to bring that data into marketing cloud intelligence and be able to kind of have your own freeform way of looking at data points. And this is when the, uh, barrage of help articles is gonna come through because these are are more complicated and more recent connectors. Uh, so the, uh, the generic data model is one of those things that we wanna just highlight here where you can see on screen that there’s some customization. You can see that red f indicate that we’re doing some formula work and things like that. Um, but, basically, the CRM model that we’re showing in account engagement before out of that connector exists with, like, lead data and some other pieces, uh, that help you to effectively, uh, bring in data the way that marketing cloud intelligence thinks that you wanna bring in CRM data. My general experience as somebody who’s particularly geared towards this platform, but not as much towards Sales Cloud or account engagement as my main knowledge sources, is that frequently, um, no two instances of what we’re trying to bring in from Salesforce look the same. So utilizing this generic data model effectively allows you to have a lot more customization to be able to look at your fields differently, be able to combine different datasets, and effectively set up the data the way that you want it. You know, in the instance here, if you can see it on the way that we’ve mapped our day data, I have closed date for our opportunity set as the way that I’m measuring against days. Some people wanna see their data measured out by created date. Maybe you want both. Um, all of that is more customizable in this version of the data model. Uh, you do lose some ability to see how your opportunities are progressing, you know, if on a certain date they were closed or if on a certain date we’re open. Uh, but I find that the trade off is generally more user friendly by using generic data models. And, again, Kate shared out that link on, uh, what those look like. So if anything here is confusing as to, like, okay. This is all over my head. Uh, you can take this away and read it in your own time and and make sense of that as well. Other pieces that we just note for those of you who are in this platform for things that you might wanna consider, uh, we have a blog that I will, uh, shamelessly promote here that I I think is helpful for this. Uh, there is a mastering, uh, marketing cloud intelligence blog that we’re showing to kinda talk through this. But as you’re bringing in Salesforce data, it’s useful to use, uh, what we call data fusions to effectively be able to map up, uh, your campaign data, for instance. Anything that you have coming out of your CRM platform tied to effectively your paid media and the way that you’re you’re sharing this, uh, with your datasets back end. Uh, we also recommend doing calculations on channel and lead source and combining those things, really, to help you basically bake the cake of what’s going on with your marketing data all in one place. Um, sometimes you may also want to combine your cost data and things like that with different measurements. All of that is possible with calculated dimensions and measurements in the platform. And as noted, just as a a takeaway, Kate has shared that link in the chat. So if you’re looking to figure out some of the ways to do this, hopefully, that can help spark ideas. And then, of course, the the burning question, it wouldn’t be, uh, 2024 talking about Salesforce without talking about data cloud in some way. Uh, so this is one of our our newer connection points. Uh, I do recommend heavily greeting the the Salesforce help page as it walks through all the things you need to do between both platforms to make the connection happen. Uh, this is a technical vendor as we were talking about with SOQL before. It is free form querying that you need to do to be able to draw on your data, so it is a little more complex. There are the options, as you can see in the screenshot, to evaluate and validate your queries. So if you’re trying to figure out how to make this all make sense, uh, that is a way that you can make sure that you’re doing things correctly before you’ve tried to save and run into an error. The idea really with this is that you’re able to harmonize some data in data cloud. And ideally, for any of you using that, that you’re able to use that process and pretty easily then share that data out to marketing cloud intelligence and pretty seamlessly already have your data monitored in a clear way and bring that into the data model that you have existing intelligence to better visualize and effectively build quick dashboards out of the platform. One thing that I will note, if you are a single sign on organization, uh, there is not currently a connection option that that works for data cloud to marketing cloud intelligence. Um, if you are looking to dig into that further, Salesforce support might be able to help you out, But that is just a blocker that I wanna know that we’ve experienced so far with this connect. And then we’ll talk about marketing cloud personalization, and then we’ll get into some takeaways and some questions. Uh, so like the pieces that we’ve showcased before in the rest of this section, yet another technical vendor, uh, and yet again another tool that’s listed under a legacy name. Uh, personalization is listed as Interaction Studio Marketing Cloud Intelligence. And in order to set up, uh, the queries in the platform, uh, once again, we have an article that Kate will share out, uh, and has shared out rather, uh, on Interaction Studio and how that connector works. Uh, so that’s just something to note. Once you do an initial setup, you can also query datasets in the the platform, again, using the same kind of box that we had in data cloud, but with a few more, uh, configurations there. So general takeaways, and then I wanna address some of the questions that I saw come in the chat as well. Um, really, Salesforce and marketing cloud intelligence, there’s a lot of different flavors that come together. Um, we personally, again, just to emphasize we’re too fine of a point here. Uh, using SOQL is the best way to bring any of these things together. Uh, there’s a lot of out of the box connectors that exist, but anything that you can query with SOQL, we really strongly recommend, as well as using generic datasets, uh, for any of your Sales Cloud and account engagement data. And just my personal plug, uh, for intelligence is really if you’re looking for a full funnel marketing story, we’ve showcased some of the, uh, Salesforce connectors. But as I mentioned, there’s hundreds of different connection options to bring in your marketing data, and it’s really a low lift no matter your level of technical knowledge. Uh, I really strongly recommend this tool. Uh, and with that, I’m gonna turn to Kate to, uh, talk us through some of these questions, and we’ll we’ll have conversation on that front. Welcome to the stage, Kate.

Speaker 0: It would help if I had my microphone by my face, wouldn’t it?

Speaker 1: Uh, hey. Oh, the suspense. Yeah. I think that’s great.

Speaker 0: Uh, you did note that, uh, you saw a question on data cloud. So this is from Matthew Clark, uh, wondering with Salesforce’s focus on data cloud for AI and other data related purposes, um, does that mean that digital ads and related models should eventually move to data cloud? Um, that would allow for people to build audiences using AI segmentation instead of relying on that marketing cloud intelligence.

Speaker 1: Yeah. And I I think there’s there’s validity to that. Right? Like, I think that so much of the intelligence model, first of all, is evident in what’s in data cloud. I I’m not saying that learning marketing cloud intelligence is gonna make you better at data cloud necessarily, but even just thinking about like, if I go back, uh, just in the presentation a little bit here just to to visually demonstrate something, Uh, where we have any of this connection piece where we’re bringing in data and at the top of the screen, if if people are able to see that if you’re in full screen mode, any of the mapping that you’re seeing in data cloud is very similar to the the style of intelligence. So just bearing in mind that a lot of the skeleton is is very similar just as as one thing to note. I I think that anything that you’re you’re doing in the future, I think data cloud is a a great starting point. I think that the one breakdown, at least as things stand right now, is the need for a visualization tool. Uh, doing any of the actioning and building out that segmentation is awesome, uh, but there is still the need to be able to crisply and cleanly be able to to do visualizations. There’s some out of the box visualizations that come in data cloud, but really what intelligence allows you to do is is kind of a yes and to that of being able to export your data using a connector like Data Cloud, uh, pushing that data into Marketing Cloud Intelligence and being able to then complete kind of the cycle of being able to visualize that data together. Along with some of the the native sources, Data Cloud has a lot of APIs built in now. Um, but for where there’s not that crossover, being able to join those things is a a better together story in my opinion.

Speaker 0: Excellent. Thank you so much for answering that. Um, and I know that a lot of people may be wondering if it’s possible to see other connectors in the platform outside of Salesforce data. So are you able to speak to that for a minute or two?

Speaker 1: Yeah. Absolutely. Uh, so before, when I shared the way that you you gather data for these different connectors, I was showcasing searching for Salesforce. But in going to this data stream list in the platform, when I click create new, um, it’ll show me any connector that exists. And starting at the top of the bat, one thing that I’ll note, just like a lot of other analytics tools, you can start with a flat file of any kind, where if I click Total Connect here, it’ll give me the option to just drag and drop a file in. It’ll also give me the option to pull data directly through tools like Box or Google Drive or Google Sheets, Snowflake. Any of these different connectors that you have just files from, uh, it’s very free form. And one other thing that I’ll note, you know, there’s there’s value adds to both of these, but just even through the lens of of why this over data cloud. You’re measured on the number of rows that you bring in. So if you are somebody who is looking to bring in tons of different sources, and touch a number of different databases, for instance, you’re not limited to the number of data sources you can have. You’re not, um, dealing with any kind of consumption on the other end. Uh, again, there’s there’s values to both models, but for marketers who are looking to just bring in some of these datasets, um, there’s just really a lot of options that you’re able to utilize. Um, and I’m just slowly scrolling through to showcase some of these other connectors. Uh, the big ones that we see utilized, Facebook Ads is nearly universally used, um, as are Google Ads. Google Analytics, I would say, is in a 100% of the the instances that I’ve ever seen. And just a lot of versatility in pulling this. Um, also a lot of versatility if you’re doing, like, Google Analytics custom data, which I’ve seen for a number of users, uh, to be able to play with that and kind of test what you’re able to use. Um, you’ll notice that here there’s no listed number of fields. You can pull in literally anything from Google Analytics, uh, that you desire. So just a lot of really cool connections in here. If there are other ones that people are curious, I’m happy to talk to those also. Uh, but this is just a a very, uh, brief scroll through some of the things that we’re able to see in here. And I hope that it helps answer the question a little bit.

Speaker 0: Yeah. We’ve got, um, about eight minutes left. So, uh, please, if you’ve got any questions, don’t hesitate to either post them in chat or in that q and a tab. Um, we’re happy to talk through any questions you may have about marketing cloud intelligence, um, while we’ve got Aaron with us.

Speaker 1: Give it just another minute. I know people might be typing. Um, but, of course, just, uh, while we wait, just wanted to say thank you to folks for for attending this session. We wanna leave us without thanking people for being here. And, uh, yeah, we’ll give it another few seconds, and we’ll stop the screen share. And, uh, if folks have questions, we’ll take them. If not, we’ll give you a little bit of a break between sessions, and, uh, really just appreciate everybody’s time.

Speaker 0: Alright. So it’s been about a minute or so. I am not seeing any more questions coming through, so I think we can, uh, call it good here. And at that, I want to thank you all once again for joining us for today’s session. This has been amazing. Um, and, uh, thanks once again to all of our sponsors for their support. Without them, Marj Dreamin would not be possible. Uh, there are some more great sessions coming up in a few minutes, so stay tuned, uh, and we will all see you again soon. Have a great rest of your day.

Speaker 1: Thanks, everybody.