Speaker 0: Great. We’re seeing a lot of people come in. Um, hello, everyone, and good afternoon, and, uh, welcome. We’re so excited to have you join us here today. My name is Nick Contati from Sercante, and I’ll be moderating today’s session. Before we get started, a few housekeeping items to cover. Yes. This session is gonna be recorded and will be available on demand after the event. Uh, we will also be following up via email, so you’ll have that in your inbox as soon. If you have a question, please use the q and a tab above top right, um, and send us over some q and a. I’ll be keeping an eye on them and making sure our speaker has a chance to answer them before the end of the session. And lastly, please use the chat. Emojis, GIFs, they’re all welcome. We wanna hear from you. Uh, now let’s get started. I would like to introduce you to our speaker today, Aaron Stamen, who has an amazing session ready for us today to talk about, uh, marketing cloud intelligence and how we can harmonize our data using, um, MCI.

Speaker 1: Cool. Thanks, Nick.

Speaker 0: Yep.

Speaker 1: Hi. Excited to have everybody here. Of course, wouldn’t be here without our wonderful sponsors. We’ve got this slide that’s been pulled up for a little bit. I hope everybody has got a chance to to see this and, you know, appreciate our wonderful sponsors for helping us to make this event happen. Um, I’m Aaron Stamen as Nick noted, and you are in harmonizing your data with marketing cloud intelligence with me, our marketing analytics program manager here at Circante. That is a world marketing analytics that I I thrive in particularly in the marketing cloud intelligence space. Uh, so that’s gonna be where we’re viewing this session from. We’re gonna talk to you a little bit about the basics of the platform and some of what it can do. And, hopefully, if the Internet continues to participate, we will walk through a in-depth demo as well for the next little bit here. So our agenda today is to just go over briefly marketing cloud intelligence and how you connect your data in marketing cloud intelligence. Um, we’re also gonna talk through of course, the session is named harmonizing your data. So we’re gonna talk about harmonizing your data across different data sources, and we’re gonna review just the platform functionalities in marketing cloud intelligence as you go through and as you harmonize and see what else it can do. So we’re gonna do just a brief introduction to Marketing Cloud Intelligence. It’s formerly a tool known as Datorama. I have been known in my life to slip and call it Datorama even still, uh, despite the name change. So just something to to bear in mind if you know this tool is a different name. Um, these are one and the same, Marketing Cloud Intelligence and Data Realm. Marketing Cloud Intelligence just very briefly highlighted. You can see a moving image of this on the the right hand side, and you will get to see it live as I click through these different things and talk through a little bit more in-depth. Um, but the real value of this platform is that it can aggregate and harmonize your data and act as a constant source of truth in your reporting. Um, you can showcase your data in beautiful user friendly dashboards and also QA your data using built in pivot tables, set up action alerts for when your data hits certain benchmarks, and you can even integrate with tools like Tableau. Um, not immediately out of the box, but other features that you can look into with the platform. There are sandbox environments available to test things with your data before rolling it out to other users. There are media pacing premium features that you can get as well as granular datasets, uh, previously known as data lakes in this tool. And just to briefly talk through before I start showcasing what we’re gonna be doing in marketing cloud intelligence, I also just wanna highlight some of the basics of how the platform recognizes data. So, effectively, data when it comes to Marketing Cloud Intelligence and in most databases comes in the form of measurements and dimensions. So you have starting with, I think, the easiest thing to understand, measurement data. Uh, you have data that is basically numeric data that you can aggregate. So that’s sums, averages, and tends to look like, in the case of Marketing Cloud Intelligence especially, tends to look like media cost, clicks, impressions, likes, and conversions. And then you have the qualitative data that you’re gonna be slicing your data by. That’s known as dimensions. So dimensions might be a text, a date, or some kind of key ID. And, again, this allows you to see your your data in different ways. And examples of that might be date data, campaigns, channels, verticals that you can effectively look at how you’re measuring data by. Um, dimensional data, just very briefly, is also broken out into entities, which have keys and descriptors and can have connections between them, um, such as campaigns being related to media buys and products. And then lastly, you have variable dimensional data, which are stand alone dimensions such as geography or device category or device browsers and pertains to the entire dataset rather than one entity. Um, so just to to briefly showcase an example, and then we’re gonna get into the Marketing Cloud Intelligence platform. But I think it’s helpful to understand just a little bit of context of how databases and how this particular tool ingests data and harmonizes your data. Effectively, if we take the example of, uh, my favorite driving bear, uh, Cody the bear, uh, from Salesforce, uh, who have a who has a driver’s license in the state of California. In this case, I always view the driver’s license as the easiest way to understand how Marketing Cloud Intelligence reads data, um, because it has a unique key of a driver’s license number. This is the only driver’s license with this number in the state of California. And that key that key in the database then has a number of attributes associated, such as a name, which is a very common attribute, and sex, height, and date of birth. Those are all very common things that we see in terms of types of attributes being name and then different descriptors. Um, this is just important to understand because I I think that understanding how data loads into a database is really important for this particular tool. So So just a good baseline to understand. Um, two other pieces real quick are that Marketing Cloud Intelligence, uh, has a number of data models out of the box. This is really a tool that if you’re thinking about analytics and you’re wondering what’s a tool that I should be using specifically for my marketing needs, Marketing Cloud Intelligence really demonstrates that know how of the marketing world by being built around marketing data models. So in a lot of databases, you’re starting from scratch And like I was just showing with the the driver’s license, you’re setting up those keys, you’re setting up the attributes, you’re setting up the the parameters. Marketing Cloud Intelligence out of the box gives you a marketing centric framework. So that includes primarily ads data is the main thing that we see in terms of the data models in the platform, uh, in terms of usage, as well as conversion data, web analytics, out of the box allowing you to plug data in and have a preexisting framework. Um, if you are one of the people on this call who is more familiar with SQL, more familiar with building a database, and has needs other than marketing, the platform also has a generic entity as well that you can make from scratch and use just like a regular database. But for most users, having the ability to have a marketing centric model is really valuable. And I have a link to to documentation on here. I I would say also just to note, this is adapted from Salesforce’s help article on data models, uh, for marketing cloud intelligence. Um, if a person can have a favorite help article, that is mine. Uh, and I just wanna highlight that for folks at home as well. Uh, and lastly, before we dive into the platform, the most common data stream type that we see tends to be that ads data model tends to be centered around media by data, meaning an ad that is placed on a site like espn.com or the New York Times, um, things like that where you’ve got an ad effectively placed on a website associated with a campaign and potentially using one of many different creative values, um using one of many different exchanges or strategy keys and effectively from a dimensional basis looking kind of like this and tied to metrics like clicks, impressions, and costs associated with the ad. Um, that tends to be the core use case that we see in the platform. And with that, uh, enough talking about these different things and enough showing of slides, I’m gonna do a very brief demo of what marketing cloud intelligence looks like and how you use data in the platform. So I’m gonna stop sharing this tab, and I’m gonna do my best to zoom in. I I would recommend for anybody who’s not viewing on full screen as much as I can possibly zoom in comfortably, I will do so. But be sure to set your screen on full screen to be able to to see what we’re showcasing here. Um, so this is Marketing Cloud Intelligence. I have aptly named, uh, Marjorieman workspace that I’ve set up, uh, where I have visualizations that have built been built out for different datasets. Uh, you can see a brief preview here. I have reporting that I’ve put together based on my different social media data and pivot tables that I’ve used to QA my data. But none of that would be possible if I didn’t go to this connect and mix tab and effectively just have a place where I can bring in my data. When we talk about harmonizing, the core thing that I think about is bringing data from different channels together and bringing it into one place in a shared data model. So in this case, you can see very briefly that my demo data that I’ve got in here consists of Twitter and Facebook data. Just a simple join of being able to put this data together and showcase data across channels. I’m I’m gonna showcase very briefly how one would normally get to this kind of data joining, and that would be a really simple process. Uh, I would just go to connect and mix in this platform. If you’re somebody who has Marketing Cloud Intelligence and hasn’t done this before, you’re you’re welcome to follow along at home at platform.datorama.com. And that is the way that you can access this tool. You go to connect and mix. You go to data streams list. And when you click create new, uh, and this is where I think a lot of marketers who have not used this tool might find some value. Um, you have the option to upload a file from scratch either just as a one time separate from the data model or more commonly into a specific dataset that exists across the platform. But before you even think about doing a flat file, you can also explore the 124 different marketing vendors that are in this tool that out of the box, just by clicking on any of these, I can set up a a connection with standard frameworks to my datasets. One thing I also really wanna highlight about this is, say, I wanna bring in data from Facebook ads, but I’m not sure that the data that I’m looking for is going to be there. I’m what’s really great is before you even try to set up your credentials, you can click this little learn more button down at the bottom right corner of any of these APIs. And it’ll tell you just a little bit in the information section a few things. It’ll tell you what you’re able to pull in here, what’s required, uh, as well as the smart lenses that are available. These are automatically created after you create a certain set of APIs. If they list these smart lenses, they will automatically generate a dashboard for you. So even if you don’t know what you’re looking for in terms of design and things like that, you automatically get a dashboard when you create some of these sources. You also have the option to go directly to uh the knowledge center that marketing cloud intelligence has with Salesforce, which also has great information about these connectors. And most importantly, you get the the walkthrough of the datasets that you’re looking at. So if you’re trying to see, for instance, if you bring in Facebook data, if you’re gonna have clicks available to you as a metric, you can just search in this dataset section to see clicks, and it’ll show you the different fields that are associated with that word, whether it’s related to post click conversions, whether it’s related to actual clicks. All of the data that you’re able to pull in is really demonstrated for you. So I can’t really do this justice in the course of just a few minutes, but really there’s a ton of different connectors you’ve got here. I’m gonna scroll through the marketing vendors, um, relatively swiftly and just showcase that you can also bring in some ecommerce vendors here as well as flat files. Um, I always like to joke anytime that I give this presentation. I don’t understand how PDF comes in. I I can explain a lot about this platform, but uploading PDFs is one that I always find to just be technical wizardry. Uh, but getting into the the more serious other options, you also have 38 other technical vendors. So if you’re looking to automate connections to Google Drive data, like a Google Sheet, or if you’re looking to do a custom script to a connector that you built out to an API, you can also bring in Python connectors as well. Uh, so a lot of different ways to harmonize your data across different channels. Um, what I wanna showcase now, just very briefly, is a type of typical dataset that we might look at. I’m gonna switch windows here, uh, hopefully pretty seamlessly and just showcase an Excel file of what a sample Twitter ads file might look like. So if you see on my screen, uh, and once again, I will be zooming in as much as humanly possible here, but be sure to use that full screen button. Uh, you can see that a typical file will almost always include date data as well as in the case of Twitter, uh, just for our sample file that we’ve built. You have campaign data such as key and name and category, as well as placement ID data and placement name. Uh, and then you have measurements that are associated. You have clicks, media cost, and impressions. And what I’m gonna do with this file, uh, just having a simple view of this data, is I’m going to take you back to Marketing Cloud Intelligence, and I’m going to showcase how I can upload a file like this in mere moments. And with very minimal setup, have the platform recognize how to set up this file and what exactly to bring into the platform. So what you see on my screen is what’s called Total Connect. This is pretty much the catchall of I don’t have an API connection. I just wanna upload a file. This is the the way that you get there. So I’m gonna click browse, and you won’t see the window pop up, but I’m grabbing this Twitter file. Um, so when I click into that, the platform showing us just the different sheets that we can choose from. It’ll ask that if you have multiple sheets in a file. I know that sheet one was the data that I was looking for. And if there was any doubt, you know, I I created a pivot table in that second sheet that it was showcasing. Rather than just hope for the best, the platform shows me here’s a preview of what your dataset looks like. Does this look right to you? And I as the human can now validate. Yeah. This is the the thing that I wanted to bring in. When I click next, I’ve this is 2023. So, of course, there there’s some AI talk that’s gonna be in this conversation. The platform looks at my my dataset and effectively looks to see, um, what is being brought into the platform, trying to figure out what type of data is it looking at. Now with 84% confidence, uh, it tells me that this data belongs to ads data. We talked about in the deck a little bit ago about that being the most core um, use case in the platform is using the the ads dataset. And because the platform is trained constantly on data back end, um, from years of just existing, the platform’s AI was able to tell the different fields that were being brought in and how they relate to a standard ads dataset. Um, bear in mind, I have not customized this workspace at all, um, but the platform recognized that the word day matched today and effectively taking from our external datasets column headers on the left hand side has mapped data to the platform’s fields on the right hand side, effectively setting up the beginnings of the database. And in addition to having day and campaign values mapped correctly, it even recognizes that placement ID and placement name are the same as media by key and media by name. And then, of course, the metrics down below, you you might see that there’s this little hashtag next to them indicating that they’re numeric values and effectively has mapped everything exactly as I would expect. Uh, there’s still very much a role for human beings here. You know, there are sometimes gonna be fields that you wanna add in or modify, and that’s important to keep an eye towards here. But a lot of times, you’re also gonna have the platform just recognize whether it’s an existing connector or a custom file, exactly the sort of things that you’re looking for in terms of fields. Now if I wanted to extract a value from my my dataset or change something, um, you know, let’s say that I wanted to, um, change the way the campaign name came in. If I wanted to set a formula for making the value default, if it didn’t have certain parameters. Uh, what I really like about this platform is you can see this if in blue. Um, just like in Excel, I can use an if statement when I use those capital letters. I can do a true false kind of statement. And, you know, this is very sloppy. Maybe I didn’t put a a true or false, uh, value to check against. But the the point being here that the platform gives you really easy to use Excel style formulas. And if you wanna go even deeper and and kind of play around with the different functions the platform has as well, what I also really like is if I wanna try to see if there’s a formula that will work for my needs, I I can go and check on this list. You can see the if is listed here. Um, it shows me exactly what an if argument looks like and how I can set that syntax. I can also double click and effectively just have a baseline template to work off of. And there’s even there’s even formulas that effectively do things that might sound a little complex, like extract, which allows you to take data out of a phrase and return a value from somewhere in that phrase. And what I really like is the platform not only walks you through that in the bottom right section of this formula editor, but also gives you examples in some cases as well so you can run with the the type of data that they’re trying to help you to gain. Um, so that’s a little bit about mapping data on the platform. I’m gonna leave this without saving on the basis of just for expedient sake. I have already mapped my Twitter and Facebook data in here, so that is already set to go. And once that data is set in, what I just wanna showcase very briefly is that in the the Facebook mapping as well, uh, similar to how we’re showcasing Twitter with its ads data, The Facebook dataset that I have in here is for conversion data, so not the same metrics, but it still has media by name. It still has campaign name. And, effectively, I can query these things together. I can look to see how my campaigns are converting, how my campaigns are getting engagement in in the form of click clicks, impressions, and also in terms of media cost, and query all of that at once through these commonly named fields, uh, which, again, I find to be named in plain English and really easy to navigate. So, of course, data loading is really important, but being able to visualize and report on your data is the most core feature that most of you are going to want. And I think you’ll see that especially in a simple use case like this, the platform loads very quickly and allows me to look at my data all at once. I can see, uh, this is an ice cream company that we used just for the sake of demoing called Scoop It. And all at once, I can see my impressions and clicks, click through rate, and media cost all highlighted to me, uh, at a top level. I can filter on my different campaigns, whether it’s those campaigns from Facebook, from Twitter, all can be filtered on this page. And I can also have my conversion data, my impression data, uh, my media cost data, all living in harmony showcased on the same, um, the same different, uh, dashboard all at once even though it’s from different data sources. And I think just in in very brief, this is kind of the the value prop of marketing cloud intelligence is you can put all of your data in one place rather than having to go and look at Facebook’s UI, look at Twitter’s UI, pull reports from there. You can set up automated reporting from those platforms, visualize them all at once, report on them all at once, and in plain English, be able to showcase value to your team and talk about different strategic, uh, KPIs all in one place. Um, and I’m just being mindful of the time here. One other thing that I wanna showcase also is, again, in line with the name of this session. Uh, there is a harmonization center that exists in this platform. So the the value of this is if you’ve got nomenclature that is really specific that you’ve got channel and campaign, um, and maybe fiscal year and month and things like that in your your nomenclature, the platform is really useful at breaking that out. So if I was to choose in this pattern tool a new pattern and call this, let’s say, campaign breakout, um, effectively, I can go in and I set the campaign name. And say I just wanna set my Facebook data to to be captured accordingly with what my nomenclature is, I can do that here. And the platform looks to see all of my different Facebook campaigns and allows me to choose how they typically look. So I can click apply. And, effectively, the platform automatically breaks out what the different values are that are included in my my campaign name without my having to specifically tell it. It understands that there are delimiters such as underscores, such as dashes that break out the way that the data is broken. If I don’t like that it broke up my age group here, where 35 and 44 should be altogether, I can effectively clear, um, these different pieces from the platform. Um, there’s some things with structure compliance and things like that that require a little bit of tweaking. Um, but you can really make it so that it’s it’s the way that you want it to go. Um, And I’m just gonna reapply this to to showcase just a little more cleanly. Uh, but really, again, just an easy way to kind of reset what your dimensional data is. Um, you know, if I wanted to change this to to goal or this to key, any of this stuff can be set in here to to extract out and can also be coordinated with the Twitter data or any other data that we’ve got in the platform to just harmonize in even further depth and with just a few clicks of a button. Um, with that in mind, I know we’ve just got a few minutes left here. Um, I wanna just briefly showcase the reporting feature of the platform as well, and then we’ll go back to the slides and make space for any questions. Um, so if I go into this analyze and act section of the platform and then to reports, I just wanna showcase the social media data report that we’ve got and just how easy it is, again, just by plain English for users to be able to pull this data. Um, I can set my date range in the platform, uh, for any range that I would like. Here, I’ve just got the last thirty days rolling. And I’ve got measurement data for impressions and media cost. If I wanted to add something like clicks, it was just on the screen, uh, highlighted for me, but I can also search for it. Uh, if I’m not sure what values I want to bring in, I can also look to see what the platform gives me as suggestions. And same with dimensions. If I wanna look for media by name, I can search for that easily, and it’ll show me any fields that are similar in terms of what I’ve searched just to to easily add here. Uh, the last thing that I’ll just highlight on this report feature is that you can send data anywhere. Uh, there’s not licensing needs that come with sending data out, uh, in terms of reporting. Once I set the report as active and I set a a timeline for how often I want this to be sent out, I can email it to any email address. You can see here that I can just type away. Uh, unlike some other tools, I don’t have to specify based on a logged user. Anybody can be emailed data from this platform. You can also bring data to Google Cloud, to Google Drive, to an FTP, AWS, uh, a number of different sources that you can place your data from the platform without having to have licensed users. So there’s a lot of robust, uh, options in terms of harmonizing data in marketing cloud intelligence. Um, and I’m just gonna briefly take us back to the slide deck and give you a quick summary of what we talked about today. So marketing cloud intelligence, um, certainly from my point of view and I I think relatively objectively is an easy to use, constantly relevant tool for marketers. Uh, intelligence has connections to over a 100 marketing APIs as we know we noted and numerous technical connections as well for any of your other data needs. And harmonization can be in a lot of ways in this platform. It can be transformed and harmonized front end and back end, whether that’s in formulas like I briefly showcased or in pieces like the the patterns tool of the platform, uh, to be front end. Uh, and harmonizing, like I said, is only really the beginning. The core that people are gonna get out of this platform are going to be, uh, the ability to visualize and report on your data because that’s so much of what analytics needs to be. The heavy lift is bringing the data in, and the value is really what you’re able to showcase with that. With that in mind, I’m gonna pause here briefly for questions and just give people the opportunity to, uh, either note those in the chat or in the q and a section of the platform. So if anything is burning, please certainly let us know, and, uh, I will answer any of those live here.

Speaker 0: Thanks, Aaron. Yeah. I’m I’m just taking a look at the q and a tab. Uh, we don’t have any questions right now, so I think, um, we’ll probably give it ten more seconds if anyone has last minute questions. We have about two and a half minutes to go. If we don’t, um, just just note oh, there you go. Wait. We have a question. Nathaniel said, where do I navigate to get to the platform?

Speaker 1: Good question. So platform.datorama.com. I’m putting that in here. Um, if you have access, that should be the place where you’re logging in. I will note and this is a great question, Nathaniel. So thanks for asking it. Uh, it is separate from any kind of cloud based instance. It’s not in the exact target space despite being a a marketing cloud product. It is completely in its own platform at platform.datorama.com. Um, if you are a marketing cloud user, there is a likelihood that you have intelligence reports, which lives in the analytics builder of marketing cloud, um, but that has slightly different functionality. Some of the some of the things that we discussed here are the same, but I will just note that particular tool is limited mostly to email journey and SMS data.

Speaker 0: Thanks, Aaron. Um, looks like we can get another quick question in if anyone has, uh, any any questions there. Absolutely. Thanks, Nathaniel. That was a good great question. Okay? Um, if there aren’t any other questions, uh, again, just note that you can reach, uh, Aaron today, uh, via the events chat if you have any questions later on this, uh, today or into tomorrow. But with that, thank you again for joining. Uh, thank you to our sponsors and, uh, for helping March even happen. Have a nice day, everyone, um, and enjoy the enjoy the rest of the sessions.

Speaker 1: Thanks, y’all.

Speaker 0: Thank you.