The Data Stack Show - 142: Martech’s Separation and Return to Data Infrastructure with Scott Brinker of HubSpot

Episode Date: June 14, 2023

Highlights from this week’s conversation include:Scott’s background in martech (3:10)Where things have gone wrong between IT and marketing (5:46)The explosion of digital marketing data (12:04)Costs of having data siloed (16:14)The convergence of marketing and IT teams around data (19:27)Navigating the massive landscape of martech tools (26:10)Needed tools in the martech stack (31:11)The importance of an accurate attribution model (34:37)Building tooling for marketers and developers to use (39:20)Future areas of development in the martech space (44:46)Final thoughts and takeaways (52:40)The Data Stack Show is a weekly podcast powered by RudderStack, the CDP for developers. 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 to the Data Stack Show. Each week we explore the world of data by talking to the people shaping its future. You'll learn about new data technology and trends and how data teams and processes are run at top companies. The Data Stack Show is brought to you by Rudderstack, the CDP for developers. You can learn more at rudderstack.com. Welcome back to the Data Stack Show. Today we're going to talk with Scott Brinker. And I actually have a huge amount of appreciation and owe a lot to Scott. He is

sort of the king of MarTech or marketing technology, something that we definitely need to cover on the show. But he's the one who first got me thinking about the data stack when I was in marketing in my very early days of my career. He started writing about this 15 years ago, marketing technology, and has written 15 years of content on his blog about that. He now is leading a bunch of awesome product initiatives at HubSpot and has a huge amount of insight into the data stack from the angle of marketing and sort of the needs of marketers in the technology stack. Kyle says, I want to ask Scott about the difficult or let's say storied relationship between engineering and marketing over the past 15 years, because he's been writing about that a lot. And there have been a lot of changes in the

way that companies operate. And there have been a lot of changes in the technology landscape. And I think both are to blame. And so I envision a future where there's mutual love and respect and fully integrated technology. So that's what I'm going to ask about you. Yeah, I have two things in my mind. One, first of all, I think he's the perfect person to share with us what the MarTech landscape looks like, what's out there what is Martek, what technologies

and what categories of products we have there definitely one of the things I would like to hear from him he's probably the most qualified person to talk about these things and the second is the connection between

marketing and data. I think it's almost like a cliche to say that the big source of innovation comes from marketing in the data infrastructure, like the needs that marketing has. I've said that many times. But it would be awesome to hear from him how this relationship has

evolved. Like how marketeers today operate like with data, like how technical savvy they are, what does this mean, how they work with like the engineering teams and all these things. So let's dive in and like I think we have the right person like to and all these things. So let's dive in. And I think we have the right person to answer all these questions. Let's do it. Scott, welcome to the Data Stack Show. We are so excited. I'm personally very excited, having followed you for so many years.

I guess I can say it's over a decade now. Time does fly in the MarTech world. Well, yeah, thanks for having me here on the DevStack. Yeah. Okay, well, give us your background. So you actually were a software engineer, you were a lot of MarTech software, now you're at HubSpot,

but give us the abbreviated version of the journey. Yeah, so as you said, I started out as a software engineer and kind of an entrepreneur, and then was building software for marketers and marketing teams and got really fascinated about, you know, with the explosion of the web, how dysfunctional the relationship was between marketing and IT software organizations, you know, back in the dark ages there. But yeah, as these worlds converged, I built a business called Ion Interactive that was a SaaS company. I let marketers do all sorts of cool interactive content. And in part of doing that, I realized, oh man, I was one of hundreds, eventually thousands of companies

that were building all these MarTech products. And while there's all this great innovation happening, oh my goodness, for like the poor marketers, like, well, I want this and I want that, but how do I get these things to talk together? That's kind of become my cause. And yeah, that's what led me to HubSpot about five years ago to at least with one MarTech company, you know, help them build out more of an integration ecosystem. Yeah, very cool. And you have a very widely read site, Chief MarTech. Do you want to tell us a little bit about that? How long have you been writing on that site?

In just a few weeks, it will be 15 years, you know, so the gray hair is starting to show. Yeah, and he's still up very consistently. So, yeah, it's been fun. And, you know, the original genesis of that was, again, more on the human side of this. How do you get, you know, people

who came from an IT or technical or software technical background and folks who had come from a very different world, you know, in, you know, classic, you know, marketing backgrounds. How do you get these collaborations? How do you find these hybrid individuals who sort of have a foot in each world? And here, 15 years later, that's actually still the most interesting part to me is like

how the organizations and the human side of this work. But yeah, we keep getting sort of pulled into the undertow of like, okay, yeah, but there is actually all this technology and how do you get this stuff to work together? Oh my goodness, the data explosion. Yeah, yeah. No, it is kind of funny. Like, you know, MarTech marketing technology

is almost a little bit of an unfortunate term just because it really, like, it is more about the teams. I want to dig into that but first of all you know as a software engineer who has built you know software to you know sort of leverage data that is used by marketers to do x y or z and having written about this for you know well over a decade a decade and a half, where did things go wrong in terms of the relationship between sort of IT and marketing, right? Because I think,

you know, if a lot of the data engineers, you know, sort of data team members that I know and that I work with, right? Like, marketing can be kind of a burden because a lot of times they're, you know, it's not always this way, but a lot of times, you know, their sort of interaction with marketing is like a ticket for an integration or like, you know, a ticket to like pull some piece of data or something, right? And marketers are extremely data hungry and generally need to move really fast, of course. So how did things kind of go wrong and how did it almost become a meme that the engineering org and the marketing org

don't get along? Yeah, well, the genesis of that problem is also quite frankly the genesis of why there was this explosion of all these marketing technology tools. It's that if we go back, you know, 20, 25 years, marketing was a relatively well-defined set of things you did. There's the stuff we do with the advertising, the collateral, we'll manage the pricing, the four Ps, you know. It was a very well-boxed profession and relatively predictable in its career arcs. Then with the web, everything changed, right?

I mean, on so many different dimensions. First of all, the whole relationship with the market. I mean, this thing where companies could sort of dictate narratives and sales processes, completely blown up. The individuals, the buyers have so much control and transparency in this, you know, but then we also got these explosions of all these different channels, all these different touch points, you know,

just all these things changed. And so many of them changed in the context of marketing teams. Like, okay, well, what are you responsible for? How do you do it? What are the practices? And it ended up chasing all these consumer technologies that, I mean, if we think back to just the massive innovations, right?

So certainly there was the web to begin with, you know, like, you know, social, you know, mobile. It's like all these different things. And so marketers have been in this incredibly accelerated pace for now two decades of just trying to even keep up with all this stuff and understand it and engage with it and manage it and that's created all this market for all these different tools that you know like oh well you need to do this or you want to do that or there's this new emerging channel here how do you manage you know these engagements in tiktok or things like that this obviously created great stress in the relationship between marketing and IT from

the beginning, partly because although marketers knew they had to work with this stuff, for the most part, they didn't have technical background on this. And so all the lessons that, you know, technical professionals have learned over the years of, you know, how do you think about scoping things and managing this and lifecycle and SLAs and all this stuff. Yeah. The marketers didn't have that background, but they needed all this stuff. I need to get ads on TikTok. Exactly. And so, you know, like IT very early on, like put all these brakes on it. And that I think was this origin of this, you know, really incredible tension between the two. Now what happened was for better and worse, thanks to all these MarTech vendors,

marketing largely took control of their own destiny. Listen, we don't necessarily need that key. We're just going to get a credit card. We can buy this with SaaS. We're good. Thanks. Anyways, you know, And so the MarTech stack in many companies sort of grew independent of the IT department. Not a great thing. Probably the only rational thing that could have happened at that moment in time. But now what's happened as we fast forward to where we are today is the rest of the organizations become incredibly digitally mature, much more advanced, you know, everything's getting connected, you know, these layers, you know, particularly

the, you know, the data layer. And so now we're trying to like converge the two. We're trying to like, okay, well, this having this Vartex stack in these isolated silos actually isn't good for anyone. It's not good for marketing. It's not good for the rest of a company, not good for customers. And so we're trying to now get these things reintegrated. And yeah, I think once again, that creates some interesting tensions of like, okay, wait,

who's doing this? Who decides this? What's the priority? Yeah. Yeah. Maybe the short history of the world. No, I love it. Yeah.

It is crazy how many marketing tools, you know, are out there now. I mean, what's the, you, because you do this every year, right? You sort of publish like a landscape. And what's the latest, you know, sort of like the latest count of tools? Thousands and thousands? Yeah, it's over 10,000 at this point. Oh my gosh. Thousands and thousands? Yeah, it's over 10,000 at this point. And I always have to disclaim that, you know, this is just giving a number like that doesn't really reflect the industry well, because the truth is, it's totally a long tail, you know, and at the head of the tail, like the majority, if we were to order these companies based on, you know, ARR, ARR, market share, things like this, it actually is a fairly consolidated industry. There's maybe a dozen massive public companies, maybe a couple hundred real leaders in different categories.

But then you get this really long tail out to the horizon of these different specialists or these new challengers or regional leaders. And I actually think, you know, I'm probably biased on this, but I actually think the long tail is a great thing. I think that's where a lot of the energy and the innovation, it like keeps that industry moving forward. But yeah, if you just give it like a count of like, well, how many are there? It's a lot. Yeah, super interesting. How much?

So when you think about sort of IT, like there's this explosion of marketing tools, you have, you know, sort of IT and engineering works. One thing that's always been interesting to me is that, you know, around the time this explosion started, it was actually interesting that, you know, let's just, I kind of frame it, I kind of think about, you know, the iPhone as about the iPhone as a convenient inflection point to talk

about this timeline of the explosion of both digital data that's being produced by consumers, by the web, by all this stuff, all these digital interactions. Then you have the explosion of the tooling of the marketers who are trying to take advantage of this, like you said, take advantage of mobile. But that's a really interesting time period because you're actually right before some of the technologies that have defined what people now call the modern data stack, for lack of a better term. So you have this 2007 iPhone, you have this explosion of mobile and you don't see sort of what we consider like your standard, you know, modern cloud data warehouse for that, that enterprises who had the ability to afford taking advantage of all this from an infrastructure standpoint did that.

We recently had someone on the show who sort of built the first big data system at Facebook in 2008. So that their product teams and marketing teams could drive better growth. But, you know, very few companies have the resources or the ability to sort of attract talent to do that. Do you agree with that sort of the need for this, you know, sort of more advanced tooling and data usage, like on the marketing side, actually sort of sped ahead of where the infrastructure side of things

was at the time that inflection point started to take off? Yeah, no, absolutely. And it's led to actually why the problem today is so challenging is basically we got used to the fact that we're going to have these stacks of dozens and dozens of different tools, and each tool is kind of going to have its own little silo of data. And so we're using this data in this tool like this. And, you know, maybe there'd be ways we'd throw pieces of it over the fence here and there. You know, but the sort of the de facto way in which people were working with these tools is they were incredibly siloed, you know, but the sort of the de facto way in which people were working with these tools is they were incredibly siloed, you know, and unfortunately, well, fortunately or unfortunately, depending on how you want to look at it, it turned out actually people could get a lot done

with those things because again, we were like pushing these frontiers of capabilities that just never existed before. So getting this capability, even if you were quote unquote disadvantaged, you know, from being piloted with it, you still were able to like have like really significant impact on the business. And so that allowed this proliferation, you know, of modern tech stack, you know, with just all these

different disconnected tools to grow to the level it did before finally like, you know, we sort of hit a tipping point where like, okay, now actually the cost of having these things disconnected is now starting to exceed the benefits we get of just having, you know, these isolated capabilities. And so I think it's perhaps a wonderful convergence of things that that tipping point has been hit here.

And also the exact moment that this idea of, yeah, like the modern data stack to this infrastructure that could say like, well, okay, technically, we probably could now pull all this stuff together and start to really connect it, you know, with a common data fabric. And so, yeah, I think that's the exact moment in history we're at here. We need it. And now it's becoming actually technically possible. Yeah, for sure. It's super exciting. I want to jump back. You mentioned cost. Can you just describe some of the costs of having, you know, sort of data siloed? I mean, I know the symptoms of that, you know, sort of data siloed. I mean, I know the symptoms of that,

you know, sort of upstream, if we think about a data team, right? There's, you know, the classic pain of like, you know, we need to export data out of this system and get it into another system, right? I mean, so much, there are so many people in the world who still export CSVs and upload, you know, to transfer data between systems, you systems. But then there's also sort of, can we build a custom integration for this, etc. And so that's one part of the cost. But can you describe some other flavors of the cost and how it's greater than the ability of an individual team to say, get really efficient on paid spend or email marketing or whatever tactic that they're executing on the marketing side yeah i mean there's an internal and external version of

this like so the external one you know is the customer experience which is you know when customers are you know touching us on these different you know interfaces that are run by separate products. From the customer's perspective, they don't know that they're separate products. They don't care that they're separate products. All I know is like, hey, I had this thing on the app. I had this thing on the website. You sent me an email with this thing.

I called up the call center. I got, you know, like, it just looks broken, you know? And, you know, if one thing has been consistent, expectations of customers just continually, you know, rise, as they should, you know. And so when we have these failures in customer experience, more often than not, you can actually trace it back to like, oh, yeah, well, there are actually systems and data barriers, you know, that allow that disconnect to happen. I think internally the costs, you know, range, I mean, again, certainly there's this cost of like saying, oh, well, I need to do X. It isn't happening automatically or it isn't, the systems aren't designed for this. So now I have to put in all this manual effort, you know, to do it. Oh, I need to run a report for X.

You know, right. I'm going to pull this together. I'm going to get into a spreadsheet and, you know, to do it. Oh, I need to run a report for X, you know, right. I'm going to pull this together. I'm going to get into a spreadsheet and, you know, spreadsheets, my goodness, that's holding the whole universe together. You know, but the truth is the bigger costs there, you could argue is actually the opportunity costs is, you know, how many things did people want to optimize, you know, a, you know, broader flow, or they wanted to answer a question, you know, about like, hey, how is a particular segment performing better than other this? And when they looked at the cost and time and effort it would take to answer that question, they're like, all right, no, screw it. It's not worth it. And so we just didn't have, you know, the data to make those, you know, things.

And I think that's a huge huge cost yeah yeah that's i think that's really well said it's like the hidden costs are often you know sort of the most pernicious you know because it no one there's not like a lot of physical weight to like it's just going to be too hard to answer that question. So I'm not going to, right. It's like, well, if you did,

what would that have done, you know, for the business? Let's jump over to the people side for just a minute, because I love what you said about, you know, sort of people want to talk about the technology that you started writing 15 years ago because you're passionate about the people side.

One thing that I've seen is that, you know, before maybe where marketers were, I'm going to execute my marketing tactics, I'm going to do this, and I don't... Get IT out of the way. I don't want to be weighed down by that. And maybe IT had this attitude, not across the board, of course, this is more playing on the mean, but IT is like, please don't, you know, please not another marketing ticket. But I think in a really healthy way, like marketers are becoming more and more technical. And I think a lot of data teams are getting closer and closer to the business because, you know, they're working with data that's driving the business. And in order to understand

the context of what they need to do, they, you know, need to understand the business. And in order to understand the context of what they need to do, they need to understand the business, which I see, I think it's a really exciting sort of almost like convergence, you know, or sort of meeting in the middle. And there's sort of marketing ops roles or like analytics engineering roles that sort of blend these concepts. Are you seeing the same thing? Yes. I mean, this has been the thing about these marketing technologists marketing ops people is when you look at their backgrounds either well it's interesting it is kind of a 50 50 split but like at least 50 of it is like people who basically worked in it software the technical people by background they came to you know, because they saw an opportunity there. They were passionate about it.

But they bring enough of the actual discipline, you know, of, you know, solid technology management practices that, yeah, it's not the total Wild West. And then I think you've got another set, actually, interestingly, is these people who their careers initially started in marketing, but they just got really fascinated by the technology. And so they put in the hours and they put in the effort to really understand it. And yeah, I do think these hybrid professionals, I mean, this is what makes it fascinating. Because there's a bunch of literature out here that you could argue it either way of the benefits of specialization versus hybridization. Sure. But no matter what, even if you say like, yes, there is value to having a deep specialist in X, we realize now that the world has gotten so complex that having people who are these bridges, you know, that span two or more disciplines together can just bring so much value in like connecting and translating between them. And so, yeah, I do think really good marketing ops people, really good marketing technologists, I think actually they help create good relationships

between the marketing department and the IT department because they understand where each is coming from and they can like do the translation. Yeah. Yeah. Yeah. It's so funny. I think about even 10 years ago, you know, sort of work, you know, trying to do data driven marketing stuff.

It's like the idea that it's like, well, yeah, the marketing ops person is going to, you know, jump in and write some SQL queries to like figure out what the, but that's pretty common today, actually. Which is really cool. I'm going to hand the mic over to Takasis. One more question.

Maybe this is a bad question for the name of your blog, Chief Martek. But based on everything we just talked about, it seems like, you know, there was sort of, you know, a technology organization, you know, sort of like marketing sort of leveraged stuff they got from them to do their stuff. And like you said, it was pretty well defined, huge explosion. You know, there's sort of a marketing technology stack that's separated and now it's coming back around. So do you see the future as it's just sort of going to be the data stack?

You know, does the MarTech stack go away? What does that architecture look like? As those integration problems, both on the technology side, but also on the team side, you know, continue to converge? Yeah, that's a great question. And I, yeah, in all humility, I don't know exactly how this will go. I think it's a very fluid thing. And it's also one of those things that it might not be one pattern that's just universally like, I think what we're going to see for quite some time is different companies with different cultures, different talents, different maturity, different industries will just, they'll draw these lines in different places. But if I were going to take my best guess at like, all right, you know, squint, here's what I think the future will generally look like, is I think the data layer absolutely has to be centrally owned. I mean, this is the foundation on which everything is built.

But I also think the specialization of what data means... I mean, you guys are more data experts than I am, but my understanding is the hardest problem in data still remains modeling this stuff and getting the definitions right. The pipes are one thing, but agreeing on what the heck it is that we're putting through it is a very hard problem. And it is very domain specific. And so you really need specialists, you know, not just in marketing, but in sales and customer service and product ops and finance and all this to really be able to have the mechanism to influence, you know, those definitions. But then there's a layer above that, which is, okay, now the actual operations. Okay. If we all agree, we've got the common data and it's piping and flowing the way

it should, you know, what are we doing with that data? You know, what's the web experience we're delivering here? How does it change, you know, the mobile thing? Like, are we tracking these like cohorts if we're doing that? What sort of actions do we take with them are different than, you know, the other cohort, you know, and all this sort of like operations and service layer on top of that. I think that increasingly like, yeah, I mean, that's still going to have a lot of domain specializations. I think you have a lot of MarTech marketing technology that's focused on delivering these experiences and executing these campaigns and programs. But that if you look under the cover, the data that they will be working with and the data that they will be

collecting and sharing will filter and work directly with that common data layer. Fingers crossed. Yes. No, super interesting. I could keep going, but Kostas, please, please jump in here. Kostas Pustilaevic, Yeah. Yeah. So I might sound like a little bit of like a naive question for people who are, you know, like in the marketing industry, but you mentioned while you were like talking with, with Eric, with Eric that the landscape in

Martech is more than 10,000 products out there. That's massive, right? I don't know. To me, at least, it feels like, wow, how do you navigate that? Can you give us a high level of the basic categories of products that fall under the martech industry to get a better understanding of also how… Because obviously the industry maps somehow to marketing itself, right? So by seeing the different product categories categories there we can also understand what marketing is doing especially like for the more technical people like in the audience that we have

yeah yeah happy to do that and i will say just as a preface to that like we think 10 000 products in martech is a lot all right it is a lot but like if you go to the there's a software review site called g2 you know and they review all you know all kinds of software not just marketing i was talking to their ceo there and this was a few months back they had a hundred and three thousand different products that they were tracking reviews on and they were the first to admit like oh oh yeah, we don't have them all. This is like just a fraction, you know, of what's out there. So I don't know,

this problem may have like first exploded in the context of marketing, but I think this is now actually a universal challenge we face is the world is just full of a lot of software. But all right, so in the context of marketing like what what is marketing technology what are these categories so in our map we have like six main categories and then a bunch of subcategories the main categories are tools for managing advertising and promotion so this is a lot of what you would think of as ad tech, you know, solutions. We have a whole thing around content and experience. And so this is everything

from like, you know, our, you know, web platforms, web experience platforms, what we do for like marketing automation for like delivering email. There's things like, you know, digital asset management systems, you know, that feed this, you know, we've got, you know, interactive content tools, like the things that I used to do with Ion Interactive. So there's all these things about like, oh, how do we create and distribute content and experiences? Then there's a whole world around what I would call social and relationships. You know, obviously social media marketing, you know, is a big part of that, but it's

also like software we use for managing community the way we're doing reviews and reputations this is where like crms you know sort of generally like looking at the relationship view of the customer there's like events you know that we run influencer so a social relationship whole bunch of stuff there. Then commerce and sales, you know? So if it's like a B2C business, of course, you've got your e-commerce platforms and a whole bunch of e-commerce marketing tools. If you're more in B2B sales,

you know, you certainly have like these tools around like, you know, sales engagement, sales enablement, you know, there's sales. Yeah, just sales automation of its own kind. And then we enter what I actually track a column for data that you could probably push back and say like, okay, well, this isn't MarTech, this is just tech. But I try and look at it through the lens of like, okay, well, if I'm in marketing, this might not be just for me, but this is something that's really essential to what I'm doing. And so it's everything from

business intelligence tools to some of the iPaaS CDP technologies of how do we get the data to the right place. There's folks who are doing all sorts of stuff about second party and third party data. How do we share and manage that? There's attribution. So all those fun things. And then the last category is, again, like data, probably not specific to marketing, but marketing is up to its eyeballs in it. And this is what I think of as more of like management oriented tools, like, you know, how are we using these collaboration tools? How are we dealing with projects and workflows? There's, you know, agile approaches to the world that, you know, marketing's embraced and, you know, turned in their own unique ways.

So, I don't know, that's kind of like this overview. When you break it down, you're like, you start out and you're thinking, there's no way marketing needs a whole bunch of tools. And then you actually start to, like, go through all the different things marketing does and engages. And you're like, yeah, no, wow, actually, yeah, that's a really wide ocean. Absolutely. So if you have to define, let's say, I'll come up with a word here, but the minimum viable marketing stack for a marketing team. What are, let's say, how to take the most basic and required stuff that pretty much every team starts with? Because

obviously there's no end of options to ads, functionality, tooling, and processes, and all that stuff. But someone starts, like, it's a new, young company. They have to build their marketing department, like, with the first people. Like, what's the main set of tools that someone needs to start with? Yeah, and you can get away with a pretty small set of stuff. So I would say, like, sort of the three things you need is, all right, so you need a CRM or something like a CRM that's basically going to be like, okay, we've got to keep track of the heck we're dealing with. The second thing you're going to need is you're going to need some sort of CMS or DX. Like, okay, well, I need a presence on the web and I need the ability to manage that.

You know, and then the third thing is probably what you would call marketing automation. I mean, it could be as simple as just saying it's email marketing, but it's basically like, okay, how do I run these campaigns? I have a subscription list. I'm engaging people. If they do come in and I get them on my subscription list, how am I nurturing them? When do I determine that they're qualified to be turned over to a sales team? You know, and if you actually, yeah, if you get your CRM, your CMS and your marketing automation platform, I mean, you can do like that is, there is a lot you can do with just that.

And often my advice to people would be, wow, if you could get really good with those three things before you worry about, you know, all the other possible bells and whistles you could bring to the world, it makes total sense. And what about like the interaction points between like Martek and like the data technology, right? Like you mentioned, you have like a whole category of tools there that are like more part of, let's say, the technology landscape of like the data infrastructure.

Are there like from all these pillars that you mentioned at the beginning, do you see that some of them like rely more on data or at the end, like the data infrastructure is something like very horizontal goes across touches with all the different tooling that marketing has. And if you take it to another level, I think it translates into how much data-driven at the end marketing itself is as a practice. And I'm asking that because, to be honest,

I'm not coming because to be honest, okay, I'm not coming like from a marketing background, but having like to build data infrastructure products, like what like I really and very early started appreciating is how much of like a driving force marketing is

for these technologies, right? Like there's a lot of work getting done even today after like, I don't know, like 15 years, like since I started like working with WhatsApp, that's the reason that we are trying like to improve the technology and even the algorithms that we have is because we are trying like to accommodate the needs of marketing in a way, right? Yeah. So, but I'm trying to understand me as like a technologist, do I just see only one phase of marketing?

Or like what I get through the interaction is actually, you know, like across the whole spectrum of marketing. Yeah. Wow. Okay. So there's a lot there. You know, so I think it's always helpful to keep in mind, again, where marketing started from wasn't a very data-driven industry. There was actually a small slice of it called database marketing for like, you know, the way traditional direct mail used to be done that was relatively savvy on this, but for most of our thing, there was that famous quote from John Wanamaker like a century ago or whatnot, like, Hey, half the money I spent on advertising is wasted.

The trouble is, I don't know which half, you know, and that's, we were kind of okay with that in marketing for a very long time. You know, again, though, fast forward to where we are in this digital age. First of all, the number of channels and things that marketing can invest in, it's just like infinite, you know?

And so the requirement, you know, that you have to be able to make choices, yeah, it's just a very different game. And, you know, how do you make choices? Well, ideally you have data, you know, that can help you make that choice. But also I think, you know, marketing's moved from something where

because of these practices and marketing around like demand generation funnels, you know, and conversion rates and stuff like this the expectation has shifted to you know that the c suite expects marketing to be able to very quantitatively define like okay where are you spending this money how are you measuring like the return that it has on that you know and so this is what's really yeah just changed the game where marketing like is so so hungry for data again the kind of data you need there is this still this idea that you know a bunch of the data is contextually relevant questionable you know at a global aggregation level how valuable it is i mean like you know i think about all the social interactions that someone has with me well if i'm in the middle of engaging you know with a social

marketing campaign or trying to do customer service through a social channel there's a whole bunch of contextual data that's really important to me you know to handling those things correctly if i extend that backwards to a higher level do Do I need to have all of that? Like probably not, you know, what portion do I want? Do I want some sort of signal that this customer engaged with us in this channel?

Do I want to have some sort of signal of like, okay, was that attached to a campaign? You know, what was our investment in that campaign? How did we ultimately measure it? There's this whole thing in marketing of attribution and unfortunately it's a it's a black art because you know what happens is people have all these different touch points with us and then at some

point they actually convert and they buy you know and then people say like oh well was it that last touch thing that we attributed to? Or was it the first touch we had? Or do we like evenly distribute these things? Or do we do some sort of like, you know, statistical modeling that like see different cohorts? Yeah, right. You know, so and then there's all the touches people had that we didn't even get to measure because like, you know, they met their friend for a beer and said, Joe, what do you actually think of this company? But, you know, anyways, this would be this, I think it's that attribution funnel that if you were maybe, if you were going to pick two things, you wanted a very universal data view of in marketing. One

would be, well, let's just make sure the history of the customer is accurate and available everywhere. And the second thing is, can I have at least as close of an accurate attribution model of how different touch points with people like influenced, you know, their value to the relationship we had with them. That would be ideal and wonderful. But that last one is like an asymptotic, like, there will never be perfect attribution. Yeah, 100%. I mean, I think we are getting to the limits of physics anyway with that stuff.

We got consumed, but that is great, actually. And okay, my next question has to do a little bit more with the marketing people and not the technologists. But it has also to do with the perception that the technologists have about the marketing people. always this idea that when you're building technology for marketeers, you have to make a very strong assumption about how thick savvy they are. No, we shouldn't expose SQL to them. No, we shouldn't. They don't know how to use Python. No, that's too much. It has to be so easy that, I don't know, even my grandfather can't use it for a marketeer.

All this stuff that I have shared in many conversations around building products that are, let's say, used at the end by a marketeer. How much of this is actually true? And how do you see marketeers developing themselves as a profession in terms of getting the required skills to become much more, not literate in tech, but being like, let's say, getting closer to use some of the tools that also a developer could use, right? Because if you think about it, many of the things that a marketeer does require developer work at the end. Planning pages, web pages, all this web work that needs to be done there, attribution, you're talking about statistics, data, BI. Sure, where is the points where you're saying, okay, that's too much for a marketeer.

Like, we need, like, an engineer here, like, involved. So, yeah, tell me a little bit more about that. Because I think, like, at the end, marketeers are, like, more savvy than we think they are. And I'd like to hear, like, your opinion on that. Yeah, well, I think it's interesting because, all right, there's sort of where it has been and maybe is today and where it seems to be shifting to. So if we think about sort of recent history, I think this has really been the value of these marketing ops, marketing technologists, people who are essentially technically oriented individuals who work in the marketing department, that basically they should be able to serve as that trend.

Like they can do SQL, you know, probably a decent number of them can do a little bit of Python or, you know, JavaScript. I mean, again, they're not going to build whole things, but to say like, oh yeah, I need to arrange a query to like figure out this sort of thing. Like that's within their scope. And that serves a really valuable purpose because again, like the marketing team as a whole has an infinite number of demands. like that's within their scope and that serves a really valuable purpose because again like

the marketing team as a whole has an infinite number of demands you know very creative people like i can come up with hey i'd like to know this i'd like to know this other thing can we do that you know and so yeah like feeding those requests raw into you know the data org or the id org yeah never goes well you know and so the marketing ops and marketing you know, the data org or the ID org. Yeah, it never goes well. You know, and so the marketing ops and marketing, you know, tech people act as a nice translation barrier there. But the truth is, in some ways, all you've done is like shift the problem over because you still see that marketers, even with dedicated marketing ops and marketing analytics folks,

can invent far more things that they want than even the marketing ops and marketing analytics folks, can invent far more things that they want than even the marketing ops and the marketing analytics people have, which is why you're now even seeing within marketing ops and marketing analytics, a shift of like, okay, can we make more of this self-service? Like what could be the scope of things that we can say, listen, marketer, you've got this question. Have at it. Here you go. And what is really interesting here is this whole space around, you know, forgive me if I put this in air quotes, but, you know, no code. You know, this idea of these interfaces, you know, that allow people to, you know, visually or, you know, I mean, my goodness, now with chat GPT, we're starting to think of like people being able to just do natural language queries that translate perhaps more accurately than we would have expected you know you know down to then what could actually be something like a sql query and i think that's really exciting again like even if you assume these no code tools are like they're only going to work with the low-end use cases and let's just say for like maybe the immediate future we see like,

oh yeah, they'll only serve the low-end easy use cases. They won't serve the complicated ones. The truth is like so many of these questions that marketers have, they come back to the R in that like, you know, it's not that it would be that hard to answer that question. It's just having some other individual like go and like drop what they're doing and try and figure that out for you is just a really expensive task. And, you know, for the for marketer, then like, you know, oh, well, I have to get ticket and be in a queue. I mean,

that sucks. I wanted to make a decision, you know, tomorrow what I was going to do on this. And so anyways, short answers. I think today you see the marketing ops and marketing tech teams and marketing help with that. And they are tech savvy. Like I think you can have higher expectations of them. But I think longer term, that frontier of what we're able to enable marketers to self-service is really the greatest hope for being able to like deal with the deluge. Yeah. Yeah. It makes a lot of sense.

All right. One last question from me, and then I'll give the mic back to Eric. So in this today, like landscape with all these products, if someone is interested in going and like building new technology for marketing, right? What you would advise them to look into, like from all these categories that you mentioned, like where do you, what's like makes you more excitement in terms of like, this is right for either a disruption,

or there are things happening here that are going to be interesting in the next two or three years. You know, the fascinating answer to that question is, I actually see this happening across almost all of these categories, because when you really dig into it, frankly, a lot of the technologies here, they're pretty long in the tooth, you know, I mean, at least by modern standards, right? They've been around 10 years, some of them around 20 years, you know, and the world has changed a lot of what's possible, you know? And so like, just one example, I'll give you like, you know, like how we think about sales engagement, you know? So, all right, well, we'll have these tools for the

salesperson to run their deal management in these stages and we'll do that for us. Well, I just came across a company, actually, I didn't just come across it, I've been around a couple of years, but like they've created a tool that is essentially a two-sided sales engagement tool. So it has an interface for the salespeople, but it actually has an interface for buyers and it allows buyers to like manage the process and like, you know, set up the deliverables the way they want from the salespeople. And so this, it's actually this incredibly creative way to like help both the salesperson and the buyers, like run the process of the evaluation and decision the way they both want, you know, under a lot more control on their, you know, and it's like, nobody did that before. It wasn't even really possible, you know, and I could go through the entire MarTech landscape and you still see just creative entrepreneurs saying, well, listen, we've

always done it this way. Yeah. But I'm not sure we have to keep doing it that way. I think there are better ways to do this. And that's, I don't know, that's one of the things I still, you know, I said, I really love MarTech because of the people dimension more than the tech. But if there is an element of the tech that I have a soft spot for, it is these creative entrepreneurs who are saying like, you know, the old way we used to do this, we don't have

to do it that way anymore. There's a better way, you know, the old way we used to do this, we don't have to do it that way anymore. There's a better way. You know? And they usually, when they first show this, like people laugh at like, oh, nobody would ever do it that way. That's crazy. What? You know, search for stuff, you know, and then next thing you know, so yeah, you'd bring your imagination to the field.

There's lots of opportunity. Yeah, that's the most important part. I think there is a lot of opportunity in marketing. So, Eric, what do you think? Are you starting the new Marketo for the next decade? I agree with you, Scott. I actually think that what will enable some of that innovation is that I think a lot of the burden that some of these marketing tools have had to carry on the data layer side will be removed, right? And so, because, you know, if you think about processing data models, even making recommendations, and all of that happening sort of inside of this tool, you have a tool that is, you know, let's say, you know, trying to decide the optimal time to,

you know, send a message or, you know or show an ad or something like that. And that in its own right is a phenomenally difficult problem to solve with software. But then also to have to basically build the underlying data infrastructure to power that means that really, I mean, this is just I'm speaking from my experience, having used a lot of these tools in the past is that neither one is awesome, right? Like, you know, it kind of does a decent job with the data and it kind of, you know, does a decent job on delivery, but it doesn't do either one of them incredibly well, right? And so if you kind of think about, to your point, Scott, if this stuff gets pushed out into the data layer and you have the infinite flexibility of all these data tools under the hood, and then these tools can just consume from that and be really good at that one piece, I think that's what's exciting.

I don't have the next big idea there yet, Costas, but I don't know, Scott, would you agree, disagree? 100%, Yeah. This whole standing on the shoulders and giants. I mean, you know, again, actually we didn't talk about it much, but you know, this explosion of all these software tools, part of it was because of the explosion of demand, all the specialist demand, but it was perhaps even more so the enablement of things like, you know, AWS and Azure and Google Cloud. That's just, my goodness, like the shoulders that someone can stand on now to build out stuff is incredible, but you're right, you know, where it is today compared to where it's now evolving very rapidly on, oh, well, what if you just had access to all of this data, you know, in like, you know, a highly performant way?

Like, oh, what could I build with that? And to, it's just, it's better on like, how many things do you come across in life that they get better on like all of these multiple dimensions? Like it's, you know, better from a cost perspective. It's better from a, you know, like specialization of like who does what really well. It's, you know, better from a, hey, getting all this stuff unified. So we break out of these. like who does what really well. It's, you know, better from a, Hey, getting all this stuff unified. So we break out of these. I mean, it just, you know, I I would not downplay the complexity and the hard

work that's still involved in doing this. Obviously this is what you guys do for a living. You know it better than I, so I know it's still a long road ahead, but it feels like the benefits that are going to come out of this progress are just amazing. And I can't help, sorry, just let me plug this one thing. I know everyone talks about these days, but all the stuff with AI, you know, again, it's great to see things like chat GPT and, you know, sort of this next generation stuff happening here, but all the real power out of AI is predicated on us being able to feed those engines with the right sort of data at the right time.

And so the fact that we've got these AI engines that have really now crossed a chasm in their capabilities, if we marry that now with truly unified data across the org, it's hard for me not to be excited and feel like, you know, truly unified data across, you know, the org. It's hard for me not to be excited and feel like, yeah, the past 10 years has been a really exciting, innovative time in the world of marketing and technology. But what seems like is ahead for the next 10 years, I think it's gotta make that look like kindergarten.

I totally agree. I mean, I think I think many marketers would agree that flames of game-changing AI within a piece of marketing software over the last 10 years have been... I mean, there has been some cool stuff, but it really hasn't lived up to the promise, I think, because of what you're saying. It actually was a problem that needed to be solved outside of the tool and that the tool can sort of access and leverage. But yes, I am very excited too. Scott, we are at the buzzer here, but this has been an amazing conversation. I've learned a ton and I know our listeners have as well. So thank you so much for giving us so much of your time. Yeah. Thank you so much for giving us so much of your time. Yeah, thank you so much for having me. Gus, it's a fascinating conversation with Scott.

As I said, personal honor for me because he was the one who sort of originally got me thinking about the data stack, of course, from the marketing angle. One of the interesting things that I really appreciated about this conversation was the discussion around local optimizations. You know, that's sort of something that you, if you work on a data team, you know, and I actually,

you know, in my current job, have the, you know, I sort of have one leg, like I work on the team that, you know, manages the data stack. And then I also work on the marketing team. And so I get to see both sides. But it's really easy to see how you can have a limited view on a data team of what a marketer is trying to do downstream and how for them, data can be such a rate limiter. And many times it can even be difficult for them to know that, right? They just experience more and more difficulty in trying to do something in their job. And so a theme that we've had on the show a ton that Scott got back to, especially in thinking about that relationship between technical teams and downstream teams like marketing is empathy. And then we also had this really interesting conversation about like, are those two things

actually just merging together? And what does the future of that look like? Which was really interesting to hear his perspective on sort of team structure that's flowing from deeper integration in the technology stack. So yeah, I thought it was a really helpful conversation. How about you? Oh yeah, I was, first of all, okay.

It was great to hear from him, like how, like this martex landscape looks like. And like, if you have seen like all these maps out there, he's the right person, like to narrate the map. Right. So it was great. Like that's, I mean, I understand now I understand like much better. maps out there, he's the right person to narrate the map, right? So it was great that... I mean, now I understand much better what Smart Tech is, right? I found very fascinating this whole conversation around the evolution of

the relationship between marketing and technology, and now we have marketing ops people and RevOps, and how does this change the belief that we've had so far about the technical skills that the marketing teams had. And finally, one of the things that I found probably the most fascinating one is in the landscape, in the industry of 10,000 vendors, something like that, it's a crazy number. How he convinced me that probably today is the time for anyone to go and disrupt this industry. So I think, I don't know, I feel like I got a lot of inspiration together with a lot of knowledge when it comes to marketing technology from him. And that was amazing. I totally agree. And he gave some great examples of ways that people are innovating, like the platform he talked about that allows a sales process to be sort of transparent between the buyer and the sales. You know, some interesting things like that, that are approaching problems in new ways. So definitely a great episode. Thanks for listening. Subscribe if you haven't. We'll catch you on the next one. We hope you enjoyed this episode of the Data Stack Show. Be sure to subscribe on your favorite podcast app to get notified about new

episodes every week. We'd also love your feedback. You can email me, ericdodds, at eric at datastackshow.com. That's E-R-I-C at datastackshow.com. The show is brought to you by Rutterstack, the CDP for developers. Learn how to build a CDP on your data warehouse at Rudderstack dot com.