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Unveiling the Future of MarTech: Insights from Scott Brinker

GrowthLoop co-Founder Chris Sell recently had the privilege of sitting down with none other than Scott Brinker, the esteemed "Godfather of MarTech" and founder of This captivating interview took place just a day after Scott's Best of Breed Marketing Summit in May, where industry leaders gathered to explore the latest advancements in marketing technology. In their thought-provoking discussion, Chris and Scott delve into the fast-paced world of martech, uncovering its explosive growth and the profound impact it has on today's marketers. They tackle the intriguing collision of AI and composability, shedding light on the transformative potential it holds for businesses in this ever-evolving landscape. Read on to discover the fascinating dialogue between two industry experts, and gain a deeper understanding of the trends and innovations that are driving marketing forward.

Julia Parker

Julia Parker

CS: First off, I feel like I'm getting the interview after the game. So you're like the athlete just coming off the court. Yesterday, you had the Best of Breed Marketing Technology Summit where you released the 2023 MarTech Map. So I get to ask you about it, which is pretty cool. Can you give our listeners a little bit of an overview of what you talked about yesterday and then we can get into the MarTech map.

SB: Sure. My collaborator, Frans Riemersma and I, we've been working on that MarTech landscape now, year over year, and we figured every year when we release it, “hey, it's nice to see how the industry has changed at that level.” But we also wanted to make it a little bit of a bigger thing to celebrate all the amazing people who work in MarTech and marketing operations. So, we coined this, MarTech Day, the second Tuesday in May. And this year we also were happy to invite some of the people who we learned from to come and speak and share some of their perspectives. 

And Chris, I'm so grateful for Flywheel Software (GrowthLoop) sponsoring yesterday's event. Frans and I had a chance to have a chat with you about the perspective that you've had about how this industry is changing. 

CS: We got to do a session around the data cloud with Darrell Alfonso and how it's changed in the marketing stack. And so in the 2023 MarTech landscape, I know you 

just released a post, around how it's seen 7000% growth. Over the last 12 years, it's over 11,000 solutions at this point. Obviously it's a crowded space. There's a lot of technology flying around, but are there any emergent trends you're the most excited about right now?

SB: Well I think again, it’s sort of stepping back from looking at individual companies and trying to get a sense of the broader evolution that's happening. I think three themes that I'm really focused on right now and I know you and I see eye to eye on a couple of these here. 

The first theme is the shift towards a more universal data layer. For years and years, every MarTech tool kind of had its own database, and these databases were kind of their own little silos, right? And it's been a lot of work and challenge over the years for companies to connect and integrate across these.

But over these past several years, sooner or later, data is making its way into the cloud data warehouse and increasingly not just flowing into the cloud data warehouse, but also increasingly flowing out of the cloud data warehouse back into these tools.

I think this is phenomenal. This is really connecting marketers and their marketing stacks to a much broader the rest of the organization. So I'm very excited about that. Then the two other themes tie into that universal data layer idea.

The second theme is this idea of composability. Increasingly thanks to APIs and advancements in the cloud, marketers increasingly have the flexibility to compose. Whether it's workflows or apps or customer experiences across these different tools and data sets. 

And then the thing that, of course, everyone's talking about these days, is this inflection point we've hit with AI, which is now changing a whole bunch of the capabilities that we can do on top of that universal data layer and this wonderful API composability across the tool set. I feel like generative AI has been the cherry on top, that blows the whole thing up. 

CS: I talk to a lot of marketing leaders and so often into the discussions I point out, “Hey, right now you're maintaining 15 databases. They're just in different SaaS tools and you're actually maintaining a 16th database for your analytics and it's your data warehouse. So why don't you just actually maintain one of them and the apps should come to the data cloud?” Obviously that's a part of what Flywheel (GrowthLoop) does but beyond Flywheel, do you see a lot of marketing technologies starting to re-architect around the data cloud so they can sit on that single data layer? Do you think that's where this goes?

SB: There's no doubt in my mind that everyone is integrating to the data cloud. Whether or not the actual operational dynamics of particular tools will treat the data cloud as their live database. Or that they might still have some sort of, intermediary, solution. I think that's a function of a lot of things. Where is the technology at? What's the cost paradigm for this? Thinking about permission management and governance. There's just a bunch of things that people factor in.

So I'm not saying that all data outside of the cloud data warehouse is a bad idea. It depends.

But ultimately I think your point, getting all the data into the cloud data warehouse, that becomes the center of gravity from a data perspective. I think that just makes a ton of sense.

CS: Yeah, that makes sense. You had recently posted on a new operational flow for marketers based on the universal data layer. In the old world, you had marketing operations going as a funnel to the data warehouse and then a new world where you showed more of a circular flow between marketing operations and the data warehouse. I wanted to dive into that a little bit because you asked the question, “Is this where things are headed?”

SB: Flywheel Software is actually a great example of this, right?

You're accessing data from the cloud data warehouse and then you’re able to organize that and orchestrate that and then feed it out into the operational side of marketing. We're seeing this trend across the concept of composable CDPs, the space that has been known as reverse ETL. The reason ETL became popular is because we needed a way to get all this data into the warehouse. And then for years the only thing you would see hanging off the other side of the warehouse was perhaps an analytics tool?

Reverse ETL was this concept of saying,”let's not just pull stuff from these other tools. Let's be able to take it from the warehouse up back into those other tools.” But it's still new. Let's be honest, about two years ago there were very few people who were really actively talking about this.

But things take time, so I think there's still a very long adoption curve ahead of companies who don't even yet realize the data assets that they have available in their cloud data warehouse that are now accessible to what they can be doing in the marketing department.

CS: Yeah, it almost feels like it, it is reaching a tipping point where, kind of in your old world, the diagram with the funnel. Everybody was using it as a sync. They would put the data there for analytics. So they would just say, “Hey, it's, this is probably good to have. We should bring this email open, click data, and all this interaction data into the warehouse because I need to produce a report for my executive team and decide how I'm going to allocate my spend in the next quarter.” And so they would bring it there and just use it for visualization. And then all of a sudden everybody's like, “wait a second, we have a lot of data there. Maybe this is where the single source of truth for our customer data should sit. Can we actually use this to start experimenting faster and activate this out?”

It's almost like they're discovering what they did by virtue of building analytics in the warehouse. If you can activate it out again and orchestrate it and try experiments, then you can learn from them in the data warehouse, then try them again and then you get that loop effect.

Moving on from the data layer, I wanted to dive into generative AI. One of the things I really wanted to dive into was the second order effects of generative AI and how this plays out in marketing. And you had recently posted something about, essentially the buyers and sellers getting further apart and there almost being this conflict of – you start with, “hey, sellers can just create more content faster and it becomes really good.” The content that you're showing in marketing to your buyers, generative AI can help with that. 

But then you started looking downfield: what does that mean long term? Do the buyers then have AI reviewing the content and telling them what to buy? I’m curious, how do you see us getting there and what does that world look like?

SB: And the disclaimer on all of this needs to be we are entering uncharted territory. So many of the dynamics here around AI at this point are what you'd call exponential in nature. And it's just really hard to predict the interplay between all these things. That being said, if we take maybe just this one simple case: if you believe AI is going to –by at least an order of magnitude–expand the amount of content that gets created, and again, probably actually really good, highly personalized content.

We've been talking about this in marketing for like 25 years, the dream of one-to-one personalization. It's here. And an enormous amount of it can be automated.

Okay. That all sounds good. Until you put on your buyer's hat. And now, I don't know how much email you get flooding into your inbox. I get a few messages myself every week. I think there'll be a ton of magic moments that happen for people, with AI where they think “That's incredible, that's perfect. That's a great message.”

But when the volume of those messages rises… We just only have so much time. So very quickly, I think buyers are going to need to have strategies for navigating this. And I think a very plausible direction to that is that increasingly buyers will have their own AI tools. You can completely imagine a Gen AI, Chat GPT layer on top of your Gmail or your Outlook that says, “I've just gone through the 500 messages you received today and here's my shortened summary of what you probably will want to pay attention to.” And that email reading algorithm is an algorithm that's trying to serve YOU, not an algorithm on the other seller side.

It's your own SEO essentially, and sellers need to optimize for your SEO. And so they're going to need AI agents to be able to optimize for all those different folks' SEO.

CS: I know we're about 20 years ahead here, but it is interesting that it kind of does break down the SEO problem where you're optimizing for hundreds of thousands of people's own search engine optimization.

SB: I wonder, I actually don't think it's 20 years away. I think we're going to see a lot of change here just within the next three to five years. And that may end up being a conservative estimate. If you'd asked me at the beginning of the year, like how quickly things would be happening with generative AI, I would've absolutely underestimated that.

I think there might be interesting things that get discovered along the way. For instance, we've had a standard with APIs forever. It's the idea of saying if everyone has their own random way of engaging with APIs, that just really slows down. It creates so much friction. And so that, as we start to move to more standards for APIs, right?

It accelerates innovation and productivity for everyone. I wouldn't at all be surprised if we see things like that emerge in this world too, where you can't optimize for a hundred thousand different LLMs out there. But if there become certain standards, these other LLMs will take advantage of that.

CS: You had another point around this too – leading to ambient applications. And a part of this is marketers being able to compose their own applications for themselves, but also that the applications and marketing applications fit more into their workflows, so they almost fall away. Whereas tools today in marketing technology are very prominent in the workflow of marketers day to day. What do you see happening over the next few years in terms of apps and the marketing technology ecosystem becoming more ambient or part of the workflow?

SB: Yeah, some of this becomes almost like a philosophical debate. What constitutes an app? What constitutes a piece of software? We've already sort of been on that journey for a while. One example I'll give you is what is a tool that everyone uses just about every day? An incredibly sophisticated, massive piece of software that everyone's using every day. Sort of a freemium way.

It's Google. But does anybody actually think of Google searches and, “oh yeah, I have to log in into my Google search app to track this.” No. It's just become like, yeah, of course I just do this and it happens. And I think what we're going to see here with generative AI embedded in more of these tools that surround us in our work, in our lives, is we're going to have all these things that we're just asking for and making happen without really having to consciously think about it. I think Google is the ultimate example of the ambient app. So if marketing technology can go in that direction, it makes a ton of sense.

CS: Are you seeing anything interesting in generative AI? Any recent launches that you've been excited about?

SB: Well, again, not to flatter you on your own podcast here, but your example with Marve. That's brilliant. I'm just saying “This is what I want” and then the generative AI is translating that and being able to pull the right data to give you the results you want. I think we're going to see a lot of that. Adobe, in particular, they haven't been sitting on their laurels here with the impact that generative AI is gonna have on the creative side of things. Not only do you create images with generative AI, but then you can manipulate them and you can do the same thing with videos and evolve them, and you can do it in this very natural language interface, or in their case, even like this cool combination of natural language interface, but also like UI elements. Perhaps it's actually easier to draw on the screen or use a mouse to, than even to put into words. I think all this stuff is going to be like a golden age of creative.

CS: It feels like it's magic when you see that too. Your idea is brought to life that quickly, even when you're just typing in and seeing images. But that applied to creative for paid media assets and email is gonna be insane to see where that goes. And what I'm curious about is on the, the targeting side with Marve, the fact that you could just say, “Hey, I want to target this group of people and get an audience report back based on your data schema.” I wanna see how those two areas meet. Because you have data on the customers in the data cloud. You have a natural language interface to tell who you want to target and the experience you want to give them. And that just so happens to be in a few channels. So if the data cloud is the hub, you can generate the targeting and the sequel, give an audience report back. But then also you hook into these creative tools, whether that's Adobe or the channel tools like HubSpot, Marketo, and you can actually generate the creative. Essentially the marketers are doing the job they always wanted to do, which was to create a customer experience that makes sense for their business and for their customer at that lifecycle phase. Versus somewhere as a project manager in the middle of all those things. Right?

SB: It's fascinating. There's definitely a concern that reducing the barriers to creation is going to dramatically multiply the amount of junk out there and the amount of spam. I actually think that's true. That's going to happen.

But there's another side to this, which is the positive view. Just think of all the people in

marketing who have all these creative ideas and things they want to try and experiment and for the vast majority of ideas and experiments they think up in the shower one morning–they've never had the ability to try it because of the amount of work it would require, the costs of specialization.

Clay Christensen always had this model of disruptive innovation. And the thing that was always magical about disruptive innovation wasn't that it was knocking the high-end things off their perch. Like, what do you have a true designer for? And a software engineer for? There's still going to be plenty of work for those folks. Where disruptive innovation always surprises is in the underserved. There were all these people who wanted to do things that they just simply couldn't.

And now with this new disruptive technology, suddenly they can. Is there going to be a ton of junk that gets generated from that? Sure. But there's also going to be a ton of absolutely amazing, brilliant things that would've never come to life before because someone couldn't take it from the brainchild idea into something that was living and breathing out there in the world.

And now for a whole bunch of creative spirits that is now possible. It almost feels like there's a ton of latent potential. 

CS: So about 10 years ago I was in channel marketing. I did email marketing, and this was literally the story of my job. Day-to-day was out of one hundred percent of ideas, if we had a stack rank, 95% of them would never see the light of day because we could only launch a certain number of campaigns. We only had access to certain data for the targeting. Our analytics team could only measure based on certain elements that they had access to. Our agency was only able to accept so many creative briefs per quarter. And I was like, “well, what do I do with the rest of my time?” And the answer was to project manage the 5% of ideas were able to act on. That's why I got into marketing technology–to make this easier. I think you're right. Like the job here, if we bring these things together, we can unlock that other potential, the 95% of all those crazy ideas. That does mean there's gonna be some bad marketing out there, but it also means there's a lot of marketers self-actualizing. So we have to take the pros and cons. 

SB: Some people might say–some of the more cynical folks out there–there's already a bunch of bad marketing today. It will be interesting to see how the good and the bad balance out. This is one of the areas where I suspect AIs that serve buyers or basically other AIs that aren't focused just on enabling the seller, I think may actually help with that too. 

And there's other things, right? In that post on the second order effects, the other thing you start to think is like, okay, well, trusted communities and trusted influencers. Not sure the Kardashians qualify as trusted, but whoever the influencer is for your market, it's like these folks who you can feel that they've done some sort of filtering, or this is a peer group that I know the other folks in here, I think those channels are going to increasingly be a source of celebrating the really great stuff that comes up.

CS: Yeah, absolutely. As more of this gets generated, you're going to need that filter, right? “What are the thought leaders thinking about it.” Before we wrap, I wanted to ask you one last question. Across these, I'm looking at generative AI, targeting, composability, being able to stitch marketing tools together. And then I'm looking at the universal data layer at the cross section of all three–and the notion of a Customer Data Platform. There's a multitude of different customer data platforms out there, whether its a fully packaged all-in-one CDP versus composable. There are ones that exist on the data cloud. How do you see the CDP space shaking out? And I think the answer is probably different for different types of customers, but what do you see happening in the space and where do you see it heading over the next few years?

SB: That's a hard question to answer, both because I think it's going to depend on the evolution at the cloud data warehouse layer–we're not done there. Snowflake, Amazon, Google Cloud, there's a lot of innovation coming down that path, and I think that is going to have a lot of impact on how we even think about what other data capabilities we need to layer on top of that. But the other thing to your point is also out of the millions and millions of businesses out there in the world, the distribution curve of where people are at with, their skill sets, the capabilities they need, the maturity of their organization to harness this stuff. That distribution is wide.

I think it's going to be a long time before there is just the one architecture that every company just uses and we're good to go. I think it's going to be a very diverse field for easily the rest of

this decade. And so different CDPs or cloud data warehouse versions of this or CRMs–all this sort of stuff, like the combinations of things that different businesses choose to use, I think will depend a lot on who they are and what they need at that point in time.


We want to thank Scott Brinker, the renowned marketing technologist and founder of, for joining us on Marketing, from the Source. His insights into the current trends and challenges in marketing technology were truly enlightening.

To delve deeper into Scott Brinker's expertise, we encourage you to visit and connect with him on LinkedIn. His continuous exploration and analysis of marketing technology will undoubtedly provide you with valuable insights and guidance.

If you enjoyed this interview with Scott, explore our series, Marketing, from the Source, for more informative and engaging conversations with industry leaders. Stay tuned for upcoming episodes as we delve into various facets of marketing and data and uncover new perspectives that can help shape your strategies.

Thank you once again to Scott for gracing our show and sharing his knowledge. We hope you found this discussion insightful, and we look forward to bringing you more thought-provoking content in the future!

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