Generative AI: MarTech’s Final Frontier?

I do think for marketers in particular, I think the next as far as I can see, we’ll say five years. I I think actually gonna be a really great time for marketers because they do have so many ideas, so many things they’ve been trying to execute, and the constraint has been on, like, the production or getting the analysis. And a lot of these tools are gonna unleash that, and they will be able to backfill the time they used to spend doing virtual work with things that actually will deliver real value to the business. So biased on this, but I do think marketers will be in a pretty good position. This is Revenue Makers, the podcast by Sixense investigating successful revenue strategies that pushed companies ahead. So, Simon, you like a good geek out session. Right? I love those. Yeah. Well, I wouldn’t say what we had today was a geek out session, but we spoke to someone who I would say has a remarkable amount of insights in terms of MarTech, and we talk about MarTech and AI because of where he sits, running all of ecosystem partnerships at HubSpot and brought huge amount of insights. Yeah. And he loves what he does. He’s so immersed in it that everything that came out of his mouth and everything that he talked about was backed by examples and data and predictions for the future. I mean, for all of us living in this MarTech world or marketing in general, he called it the golden age is is what’s about to come given all of the advancements and, implications of AI. And so I feel like we should just end the intro and get right into it. Yeah. Scott Brinker, VP of platform ecosystem at HubSpot. Also the author of the marketing technology landscape. We just got ten thousand billion logos on it, but incredibly helpful. So AI and MarTech. Let’s do it. Let’s do it. Scott, thanks so much for joining us. I always say it’s the beginning of every episode that I’m excited for this one, but I am because, again, I’m excited for every episode. But this is always a good one. This is a great topic. We’re gonna dive into another AI topic on AI and MarTech, and you are imminently qualified to talk about that. But Imminently. Imminently. I don’t use that word. Every can I just say, I don’t know, Scott, how many keynote presentations I’ve been at where your name and your slide is, like, one of the setup slides for any conversation around MarTech? It’s ubiquitous. Well, if if only I got royalties for those. Yeah. And, I would be on a beach, on an island. So just for the audience’s sake, again, like, you’ve got kind of your core role at HubSpot, but also kinda your work with chief Martech. Could you just talk a little about both and kinda how they come together, and then we’ll we’ll dive into the meat of the thing? Yeah. Sure. So I joined HubSpot, a little over seven years ago. You know, HubSpot had created an amazing, you know, marketing product. They’d started to go into, like, sales and CRM. And then the founders were really ready to take HubSpot from being a great product company to really trying to transition and be a great platform company where the value for customers wouldn’t just be our own products, you know, but all these other amazing products that were popping up all over the martech and sales tech landscape, and beyond that could integrate to HubSpot. So I joined to essentially help build that ecosystem in that program. That’s where I currently, run the entire app partner tech product ecosystem. It’s a joy. Basically, every day, I get to see, really cool things that all these other companies are innovating and how combining that with HubSpot creates really awesome solutions for customers. And then, yeah, in parallel to that, I’ve been writing this chief martech blog for, goodness, sixteen years. You know? And it’s really started from a passion I had long ago being a a tech guy who then sort of dabbled in marketing and then service marketers and then was dabbling back in tech. I’ve always been fascinated by that intersection, between these two worlds. I mean, if you think about, you know, like, twenty years ago, you’re a high school guidance counselor where I’ve been like, okay. Marketing’s on this side, you know, way over here. IT and tech is on this other side, you know. And we’ve headed into a world where those two things are, like, collided and entangled. And so I’ve been doing that for about sixteen years, really, as a labor of love, you know, doing things like that, MarTech landscape, which I always feel the need to apologize to inflicting that upon people, you know, and covering other topics, not just about the tech itself, but what’s always been most exciting to me is how this is changing marketing, how it’s changing who’s in the marketing department. We’ve seen the rise of the marketing ops roles, how it changes the strategies, the way that, you know, we execute marketing. So I don’t know. Between, HubSpot and Chief Martech, it’s kind of all Martech all the time. I’m a very unidimensional person. You just sometimes wanna go out to a farm and, like, just use, like, no technology and just kinda stare off into the sky, I would imagine, every so often. Sadly, when I go out to the farm, I bring the laptop at my heart. It’d be a great time to work on a landscape. So yeah. No. Well, listen. Like I said, you know, your your name is synonymous with the explosion of MarTech, and you mentioned you’ve been doing this for sixteen years, with chief MarTech. There’s a different type of explosion or boom happening. Maybe those aren’t the right adjectives, but we gotta talk about AI and the Gen AI evolution. How do you see Gen AI shaping marketing strategies beyond what we know, right, beyond the content creation? Like, can you talk specifically about industries or applications we might see emerge as leaders? This is, both a fun topic, but it is actually really hard topic to talk about because, trying to walk the line between authentically capturing the significance of the changes that we’re seeing and the ones that if you extrapolate are, I think, actually very reasonable to see as, you know, significant changes. But not tipping so far in tone of people saying, oh, it’s just a bunch of hype and, you know, hoopla. I think the Gartner hype curve has never been harder to navigate, than it is in this current wave because there’s things you hear and you’re like, oh, yeah. No. That’s crap. That’ll never work. And then next week, you see it and you’re like, oh, yeah. No. That actually does work. It’s a hard time to be a prognosticator. You’re either too far ahead or too far behind, and the next day, it changes. So that being said, I really do without forgive me for the hype. I think it’s gonna transform pretty much every aspect of what we do with software. And I think the two things that get me most excited about it that apply to marketing that are also, beyond marketing is, first of all, this ability to tailor experiences both to our customers, but to our employees, ourselves in a way that we never could before. So much software, and I mean, all due respect to the incredible profession of UX designers, you know, so much effort has been into, like, okay. What does the customer wanna do? What does the user wanna do? How do we craft an optimal set of steps that they can take? Will they figure out this menu option and then this config option? You know, for anything they want to do, whether it’s a prospect on your website or it’s, you know, a marketer who’s trying to, like, pull some data or, you know, put together a campaign. It’s like, even with the best and most user friendly software or websites or mobile apps, people had to kind of figure out, like, how do I translate what I want into how this software thinks I should, you know, ask for it. And the thing that’s just blown my mind with these generative AI interfaces, and they’re still very early in, you know, evolving, is we’re sort of leaping past having to learn the language of the software. And now the software is starting to learn our language, you know, that if we can describe in natural language what it is we’re looking for, the software can translate that into, oh, okay. This is the thing I would need to do. You know, it doesn’t even have to be a black box. I mean, you’re saying this, like, for instance, using this for, like, reporting. You know? Oh, I’m looking for a report that has x, y, and z, and I wanna compare, you know, this cohort with, you know, the one from the campaign last quarter. It can actually not just give you an answer and say, trust me. It can actually use that, request to configure a report, bring the report, but show you all the settings on the report so you can sort of validate, like, okay. Yes. That is the segment I was looking for. Yes. This is the data value I want to compare. But to have leapfrogged, having to, like, skip all this, you know, incantation of, like, okay. How do I configure this report? What was the data field I want for that? I mean, that’s magical. And so I think this gets to a place where it really does start to tailor software experiences to what we want instead of trying to guess the other way. And then the other thing I’ll say that is very much related to this is it’s a huge force for the democratization of who can do this stuff. You know? I mean, software. Right? We’ve had this, you know, priesthood of software developers, that if you became a software engineer, okay, you could unlock the mysteries of the universe with this, you know. But most of us weren’t software engineers. There’s a lot we just basically couldn’t do, And we’ve slowly seen over time, you know, things like no code and low code, and it’s tried to, like, move that, you know, line, but still, it’s been a pretty decent gap. And it’s not just like software engineering. You’ve had the same thing with, like, data analysis. You’ve had even with content creation, like, doing things like editing videos, you know, is one of these things that, like, you kinda had to, you know, learn a very special set of skills to even be able to do halfway decent, you know, work with that stuff. And what we’re seeing is across all of these different domains, whether it’s, you know, creating apps or, like, doing, you know, data analysis or doing more advanced kind of, you know, content creation or editing, that these AI interfaces, there may be again still ways away from being equivalent to the best possible person, you know, in each of those domains, but they’re enabling this democratization. And as a result, I think it’s just in this opportunity to, like, unleash so much creativity. Like, marketers, one of the reasons I love marketers is every single hour of every single day, ideas, they’re, like, popping out in their head. But there’s a tiny fraction that they ever even, like, attempt to bring to life because less than the barriers, you know, these things cost time and money and talent. You know? Boy, the way we enable more and more people to say, like, for more of those ideas, actually, yeah, prototype this up. Actually, that wouldn’t be that hard to put this out. What would people think? How would this react? I think it’s gonna be the absolute golden age of marketing. It’s funny. The democratization of of software and the software development. I was on a tool. I forget what it was called. Actually, I do know what it’s called, but I wanna start plugging other people’s tools right now. But, literally, it was like a box that said, build me an app that does x using like, it was, like, different development frameworks, and it did it. And then some of these no code tools now and this one, I will say Airtable, for example, they now have prompt based. And I did this the other day too where I was apparently, I have no life, but that’s another story. I wanted to kind of Yeah. Reorganize how we manage the show, how we hit a podcast. And I was like, I want a podcast CRM that does this, and it built it. And it was pretty darn close, which, you know, again, I think for marketers, even trying, you know, like, fixing your website, you know, when you had to go and go find someone from a coding perspective that you just got I need a code that does this. And it’s, like, scary good in terms of what it can do. But that I guess, that to the side. Sort of thinking about your role at HubSpot, you must see everything. Right? Anybody who’s trying to get into the ecosystem is running apps by you and your team, which I’m sure you’re not sitting there going with a hammer in and out. And so many of these tools are popping up and they’re selling like hotcakes because they’ve slapped AI on them or they have some AI feature and some people are just trying to fulfill my board’s asking about my AI strategy. How I’m gonna be more efficient with AI, blah blah blah. Like, do you think that’s gonna die out to a point where, yes, AI is critical, but it’s gonna be just like any other feature. Just like, oh, it can integrate with HubSpot or it can do this or could do that. It’s just AI is there. Or is this something that has, you think, legs for a while? Yeah. I think it has legs for a while because I think the magnitude of the change the closest thing I can even begin to compare it to would be maybe, you know, at least within my lifetime of this was the introduction of the web and the significance of how that changed so many of the ways in which we do business. What’s challenging, exciting, and terrifying all at once is, you know, when we really think about the evolution of the web and the language of its impact on business, it really was a good fifteen year period from, like, yeah, nobody does that, you know, to, like, wait. You’re putting an ad on a website? How are you? That’s next thing you know, you have, like, Google is a multibillion dollar industry there. The thing with AI that’s just really wild is it’s at least as significant of a change, and I think in, like, what’s actually possible with computing technology. But the speed at which this is evolving, there’s just nothing I can compare it to. And I’m a big fan of, Ethan Malek, anyone who’s probably studying AI. Like, he’s his professor from Wharton, is constantly writing things up on LinkedIn. He’s experiments with, you know, hey. What can this model do? And we’ll get this example. It’s great. There was something he said a few months ago that really stuck with me where because it was right around the time back in the fall, people were like, has AI hit its limit? Is it maybe not gonna be able to advance anymore? Which we now know the answer. No. Actually, yeah, it’s gonna keep advancing. But at the time, he made the point of, like, even if there was absolutely no further advancement at this exact moment in time and just everything that’s become available in the past year and a half is where it ends, it would still take at least five years, you know, for businesses to even begin to have a prayer to, like, harness that capability, incorporate it, you know, into their processes and, you know, skills and the way they think about doing things. But, again, the punch line is, like, it’s not stopping there, and it is continuing to accelerate on so many different dimensions. So I think AI is gonna be a big story for us for at least the rest of this decade. I do think every software to your point, every software company is gonna have be entangled with AI. So, you know, AI companies, software companies effectively become a tautology. It’s an interesting point because, as you mentioned, there’s no barriers to entry. Right? Or much lower barrier to entry now. So it begs the question of disruption versus integration. Do you think that some of these newer challenger platforms or the incumbents are better positioned for this next wave of innovation? Yeah. What’s that, famous phrase that’s been kicking around here recently of, will the startups get distribution before the incumbents get the innovation? I think in this case, actually, the incumbents are in a pretty good spot largely because, first of all, they haven’t waited. Parliament is like, we’ve seen this movie now a few times. Everyone’s read Clay Christensen’s books. You know? It’s like at a very high level with boards and, you know, executive teams, you know, at these incoming companies, they recognize this as a disruptive moment, and they are absolutely taken pulling out all the stops to make sure that, you know, they move to the next generation. I think the nature of this transformation is also one that it is fairly easy for the incumbents to make this leap. I mean, the difference between, for instance, you know, going on prem to the cloud, there were a lot of reasons why even when the on prem companies, like, wanted to make that change, there was so much legacy structure in the way in which things were built. It was hard to move as quickly. I think the shift from, like, cloud computing to AI powered cloud computing I don’t wanna underestimate that there are definitely a number of model changes, you know, at play there, but they don’t seem as heavy of a gap. Again, we’ll take Salesforce. You know, I think what Danny often with, like, turning the wheel hard to the right of, like Right. Right. Right. It’s not Dreamforce. It’s Agentforce, my friends. So, I think they incumbents to grab me in this game. That being said, I mean, the thing that always works in favor of disruptors is they have a completely clean slate. You know? And I think AI is one of these things where there are so many possibilities that we’ve yet to even consider, you know? And it’s not necessarily like a one to one, like, oh, we can do a slightly better CRM, you know, than the incumbent CRM did. Maybe there’s something completely unrelated to CRM. There’s some whole new thing that none of us have really even conceived of before. Or is it even possible before? So I don’t know. I think there’ll be winners on both sides. It’s not too much of a trying to walk the middle line there. Yeah? No. Not not at all. I think that’s a a fair answer. You talked a little earlier about experiences. Right? And personalization, we’ve had some some great guests talk about personalization in the past. I think personalization can go for something people kind of toy with. It’s an experiment to a much more strategic sort of business initiative. But given all these tools now and given all the data available and the ability to act on data or really just on a dime, completely rework whatever experience it may be, what do you think about where personalization is gonna go? And do you see, like because there’s there is so much data. And, obviously, one of the great advantages of AI is that data doesn’t have to be so structured and it can kind of feed in and all that. But, like, what’s sort of gonna take us to the next step for having, like, this sort of universal, maybe it’s a data layer that can then be used against content to create these personalized experiences? Like, any thoughts on on that? And again, like, within a marketing audience, especially, like, how they could really start to think about what’s personalization two dot o maybe if they’re already doing a little bit here or there. Alright. So two answers to that. One is, you know, I think to really harness the power of personalization, we’ll need to cross over the line where we feel comfortable with the AI executing personalization without a human in the loop. You know? And there actually are cases where we’re doing that right now with some of these things like customer service chat bots and things like that. But I think in a lot of marketing cases, we’re still in a place where, you know, bulk marketers are like, yeah, we’ll leverage this AI to accelerate our production, but we still want final approval all over what’s happening. And given the current state of things, I actually think that’s smart. But there will come a point in time, I believe, where we will cross every line that, you know, this is ninety nine point nine nine nine percent, you know, currently what we want and the benefit we get from letting a truly custom tailor things to individuals. Well, more than that way, you know, what we then see as the remaining risk. But that being said, you know, what you’re saying about data, obviously, data’s like the the secret sauce to all of this. Like, the AI itself is, you know, effectively commoditized, you know, and it’s the data that makes the difference between this company has an amazing AI experience and this company not so much. Barclays have always been wrestling with data. We have this embarrassment of riches of, you know, in the digital stack, digital, you know, touch points, digital operations. We get more and more data than we know what to do with. The problem is, like, organizing that data and making sure it’s clean and good and, like, that’s just a frigging ton of work. And I’m not saying that that problem is gonna completely go away, but one of the most exciting things right now here with these generative AI engines is they are very good at basically taking messy data, unstructured data, and, yeah, here we’ve got, you know, this sort of behavioral stuff here. We’ve got this buying history there, you know. And sort of like, you know, consuming that and being able to somehow synthesize, like, oh, well, actually, this would be the relevant insight, you know, from that tangled mess, you know, that you just threw at me. And I think that is gonna be really amazing for folks because I don’t think we’re gonna magically solve our data problems, anytime soon. It’s almost like now we have a technology that says, even if your data is kinda messy, you could still get a ton of value out of it. So I think that’s gonna be really exciting. And then the other thing you said too is, you know, from a data perspective, as marketers, we’ve thought so much about the customer data infrastructure, you know, and how that sort of operations and architecture works. Frankly, we’ve thought relatively little about an equivalent architecture for content. You know, maybe you have a dam, you know, maybe you have certain, like, workflow processes, but it nowhere near as mature as the customer data infrastructure. Because, again, we don’t really have a mechanism to take advantage of, you know, more structured content oriented data. Again, with generative AI, I think this changes, becomes a huge asset to be able to feed into these engines. And so I actually think that’s one of the areas we’ll see a lot of innovation over these next few years is new technology sort of in the content stack, you know, not just the customer data stack. Can we talk about AI agents for a second? Oh my god. And and you hit on it a little bit with the customer service example. Right? But AI agents are coming for people’s jobs. That’s what you hear at least, and I don’t know how well, I’d love your POV on how true you think that is and how you envision businesses adapting to meet that moment. I see both sides of that. I do think for marketers in particular, I think the next as far as I can see, we’ll say five years. I I think actually gonna be a really great time for marketers because they do have so many ideas, so many things they’ve been trying to execute, and the constraint has been on, like, the production or getting the analysis. And a lot of these tools are gonna unleash that, and they will be able to backfill the time they used to spend doing drudgery work with things that actually will deliver a real value to the business. So biased on this, but I do think marketers will be in a pretty good position. Boy, if I’m a, you know, contact center, call center rep and you get more and more of these agents, AI agents are able to, like, self-service a larger and larger percentage, at least first line, if not second line questions. Yeah. There’s just nowhere around it. We’re just not gonna have as many contact, center reps. And I will say, well, as soon as we get beyond the context of MarTech, my expertise falls off the cliff. A side effect of having spent twenty four seven every day just on martech. But, outside of my domain though, I think anyone who’s thinking about, like, wow, the broader societal impacts of this, I do think they’re gonna be incredibly significant and challenging for us. A follow-up question on that to you then because this has been a debate in in another CMO community that Sixense runs. How should companies position their agents? Should they be open and honest that somebody’s interacting with an AI, whether it’s via email or via chat, or do you feel like those lines are being blurred as well? My opinion is I would be open and honest about it. You know? I think it sets the right expectations, and then it also gives you a very smooth way, particularly for a lot of these, like, you know, customer facing agent experiences. I think it’s so critical to make it really easy for someone to get through a human if they want. And and by having distinguished saying, like, this is not a human, you know, if this gives you what you need fast and easy and great and you love it, awesome. If this is not the experience you want, if this is not the droid you’re looking for, let me click through and, you know, talk to a human. I think the interesting thing, we could get into some more practical sort of steps for marketers. But this this whole conversation now, you know, first, like, SaaS is dead. Again, like, everything’s dead on LinkedIn. But software as a service is dead. But now this conversation of service as software, we’re not competing with other software products anymore. We’re competing with labor. And this idea, like, again, we’re talking about a a I agents and all that, replacing things. You talked about the the contact center, you talked about marketers being well. But do you think that we’re going into a into a world where could a one a human be essentially competing with an AI agent for a role? And not, like, literally, like, face to face, but there’s an organization that puts somebody out for a hire and now, like, oh, wait a minute. This is a maybe this is labor that can go to AI. Again, as Ethan Mallick would say, it’s the the jagged frontier. There are places where that’s absolutely the case today. There’s places where we’re very far away from that today. You know, we talked to contact center. Another example, which there’s actually a research paper, and I saw this because of something like Keith and Malik shared. It was an academic paper where, I guess this had researchers actually looked, you know, at the impact this has had on, you know, some of these job sites, things like Fiverr or Upwork, you know, and the degree to which there were certain kinds of tasks that people use to outsource, to those sorts of services that have seemed like an absolute precipitous drop off because now people are just getting it done with AI tools. I mean, so that is a very, like, one to one example. Yep. We used to pay a human for this as a service. It was an outsource service looking for a particular outcome. I’ll pay you two hundred bucks. You give me x. You know? And now I have an AI agent that I don’t know. Pricing models vary, but, you know, I pay five bucks to this AI agent, and it gives me x. Yeah. Those are those those scenarios are real. They’re again in the spectrum of all the things we do as humans and professionals in all sorts of disciplines. I still think the cases are a relatively small percentage, but one of the things that makes it challenging is the things that seem to be most affected by this are the things that have had the property that are not particularly complicated, but they’ve required time. You know? They’ve required a certain level of skill, not a huge skill, but, like, a basic skill. And And and there are things that are kind of embedded in stuff that we constantly need. Right? We constantly need people in contact centers, you know. Marketers constantly need some sort of, you know, like graphic generated. And so there were a lot of people who actually were serving, you know, even those relatively narrow, well defined use cases. And those are the ones that you have AI start to be able to replace that. And, again, in some of these cases, it’s able to replace it very quickly. Sometimes people talk about, you know, the examples of the industrial, you know, revolution or, you know, cars. You know, we’ve had these things where there’s been historical cases of a new technology displacing previous industries or workers the way they’ve done. And, yes, over time, we’ve all adapted. I sometimes hear the, you know, happy happy joy joy version of this of like, oh, yeah. Sure. It’s gonna displace, you know, these professions. But professions have always gotten displaced. We don’t have people doing, you know, calligraphy on, you know, like papyrus scrolls anymore. But the time frame over which those adaptations happen where particular things fell off and new things froze, you know, very much were in decades. And so to be in these scenarios where some of these things could have that, you know, trail off in a matter of just a few years, we just have no historical precedence of, like, okay. Well, how do you adapt, you know, people to these new careers and these new opportunities, within that time frame? And so, again, now I’m getting over my skis. This is a much bigger issue than me as a MarTech nerd and, you know, qualified to talk about, but I think it’s a really significant one. So, Scott, we have a question that we ask everyone of our guests at the end of the podcast. What is the most ridiculous thing you’ve been asked to do in your career? It could be ridiculous, good, or bad. I don’t know. Put fourteen thousand little logos on a slide. That’s pretty ridiculous. I mean, seriously. No. Totally. Totally. Do you actually do the logos on the fourteen thousand logos on the slide? No. Now we’ve actually gone ahead and, computerized it, but I would say up to at least the eight thousand mark. We were still placing those things, by hand. You did ask yourself to do that though, or did somebody else ask you to do that originally? No. No. Yeah. Fair enough. I just wanna make you feel free, like, you know? Yeah. Of course. I should’ve acquired by I should’ve quit on myself immediately, you know, when being asked to do that. Actually, what should be another question? What’s the most ridiculous thing you’ve asked yourself to do? Because I could have a myself, I have some pretty ridiculous answers on my own. So I’m an entrepreneur by nature. Everything I did actually before the work I currently do at HubSpot was all, my own ventures. And I like to think even what I do at HubSpot is so tied to the entrepreneurship that happens around HubSpot. And the reality is entrepreneurs, we sort of thrive on the ridiculous. You know, that’s what we get inspired by. Wow. It’d be really ridiculous if, you know, you could do this. You know, everyone laughs, and then you’re like, yeah. I think I can try and make that happen. Not to say that we always actually succeed or make it happen. The the odds are very much not in our favor, but the ridiculousness is kind of what, yeah, gets us up in the morning. Your intro started with the word joy in what you do, and it’s it comes across so clearly, Scott, and it’s infectious. So thank you so much for your time. Thank you for having me. Really appreciate it. Thanks so much. You’ve been listening to Revenue Makers. Do you have a revenue project you were asked to execute that had wild success? Share your story with us at six cents dot com slash revenue, and we might just ask you to come on the show. And if you don’t wanna miss the next episode, be sure to follow along on your favorite podcast app.