John (6:25)

Great. Yeah. I'm John, I'm the CEO over at Compound Growth Marketing. I spent the first decade of my career in house building out performance marketing teams and then started compound Growth Marketing.

Dave Gerhart (6:37)

Cool. All right, let's go, let's go around the horn.

Tammy (6:40)

I'm Tammy, I'm a chief customer officer here at Compound Growth Marketing. I come from a zero to one tech startup inside of a series B services startup. So Atlas was the name of the software. It's a network led growth product. And before that I spent about 15 years at a global ad agency actually mostly doing B2C marketing. And so I've sort of spent the gamut on either end of the spectrum doing large kind of consumer real like advertising campaigns down to like 0 to 1, wearing every single hat, developing end to end customer experience from go to market all the way down to actual consumer experience on the, on the CS side of things before joining the team here. Really excited to be here. Thanks for having me.

Dave Gerhart (7:26)

Yeah, good to have you here, Justin. What about you, sir?

Justin (7:29)

I'm one on the call that's not part of the compound Growth team. So my name's Justin. I'm head of marketing at a company called connexpayer. I'm coming to you from Central Florida. I'm actually in my first marketing role in this capacity. So I come from a life of product. I've been in product for a long time, both as a, you know, creative director, designer, managing managing product teams. So that's my background. Always been in B2B SaaS. New to payments but big fan of the Exit 5 community and happy to be here with you guys.

Dave Gerhart (7:56)

Appreciate that. All right, nice to see you, Dan.

Dan (7:59)

Hey everyone, my name is Dan. I am a GTM engineering lead. As you can see on the screen, I have a background in rev ops and I actually got this role through Exit 5. So quick shout out right there. Me and John connected on Exit 5 and the rest is history.

Dave Geart (8:14)

Love that.

Dave Gerhart (8:15)

All right, so my question straight out of the gate is can we try to back this up first? And there's been this rise of GTM engineering. I'm going to let you with this crew here try to try to define this. Let's let it. Sometimes people get mad. We'll do a webinar. Not. Shit, I said webinar. We'll talk for 40 minutes and then someone would be like, you never defined the thing. So let's let's come out of the gate and say, what is a GTM engineer? What is that role today? And then I want to kind of get back a little bit and talk about where, how did this role come from? Isn't this just marketing ops? Marketing ops. First there was marketing ops then and don't yell at me, this is my opinion. First there was marketing ops and marketing ops became rev Ops and now RevOps has become GTM engineering. Am I understanding that right? What's the role of GTM engineering today? Let's start there.

John (9:04)

I want to pass the ball over to Kami pretty quickly, but I want to recognize that we're in an upgrade cycle in the economy and what that means to us. When we think about that at compound growth marketing, we're seeing increased new technologies come onto the scene that are enabling new products to come into the market faster and find scale and offer new capabilities oriented around artificial intelligence. So that is one key thing that's happening. As a result of that, we're seeing fragmentation from like where you used to be able to do everything inside of HubSpot or you had some major service providers who are providing utilities in certain ways. We're seeing a lot more tools come onto the market which is requiring teams to connect systems together in order to work efficiently with the best technology out there. I also think capitalism works in really interesting ways where one of the killer use cases of artificial intelligence is its ability to make engineering teams more efficiently. So at the same time that we're all kind of starting to be concerned about our jobs, we're concerned about what's going to happen with engineering jobs. On product. There's an incredible amount of a flow of talent coming into the market who are looking for opportunities in different places than they originally were. They may have been working on product initially at Facebook, but now they can take a lot of that engineering and systems mindset and bring it into other capacities inside the organization as well. And so I think there's a lot going on, but the kind of driver of this is significant technological change and a rebuilding of the marketing technology stack.

Dave Gerhart (11:00)

Can you.

Tammy (11:01)

I think that's a really good, a really good preface as to like what's happening at the widest scale. I think drilling down to the role itself, for me, I think about like, the actual definition of like the back end of the, of the role is the signifier of operations versus engineering. I think about operations as someone who exists inside of existing systems, who's operating inside of existing systems, whereas an engineer can exist inside of Existing systems, but is usually building systems and then I don't know.

Dave Gerhart (11:34)

Did you see in the chat, by the way, Vlad had a good comment to build on that, which is like a rev ops ads and integration gtm.

Tammy (11:40)

Exactly right. So like if you think about existing systems versus building them, that's usually how I think about operations versus engineering. So I think Vlad's right. I think about the front end of those job sort of titles as the fluency of, you know, the language that you speak. So revenue, I think you skew more sales. Like you're right. There was probably a. It started as markups and then, you know, you sort of became rev ops because you had to be fluent in both sales and marketing. And I think the expectation of a go to market fluency is really end to end. The motion itself is your. Are you product led versus sales led? If you are a product led, you know, if the, if the, if the business motion is product led, you have to know that you can't just rely on sales. You have.

Dave Gerhart (12:32)

Okay, okay. All right, I'm vibing. I understand. Before I keep building on this. Dan, Justin, anything worth adding on this before we go deeper into GTM engineering?

Dan (12:45)

Yeah, I love how you said marketing ops to revops to GTM engineering because that's literally my career path right there. Just riding the wave there. But I guess the big difference, and I feel like a lot of people are confused where rev ops ends and where GTM engineering begins. Right?

Dave Gerhart (13:00)

Yeah. Just to build on that while you. Not to interrupt you, but while we build on this, the question in my head is like, so if I'm the cmo, am I going to do I now need both of these things or you just evolved into that role, right, Daniel? Yeah.

Dan (13:14)

Yeah. And when I was in Revops, like the thought process I had is how can I enable everyone, right? Like, how can I give them the data they need, the processes they need to do their jobs, Actionable data that they can use to be a little bit better. So getting everybody up to that 100% mark. Right. And in this new role in GTM engineering, I'm kind of thinking, okay, what can I do to give us a competitive edge? Not entirely a support role for everyone, but what competitive edge can I give us in our go to market, you know, motion? And how can I get us above that 100% line? Right.

Dave Gerhart (13:44)

Are we going back to like the era of like having a growth hacker on the marketing team? Is it closer to that?

Dan (13:50)

I think, I think it's similar. Right. Like, I think that's there have been like large teams that have spurred in organizations where they, they have brought engineering into marketing before. Like, this isn't a new concept per se, but it's just something that you couldn't do at a, at a smaller org. Right. And now with these new tools coming up, it enables that kind of mindset.

Tammy (14:09)

Again, I feel like. Sorry, go ahead.

Justin (14:13)

Well, I was gonna say. So I agree with everything you guys have said for sure. Kami, when you were talking about the, you know, the engineering, like the second half of the title being indicative of where time is spent, the two words that keep coming up for me when I think about the engineering side of go to market is like architecture and scale. And so for, like, for a marketer thinking about being able to zoom out and come up with that strategy for connecting disparate systems with all the new tools and the new ways that we have of doing it now, it's much more of an architecture mindset, being able to scale that like anything that we do now has to be able to scale rapidly and almost lean more towards like personalized ABM marketing. Where before that was a really separate initiative, but now you can kind of skirt the edge of that just with better tooling.

Dave Gerhart (14:54)

Can you all try to take me a level deeper on this here? One of my questions is like, okay, I got it. You got a gtm. Like, I can understand why you might want to have a GTM engineer on the team, but what's different now than like 10 years ago? Because I haven't been a marketing leader in a while, but in a future, in a past life, we hired an engineer to be on the marketing team and her job was to like, you know, hack stuff together and have development skills that we didn't have in house. And we've also had, you know, everybody's seen the Martech, you know, landscape. There's already been 30,000, 50,000, you know, SaaS tools for marketers to use. And so what is it about AI specifically that makes this GTM engineering thing more relevant than ever? Maybe there's something to build on with where Justin was going with the infrastructure and architecture and scale. But I want to try to drill into that and understanding that maybe not everybody on this call is an engineer. So what is it that's happened with AI in the last year or so that makes this different than. Yeah, we already had 50,000 software tools. I needed someone to integrate that. I needed someone. Marketing has been tech enabled for a while now. I've always needed somebody to be able to write Code. So, so what's different now?

Tammy (16:10)

I think it goes back 14 years ago. So, so we're on, we tend to be on seven year cycles. So there's like what was it 14 years ago? It was, it was big data. Big data was the thing like Clive Humbly said that you know, data was the new oil. And then seven years ago it was machine learning. We were in the era of machine learning. And so there was like oil refinement, right? And then now it's all about, we're in the AI era where AI is now universally available to everybody. And so we no longer need data scientists to make sense of all the data that now like everybody is their own data scientist. And so what that means is that like now product is no longer a moat because literally anyone and their mom can make a product. So what that now means is that your moat is network effects. So the person who wins, or the company that wins is the fastest to get the first customer on. Because the first customer on means the second customer can get on and the fourth customer get on and the eighth customer can get on. And so your network effects can start to take effect. And so that means that your product has to be as simple as possible to buy and your, that means that your go to market motion has to be treated like a product. And what makes that different is that the products available. So what's different like the go to market engineer now different than the rev ops person before or the like the growth hacker of your in that kind of capacity as you were kind of calling it Dave, that what's different now is the software is just different. And so software is not clunky anymore. It's not going to be clunky in the future. It is going to be incredibly easy to adopt. You won't have the same switching costs to implode the, the entire organization. And something is, you know, better, faster, cheaper. And so I think there is just going to be so much more available and you can actually just work towards outcomes. And rather than adopting all of these sort of like complex workflows that take a team to hack together or incredible experts with like crazy, you know, degrees to act together. And so I think it's really about people who are just really, really focused on increasing the revenue per employee both from two angles. One is getting your sales team more, you know, essentially more enabled as Dan was saying, getting them plus 100% and then two, getting revenue per employee down, trying to reduce headcount in the, in.

Dave Gerhart (18:36)

The org for the marketers here. Like since this is a marketing focus session. Like I get a bunch of it about, you know, products are getting built.

Dave Geart (18:44)

But I think for, for most people.

Dave Gerhart (18:46)

Here, this role would sit on the marketing team. So what are some specific examples? Maybe you're seeing from customer. Other people in the world that like GTM engineers are. I, I still don't really know what they're doing. Like, they're just, there's just a lot of, there's a lot of big words from all of you about, you know, infrastructure and integration. But like what do they, what do they do? Do they, you know, is it like what Tom Wentworth did, which I saw this week. He's the CMO of a cybersecurity company. They're developer tools. Whatever they do something I don't understand. They made like they did like a custom ABM campaign because they want to get anthropic as a customer. And so they made some like, you know, they growth hacked or GTM engineered some, some video game and that's a cool play. Is it that stuff? Like I, I need more specific examples. Otherwise I'm just going to leave this call thinking like, yeah, this just another, this is just another buzzword or someone in the chat said like, it's just, is this just Clay trying to like create a category around GTM engineering?

John (19:40)

I think that's a great point. So I'd love to kind of go into some of the examples that we've built. We're big fans of Tom here and so that's one of the campaigns that, that we've actually had the opportunity to work with him on. And a good example too of how I think a go to market engine.

Dave Gerhart (19:58)

Wait, you guys did that with him?

John (20:00)

We're working on the ABM campaign with Incident. Yeah.

Dave Gerhart (20:03)

Cool.

John (20:04)

And so it's a good, I mean Tom is the ultimate go to market engineer. I think he was one of the first people to build on top of the Drift API and really think about how to use the tool in different ways. You know, I would look at, if I were a company today, I'd look at breaking out the go to market engineering into different functions inside the funnel. To think about like the mid intent funnel, what are the different offers that we could build using Lovable and some of the other tools out there to capture customers when they're in pain. How can we get in front of those users and build a really strong engagement point for them? I think another interesting use case is we now have so much scale. We've been recording calls using Gong Chorus Fathom all the call recorders recently. And so another interesting use case that we've been digging into and even seeing some of our customers using is how do we analyze call data to understand intent but also how can we start to use that for attribution, Self reported attribution. We don't just need to ask people.

Dave Gerhart (21:16)

To fill some really good, there's some really good stuff in there. Wow.

Dave Geart (21:19)

Like, okay, we're getting warmer here.

Dave Gerhart (21:22)

I'm taking notes. So John, you've always been an advocate of this mid of mid, this mid funnel stuff, which is like for anybody that hasn't listened to me and John's conversations over the years, which I don't know why you would have maybe 200 of you that, that have been around. But basically like, you know, John's always kind of advocated for this. Like if you, especially in the world of B2B you, you hit a B2B website and typically the, the main action on the website is to drive someone to get a demo, contact sales, get pricing, request a quote, right? And like those are things that are much further down the funnel. And like when I'm ready to buy, that's when I'm going to contact sales. I'm never like, you know what I got, I got an afternoon to kill. Why don't you, why don't I contact sales for this piece of software I'm thinking about buying and see what, see what it can be. And so you know, we've talked a lot about companies that have been built great tools and basically built products as marketing over the years. So things that come to mind and feel free to put your ideas in the chat. But like HubSpot's website Grader is like the OG example of this, right? They sold SEO software and they created this amazing tool that if you'd put your website in it would tell you all the things that were broken and wrong with it and how to fix them. And then like behind the scenes they now know that the person who filled that out like has an SEO problem and they can help them. Another one was Optimizely. They used to have a way to preview AB tests on your website, right? At Drift, we built a way to test the bot on our website. And so that's kind of cool now where you're like, okay, if I got a GTM engineer on my team, instead of gated content and ebooks, we can really build some high intent mid funnel tools here. And we're all sitting on this gold mine of like all these sales calls and customer calls that we Have. It's not just like V1 of this listening to Gong to understand pain points. It's like I can now take all of this data and use it, you know, use an LLM to basically understand trends and understand topics and key objections and then we can have a GTM engineer like build some experiences around this stuff so we can get people to interact with our stuff.

John (23:23)

Is it going in 100%? Yeah. So I think part of the role here that we're talking about is there's like an element of R and D. I think Justin said that last week when we had a conversation about this. But there is a piece of, we have tons of unstructured data that we're now figuring out how to structure in order to pull insights from it. So Dave, you've been a proponent of, you know, we don't need to measure everything. We just kind of intuitively know that things are working for us because they're different. But you know, there are ways now that a go to market engineer can scan through GONG calls to even listen to the messaging of how customers are talking about a product or a category to understand how certain companies are having a influence on the market. Right. Thinking back to the drift days, you guys had conversational marketing. So it would be interesting if after you had launched that to listen to the sales calls and see how many times that the prospects who are looking at purchasing drift were using that in the conversation versus using some of the language that maybe your competitor at the time Intercom was using in their marketing messaging. And so like I think there, there's a customer feedback component to this of we can take this call data, we can route it into Air Ops or we can route it into Clay. We can use it for messaging and helping us improve our ad copy. We can use it to help us build a Persona GPT for our customers so that we can understand how customers are thinking about this and even simulate the objections that they may have in the sales process or to some of the messaging or ads that we put up across the Internet. We can use that GPT to get feedback on how they'll respond to the website website copy. So there, there's a ton of use cases that we can use just from that one prospect and customer feedback cycle.

Dave Gerhart (25:32)

Dan, Cammie, Justin, I love that you.

Justin (25:35)

Talked about getting the data into a source where you can make use of it because I. That's something I'm toying with. Like we use anthropic. So I've got Claude set up with a couple different projects so I'm trying to centralize, like, I think part of this engineering process is training your AI with the absolute best information that you can and organizing it incredibly well for future use, not just by yourself, but, like, as your team grows. I don't know what it would look like to open up Claude to a sales team. I don't think many of us probably want to think about that necessarily. But, like, if. If people could go crazy with content but have it all be centralized to your. To your product brain that's really well constructed for constant output and iteration. I think that's a big part of the engineering role too.

Dave Gerhart (26:14)

This is a perfect example of Matt's messaging on the side of my team. I'm all fired up because this is the stuff when I'm like, yeah, this is what's fun. This is like what we can make fun with marketing and this is where we can build great things. It was like in the past, it was like, let's make an ebook and you're going to download it and then sales is going to call you. But now what if we can take all this data and actually build a meaning? Because I still think that the best way to help somebody, the best way to get something, to buy something, is to help them in whatever capacity, whether you're a real estate agent and you're going to have, you know, make an amazing drone flyover mockup of the house and like, picture yourself at the house. Like, I need to. If I'm going to go spend $100,000 on a B2B product, or 100, you know, whatever it is, I need to feel good about that. I need to feel like that company helped me, that company understands me, that's going to happen later on in the sales process. But up front, man, if I had some tool, if I use your tool to like, improve some process of mine, like I used, you know, optimizely, say, you know, website conversion tool back in the day and like, they helped me out for free and gave me a bunch of opportunities here. And now I have to upgrade and talk to their sales team and buy the product to get the full thing. Like, that's where the. That's where the gold here is, is like, we can get back to doing really good marketing stuff. And then as the copywriter, storyteller, nerd in me, I love the stuff about using the customer, all the customer calls. John mentioned this Persona GPT. Basically, you're missing out on a huge opportunity today. If you don't have your ideal customer profile and your customer Persona is like nailed. And then you know, whether you use Claude or ChatGPT or whatever and you're constantly writing and iterating copy based on that and you have this kind of brain that really understands your customers. Imagine being able to go and say, hey, what are the most common objections for the last six months on our sales call And I know that as a marketer and I can address some of those things, you know, heads up, going in question for our, this, this question in the chat. I'm curious to hear this from our, from our panelists. Everything that we're talking right now. Christine, I'm not, this is not who I think you are. I'm just kind of, this is how I read this. Like, but isn't that just plg? How do we answer that?

Dave Geart (28:22)

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John (29:56)

What isn't what? Just plg everything.

Dave Gerhart (30:00)

Hello everything. We've Just been talking about like the, this like marketing stuff, creating marketing tools like in that example, like these mid funnel tools, isn't that just plg or are we just going to have a silly debate about like names? What do you think?

John (30:12)

Yeah, I mean I, I've seen that. Isn't this just for a lot of things? Right?

Dave Gerhart (30:16)

So we're, Isn't this just abm? Isn't this just good market?

John (30:19)

Isn't this just rev ops with AI? Like yeah, yeah. So I think partially it's, it's a challenge to kind of answer all of those at once and that and have everybody ask these like different questions. But then you know, we're kind of looking at it and I've been asked, isn't this just five different things and now we have the ability to put this all into one function.

Dave Gerhart (30:41)

So yeah, I think, I think my, my read on that is like on, on plg and this is not to get into the nuance of definition but like PLG to me is like if the true definition of product LED growth, which is like you have Slack and then Slack has a free plan and you try to get people in the free plan and upgrade them. I see this more as like we're using data and design and creativity and engineering to build tools that the marketing funnel and this GTM engineering concept. You might not be a PLG company at all. You might sell something that is like super high touch. PLG also means like really touchless. Right? Like I don't, I don't have to talk to somebody. I don't have to like do this crazy onboarding. It's very, you know, low friction. But you could sell a really high end infrastructure type of product that is not PLJ at all. But what we're talking about is using this new kind of role in marketing to create, to basically have the power of a developer on your marketing team to make more interactive and engaging marketing content than kind of just the standard content playbook.

John (31:43)

Yeah. And one thing I'd call out is when I was working inside PLG companies like when I was at Workable and I was at yesware and I was at Log Me in. Sometimes that funnel is limiting because you're looking to drive a user in when they're looking to access their, when they are looking to set up email tracking or they're looking to build an integration between Gmail and their Salesforce instance in yesware's case. So I was sometimes limited by the funnel and the lens that I could bring users in to the product and ultimately drive them in. So in order to expand the opportunities to engage with those customers, that's where I would create a mid Intent funnel in order to get users to start to understand. So in Guessware's case, we knew that when somebody was in market they were looking for email tracking or they were looking for ways to connect their inbox box with Salesforce automatically. But before they had that use case, they may be looking for email templates to share across their sales organization. And so we built out a mid intent offer for free email templates. And so I think the mid Intent funnel is not meant to be plg. It is meant to expand the breadth of helping you identify customers who are coming into market and ultimately going to be looking for a solution like yours in the near future. And I think the same was true with Test Drive at Drift. Dave, when you launched that and then we came on board and supported running Facebook ads to that, the challenge was that the PLG funnel wasn't working for a segment of your audience and you had a part of your audience that needed to build the case internally in order to get Drift to the table and be able to have a conversation about it. And so I think in a sales led motion sometimes you do want those high engagement, great brand moments to ultimately push users down funnel and generate that velocity.

Justin (33:54)

I also saw something that Imran just put in the chat in terms of plg, companies usually need a free or a light version of their of their software. So coming from a sales led organization, I guess the way that I look at it is for a product led company they can pull somebody into the story, into the brand story sooner by getting that buy in on trying it out on a temporary basis. But for, for sales led companies that have like longer buying cycles and the threshold is higher, I think it's, I think it's a way for us to tell a better story before somebody starts becoming engaged with the brand. So since we don't have that opportunity for like a light or a free version, it's how much of a better story can I surround my product with, my user stories with all of those types of things to get them engaged in the brand rather rather than the free model.

John (34:39)

There was a good question in the chat about the revenue per employee and thinking about shout out to come back to Cami's comment on revenue per employee. This feels like a core deliverable for what this role is focused on. Efficiency is the role. Now I love that call out and I think that's good area to dive in a little bit. Deeper because I do think there are KPIs associated.

Dave Gerhart (35:04)

Let's, let's first explain, let's first explain just like the, the, like the metric of revenue per employee and also in the context of marketing, like why, why do I care about revenue per employee? I'm a marketer on the, I'm a marketer at the company. My job is to generate pipeline for the, for the company. Like that's revenue for per employee. That's like the CEO and CFO's job. I'm going to run campaigns to build pipeline.

Tammy (35:27)

I mean maybe agree to disagree on that Dave, because I think that revenue per employee is absolutely something that go to market and with marketing within that should be either contributing to if not directly attributing to. Because there are three levers that go to market can control. One is volume of sales, like so pipeline. Right. Like one is velocity and also contract size. So the other I think where, where go to market engineering is really helpful in terms of driving efficiencies is like what data flows, where to what taxonomy and how are you thinking about, you know, who, who needs to see what, where and how. And if like sales enablement is a core component of how it is that like go to market engineering is thinking about their job and, and what it is that they're effectively trying to do, then the salespeople who are responsible for looking at the CRM and helping and all the intent signals of their key account lists, I think helping to drive any one of those levers at a higher velocity is absolutely contributes to revenue per employee. So you're trying to get them to either close more deals faster or at higher contract values. And then the other way to look at revenue per employee, even if you don't drive more revenue, you can reduce headcount. So you can make that headcount more. You can make the company more efficient. So revenue goes up per headcount.

Dave Gerhart (37:01)

And what, what role does the GTM play?

Tammy (37:04)

Reduce the headcount. So you would just be slightly more efficient.

Dave Gerhart (37:09)

So you have. So instead of having multiple people on the team, ideally you can have a gtm, a GTM engineer who's able to basically be like a, the concept of like 10x engineer but for somebody on the marketing team.

Tammy (37:20)

Exactly, exactly.

Dave Gerhart (37:21)

One person with AI and tools.

Tammy (37:24)

Instead of four rev ops people, you have one go to market engineer that is supported by multiple agents or something.

Dave Gerhart (37:30)

Got it. And by the way, I wasn't, I wasn't disagreeing with you. Like obviously revenue per employee is super important. I'm Just trying to like put myself in the shoes of like totally the average marketing manager at the company. Like, I get there's a, this, like I see people write about this on LinkedIn and it's like, you know, SaaS marketing sucks and it's broken. Like the marketing team doesn't care about, you know, CAC and the profitability. I'm like, do you think that the average 24 year old marketing manager at a SaaS company has like the, the fingers on the controls of the profitability of the company? Like they don't gonna execute. I'm not saying that's a, that's a good thing. I'm just saying at most companies it is not. They don't have the breakdown. And so like we shouldn't be yelling.

Tammy (38:09)

Yelling at this, yelling at a middle manager for anything. Yes, agreed.

Dave Gerhart (38:13)

Yeah.

Tammy (38:14)

But I, I think, I do think that there should be fluency of everybody in the marketing function about what senior leadership actually about.

Dave Gerhart (38:20)

I think that is absolutely. And that that's usually the crux of the, the issue in, in marketing is like so many things come down to like, what is the company strategy? What are the company goals? Okay, everybody's on me in the chat right now. We got to get Dan in the mix and he's, he's hijacking the chat. He's doing a great job. People just want to know, like, look, you brought Dan on this thing. We haven't even let the guy talk. They want to know what he does all day as a GTM engineer. So Dan, Dan was. Dan already signed himself up for an exit 5AMA on this. So you better bring the heat right now, my friend.

Dan (38:51)

Yeah, no, I actually came to this event to figure out what I should be doing all day. So no, I'm just.

Dave Gerhart (38:56)

Great. It's great.

Dan (38:57)

I think to preface, have you tried Claude? Have I tried Claude? Not yet. No. To preface the answer, I think if I'm doing the same thing in six months that I'm doing today, I think I've failed as a GTM engineer. Like, I think stuff is about to change in a big meaningful way. Some areas I'm spending a lot of my time in right now is. And I know people are clowned on this Clay and Unify and tools like that, testing them out, seeing what I can do when I pull. Create tables of target accounts, existing customers, what data points we can pull in, what actions we can trigger from that. That's the focus right now. I spent a good amount of time trying to upskill our internal employees on how to use tools like ChatGPT. And what I found is some people have a really hard time with prompting, so I kind of shifted that a bit and spending some time building out like a library of custom GPTs that kind of enables our sales team and, and I think this is going to be something we're going to see a lot of people like, kind of seeing some of their custom GPTs for people to kind of look into and pick and choose and bring into their own companies and adjust them to make them more relevant to your use case.

Dave Gerhart (39:58)

Can you explain for people on here who might be like the average lightweight ChatGPT users, can you explain custom GPTs, what they are, how they work, and how do you share them with the sales team?

Dan (40:11)

Yeah, for sure. It's very similar to when you're using ChatGPT. You know, you're putting in your prompt, right. It's very similar to that except for you find instances where there's reusable tasks. So tasks where you're going to be running this over and over again. Like if you're an agency and you're reviewing for every one of your clients all their nurture email sequences. Right. Well, it would make sense to make a custom GPT which is just a set of instructions you give ChatGPT, so that when you paste in subject line and the body content of an email, it goes through and says, hey, here are the nine criteria that I want you to look at this email through the lenses of, and I want you to provide feedback on how we're doing in those nine areas and then give, you know, actionable feedback on what we should do next with this email. Is it good? Do we need to make improvements? And so it's just an instruction set for the GPT to kind of give a frame or reference of the request. Right. It's really powerful when you have these reusable use cases within your teams. But yeah, so spending some time like building that out for our team internally and also for our clients as well of like, what can we share with them? And then I think there's this kind of third area where I'm kind of dabbling in now. And I think it's, it's more exploratory now, but I think somebody brought up MCP and chat model context protocol and this has kind of been hot in the streets.

Dave Gerhart (41:28)

Yeah. Can you explain this to me? Like my second grader, everybody's talking about MCP every time I open LinkedIn. Oh, you guys need to MVP server for this. And I'm Like I think there's a lot of people talking about this, but they don't actually know really what it is. I don't know what it is. What. I'm just a thought leader guy. But can we explain why is this topic becoming really relevant now? Why does. Why is Tom Wentworth asking tools that he uses to. To build their own, to let him build their own, his own MCP server? Can somebody explain this to me? Like I'm a child for sure, yeah.

Dan (41:58)

So I think HTTP Server, it's basically an instruction set for LLMs for tools like Chat GPT to interact with tools and pull data out of it with context. Right.

Dave Gerhart (42:09)

So right now use an example while you explain it like a popular tool that marketers use.

Dan (42:14)

I'll talk about HubSpot because they just came out with their own like first party MCP server. So basically HubSpot, you know, before they came out with their MCP, if you were had an LLM and you wanted it to pull data from HubSpot, it'd be using the API. Kind of like how, how most tools interact with HubSpot. The MCP server creates. How do I simplify this more? It creates instructions basically where it's like, hey, if you get a request that's like, hey, give me all like my top 10 contacts, like it, it shows it how to pull all the contacts and then pull the information it needs to give the right output to the end user. So it's just more instructions on how to use the API for the LLM basically is a really simplified way of saying it. And so that's where I think right now I'm testing a lot of agents right now. Zapier agent I'm looking at because they have a nice free tier and I'm doing some stuff and I'm not entirely happy with the output. Right. And it's because it doesn't have all the data it needs to when it talks to HubSpot. Right now I don't think they've adopted the MCP yet. And so I was like, hey, give me this contact and tell me all the recent activity on the contact and summarize it before I hop on a call. And it didn't do a good job of pulling the activity associated with contact. That's because it didn't have any instruction on how it would go about doing that. So that, that's where I think as more tools come out with mcps, like agents are going to become a lot more powerful. You're going to have marketers who have agents that Every day, look at all their campaigns and LinkedIn and call out any ones that are eating up budget but aren't performing any results. And it might message you in the morning, say, hey, these campaigns aren't working really well. Do you want to remove. Take budget away? And if it has right access, you know, you could say, yes, take it budget away. And then it will like turn off the faucet for those. So that's kind of an actionable thing that I don't think we can do right now. But as these MCPs become, you know, more prevalent, agents are going to be. And that's where I think in six months, I hope that I'll be spending a lot of time on is how do we enable people through agents.

Dave Gerhart (44:09)

Cool. The agents. The agent examples are. The agent examples are great. Which is like, oh my gosh, there's so many things that I could think about right now that are kind of daily, weekly rhythms and routines that we do in marketing. Whether it's website analytics or monitoring social or monitoring ad campaigns, we all work out a Slack like to just have a bot that could basically send us updates in Slack. Or it's like, hey Dave, here's. Here's a recap. I used Dharmesh's like agent AI. I sent it to Matt and Dan on our team last week and I was like, here's a. Here's a summary of your most popular LinkedIn post over the last six months. And here are the trends and here are the key topics and like, stuff like that is super useful. So would you as a company. I'm a writer, not a. Not a tech guy. Would you as a company, like, would we at Exit 5 have our own MCP server and like, we would connect to all of these other tools and like, that's where all of our stuff would live.

Dan (45:01)

You would probably consume NCP servers rather than have your own. Unless you have like a database where you're storing some data and you want to expose that to LLMs. Okay, I think real quick, the one thing I. My example was a good example, except for it only touched upon one system. I think where a lot of power will come is when these LLMs can interact with multiple data sources and pull the data together and bridge that gap. I think that's another really exciting thing that hopefully will happen.

Dave Gerhart (45:28)

Anybody want to build on those. On those. Anything else?

Justin (45:32)

The use case that I'm looking at just as like another. Hopefully we can get there soon. I made the comment earlier about enabling salespeople to go run with a Custom GPT for creating marketing materials. The idea of using an MCP to connect, you know what I've been building with Claude for my product marketing, brand projects where all that knowledge is stored. Being able to connect those to a service like Gamma as an example and be able to start having conversations between Claude and Gamma where the content is going straight from one tool to the other based on a series of prompts and being able to just continue decreasing that time to market so that you can test ideas faster and get more tailored stuff out there.

Dave Gerhart (46:10)

A lot of Dan fans in the chat right now, this is like great. They want this tactical stuff, they want this specific stuff. I tried last night, I was trying to make. I was like, why can't I just. I had to schedule an event on my calendar and it's very umbersome to click five times into Google Calendar. And I was like, why can't I just go to my chat GPT and write in my chat GPT and say book a call with John short tomorrow at 1pm on my calendar. And I thought you could do it with Zapier and chatgpt, but I think their, their integration was busted and I couldn't do it. I gotta work on that later. But these like mini recipes and that's just a silly one. Like I wanna operate as a mark, as my life and a marketer I'm getting used to. And I was listening to Jason Lemkin talk about this earlier in the week. Like software tools are. There's gonna be a big disruption happening where like we are all getting used to now writing text based prompts to these tools and getting this amazing output. And so I want to be able to say, put a meeting on my calendar tomorrow at 3 o' clock to, you know, and just write a voice command or write two lines of text to be able to do that. Think about all the other things in marketing that we now expect to be able to do that. It's like there's a world where like why would I ever log into Salesforce ever, ever again?

Tammy (47:20)

100%.

John (47:22)

We've been using Day AI as the CRM for compound growth marketing. They are starting to play around with agents and so we have those capabilities inside some of the tools that we're using already. The one thing that I would kind of underline there is in order to be able to write those prompts and connect with Salesforce and have Salesforce talk to HubSpot and then have HubSpot collect data from Clay, you need to have the proper wiring set up. Inside of your business. And so I think marketing is moving towards the state of simplicity where there's going to be less need for specialists and more need for generalists who can do a lot of different things in a lot of different ways. That prompt I think is a great example of why we need to focus on building systems that are building software into systems that talk to each other and allow you to spin up a campaign by writing a prompt and having it talk to Canva and HubSpot and all the different things, different platforms.

Dave Gerhart (48:28)

Yeah, actually I saw in, in one of our notes that I meant to get back to there was a Justin, a note from something Justin did with like Claude and, and Jen Spark. Is that A or Gamma maybe? Did you build something like that?

Justin (48:39)

So well, we had somebody on our Rev Ops team build a. So an onboarding application is a big part of our process. Somebody in the com, somebody in the chat was talking about, you know, time to revenue. So for us that's something that's actually really important. We, we send people through this application process for underwriting and we've been leaning on classic form tools like you know, jotform, all the different ones that are out there. But one of our guys on the RevOps team went and used Claude code and built a fully customizable configurable like onboarding workflow for our customers that was just top notch. And being able to do stuff like that, like this idea of prototyping and bringing things out faster is one of the big things that I'm seeing add value in a big way. So that's, that's an example of like when you get somebody in the pipeline or in, in the door. That's another example of how you can get them faster through the revenue.

Dave Gerhart (49:29)

Nice. I like it. I, I think there's just a. It now to me is the time to question everything. Like I'm trying to even do it in my personal life and just like how I would go through and create something in the past is, is different now. And so it's like yeah, okay, I could use can or Canva and I'm going to use Gamma and I'm going to write this chat GBT prompt. I think it's like you gotta force yourself to try to try to learn some of these things. And I also think that's how we go beyond the like V. One of this AI stuff was just like AI, there's a lot of AI slop AI generated content and I, I love it. I think that is I lick my chops when I see that stuff and see people talking about it because I think that for real marketers, for people understand the craft of marketing, the art of storytelling and building a brand and positioning and creative like huge opportunity marketing is not AI slop. That's just going to be like, yeah, you didn't buy a $200,000 piece of software because that company wrote like a cute listicle back in the day. It's, it's going to be the same thing. And so it's going to get, you know, it's going to make marketing really hopefully do, do meaningful stuff and matter again. Okay, we have a couple, we obviously this, this went by really fast. We have a. I'll try to get to a couple questions, but I know that the CGM team is good at marketing and they're good, they're thoughtful on this stuff. And so we're going to give them, we'll give you guys all these Q and A's. And John, I'm sure you and the team will probably maybe like write, write up responses to these. There's a lot of follow up that we could do for this. And by the way, anybody in the chat that was chirping me about, you know, you came to this to understand what GTM engineering is. Like you could have just gone to ChatGPT and asked what the heck is GTM engineering? Like, you didn't have to come to this. So that's, you know, we're all here for a reason.

John (51:05)

If people could drop the tools that they're using in their, in their go to market engineering stack.

Dave Gerhart (51:11)

Okay.

John (51:12)

In the chat I'd love to see like, all right, you know, clay era do that now.

Dave Gerhart (51:17)

What are you using? What do you, what do you, what are your GTM engineering tools? Mine is like I use this great tool by open AI called Chat GPT.

Dave Geart (51:26)

Sick.

Tammy (51:27)

I want to hear that. And I also feel like this group is a good group to ask the question of. Like there seem to be some really big feelings about go to market engineering. I want to know what those big feelings are. What are these feelings?

Dave Gerhart (51:40)

What are the big feelings? I think my perspective on it is that the big feelings come from people just roll their eyes whenever Mark, like whenever we create more new, you know, it's just a rebrand. And yeah, that to me is just LinkedIn, like perfect LinkedIn fodder for like marketers to yell at each other about. And I think we as marketers, like I tell my wife about these things, she's like, who cares? She doesn't Work in marketing.

Tammy (52:03)

Yeah. Yeah.

Dave Gerhart (52:04)

I think there's just something about marketers being marketers arguing about well no, that's always been ABM or Rev up da da da. So I don't, I don't think it's anything other than that.

Tammy (52:12)

So I actually, I feel like I have a perspective on that and I love when there's a rebrand and the reason why I love it is because I think that it's a signal that the former brand has been diluted that calls for a rebrand. There is this like founder mindset that like there's this need for something, something new about the role. And I think that go to market engineering is like a call for. There's a. What was formerly known as Rev Ops has been so diluted because you're working these. In these existing systems and if you're, if you're anything like me, like you, you know, a person like Dan who is a representative of someone in RevOps who's really good and you've worked with some really sucky Rev Ops people. And that big swing of like Dan and Sucky is that that is indicative of what we've all worked with. Now there's this opportunity to like when you post a job posting for a go to market engineer and Revops, you're going to get two very different profiles of people. You're going to get all dans when you post a go to market engineer versus when you post RevOps. To me that's an indicator and I don't know, I like these brands.

Dave Gerhart (53:26)

I think it makes sense. Like I'm thinking when I think of Revops, I think of a partner of mine in a previous company and their job was much more like on the reporting side and managing the like SLA between marketing and sales. And the GTM engineer to me is more of like growth hacker creator, you know making, making landing pages and tools and webs, you know that just, just doing stuff.

Tammy (53:48)

Yeah. A little more product engineering mindset.

Dave Gerhart (53:50)

Yes. Okay. That's really good. John, do you got. You got the. The chat blew up with a bunch of tools. Some really, some, some good stuff in there.

John (53:58)

Yeah, I'm seeing a lot of air ops. Jasper just came up a lot of the LLMs ChatGPT Claude, some that I need to look into like relume IO Oh Justin, you dropped that one in there.

Dave Gerhart (54:12)

I'm just going to make a name right now.

John (54:14)

Snake triggerfi, Common Room. That whole class is really interesting right now.

Dave Gerhart (54:20)

So yeah, let's wrap on this and then we before you leave we have a poll we need to do. We need to do a. Our AI agent is going to ask you to rate this session and. Because that feedback really, really helps. But just kind of synthesizing a couple questions. Is there a right somebody who's listening to this who kind of gets what the role is and maybe believes in it? Is there like a stage or size of the company or time that it makes sense to bring this? Is this an early stage? Is it later stage? Like, when do you think about hiring this. This person?

John (54:48)

Yeah, I'd be looking at bringing it in in the first five marketing hires at the very least that you're bringing into the organization. We got an interesting question a couple of weeks ago from somebody who we're talking to, works with a lot of different businesses. You know, they were trying to figure out when the right time is to start building AI integration into their business and, and specifically into the marketing stack. And. And they wanted to build a base layer for marketing before they started really investing in AI. And you can't get too early here. I think you want to be thinking about how you can grow as efficiently as possible and how you can be reducing the cost to acquire a customer and how you can boost the revenue per employee. And so I think having a really strong systems thinker, no matter what you want to call them, having a really strong systems thinker in the organization who can help you scale how you use artificial intelligence to create content to, you know, support product marketing with getting feedback from customers and automate those workflows is going to be really important for any business. So it's one of the first three to five roles that I'd look to bring on in any organization.

Dave Gerhart (56:07)

Also seems like one of those, like, you know, when, you know, if you're interviewing someone and they're listing off all these tools and they're telling you about things that they built, you know, that's your GTM engineer. Okay, please, real quick, go to. On the, on the top, there's like that Polls tab. Go to Polls and we ask you, please rate today's session. Not a, not a webinar, on a scale of 1 to 5. Leave us some feedback. But hey, I had a blast. Like this was fun riffing with you, with you all. We got some great comments and feedback. The chat was. I'm gonna give it up to the chat today. Our panel is great. But I'm gonna give it up to the chat we had that was electric. We had 260 people in here today. And like, clearly, passion, I think we got to do more of this. I think people want to hear real specific examples. We gotta. We gotta keep. Keep relying on the chat. No, no slides, no promo. This was. This was lovely. Good job all around. Dan, Cammie, Justin, we'll see you all on LinkedIn and in the slacks and emails and around. John, good to see you. All right, I'm out of here. I'm gonna go pick up.

John (57:04)

Happy birthday.

Dave Gerhart (57:05)

Thank you. Thank you. It's not about me. It's not about me. I'm here for the people. But I'll see you all later. Excellent job.

Tammy (57:11)

We'll see you, everyone.

Justin (57:11)

All right, bye. Thanks, everybody.

Dave Gerhart (57:13)

Bye.

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