The Data Stack Show - 12: Building a CDP on your Data Warehouse with Nicholas Ziech-Lopez of MessageGears

Episode Date: October 28, 2020

In this episode of The Data Stack Show, hosts Kostas Pardalis and Eric Dodds talk with Nicholas Ziech-Lopez, director of product strategy at MessageGears. MessageGears is designed to reduce data friction for marketers by connecting directly to a brand’s data source and using their live data. This episode centered around the world of CDPs and where MessageGears fits in that space.Highlights from this week’s episode include:Nicholas’ arrival at MessageGears and the company’s background (2:20)MessageGears data sources (6:52)Accessing the data warehouses (9:19)Coordination and crossover of data and marketing roles (20:57)Being a customer marketing platform (31:43)Dealing with messy data (36:04)Bridging the physical and digital world with consumers (43:49)What’s coming up next for MessageGears (51:09)The Data Stack Show is a weekly podcast powered by RudderStack. Each week we’ll talk to data engineers, analysts, and data scientists about their experience around building and maintaining data infrastructure, delivering data and data products, and driving better outcomes across their businesses with data.RudderStack helps businesses make the most out of their customer data while ensuring data privacy and security. To learn more about RudderStack visit rudderstack.com.

Welcome back to the Data Stack Show. Today, we have a really interesting guest, Nick from MessageGears. And MessageGears is a CDP. But interestingly, they run primarily off of a company's owned live data that comes from the warehouse and other microservices. Very interesting. They coordinate sort of cross-channel consumer messaging. And I'm fascinated to learn more about their data sources and how they accomplish that. But Kostas, CDP Space is crazy. What are you going to ask Nick? Yeah, absolutely. I mean, for me, it's going to be a very interesting conversation today, first of all, because our friends there at MessageKeyers, I always enjoy chatting with them. They have a very clear and interesting perspective around the CDP market and what's happening out there, which, by the way, it's a very noisy market. So I think it's

going to be very interesting to hear Nick's opinion about what the different products are there and what they are doing, how they differentiate and all that stuff. This conversation is not going to be that technical, but for me, what I find very interesting and what I want to learn more is, first of all, learn more about CDPs in general, make it more clear in my mind what the CDP is and what's the value behind using a CDP. And also learn more about what marketeers are doing with technology and how data is transforming the marketing industry. And I think Nick is the perfect person to enlighten us on that. Great. Well, let's hop in and start the conversation.

We are talking with Nick Zeke-Lopez from MessageGears, which is a CDP and a pretty unique CDP from a technical standpoint. Nick, welcome to the show. Hey, thank you very much for having me. Very excited to be here. Well, the CDP space is crazy in and of itself. We know that firsthand from working at RudderStack. But Nick, we'd love for you to just give a brief personal background. How did you get to where you are today? And then tell us about MessageGears. What do you do and what makes you unique in the world of CDPs? No problem. Yeah. So I came to MessageGears mostly by way of analytics. My previous stints were either an analyst at large credit card companies or kind of at a machine learning company for a startup that was doing some new tech. you know, not analysis for analysis sake or data for data sake, but solving a very real marketing problem with large amounts of data, with data access, with, you know, by way of data. So I, you know, I've been at MessageGears for a couple of years now. I'm the director of product

strategy. And at MessageGears, we, you know, like you said, we solve a lot of the CDP problems and we actually consider ourselves a customer marketing platform, you know, because to that point, although we are centered on data, although, and I'm sure we'll get to it, you know, the data problems that we solve are, you know, important. We're doing it in service of better marketing because, you know, we see ourselves as consumers, as, you know, as people with phones and TVs and computers, we want better marketing. And what we see getting in the way of it right now is access to lack of and use of data. Got it. Super helpful. Would love to know, could you just give us a quick rundown of what does MessageGears do for a business? What types of activities can you execute just to give us a sense of, you know, what are the product features?

Sure thing. So what message use does is we say we reduce data friction for marketers and data friction can be seen for any large enterprise. Any enterprise that is marketing, you know, on the scale of millions of users, right? These large, large companies that are sending millions or potentially billions of messages a month. And data friction is any customer experiences or brand experiences that you want to enable that are getting slowed down by having to move data or having to to wait on or use data and other platforms. So to give you an example, a lot of large companies think about like the 90s and the early 2000s for their email programs, their databases simply couldn't keep up with the high and low or the high demand and low latency that an email marketing program might need, right? You might be running, you know, a query every minute, two queries a minute to define these audiences and send these messages. So what they do is they would

take snapshots of their data and upload them into these other systems. And that was a lot of how email marketing got built, is I'm going to take a snapshot of data once a week, once every few days, and I'm going to send it over. And then I'm going to send all of my email as the marketer, I'm going to log into that system, and they're going to handle the data for me. And the issue there is that now you're not working off of live data for so many of these use cases. You have to wait for the data to populate. Oftentimes you're restricted on the kinds of data you can use because it has to match what that system can do. And so the marketing, for lack of a better term, wasn't that great. And I think a lot of us have experienced that, right? If you've ever purchased a product and then you got an email like 20 minutes later that

was like, oh, don't go away. Make sure you finish your transaction. And you're like, wait, what? And you go log back in. Maybe it's for tickets or something else. And it's because they were working off of this old data. They didn't know everything about you. So what MessageGears does is in message sending, in audience segmentation and activation, in interaction

management, we connect directly to a brand's data source. So directly inside of their VPC, behind the firewall, to their private cloud and use their live copy of data. Because in the year of 2020, databases, data management systems have gotten so much better and more performant that we can do that. And we allow marketers and marketing ops to operate directly from their own data and run their marketing operations from there. That's incredible. One question for you, we are data source nerds ourselves. When you say live data inside the company, and I want to return to the BPC question, and I know I'm monopolizing the conversation and Costas probably is chomping at the bit to ask a bunch of questions as well,

but what are common data sources? I mean, I would guess the warehouse, but what are other live data sources? And we'd just love to know what that looks like for a typical customer. Yeah, yeah. That's a good question. So these enterprise brands, the movement we've been seeing over the last five years really is going to these private clouds, these highly performant, typically file-based data storage systems. And so we're seeing a lot, you know, the usual suspects, Snowflake and BigQuery and Redshift, some Azure data sources in there too. And that's going to constitute a lot, but not all of that brand's data. And for many of these brands, they have, you know, we always talk about it. It's the most overused phrase, but this 360 degree view of the customer, right?

Where they have or they're storing or they're interested in storing everything that they know that their user has volunteered to them for better marketing. But, you know, in addition to that, we do see a lot of these, I'll say like micro service types of APIs behind the firewall, things where their IT team or their architecture team has surfaced instead of direct database access, access to an API, a lot of file storage that we see as well. And it's because, you know, quite frankly, no two of these large enterprises look the same.

And you guys know that. But we are definitely seeing this move towards now performant and stable data management that we can then run marketing ops off. That's the majority of what we see. So Nick, I have a question about the experience that the user has with message gears. And if you could spend some time explaining a little bit how the user has with message gears. And if you could spend some time explaining a little bit how the user, like the customer of message gears, interacts with the product itself and focusing a little bit more on the data.

I mean, you touched and you described a lot of how the data is accessed, what kind of sources, where the data come from and all that stuff. But I think it's also very interesting to chat a little bit more about the nature where the data come from and all that stuff. But I think it's also very interesting to chat a little bit more about the nature of the data. I mean, at the end, what is this 360 view we're talking about, right?

I mean, everyone talks about the 360 view, but you from the perspective of the application that actually consumes this data and generates the value at the end, what have you seen so far being like the most interesting kind of like data sources, let's say, or data types that you see there? And how does the messenger customer interact with this data and ends up like running a campaign at the end? Like, what's this? How this experience looks like? What we try to offer is the ability for both, I'll say, technical and marketing users to come in and have their experience of the application and the marketing world. So a very technical or very data-heavy person might log into our application, might configure their data sources by connecting directly to their databases or their file-based APIs. And they might go in and type some SQL or to extract their audience

or their what we call context data, right? Like the deals of the day type of data. And what they can do there is because they have direct access to their data, they can surface just about anything to the marker, right? They can say, oh, I want to define this audience. I'm going to give the marketer these parameters and really kind of, maybe there are cross-table joins, maybe there's multiple databases. That's what they do. And that's a lot of the administrative, the data-heavy work that really sets up the ability for the marketer. And what the marketer is doing is

they're logging in and they're designing the you know, the email and push and SMS templates of, okay, what kind of experiences am I going to be creating? What kind of campaigns over the next month? What kind of campaigns will be launching? Right? So, I mean, think about it now. We are, we are in the middle towards the end of October here. We've got the holidays coming up. So the market is going to be coming in and designing either drag and drop. Maybe they're writing HTML, but saying, these are the kinds of images I want everybody to see. And maybe they're a little bit disconnected from the data. Maybe they don't need to understand how data works.

Maybe they can use our drag and drop SQL interface or potentially our, you know, we say visual segmentation builder because what they're focused on is maybe less of the data and more of what is this experience? What is this orchestration, this customer journey that I'm setting up? And then what's very important for them is maybe because they're disconnected from the data.

How do I know that this is the right messages going out? How do I QA this? How do I send these tests? And so what we try to do with our application is equally serve with both of those. Because what we've seen a lot of in the market is that tools are either totally created for, you know, marketing users, but make it impossible to use or upload or quite frankly, you know, make a value of your data.

Or, you know, in a lot of these segmentation platforms, we see tools that are marketed that they could be marketing friendly, but they're quite frankly, too complicated, too overloaded. And the mix between either creative or actual experience and the data that they're using is too muddy. So we try to do is make fairly straightforward workflows so that whether you consider, and maybe you're both, you can be both, you know, technical using SQL understanding of the data and understanding the experiences you're creating. But that's kind of our product, I would say, philosophy is that if I'm coming in to do one thing, it should be fairly straightforward for me to do that. Does that make sense?

Yeah, absolutely. And I find it extremely interesting that you understand the value of the existence of these two roles there. You have the engineer on one side that has to deal with the different aspects of the data lifecycle. And then you have the marketeer. The marketeer always will be interested about the message, about what we are going to communicate and to whom we are going to communicate and why. And I think one of the mistakes that we people in technology do is we try to take each one of these roles, like salespeople, marketing people at the end, and project to them technical leaders that at the end they shouldn't have. And we talk a lot, for example, about the marketeers that they need to work with the data or try to learn SQL or

have visual interfaces to create data sets and all that stuff. But yeah, I'm more of a fan, to be honest, of clear distinction between the roles. I think that things can work in an optimal way at the end. And I find it extremely interesting that you are doing this on the product. And I'm very interested also to see how you separate the experiences because these two personas probably have different needs. So probably I will focus a little bit more on the data engineering side and Eric will probably focus more on the marketing side. So my next question is from a technical perspective, I mean, you've seen that

we've seen lately like a huge growth of interest around the cloud data warehouses. We had like the IPO of Snowflake. There's a lot of hype around that. And for a good reason. I mean, the democratization of like accessing a data warehouse is like a very big thing. If we consider that like a couple of years ago, a data warehouse was like a luxury for Fortune 500 companies. So how do you see like the importance of the data warehouse and what are like the kind of trends that you see from interacting with your customers and the data engineers inside these companies?

Yeah, you know, just to that point, a few years ago, the data warehouse itself was almost like a walled garden. I remember being an analyst at a Fortune 100 company and just not being able to get any of the access. Like I am this guy, I know the problem that I've been tasked to solve. I understand that this area has the data, I know exactly. And it would take months and months because they, you know, they simply have to do everything they could because they couldn't open up their data due to the fact that it would, it would fall over. Right. And, and, and, and maybe this is the same database that's supporting the website. Maybe this is the same database that's doing something more important than some analysts running off and solving problems. And so, you know,

we talk about the democratization of data, we talk about data as a currency. And what I think, to your question of what do we see in the marketplace? And I think that it's a little bit, it's multifaceted. I think it's understanding that any improvements to data, and it's kind of getting IT out of the doghouse a little bit of, it's not data for data's sake. It's data for the, you know, for the entire marketing environment. This kind of fusion of marketing ops and marketing of what used to be, you know, a little bit of a separation there of, you know, yeah,

marketing crafts the message, marketing glitters the experience, marketing ops makes it happen, right? It's a marketing ops job to make sure that data keeps moving. You know, they're really two sides of the same coin, that if they work a little bit closer together, marketing ops can get the data faster or work off live data or make it easier. Marketing can offer better experiences. And I think that it's, that is affecting a little bit of the, I would say the profit motive or the revenue and a lot of what you're saying of yeah this data is fast but it's not about the data being fast it's the data is fast and so we can blend right so we can and we're looking at it from the marketing lens but i think that these companies are seeing it through everything we now have fast access to

all of our data so we can blink so we can within the store we can offer these experiences better when when you click go on the website instead instead of waiting five seconds, you wait half a second and our NPS shoots up because people aren't, you know, sitting there staring at their browsers. I see that. And I see that people understand the value of data. And, you know, just as an anecdote, I was on a panel a few months ago about a small business that had a small, I'd say midsize business that had really had kind of turned around on, on specifically Snowflake. And, you know, their, their director of it and their director of, you know, data management was going to marketing with insights that he found because the data was so quickly that,

that, or it was so it was returned so quickly and was so available that he was able to query and do things that, that, that even marketing didn't have the time to do. So he's going at them with things that he, did you know when the weather is hotter, we sell more? Did you know about, you know, kind of, you know, putting data in the front seat there. And, and that's so, so it's not only the, you know, the profit sharing, but it's, or not the profit sharing, but the profit sharing, but it's not the profit sharing, but the profit motive. But then it's the idea that, OK, what are we going to do with this? We've got all these actions. What are things that we didn't think about not being able to do before? And this looks different for every business.

But but this kind of this idea of dream and do founded by technology, founded by data. Right. The kinds of things of I remember listening to a talk given by a food chain that said that they can tell, and I love this kind of thing. And this gets to data sharing, which we can talk about in a second. But when you land in a plane, they can tell because you haven't shared your location for a long time. And now your location is very, very different. And this is a chain that had restaurants all throughout the airport. And so they know that they could send you a message right then. And you turn off airplane mode, but they realize that that message was going to get lost with probably potentially the dozens of messages. I know Eric's a super popular guy. He's probably getting blown up by text every time he turns airplane mode off.

And so it's going to get lost. So what they getting blown up by text every time he turns airplane mode off. And so it's going to get lost. So what they do is when they sense that you probably just got off a plane and that you're near an airport, they wait four to five minutes for when you're probably standing up and getting off the plane. And that's when they hit you with the notification saying, hey, you might be here for a later. Why don't you come and try Blink? And it's because they're able to see all this data about their customers so much quicker. And I know that was a very long answer to your question. But moreover, we're seeing the idea that it's not data for data safe, but the ability to data to power what and then to do what. And then the third part of it is really when you invest in your data, the cost of everything else goes down. You're investing in the right place.

So these expensive third-party tools that you were using to monitor things like location, to monitor things like signals from around your website, you don't need because your data is there and you have access to it. And the total economic impact or the ROI there shoots up, if that makes sense. Yeah, yeah, absolutely. I wish I was that popular, Nick. I really am. More like you wish you were on planes more often now.

I'm the guy who pulls his phone out of his pocket, turns off airplane mode at the end of the flight, and then sort of sadly slides it back in and looks around. People realize, oh, that guy hasn't heard from anyone because he's... And I don't know if you know, but we are all talking about you. We see you do that. One thing you said, and this is really interesting because Costas and I have had a few conversations on the show

with people who span the data and marketing worlds. And in particular, I'm thinking about someone we interviewed actually also named Nick, who exemplified that. Where you said it's sort of the crossover between marketing ops and marketing, I think is the way you described it. Are you seeing roles like that more and more specifically? It's something that we've been very interested in just as we talk with people on the show, is that there's sort of a new skill set where you have, really like you as someone who comes from an analyst background and then gets into actual marketing execution and, and sort of coordination. Is that,

do you see those roles at large companies emerging? Oh, definitely. And, you know, it's played into, into a little bit of ours and I'm sure many companies strategy too, of this recognition of whether you call it CRM, whether you call it marketing operations, sometimes even roles, and if we're getting tactical here, whatever the analytics are, this idea of, like you said, people that understand and appreciate both, both from a talent perspective and also people that appreciate both from a revenue perspective, right? People that can understand kind of what I was

saying earlier, that if you invest in your data, what it does around the company. We're seeing these, you know, we're seeing a lot of that increase. And, you know, I think it matches a lot of the demand that companies have, but quite frankly, and I'm interested in your thoughts on this as well, I think it's matching a little bit of where the world is going. I think that it was, you know, you look 10 years ago and the big thing for everybody in, you know, in college and university or looking for jobs was, you know, learn coding, learn coding, learn coding. You got to understand how to code. And I think that that's absolutely still true. But, you know, you know, five, 10 years later, learn data, learn how to work with data because, you know, we are always going to need people to develop these programs and develop kind of these, you know, human computer interfaces. But if you have a good understanding of data and not only that data analysis, critical thinking, no matter where you apply that, whether it be marketing or sales or what have you, in the year 2020 and beyond, that is just a great base for how we're looking at the world.

Because the world is changing, because this data is so available. Are you guys seeing something similar? I would say both at big companies or just in the world in general? Yeah. We were talking with someone the other day and we sort of have a warehouse first view of the world and we were talking about building audiences. And this person made a statement that really, I wouldn't say it caught me off guard, but it just really caught my attention. And they said, we were talking about building audiences on the warehouse. And then the challenge that a lot

of companies face is they do a lot of work on the warehouse from a BI perspective, but it's technically actually pretty hard to syndicate that work to the rest of the data stack, which is a whole other subject. But we were talking about that. And we were saying, you know, the most generally the most robust audiences you can build come from the warehouse, because that's, to your point earlier, where you have the most comprehensive data set. And a lot of times, that's because there's internal data that, you know, you don't want to access by third party systems. But that also represents some of the most important touch points for customers. So all that to say, this person said, marketers who want to build audiences, but they aren't

willing to learn a little bit of SQL to sort of mine that value from the warehouse. He said, I think are going to become, he didn't say obsolete, but he said, I think that that's just going to become increasingly mandatory as a skill and marketing, which really struck me because when you think about writing SQL, marketing is not the first role that comes to mind, but he felt very strongly about that. And, you know, I would say anecdotally, we would see the same thing. Right. I mean, people who are sort of executing on data that drives customer experiences are getting closer and closer to the data. And many times they're just actually getting into the warehouse at the store, which is pretty crazy. I mean, I mean, to that, you mentioned the most, you know, the most important audiences come from the warehouse. I'd say the most important

audiences come from the heart. That's a whole other topic. But, but to that point, I think the other thing too, is demystifying this ability to work with data or, or, or technology or anything. I think that for a long time, that process has been, and I'll use the word mystified of, you know, it's SQL. It's a programming language. If you didn't excel in math and engineering in college, this is not going to be for you. When really what we're talking about is a straightforward set of more of a, a kind of an instruction set for the data you want. And, and I do think that that's part of the, whether, you know, you call it like the, the marketing of the position or whatever that is. I think that if we start thinking about it more like that of, Hey, you know, SQL and analysis, this isn't like this, you know, this isn't the math that you may not have enjoyed. And, you know, and I think there's long been that kind of stigma of like, yeah, you go, you go into marketing and sales because you didn't want

math and engineering. I mean, that, that, that stigma certainly was, I went, I went to the university of Illinois and it felt like the college of engineering and then the college of business kind of did that a little bit of like, yeah, marketers aren't engineers. You don't do that. And I think what we're talking about is, you know, there's a ton of space, a ton of great space for this hybrid. Can you think creatively and understand the experiences your customer want to have, as well as be able to extract this data and do analysis? And I know we're way far away from where we started here, but just to say that I do think that that is where most of the world, if not the market, is going. Totally agree. Costas, I was waiting for you to jump in with a question. Yeah, I was thinking while you were chatting about data in general,

and it's very interesting because I had a conversation earlier today with someone else who asked me like a bit of a similar question the question was more about where is like the technology or IT market going actually but I think it's very relevant to what we are discussing here because if we see like the cycles of technology and what is happening like in the. And that's related, Nick, to what you said about what you were hearing that everyone who was going to college was like, I have to learn how to code, blah, blah, blah, and all that stuff. And now it's all about the data. I think it makes a lot of sense because what has actually happened in the market these past

few years is that we had the sassification, let's say, of everything. Like we pretty much have like a SaaS platform from almost every human activity right now. From finding a babysitter to doing sales and I don't know, even like cemeteries have a SaaS application right now. It's like uberblank.com, whatever that is. So the next evolution to that is because after you have like, and by the way, software is becoming a commodity, right? Like exactly because you have all these platforms.

Like it becomes cheaper and cheaper actually to build applications around these platforms. So the next wave of innovation is actually will be coming like from the data that will be available because of these platforms out there. And to make a comment and actually give a compliment to the marketeers out there, the marketeers, they might not, might be like, I don't know, maybe afraid like to try SQL or like write code or whatever.

But they're one of the few types of people or like professionals out there who are really in the forefront of using new technologies. When something new comes and there is an opportunity there, they will give it a try. I mean, marketeers are much faster in adopting new technologies and trying to use technology for their business compared to, I don't know, like sales, for example. Or even engineering in some cases, to be honest. Engineers in general are much more conservative than people think. So yeah, these are like my thoughts and I agree with all the stuff you said so far.

I think that data is going to be a very interesting space for everyone. It's like a skill that working with data, anyone needs to learn how to do. And I think that, to be totally honest with you, we're hoping that that plays to our strength, right? MessageUse is a fairly new company. And we consider ourselves a customer marketing platform

because in many ways we're going up against these ESPs, these every channel service providers, these monolithic marketing clouds that seemingly offer everything and have been around for a fair amount of time. And what we do see is, at the end of the day, people want to create great experiences, right? That's why you're in marketing. That's what you do.

And what we have seen and what we're hoping to continue to see is, it's more than the promise of being able to create a great experience, but it's the right experience. And can you do it easier? And can you do it faster? And can you do it in a more efficient way? And our ability, right, and this gets to a little bit of our, you know, unique place in the market, but our ability to install kind of where they are and give them, you know, we talk about having a free POC. Most other people can't do a free proof of concept. So the ability to just say, hey, I'm pretty sure, I'm pretty confident you have just invested in this large modern data warehouse.

I'm very confident that if you try it, you'll like it. And I'm willing and I'm so willing to do that, that I'm going to do it for free. It'll take, you know, it'll take a day. And if you don't like it, that's fine. Maybe, you know, maybe we're not in the right place. We talk a lot about us having definitely a certain customer profile in terms of number of records and sending.

But it's the fact that, hey, do you want to do this for your customer? And are you willing to try? Yeah, absolutely. So Nick, I'd like your opinion on something that I'm also trying to figure out, to be honest. There is a lot of noise around the markets of let's say CDPs customer data platforms that traditionally are considered

based also like on the definition that Gardner gives like a marketing tool right there's a lot of noise in these tools like many different tools that they call themselves CDPs there are coming up with like new names for the products like we have CDPs. They are coming up with new names for the products. We have CDPs, we have CDIs. You mentioned earlier on the introduction about message gears that you define yourself as a customer marketing platform, right? Yes. So can you help us a little bit navigate this landscape of these different products and what a marketeer should have in her mind when choosing to direct with these tools?

I mean, personally, I'm a bit confused, to be honest. So I'm pretty sure that many people, many customers out there are confused about the difference with all these different tools. So I think it would be great to hear from you because you are an expert in this. Sure, sure. Absolutely. So what we're seeing a lot of it go is just this idea of, you know, we can solve these, you know, I don't say data problems, but we can work in data for you because, you know, that's kind of

the common word there is customer data what. Now, what we see a lot of the customer data platforms doing is saying, all right, what I'm going to do is I'm going to get to know all of your customers and I'm going to store a little bit of your data. And as people kind of interact with your brand out in the world, maybe they go to your app, maybe they go to your websites. I'm going to collect that data and I'm going to keep it. And then you can create, you the marketer can create workflows that you want me to do for them. And that works super well for, you know, lower to mid market enterprises, right? You know, you've got, you know, thousands, maybe low millions of signals a day. And, and that, and what the platform does is it's holding your data. And that think, works fine. And where that idea of a CDP, this platform, breaks down a little bit is at scale, right? Now, instead of millions of interactions a day, you have hundreds of millions. Maybe you have a billion interactions a day. Maybe you're a huge company with a large web presence, and you have all these sister companies.

And for another tool to store a copy of your data is no longer really working, right? The scale doesn't work there. They can't persist it. And then we get into this idea of, you know, customer data integration or, or something like that, where our customer data infrastructure, which is okay, maybe we're not a platform. Maybe we're, maybe we're, we're bigger than that, right? We're an entire infrastructure that can help then send that data back to you. And, you know, but, but primarily they're kind of doing the same thing. They're, they're taking your data and they're going to try to collect it for you because that can be difficult. You'll probably want to rely on a software to do that, but then they're going to store it and they may make decisions or you may make decisions

in that platform. That's where we see a lot of it going. And the reason that message users long call themselves a customer marketing platform is because we don't want to store that data for you. We believe, like you said, we believe in a warehouse-first world. We believe in the democratization of data. We believe that, hey, data is going to be flexible and the brands are going to want to own that data. And we're seeing that play out. So if you are the data platform, if you are your own data platform, you've got this and you have the ability to collect and store and use this data, then we're a marketing platform that we're going to connect directly to your data and put that and then activate and do the kinds of segmentations using your own ability. And you know what?

We don't need to store your data at all because we're going to send you messages and you're going to select your own data. And in that way, you don't have to worry about PII. You don't have to worry about GDPR compliance or CCPA. You're going to be just fine. And in that way, we're not, we don't consider ourselves a service provider either because we're connected to your data, right? We're a platform that is connected and integrated directly with you.

So it's not like you're sending us something and we're doing something for you. That's what a lot of the every channel or the email service providers are doing. And so we see ourselves in that space. Not to be a Debbie Downer, but this is just based on both personal experience and a ton of stuff we see at Rudderstack, but there's sort of a data is messy. We say that a lot. And so I'm interested to know, you are getting, you sort of run on direct access to a company's sort of live data, which is, has so many advantages advantages. That's such an interesting way to approach the problem. But data is messy as well. If you think about a warehouse source, everyone likes to think that their data governance is in tip-top shape and

that their warehouses are in tip-top shape, but it's messy, right? I mean, there's lots of, generally lots of cleanup that has to be done. From a technical perspective, do you run into those issues of message gears and how do you manage through that? I mean, that's a really interesting, you sort of have the most rich source of data, but it's also, it's data, right? Which means that it's messy and oftentimes needs cleanup. How do you, do you see that and how do you deal with it? Sure, sure. So I'll answer that in kind of in two ways. So when we see, and for a lot of these organizations that make the move to these cloud data warehouses,

that kind of comes with it, right? And what I think you're helping describe is the data ecosystem. It's not just data storage, it's data in, it's data activation, it's data out, it's life cycles on that data, right? I'm sure we could talk for hours on that and much has been said about that, but it's cart and horse of if you're going to invest in this new data platform, data, you know, or data warehouse, how are you going to ensure that, you know, it doesn't go

bad in six months when it's garbage in, garbage out. And so what we see is a lot of brands are being mindful when making that transition from a legacy database to a new database. They realize that not only are they upgrading their data storage, they're upgrading a lot of their data processes. And what was it? A couple of years ago, I saw something the other day that the rise of the chief data officer, whose actual fiduciary liability of the company is make sure that their data is in a place that's usable. So we're seeing that.

But that's not to say that it's not like before when they were shipping their data. That was always kind of a messy process as well. What they're doing is they're activating the good data that they have. But while a lot of these other types of vendors that make copies of data, make it look very clean, that in itself, copying data, whenever you do is a messy process, you have terabyte sized feeds. And what we see is even if there's a little bit of an investment that needs to be made to ensure that the data in this data warehouse is clean through whatever processes. And I think you guys know a ton about that. What we're seeing is people understand and are just so willing to run away from the headaches of my data is copied into three

different platforms. I am getting data feeds both in and out hourly, and I'm getting so many that one breaks a day and when one breaks, marketing activities grind to a halt. Those headaches are the kinds that they're willing to then invest in. Okay, yes, we've got this new data warehouse. I want to invest in ensuring that everything in is both makes sense, passes audits and all of that, because this other thing was untenable for the size of my order. Got it. Super. Yeah, that's super interesting. I mean, it is so interesting that, you know, that sort of the richest source of data, you just have to manage very closely I know you've managed several sort of product features that relate directly to that. And you sort of understand the concerns around that.

Any questions from your end? Yeah, I have actually two questions. One is a technical question that has to do with the VPCs. And then I have like a product question for Nick. But let's start first with the technical question that has to do with the VPCs and then I have like a product question for Nick. But let's start first with the technical question that has to do with accessing the data and accessing the infrastructure that the customer has. We have been discussing so far Nick about like the revolution of clouds, data warehouses, but still I mean it's pretty early right? I mean it's not like many companies have done the migration to the cloud.

There's a lot of on-prem installations. And even on the cloud, there's a lot of, I mean, for security purposes and the reasons, companies prefer to have their own VPCs. So things become a bit complicated when someone wants to be a platform that accesses the data sources that the company has? How do you deal with that? And how's the experience around that? And how important it is at the end, based on your experience on message gears?

Sure, sure. So what we have found is when you can get, when the marketing operations or the technical marketing organization really understands the value that can be obtained or understood from directly accessing the data, many of the hurdles eventually get out of the way. Because what they're doing and what you're already doing is taking your data and copying it somewhere else. So whether it's Privacy Shield or whatever certification you have, you're sending that data elsewhere. What we have is the ability to access any data, but it is important that we give IT and these people the ability to then say,

well, what's sensitive? And we enable KMS encryption for anything leaving the platform. We don't store any, when things leave their VPC and eventually come to our kind of elastic processing cloud for delivery, we don't store any of that information. It's all ephemeral. And I think that, you know, it's two-sided of convincing them of the value and letting them see what can actually happen, which to be frank is difficult sometimes because of the, like I said, the literal decades of doing it the other way. And then on the other hand, the assurance that through encryption, through non-permanent data storage and all these things, there really is no risk here. This is, compared to the fact that you're sending

all this data to other vendors right now, we definitely do see teams jump on board. That's great. I think that as, I mean, the market matures and like companies see that like, okay, it's the same level like secure to use like the cloud and there are all the best practices in place and everything that has to do around security

and understanding the risk around that. I think as exactly as you said, that's when they will start also balancing the value of like interacting with tools. We'll see more and more like adoption around that. And I think that's, I mean, testament to that that is also the growth of all these cloud-based companies like Snowflake, for example, which is crazy what happened with their IPO. So yeah, it's very interesting to see what's going to happen and how fast actually it's

going to be adopted. And I think the technology is there, the best practices are there. It's just the insecurity that we people have to deal with and make the right choice at the right time. And through adding features of like the actual data access features. And, you know, for a long time, we've connected to a lot of these traditional databases through something old, reliable JDBC. But a lot of these native integrations, these native APIs that go orders of magnitude faster than a JDBC connection, they're making that data access in many ways, parallelization to throughput, rich enough that it's kind of the stick of needing to continue to, I

would say, innovate and change. But then there's the carrot of, man, this is so much easier. Man, this is so much faster that I see a lot of the organizations realizing. Yeah, absolutely. Nega, I have another question. That's actually my last question about the product. We're discussing all this time and

we have been discussing more about the data, how someone experiences you working with the data through message gears. Put it in a bit of like engineering terms where we monopolize like the discussion around like the input but i'd like to learn a little bit more about also the output from what i understand and correct me if i'm wrong at the end what someone is doing on message gears is creating campaigns to communicate with the customers. And this happens mainly through SMS and emails.

Is this correct? Yes, that is correct. So what we do is we offer the ability to define these audiences using live data to connect to any of these internal or external data sources to enrich your campaigns. So for instance, in one database, you might have all of your audience records, but in another database, you have today's coupons and today's details. We might connect to both. And then the user might, using our segmentation tool, the user might create workflows and rules to say, depending on spend and recency and customer profiles and any of the hundreds or potentially thousands of things that they know about their customers, who's in which brackets for segmentations and who's in what segments, right? Are you a loyalty member? Are you platinum loyalty? Do I think that your

purchase recency has gone up? And then they use those segmentations to activate on any one of our native or integration channels. So like you said, they're sending email and push and SMS, but they're also exporting groups of people to, you know, you know, Facebook, you know, customer match or sorry, customer or Google customer lists, you know, activating through various third party, I would say, you know, other ESP and mobile providers because they're bought in on using their data. So we have a tool that allows them to send and activate that data and create creative on many different platforms. We also have a tool called Engage, which is now that the message has gone out,

how do I make sure that that message is always good? So we team up with companies like Movable Inc. where we have a real-time API that surfaces a lot of that, a lot of, I would say, customer context or offer context, so that if you send an email campaign to 50 million people, you can get dynamic live images using real data for an API that is getting hit five, 10,000 times a second and is still resilient. That mostly, and I'm trying to kind of give the elevator pitch version here, but that's what the user is doing. And those are the kinds of operations that MessageGear wants to enable. Because at the end of the day, we want better marketing, both as consumers and as providers. And we provide that tool set to allow users doing that using data. That's great. So from your experience, have you seen like any kind of

like new channels appearing that are raising in terms of like popularity? And I mean, as you can see, I was only aware about like SMS and email, but I'm not coming from the marketing world. So I'm very interested to hear like, what are the platforms that appear right now and that's like monopolize the interest of the marketeers out there sure so the first thing i'll say is is our approach to mobile push messaging is a little bit different than what you see on the market a lot of these marketing tools have have these sdks or standard development kits that sit in your phone and you know the the IT team or the development team doesn't control, they install the SDK. And then the marketer gets all of these features.

The issue is that these SDKs break, these SDKs are expensive. The SDKs, they want to be the center of your world in many ways. And so we offer an SDK-less solution, which not to go into too much detail, we're seeing that get a lot of traction because it's basically the ability without installing any third-party software inside of your application to send messages, send push messages, you know, in-app messages or different kinds of, even in the message center, without this third-party, you know, code sitting in your app, giving the development team around the app more and more of an ability to control what's going on there. And we can get to that,

you know, I can go into more detail there if you'd like me to, but we're definitely seeing that get more and more traction among marketers. But, you know, the other kind of channels that are blowing up, and they've always been blowing up, but things like the right time to use social media and how I think that because, and by the way, I think as a society, we're, we're rethinking a lot of social media right now, understanding where it fits in our lives. So I think it kind of echoes a larger sentiment, but you know, when to use social media, when to use direct communications. And then even I'm going to take the two that you were cognizant about the right time. How does your consumer view email? Is your consumer someone that is going to open all their email every morning? I know my wife is an inbox zero person. Or is your consumer a

person that's going to scan the subject lines, but is going to really engage through text? I would say that I almost followed that category. And then understanding when to communicate what messages on which channels to that person. I think those are the really cool challenges and channels that marketers are delving into. Is this a message that I want to go ahead and spend the extra CPM for to reach out to you versus SMS? Is this the right time to kind of lean back on the email because I think you haven't been opening? Or is the fact that you haven't been opening meaning that you're seeing them, you're okay, you're just not in a spot right now to respond? I'd say that not only these specific channels, but the challenges within channel optimization, not just from a cost standpoint, but from which messages on which channels are going to make this consumer most happy and familiar with my brand. I see that marketers are really making some really good strides in those areas.

And those are things that, you know, coming from my background in analytics, I'm incredibly excited with because I think it goes to, you know, I think we were on a webinar a few weeks ago and you made the comment that having data about a customer is very similar to if you had a customer in your store. What would you notice about them? What would you look at? And I think that marketers are getting closer and closer to, you know, I don't know you. You live across the world, but you have my app and you go to my website and you buy our products. And I'm getting closer and closer to being able to interact with you like I knew you,

like I was talking to you and reading these signals and seeing you in my store. And honestly, that as a consumer, that excites me because I think that's where we want to be. Absolutely. I think that's the holy grail of trying to bridge, let's say, the digital with the physical world. And that's exactly what we are trying to do with the data. And that's the right balance that we should find there. And okay, I know that in this whole process, like there are also things that's happening that some people might feel like creepy, but at the end, I think humanity will manage

to find like the right balance there and do that. Just to that point, I think that people are getting in a place of you're volunteering information to a brand to get better experiences. Where the brand lets consumers down is if you're tracking my location, if you're as many apps do, if you're monitoring my activity on your website and you're still sending me the same crappy emails and messages, then no, you did not deserve any of the information I gave about you. Like you threw that away. But if I'm volunteering this info and

you're creating more relevant experiences for me, well then yeah, that's, I mean, that's up to me as a consumer of saying, yeah, I'm totally happy with that because telling more to you about myself is better for me and you. Absolutely, absolutely. I totally agree with that. So Nick, anything exciting that you can share with us about MessageGears in the future,

like any product features that you plan, anything that you'd like to share with the people out there from what is coming next with the message gears yeah yeah absolutely so to give a little bit of a peek at our i'll keep it to the short term i'll say roadmap what what we're focused on right now is making it easier for these i would say either hybrid marketers or data people to access and use their data. So things like, are you able to record and understand everything about your audience through time? So message use is giving you the ability to kind of decorate and enhance what you

know about your users through what we call the addition of labels. Am I able to use that and drive workflows off of that? Am I able to make our orchestration and journey builder easier to use and more flexible coming off of that live data? Another interesting feature we have coming out is the ability to have these globally defined definitions of segments for users that are able to be controlled in a workflow outside of just a pure segmentation. So, you know, maybe a customer brand specialist can come in and define what a high loyalty or a high value user is. And then, you know, marketers can come in and draw from those definitions to make, you know, audience segmentation much faster. At the end of the day, our, you know, what we're trying to do is make the tool easier to use and more powerful as I think everybody's trying to. And I'm really excited on a lot of these ease of use features that will be coming

out. And quite frankly, I'm really interested to see the kinds of going into 2021 in a post-COVID world, the kinds of cross-channel and third-party use cases that a lot of our marketers have. That's incredibly exciting. And I think that it will be fascinating to sort of see with the increased amount of digital data and then sort of the slow return of physical data represented digitally, especially for retailers who have both online and physical presences is going to be, it'll be fascinating. So many exciting things ahead. Well, we've covered a ton of ground on the show today, Nick, really fascinating conversation. Thank you so much for taking some time to spend with us and best of luck launching those ease of use features.

And we'll check back with you in a couple of months on the show. Hey, thank you so much for having me, guys. I had a ton of fun. Well, that was a great conversation. It's so interesting to learn about all of the various ways that people can communicate with their customers and all the data sources available. I mean, I think about starting my career in marketing well over a decade ago and just the amount of sophistication that's available now and the data sources is unbelievable.

Costas, what did you take away? Yeah, it's amazing to chat with a person like Nick. I mean, he has a great understanding of what's going on in the marketing industry right now and the transformation that's actually happening through the usage of data. I found very interesting the strategy, the product strategy that our perspective would say that Messenger has about the distinction between a data engineer and a marketer and making it extremely clear which part of the whole process of working with data to drive marketing campaigns should be done by who. And I find this extremely

interesting and a very good approach in terms of product design. Overall, I mean, it was a great conversation. We've learned, as I said, before we start this episode, I was hoping to learn more about what CDP is. I think Nick today really helped me to do that. I think it's much more clear. I understand much better roles that are involved in operating a CDP. What are the changes that are happening right there?

And what actually CDP does, which to be honest for me, it was something that I was missing in terms of like what kind of like marketing functions are performed by that. It was great for me, very informative. I learned a lot and I have a lot of trust to the message care people that they are going to deliver even more innovation in this space and I'm looking forward to chat with them again in the near future and learn what they're doing totally agreed great chat and we will catch you next time on the

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