What's up, guys? Welcome to the Humans of Martech Podcast. His name is John Taylor. My name is Phil Gamache. Our mission is to future proof the humans behind the tech so you can have a successful and happy career in marketing.

What's up, everyone? Today, we have the honor of sitting down with a true Martech Jedi master, Paul Wilson, founder and chief strategist at GTM Systems. Paul kicked off his career in software sales and cybersecurity and was later introduced to the intricate world of email and Martech at an Ottawa based startup that offered anti spam and antivirus email filtering software. He would later start his mood lighting freelance career founding CRM Nerds where he would provide strategic leadership for Martech implementations for a variety of brands. And after a short stint at Bell as APM for their CRM business solutions, Paul led Martech and SalesStack at two startups, DNA thirteen, an Ottawa based brand reputation management tool, and Clockwork, a Minneapolis based developer productivity tool.

Paul also worked at two agencies, first Shift CRM as a Salesforce consultant in Ottawa and later at Percudo, a senior solutions architect in Denver. He then made the mega move to Marketo, first focusing on partner development and later as the head of Martech and innovation. And after their acquisition by Adobe, Paul was one of the leads on the project to implement Marketo for all of Adobe's b to b business. The mega moves didn't stop there, though. Paul took on the role of senior director of marketing ops at Slack and was later promoted to VP after their Salesforce acquisition.

And finally, after a short stint at One Trust, Paul strapped on his jetpack and went out on his own to found GTM Systems dedicated to preparing businesses to harness the power of Gen AI. Paul, what an incredible resume and career journey. Pleasure to have you with us. Thanks for your time, man.

Yeah. Awesome to be here. Very excited for this.

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Check them out at knack.com. That's k n a k, and tell them we sent you. I think this is quite a bit of time in the making. I know that at at CRM nerds during your initial independent consulting project, You assisted this little tiny company in Canada called Chipworks, which just so happened to be my first real tech job. And I have to say that your influence sparked my interest in marketing ops at a very early stage in my career.

And I'm incredibly grateful for the world that you introduced me to at such an early stage of Martech. And so typically, the advice that we hear a lot for early career folks is to hold off on freelancing too early until they have more experience, a bigger network. But it seems that if one's skills and specializations are ahead of their time, freelancing early could be beneficial. Curious if you agree and and walk us through that CRM nerds journey.

Yeah. So it's kind of an interesting an interesting take on where the role of the freelancer fits in the technology maturity curve, and I think that where marketing automation and marketing technology back in the day that we're talking about at Chipworks, you know, really we're looking way back in time to, you know, 2012, probably 2012, 2013 and at that point in time marketing technology was really, you know, on that phenomenal rocket ship launch of the impact that marketing automation can have on the sales cycle. And when technology is new or rapidly evolving, those are the opportunities where I think freelancing has a big role to play in advancing the marketplace. So, you know, at that point in time when you and I met, the platforms like Tardot, HubSpot, Eloqua, Marketo, all of those systems were really kind of new, and mature agencies didn't have a stable of people who have a lot of experience, and it made sense for me at that point in my career to stay in that freelance space because it gave me the opportunity to be exposed to many different challenges, many different organisational sizes, many different organisational cultures, and that helped me evolve the skill set that then became core to to where I am today.

I believe certainly that we're at that same precipice right now. I think that there's been kind of a plateau in the marketing automation space, the go to market system space. I think that whole ecosystem has kind of been where it is for a while, and I think the next push that generative technologies are going to make in the market we'll see a lot of people who in this tumultuous year of 2023 who are now in the, you know, independent because there's a lot of people who are now independent consultants. Mhmm. Their opportunity is to adapt in the marketplace with the technologies that are now changing and bring the skill set that they have to help companies through the transition that everyone is going to be going through.

So I'm I'm a core believer that freelancing in the right marketplace at the right market maturity is, it's an important part of the market.

The fascinating take. You know, six months ago you talked about launching GTM systems and, you know, the launch of 2023 generative AI just took off in a completely different way. As an independent consultant myself, integrating ChatGPT and all these wonderful tools into my toolkit has been a huge boon. But I also see that organizations themselves kind of struggle with how do you make the most of this generative AI? How do you, at that cross section of Martech and generative AI, what excites you the most about the future and the types of projects that you have on your roadmap?

It is definitely an interesting time, and I think that the the challenge that we're seeing in the market right now is it is a lot of buzz. There's a lot of desire to take advantage of these new capabilities and make generative a productive component of marketing planning, sales planning, and that whole digital experience. However, what what I see in the market is there's there's kind of three components of what needs to be in place for an organization to step into the realm of leveraging these technologies. The first is awareness of where they are. So I think I saw a graphic.

I I wish I could find it and I'd save it, but I didn't. A person stepping onto an escalator, and they had one foot on the on the ground level, and the other foot was, like, six steps up ahead. Yeah. Classic meme. The graphic said, what the CEO thinks you can do right now with Generatives, and the other foot on the ground is where you are.

And I think that it's that space right now that companies are struggling with. So that awareness of where are we as an organization in our ability to prepare for this is is one of the core first things that I'm working with companies on. The second is what is the what are the needed data points? What is your data architecture? Is your data foundation prepared for the requirements of that overriding generative AI modeling that needs to be, you know, needs to be in place.

So if you've got silos of data across systems that are not connected, that are not contiguous from a data perspective, you're going to have silos of generative capabilities, and that's a fractured experience and that doesn't scale. So not only do you need to be aware of what data that you have, what is the quality of that data, what is your content plan, what is your maturity level, who in your organization could take advantage of this. There's what are the foundations of that data that you have, is it all in one repository, is it in a bunch of different silos, are you trapped, is your data trapped? And then the third element is what is the organizational impact? Do you have privacy and data governance policies?

Do you have a stipulated set of instructions to tell your organization do not use these technologies. Are like, are you leaking a bunch of PII? Are you leaking a bunch of proprietary data into a bunch of generative systems? Or do you have a policy? Do you have a plan?

Do you have an organizational reorg plan that says, okay, we are now going to move to this new paradigm where we're leveraging these technologies. These technologies are going to be sunsetted over the next period of time. So there's there's an awful lot inherent in that long term view of a long term vision related to this technology change, and it's a lot to bite off. And so what I'm looking at is how do companies begin that journey? And really that awareness and that sort of auditing of what's possible is that first phase.

And I think a lot of companies have a very strong appetite to build that roadmap and really understand where they're going. So that's that's where we're focusing to start.

I think that's a fascinating overview. And I mean, it describes in a lot of ways my own journey with, you know, just ChatGPT as an example, using the data analysis tool. I feel like as a veteran in the marketing operations space, it kind of feels like, Hey, everything we've been telling you about data management for the last five thousand years is finally coming to fruition. Everyone's like, Oh, I really wish we had clean data. And everyone's thinking, Well, yeah, we've been telling you this forever.

But I think there's something to be said about having clean data, good data systems, and then recognizing how to speak to these machines, like natural language processing isn't

Right.

I know, Phil and I play with Dolly three and Midjourney all the time, and it can be incredibly liberating and then also incredibly frustrating. Talk us through, like, I guess, little bit of a two part question here, but, like, the marketing operations perspective and maybe why we're in this space really primed to be, the guardians of AI and generative AI in the organisation. And then the type of data language that we need when we're thinking about this new phase of Martech.

You know, look at it and think that the paradigm of today and then the future and what it means in marketing operations, you you you kind of hit the nail on the head. We're the we're the stewards of what the experience is, and this is where, you know, we've we've all seen the evolution. We've seen people update their LinkedIn titles to say Mhmm. Go to market GTM. GTM is everywhere, but at its core, all experiences now in b to b are digital experiences.

Curating the digital experience is what we have all been professionals in in marketing operations since the dawn of marketing automation. So we didn't really understand it then, we called it the thing, and over time we've tried to exert that control, we've tried to explain the significance of what that digital experience feels like, and to many, you know, to a certain extent we've won those battles, but also there are areas that we lost ground, and one of the areas that I think of is in 2014 or so when Outreach launched and SalesLast launched, that's nurture. That's marketing nurture. All of a sudden, BDRs and sales organizations are doing nurture. What are they doing doing nurture?

We we we lost that territory. Generative technology and that gift is going to mean that those digital experiences that start from filling out the form or whatever the future of forms is, and that's a whole other podcast. From that moment through to the customer success management, the automation of all of that digital experience is going to be in one organization. So that's why when I looked at, you know, what what I call a business, I thought about the butterfly effect because, you know, really, I think that's in in essence what marketing automation is, but go to market systems is all of the data and systems that curate that digital experience, and marketing technology professionals are the people who have that depth of expertise. They have the depth of understanding the data that's needed.

They know what that future experience is going to look like. So I think, like a generative AI model, I've wandered a little bit off topic, but I think that at its foundation, the skills that we have in marketing automation and marketing operations are the skill sets that will really persist across the evolution of how technology plays in that whole go to market brain.

Yeah. Very cool. It's interesting to hear you walk through the the GTM spectrum and how many touch points there are within a company. But at the end of the day, the thing that combines all of them is the data and understanding the nuances of what to trust the data in certain silos or like, oh, it's coming from two different pipelines. But we know that this one is it's better.

We trust it a bit more. How much of the work for GTM systems is actually going to be you being the person in between these GTM teams and the data team. You know, like GTM teams and ops teams understand the usability of the data. They understand the use cases and what we need it for. But they're not always the teams building the pipelines and the reverse ETL and putting that into the warehouse itself.

Today, in the cloud data environment, it's the data team. So how much of the work that you're embarking on is actually like sitting in between both of those teams and translating some of those use cases?

That's that's still kind of unclear, and and the reason it's unclear is the evolution of technology hasn't yet indicated what technology systems are going to be leading those changes. And, you know, one of the ideas that, I'm trying to think through and formulate a way to ask them and articulate is in similar fashion to the way organizations have gone from being in the office to being remote based because COVID was this transformative, unpredicted cataclysm within work. I suspect that we're going to see something similar over the span of two to three years where today when we think about generative AI and we think about what needs to happen, we're stumbling around the ideas that we need to clean our data and I believe that technology is going to have a massive effect on what that level of effort will be, because right now we look at terabytes of data and think, holy cow, I don't I don't I don't know even where to begin. I believe that machine learning is going to come in. People are going to begin, you know, constructing algorithms that do a good job or a good enough job of scouring and cleaning historical data, and we're going to be able to fairly rapidly once that evolution occurs be in a future state where we no longer need a lot of effort behind synthesizing and cleaning data.

Algorithms will be able to do a good enough job for us. And so then it becomes, what is the what is that curated experience? Like, then we're focusing on that digital experience. So what is the right content path? What path?

What's the information that's needed to be able to inform a large language model on what is the best content by persona, by geo? And that's where I'm trying to have conversations with prospects and customers about where they should focus. Mhmm. So it's no not not so much focusing on cleaning the house. It's, okay, where do we wanna move to?

Right. Yeah. The the curative path, like the the personalized path that you just mentioned there, you actually wrote a really awesome article on the impact of of generative AI for sales tech and Martech industries and how it will be similar potentially to the impact that Napster had on digitizing the music industry. And in the article, I found it fascinating how you're predicting that governments will eventually require user consent before companies can use AI to process their data and tailor that experience, that that curative experience. What advice do you have for marketing ops folks that are just starting this this journey today who are working on such experiences, but might be completely overlooking this this new potential requirements, where the infrastructure required to support and choose your choose your own adventure type capability where, you know, you might have like click here for a traditional experience or click here for the AI experience.

Like, would love you to unpack that.

Yeah, I believe that there will absolutely be government involvement. Obviously, maybe very geo centric, where in Germany it could be that in The in a similar fashion to GDPR, there are mandates that say that an individual's data can only be used to tailor their experience if you have their consent to do so. And so from an infrastructure perspective, the the early stages of that are focusing and understanding on what the consent and preference requirements could be in the markets that you are looking to be active in. And that's both marketing and selling in those markets. And looking at the leadership of companies like One Trust, companies that focus on the capabilities and ensuring that companies have the ability to properly respect and reflect those preferences.

And so the the early stages would be, do you have a unified and formal consent management process? Do you have enough of an understanding and documentation of what that means in your organization to be able to reflect a change like the choose your own adventure option across all of your web properties if that kind of legislation came along. We know that legislation takes a while to come to fruition, but I believe that in the span of engineering to the future, it's an engineering exercise that needs to begin today and it's a differentiator that companies need to be able to plan for in the market to say we will 100% respect whether or not your data is used to personalise your experience based on your own preference. So that's the capability that I think needs to be looked at now.

It's pretty fascinating talking about the, you know, the opportunities for personalization with AI and data enrichment. When we had Scott Brinker on the show, we got into the topic of composability and Martech as an overall overarching think he just released that there's what, 17,000? I don't know. I always get it wrong. It's it's such a huge Martech constellation now.

It's hard to keep track of.

But Well, but the the by the time that we've had this conversation, there's, like, 8,000 new pieces of Martech that are in the marketplace.

All generated by AI, you know, new startups Yeah. Coded overnight. I think, like, the idea of composability has been such a huge topic in our recent episodes overall. I'm really curious about your take on it. Like, to me, I see composability and AI.

AI can play this almost connective tissue role between these different platforms. As you were talking about managing consent from all these web properties into email land, this is a dog's breakfast of problems for most marketing shops. Like, hey, I have 10 different tools at play. How do I manage all of this? And then how does AI play a role?

So maybe talk to us a little bit about the role of like data provisioning, data enrichment, AI, Martech. Huge question, but curious on your take on this.

Yeah. This is this is another episode. Like, the the whole the whole notion of what is infrastructure to me is going to adapt, and Scott Brinker definitely is leading the edge of those conversations when it comes to composability, the idea of data, and the usage of data. He spoke at Mobsypalooza a few weeks ago, and one of the core things that to me really resonated on one of the slides that he had there is the idea that the sanctity of data. So when you're talking about a dog's breakfast of permissions of systems and whatnot, in a land where data becomes a baseline and common, where you're no longer working with, you know, data in marketing automation, data in CRM, data all over the place that copies data from other systems, and there's this soup of connected pipelines.

When we can look at a future where, you know, Redshift, Snowflake, where there's a central repository on which microservices run, but the microservices don't hold data, that data repository becomes that central place where permissioning, where consent, where preference, all of those elements are harmonized because it's in a central location. So the composability becomes a little less of this, I'm going to pull from here, I'm going to pull from there, I'm going to tell you what all of this means. It becomes the data architecture of what is that backbone repository. And then on the topic of, you know, enrichment, I think that it's going to be a very interesting evolution when the the generative infrastructure, the generative consumption across all of the Internet becomes the repository that's accessible and available to a large language model, it is no longer going to be really the outside vendors that are significant. It's going to be how is a company leveraging its inherent intellectual property, its own knowledge bases, its own customer history, its own persona.

So the enrichment sources are going to become internal sources. Not that external sources won't be critical, but those external sources are going to become harmonized because the machines are gonna take over the Internet. The data is just going to become available, and the enrichment is gonna become more the impact of that real time enrichment where, you know, Phil completes a form or filled whatever the the future forms, which is that other podcast episode. Whatever happens, Phil hits the radar, and a real time generative engine is going to be able to know two other people from Phil's organization are also active and taking, you know, consuming content off our own web properties. While that's going on, we know that there are already two instances of whatever the product is that we have active within that account.

So the response when still takes this action and alerts us that he's interested in more information, the response will be a generative, created, interactive communication that says, hey. You know, you're already a customer, so we already have all the paperwork needed. If you're interested in more, here's a product led growth stream that you could hop your way into and just continue a try like, all of that kind of contextual information will be Bill's experience. And so that will be all contextualized off of the data model, and enrichment becomes a micro surface that we no longer have to be aware of. It just becomes a component of what that generative experience looks like.

Very cool. It's fascinating and exciting to hear you you break that down. This episode is also brought to you by our friends at Sensus. Sensus is a data activation platform loved by marketing teams at Sonos, Canvas, Crocs, Notion, and more. As a customer, I've experienced the magic of Sensus firsthand.

Their no code audience hub and reverse ETL enable me to use our cloud data warehouse to power growth and create highly personalized customer journeys in all of my marketing platforms like Iterable and Google Ads. If you like the Humans of Martech Podcast graphics and you want your very own image, we're doing a monthly raffle for a personalized t shirt designed by us. Enter to win at getsenses.com/humans. And I feel like, you know, maybe some listeners are thinking that this is, like, five years down the line for my enterprise company. Like, we just started rolling out Redshift, and it's it's broken still.

Like, the ETL pipelines aren't perfect yet. Like, this future sounds amazing, Paul, but like we're like we have so many strides to get there, right? But the flip coin is the listeners that are at startups who have had a data warehouse in BigQuery for three years already, who have like three people on the data team who have built out a composable stack, and they already have this warehouse native approach. Like this becomes reaching like a lot sooner than than some of these enterprise companies. So like, if I'm, if I'm a marketer listening to you talk about this, like this future, which might be a lot faster than than some realize.

Like, what is the job of the marketer look like in three or four years when, when some of these things are are no longer theoretical, but but actually practical in nature? And you kinda spoke to this a little bit. We had a guest last season, Pratik Desai. I don't know if you know him. He he used to head up personalization at Salesforce, and he's predicting that large in large enterprises and heavily regulated industries, marketing ops folks are going to morph in this like role of AI regulators.

And you seem to agree with this prediction. In one of your interviews, you explained that rev ops and mops folks are poised for these roles because they understand the practical elements of the data, the nuances, what pipelines to trust. So what advice do you have for for the listeners who are keen to take on these roles or create them within their companies? Like, how can they become experts in in that specific area that's that's gonna be mainstay in in probably three, five years?

Yeah. Great question. And great big huge disclaimer, I am not from the future, so, you know, these these are these are ideas, and I look at this as something where, you know, the ability to look around the corner in your organization, and the ability to think through what the near term impacts of technology are on your job is the most important skill, not only for marketers, but if you're a BDR today, if you're in RevOps today, if you're in any of these roles where what you do is likely going to change, I think understanding the skill sets that are most important to your ability to adapt what you have right now for what companies will need is how you ensure paycheck protection going forward. And I think that for marketers today, if you're in marketing technology, the skill set is being aware of what platform changes are happening in the big players. And so, as an example, you talk about Salesforce and I had the great experience of learning and understanding a little bit of Salesforce from the inside, and their email engine is built in such a fashion that marketers don't choose their audience.

Marketers don't say, I want this to be sent to these people. Marketers submit their content in rich text format for emails, and then there's an engine that looks at what the next best offer is by an individual's persona and the content that that individual has consumed. And the engine then assembles the next best email to go to the individual based on that individual's prior activities. So rather than the marketer saying, I want these 18,000 people to get this piece of content, The content engine determines what the next best piece of content is for people. So if you're in marketing and marketing operations today, I think understanding that that prompt based universe is going to be arriving sooner than you probably expect, where a marketer isn't going to be asking marketing operations to pick the audience or to to give instructions to the marketing operations team who the audience should be.

A marketer will say, I would like to send a three step nurture to mid pipeline personas of this regard in this geography. I'd like to launch it by this date, and the audience will get assembled. So some of the minutiae of what marketing operations teams are doing today is going to adapt, and that's going to change, and I believe that's gonna happen from small business all the way through to enterprise. Because those sorts of capabilities, although they're difficult today, machine learning is gonna make those fairly easy to be intercepted pretty quickly. So that ability to adapt, that ability to look around the corner, to see and sense the changes that are happening in your role, I think that's that's the core skill.

That's the core adaptability that we need to do in in our space.

The phrase that comes to mind is with great power comes great responsibility. Remember,

with great power comes great responsibility.

And, you know, as a marketer, I was thinking through this thinking, you know, this sounds really exciting to me. If I have clean data sets, I have a good sense of where my customers are within the journey. I can deliver content that is like chef's kiss. But as a consumer, I'm actually of two of minds. Like, one is is, man, this is freaky.

Right? Like, people are gonna be able to, like, know things before I know them. Maybe you're not from the future, but these AI models sometimes feel like they are. Then there's the other side of it, which is, we just covered this in like an episode about email, Google's new spam, is like, maybe you'll cut down on the BS out there. Right?

Like, hey, you're describing a journey to Phil earlier. You know, you're already showing all these indicators. Why don't we just smooth this for you? We have AI here. What are things that, like, both sides of the coin should be thinking about?

Like, how should marketers be thinking about this great power that they have and and using it responsibly?

Well, I think you've really hit the key, and that is, you know, the the tailoring, the the the targeting, the you know, I I think of brands that I experienced today, you know, do it very, very well. I I think it's become a lot more commonly understood, but it wasn't very well understood until recently that Netflix curates the iconography of a show based on the user.

Mhmm.

So if I log into Netflix using my account, I see something very different than my daughter might, than my wife might, than you might for the exact same show. And so that notion from a marketer's perspective is with great power comes great responsibility, and the responsibility is don't be dumb. Like, don't, don't annoy me. Don't overcommunicate. Don't say the wrong thing to me.

Don't offer me something that isn't applicable. If I'm already a customer, stop sending me offers to become a customer. Like, these kinds of capabilities are going to catch the attention of your audience. Mhmm. And the audience is going to appreciate the respect that you should be able to deliver with these new capabilities that are gonna be unlocked by good data and systems and machines.

So

I think there's something there that I found heartening, which is the idea that, like, marketer's soul still is intact. Like, the idea of this intuitive sense of what to send, when to send it, how to connect in with your audience. Like, this doesn't go away. But now that we have these capabilities in our toolkit, like, them judiciously, I think, is gonna be almost as influential as, you know, we're gonna be flooded. I'm sure of it in the next two to three years with, like, like, LinkedIn already is flooded with with clearly chatty p t authors and so on, and we're guilty of it from time to time ourselves.

But, like, I can see I can see that this is, like,

coming back. This is the confession session.

The confession. Well, we that's a whole other episode as we've been saying. But I think I think this idea of this disclaimer of was this generated by AI or not gen I don't think unless governments mandate it, it's gonna be hard to determine this, especially these tools get better and better.

I think it's gonna be impossible to determine, and that's one of the kind of the double double edged swords of this technology. I mean, I've seen I've seen a lot of the discussion and debate, and I am not gonna try to lay into it here, on whether or not machine learning is any different than human learning. And if you go and study, English literature and you become an expert in English literature and you are then authoring content, yes, it's different than a machine that can do that same knowledge compression and new and no things to deliver new content into the market. It's gonna be it's gonna be impossible to determine at a 60,000 foot level what is real content and what is not. But I think what will always be consistent and what marketers can focus on is the overall experience needs to be authentic, and I don't believe that machines will ever be in really in a position to do that.

And I think that's where marketers need to leverage machine learning, not as a crutch and not as the author, but as, like, a thought partner, like a brainstorming partner, like, yes, I don't necessarily need to author the landing page for a webinar. That is not necessarily something that is going to be a huge value and huge differentiation. But I am going to look at thick suggested pieces of content that a machine learning engine can generate. I'm going to take those six pieces that construct a nurture flow and make them more authentic. I'm going to curate them.

I'm going to I'm gonna use the machine to help me generate those six pieces, but I'm not gonna leave those six pieces the first thing the machine suggests. I'm going to touch them. I'm going to adapt them. It's going to be humanized.

Yeah. Very cool. Yeah. This this difference between the human machine intelligence is a topic that I've gone really deep on recently where we're prepping for an interview in a couple of weeks with Brittany Mueller, who's gone super deep in the ML space. She's a former SEO scientist at Moz.

And one of the books she recommends is Eric Larson's The Myth of Artificial Intelligence. And he highlights in the book I'm only halfway through it now but the distinct nurture between human intelligence and the overlooked role of abductive reasoning and AI research today and how it's not a thing yet. But it's probably just a matter of time until research evolves from deductive and inductive inference to embracing this whole new element of abductive inference and enabling this form of reasoning where we kind of just talked about kind of the intuitive problem solving that makes marketing ops tick, right? Like that it could be positioned to replace this uniquely human experience of the Eureka moment or whatever. So I guess, yeah, like I you don't want to go too down this rabbit hole, but I'm curious, like, well, while we're on this thread, like if you have thoughts on like, how do you think we maintain this uniquely human aspect of creativity that is at the heart of marketing and intuition in the face of advancing AI tech that someday probably has abductive inference in there?

I guess you have to give me a time frame. Are you asking me to look ahead for, like, twenty years? Because I I I honestly wonder in twenty years if it won't be marketing generative machines, marketing to purchasing generative machines that consume the content. You know? So I think that one of the significant paradigm shifts that we will likely experience towards the end of my lifetime and to the generation that follows is the humanities will reemerge, and people will begin really valuing human generated experiences and content.

And if that potential does in fact happen, then marketers will return to being the the creators of true genuine content, and that'll be a differentiator that emerges in business. And so the what's old is new again model will probably emerge, but probably for the next ten to fifteen years, we're going to see how machines can consume their understanding of us and express it back to us in what it delivers. So I'm gonna leave those science conversations to the scientists, like the person you're going to talk to. So

let's switch gears a little bit here. We've been talking a lot. Well, we've been touching a little bit on this thread, but I think talking a little bit more. We we both have a mutual admiration for a company, local company in Ottawa, Knack. I know you took the stage with them to talk a little bit about scaling campaign creation.

I want to talk a little bit about what you think Knack is doing well in this space, because I think that they're doing a lot of things quite well, and how this fits into this conversation around generative AI and scaling the campaign creation across the organization.

Sure. Yeah. I I think that in the evolution that I imagine, again, I'm not from the future, but I think I know a little bit about where it's heading. The silos that exist today, the silos in marketing, emails, sales, generated automations, customer experience, so everything from marketing automation to CRM to the customer success like Gainsight of the world, all of the intent of those platforms is to create experiences, and my hypothesis is a lot of the technologies are going to change. There is going to be an adaptation that occurs.

Where NAC fits to me is it becomes that self serve layer for the people who want to deliver those experiences to have a common platform on which they can generate, curate, and manage that email digital experience, the landing page digital digital experience, and the back end systems can morph. You can go from one platform to another. You can have different systems get changed and swapped out in the back end, but Mac be remains that persistent layer And inherent in the way that that product has been created are all of the procedural elements that companies want you to go through. The idea of, you know, we're going to create brand standards that you can't break. We're going to establish an approval process through which you have to go.

You know, all of those mechanisms are inherent in the product. So where I've, you know, implemented that and where I've seen to have great success is marketers get to create content. They get to see what it looks like. You no longer need to go to the marketing operations team because you want one word to go from one line down to the next line just because you didn't like the way it looked. Marketers are empowered to do what they would like to do.

And I think when we look around the corner and look into the future, Knack can become that almost the Tinder of email where a generative engine might be creating the content in the back end, and the marketer is sitting looking at that content, editing it, manipulating it, humanizing it in an environment, and they don't need to worry about the back end delivery mechanics. So it becomes that layer of human interaction and all of the technologies and everything remains down in the background. Marketers, sales people, customer success people, they can interact at that Mac layer and just stay there.

Very cool. You're almost explaining what's happening in commerce with the headless advances and all the different decoupling pieces of it. Right. That'll be super interesting to see how that plays out. What we're seeing on the CDP side of things, unbundling the CDP, unbundling at some point potentially the marketing automation platform and all the different pieces to it there.

Yeah, NAC has a really interesting future proof product in that space. In the talk that you did with Pierce and Don Lee at Meta, you introduced this concept of campaign engineering. And how how do you see this role evolving in the in the future? I feel like we're we keep, like, putting you on the spot about, like, peer into the future, Paul. Like, you're from the future.

Right? But what skills do you think are critical for someone in in in marketing ops today or or maybe in, like, smaller teams and and they're wearing both hats today that they need to possess in order to effectively bridge the gap between marketing strategy and this idea of, like, operational execution?

Yeah. And so the the idea there is, throughout my career, and I will go out on a limb and say everybody who's listening who is in marketing operations will nod their head at this. Throughout my career, I have repeatedly been the person in the room saying, hold hold on. We don't have that data. So the campaign engineer is the individual in the room who is the connector, who is able to harness the vision and the imagination that a go to market experienced person, marketer, seller, customer success person, is able to understand what they want, what those people would like to deliver into the market.

And the campaign engineer is the person who understands what it will take. And almost also, is it worth doing? So, again, also, I'm expecting I I'm imagining there will be head nodding here. There's those moments where marketers have this grandiose idea and you go through the exercise and you construct this magnificent battleship that gets launched into the universe for four people to interact with. And no one ever seems to pay any attention to the idea that is this even worth doing.

And I think that that's where this campaign engineer role fits. It's an individual who does have an appreciation and understanding for the goals and objectives of the business and has a deep understanding of the current capabilities and the current datasets and knows how to get there from here and connects the dots and assesses if there's value, if it's worth doing, or knows how to communicate to leadership what the decision points need to be to determine if it is worth doing.

Awesome. Love the breakdown, Paul. I'm I'm happy that we're able to slide in a a Star Wars reference with with battleship there with the cover art. I was afraid we wouldn't be able to to get a reference in there.

You it you knew it was coming. You knew it was coming.

I thought for sure we're gonna have to redo the cover for time travel. So Paul Paul from the year 2044, just letting us know where AI is. You know, one of the things you touched on which really resonate you know, some nodding over here. So it resonated with me is, like, how how do you get these teams to to work together? And your experience, like, that human factor, I think, so important in in for marketing operations professionals.

In my opinion, the top marketing operation professionals are have a great human touch, the high emotional intelligence. But what do you see working in the places that you've worked in the past for getting these technical teams, non technical teams, to get these complex projects out the door without anybody being killed in the process?

Well, we don't report the deaths. That's the first key thing. I think I think the key is having an appreciation of understanding that everyone is trying to do good work. You know, at the end of the day, I I've I've not yet worked with any individuals who are at work to intentionally cause problems or to intentionally do bad things. And I think if you begin with that platform that sort of assume good intentions, it is it's it's helpful, and I know it's not always possible.

You know, human dynamics are a complex mix of chemistry, behavior, and organizational dynamics, and how people end up in the roles that they're in. So I have always tried to maintain a common element that we're all 360 degree humans at the end of the day, and what we may bring into a meeting room or what we may put into an email isn't necessarily completely planned. It isn't properly thought through. Sometimes it just is what it what it is, and it relate it includes having just received a phone call that a kid is barfing at school and you have to go pick up that kid. Like, the the realities of being in organizational dynamics mean you need to bring that level of understanding without being intrusive and and, you know, well, why are you acting that way?

Just assume that people have good intention. If they aren't on their a game, it's not about you. It's just it's to where where they are, and so be where they are and do your best work. That's the way I try to work.

I love the compassion in that in that answer, and I definitely vibe with the barfing kid at school interrupting your day. Bali had a beautifully written post about balancing marketing ops and admitting that you've battled burnout in your own career, something, again, I can resonate. Your father, a husband, a founder, a carpenter, an amateur carpenter, a meat smoking aficionado, we should talk about this in another episode, chief strategist, a public speaker, a board member. Man, you've got a ton going on in your life. And we ask all of our guests this, I think it's probably one of the most important questions we ask in this show.

Like, how do you find balance in your life between the success in your career and the happiness in your life?

Well, I'm to call it out. It's elusive. Think that, you know, as you've highlighted, I have a lot going on. I'm an ADD human. I don't always complete all my projects.

I often start things and get partway through and they fizzle out, But I think that where I found balance is in knowing that to be true, in knowing that there there are some great mistakes that I have made, and it's in recovering from those and and getting back on track and pushing forward that I find happiness. It's it's in knowing that time only goes in one direction, and we can't focus too much on what brought us to where we are. But if we use it to inform where we go next, I think that's that's really critical. And back to that to me, back to that notion of humanity, you know, I try to ensure that I approach everybody and treat them the way that I would like to be treated in the circumstance that I'm in. So, you know, where I've felt time get out of whack, and I've I have had many of those points where work has definitely overruled everything in my world.

You know, I I am now at a point where I can assess it and determine, okay. Is there a return down the road for me losing all of this time to work right now? And, you know, I've had to make that assessment multiple times in my career and I have gotten it wrong, I definitely have, and it's had an impact on the path of my life, but I am the one responsible for that and so at the end of the day as corny as it is, my happiness is of my own determination and I need to determine whether or not I'm pleased with the decisions I've made, but they are in the path, the direction that time goes is only towards the future, so I need to accept and move ahead and be you know, make the best of the situation that I'm in.

Love it. Super insightful, Paul. Thank you for sharing the the candid answer, the honesty behind it there. Anything else you wanna share with our audience before we go? I'll share a link to your LinkedIn.

Is that the best spot for folks to reach out if they wanna hear more about GTN systems?

Yeah. Absolutely. And just I'm just gonna call it out. I loved being on this. I think you guys I I love the idea of the humans of Martech.

I think you're probably going to need to adapt, you know, Martech and others, you know, over the course of the next couple of years as technology pushes us all into the same space. But it was I'm honored to be able to be here.

Thank you so much Paul. Thanks for reaching out. It's good catching up again and hopefully she's listening but a quick shout out to your wife Ginger who I know is in the Martech space as well. Makes for fun dinner conversations I'm sure.

Five whiteboards in our living room. I'm not joking.

Amazing. Thanks, Paul. Appreciate it. This episode was also brought to you by Iterable. Your customers didn't fall in love with a robot.

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