#546 Reinventing GTM: Jonathan Kvarfordt on Building AI Native Revenue Teams

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Mehmet: Hello and welcome back to the opposite of the CT O Show with Mehmet today. I'm very pleased. Joining me, Jonathan Kvarfordt. He's the head of GTM, growth at momentum.io. Folks, you know, by now I don't steal much of my guests slides [00:01:00] and uh, you know, I don't like to speak on their behalf because I have the theory, which no one can introduce someone better than themselves.

So. Jonathan, thank you for being here with me today. Of course. Before I pass that to you, to give us a little bit more about you and, you know, your journey, what you're currently up to, we're gonna talk, as you can see, maybe from Jonathan Title, GTM, go to Market. This is an important topic, and this is, you know, I, I talk also myself a lot about it, whether you are a founder, um, you know, of a startup, or maybe you are a.

CEO of a scale up. This is something important and in general, because I believe everyone should know about, you know, these terms and about, you know, sales, marketing and everything. Without a further ado, Jonathan, thank you again. The floor is yours. 

Jonathan: Well, thank you Mehmet for letting me be here. I appreciate it.

So again, my name is Jonathan Kvarfordt. Some people call me Coach. It's a nickname I got and just is stuck. Um, I know I, I need to change my title on this recording 'cause it says Head of GTM Growth, but I literally just got a. Um, a new title last week, which [00:02:00] is VP of VP of GTM, strategy and Marketing. So what I do for Momentum, I was a customer before two and a half years ago.

Loved the team in tech so much that I literally begged them to let me come on board. Thankfully, the, the team let me come on. Um, and I've been leading marketing since February of this year, and it's going really well. So I'm kind of a weird duck because I sit in a lot of different places where, um, I, I'm deep in the AI space because I have what's called the GTM AI Academy, where I've had 10,000 people plus go through to learn how to use AI and go to market roles from leaders down to AEs.

And then, um, I teach at Bright University ai. I'm an advisor to several different companies helping me with both go to market and ai. I do prompt engineering for momentum's product as well as marketing. So I'm kind of like a nitty gritty, uh, nerd in some ways. Um, and just love to be in shows like this and talk to people like you and just jam out on what's going with ai, what's good, what's bad, and all the, all the goodness.

Great. 

Mehmet: And thank you again, Jonathan, for being here with me [00:03:00] today. Now, let's of, you know, let's start, okay. And, uh, put, put the things, uh.

You've seen firsthand how GTM has evolved, right? Um, and things are moving fast. You mentioned AI also as well. So what do you think, you know, today are the biggest misconception revenue leaders still have about, you know, I'm interested. I'm, I'm usually keep the AI later stage, but you know, my feed is full right of using AI in, in, in GTM.

I would love to hear your take, Jonathan. Um, in just where we are right now, you mean? Yeah. Yes. And how, how, you know, 

Jonathan: things evolved also in your opinion. Yeah. It's an interesting discussion. So we, I, I feel like a lot of times there's this disparaging view because. As an example, back in April, the CEO of Shopify came out with an AI memo, which kind of sent these reverberations across the industry where he said essentially [00:04:00] that they're not gonna hire anyone unless they know for sure that they can't do it with AI first.

You know? So it was a fascinating memo that kind of sent shock waves through the business world, in my opinion. And then you have people like Duolingo who essentially said the same thing, where the Duolingo team's doing the same and trying to push AI instead of humans. Um, Salesforce has come out and said their 30 to 50% of their work is being done by ai.

So you have all these marketing things happening to where people feel this pressure because of all these companies saying, Hey, we're, you know, we're doing AI like crazy. And a lot of people are still struggling with the basics. Um, so what I did is, and with Momentum we're a data company. We, um, looked into conversations that we had with, with, uh, people over the last.

Like from January to July, and we tore apart the conversations and figured out, okay, of all these sales conversations we're having all about ai, by the way, various companies, various industries, different sizes, different titles, and we found some patterns. So McKinsey reports that 78% of companies [00:05:00] have done some sort of AI adoption of some kind, which in my mind usually comes down to like a copilot license rollout or Chet BT licenses or something.

But it's not. It, it all depends on a human prompting something to get the AI adoption. And I know from just teaching prompting that most people don't know how to prompt, which is not a bad thing, or I shouldn't say, it's not a dis, we've never been taught how to prompt. So I know for a fact that a lot of the AI adoption is not showing good ROI because people not taught of how to do it.

And I personally believe a lot of AI power can be experienced from not having a human adopted in the first place. So anyways. Our data showed of a thousand companies we talked to from 50 employees up to 10,000 plus employees. 7% have what we call operational ai. So every time I talk to someone, it's the basic fundamental items they need to automate or use AI for that they're not, because they're just using it as a chat bot, you know?

So even though the market is saying how advanced we are in in the AI space is like crazy 'cause [00:06:00] it's advancing so fast, there's so many capabilities. But it's not, um, the actuality or the reality is that most people are still ba are struggling with the basics of how do I get this to be involved operationally?

Does that make sense? Which is good for me because from a momentum point of view, that's what we do, is we help with the fundamentals and automating the process. But it's, people are still like very, very, very new to the world of getting it into their systems and process. 

Mehmet: Right. Jonathan, I'm gonna ask you something.

And I work in sales myself, you know, and somehow I'm still involved, um, in, in different, uh, perspective, let's call it this way. Um, sure. So things that, you know, I, I want to go a little bit back, uh, in, in history, like little bit and uh, 'cause I want to tackle the point of the data, right? So back in the days and not long ago, you know.

Any, uh, sales op team and, you know, of course the, the, the, the leadership, the sales leadership from the CRO all the way [00:07:00] down to, uh, frontline managers, you know, we were, we're using, um, like. Different systems, right? So relying on dashboards to, to forecast, take decisions, um, and, you know, um, try to, to, to, to, to see what should we doing next now with, you know, this new, I would say, um, AI push right?

If people, and you know, we, we used to hear like, you know, they, they, some organization used to struggle despite, you know, having the latest and greatest when it comes to, you know, the dashboards and all these nice reports right now with this ai, like, how me, as, as this, you know, probably maybe a, a, um, A CEO or maybe I'm A-A-C-R-O who's trying to see.

What I should do next, right? To [00:08:00] have this shift from just dashboards, you know, to insights and, you know, making sure that, you know, I'm, I'm able to see, uh, what matters. Plus how do I make sure that, you know, my. Main, I would say component of making everything we, we, we talk about working is the data to make sure, like also I have the required data in my systems that allows me to have better GTM.

Jonathan: Yes, 

Mehmet: I know it's a loaded question, but 

Jonathan: it's, it's loaded. So you're essentially asking me where does someone start, essentially? Yeah.

So I have, I have very opinionated opinion on this. So I get people all the time who come to me and say, Hey, coach John, what should I buy? What AI tech should I buy? Mm-hmm. And to me, that's asking what? It's trying to start at step five as step one, and [00:09:00] there's four steps have to come before that, if that makes any sense.

Um, only because buying an AI tech just to buy an AI tech is a waste of time and money because we don't know if it's getting pointed at the right challenge and initiative to make sure there's ROI. Does that make sense? So for me mm-hmm. It's all about understanding first. Like a lot of people out there are saying, focus on your problems.

My challenge with focusing on problems is that there's no shortage of problems. Everyone has a bajillion problems. The question is, what's the priority? And priorities get defined by initiatives. So for example, if I'm a company, I have a hundred million in revenue and I, and I have been given the tasks to grow by 25%, in the next year, I have to go to 100 to 1 25.

That means my metrics have to change. Like for example, my a CV number of opportunities, win ratio and sales cycle. Those have to change in order for me to get there. So the question is really understanding where are we at now? Where's the gap? And what leverage do we feel like we can pull to get there? Um, and it could be something in cs, it could be we gotta [00:10:00] reduce our churn by a certain percentage or, or we have to do more upsells or whatever the case is.

But what's the business initiative? Where's the gap analysis of where, where the problem is metric wise, and then understanding where is the friction? Is it based on the data? Is it a lack of skill? Is it a lack of process? Like where, what is happening right now to make that not happen? Then you aim AI at that problem.

'cause then it has a priority to it. And you know, it has ROI to it. Um, it's not easy to do. It requires a lot of what people call unsexy work. 'cause no one gets on LinkedIn and says, Hey, I just mapped out 30 workflows that no one, like, no one cares about that. What they care about is like I, what I did is I aimed an AI agent at this problem and had this result.

That's what people talk about, but it requires the unsexy work of understanding where the heck is the data, what is the humans doing, what's the step-by-step task process? And that's very time consuming to do. And AI can absolutely help, but humans have to direct that process. So. That's one side, and the [00:11:00] second part of it is we're in this world where everything's changing.

So you have two options. You can either do what you've done in the past, the same process, same skills, same stuff, better, faster, easier, cheaper with ai. Where the new world is, thinking about first principles, where are we going and is the old way of doing things the right way? And can we do something different and better with AI than we wouldn't have done before?

So it's understanding which way do we go. And that's up to every leader to decide on where they want to, which, which track they wanna go down. But I think it's important to be aware of there's different ways of doing things now more than ever. And it requires humans to, to make sure that they have. Um, and understanding of where to direct that power, whether it's doing the old stuff faster or doing something totally new.

Mehmet: Cool, Jonathan. Uh, I know like at Momentum, you, you did something which, uh, might look for, for some people, um, um, you know, new or [00:12:00] maybe un you know, like controversial. I don't know, like maybe they find it weird, which is you made it a Slack native now. Mm-hmm. Why do you believe, uh, slack and maybe other chat platforms in general are now the operating system for, for uh, GTM teams?

Jonathan: Um, well, interestingly enough, I think that this operating system concept is gonna be where the battle will be because as you see, if you use chat, CBT or Claude, like the desktop or the interfaces they have, they're doing what's called MCP connectors on the backend, where they're connecting to every major platform you have.

And then people are running their businesses through CHATT or through Claude or through some sort of AI interface. Now Slack is nice because it has more connections anywhere else. It has your team there. So I personally think right now what I'm using more than anything is Slack because I can have multiple agents talking inside of Slack and I can operate the whole thing from there.

And if you think about it from a revenue point of view, [00:13:00] thinking large scope, how past companies used to dictate their value was by requiring people to opt in or to have a tab open, or to use the technology by being in the tech. The challenge was for sales or CS people, that meant they had to have 20 different tabs open.

They had to understand how to use every single one of those tabs. And then do their job on top of all those tabs, like that's how they showed adoption was we have people inside of our technology. The new World is totally that backwards from that, it's where it should be, which is saying, where is the human at most of the time?

Is it email? Is it Salesforce? Is it Slack? Whatever it might be. And how do we go to the human in their workflow? So instead of requiring them to opt in to anywhere, we're going to them. So it means that the adoption needed is much, much lower. It automatically pops up. Things like with momentum, we pop up things to people all the time, whether it's a team leader or whether it's an individual or whether it's a CEO, we communicate what's important to the right [00:14:00] person at the right time for the right reason.

So in that way, it doesn't require anyone logging into anything. We just go to you when it proactively happens. Does that make sense? So it, it's really changing the, the, the paradigm of thinking instead of someone logging into 20 different platforms, how do we make it so there's one place to go where everything coincides and makes it really easy for the human to interact with however many agents you have so they can do their work and spend more time in doing what they're supposed to do in the first place.

Mehmet: You know, this is, uh, a, a good, a good, um, I would say direction for, for I, I believe any company to, to start. Think about this way, right? So, so this is, again, the goal is to streamline and eliminate friction. Now, talking about that, um, now where do you see, for example, um. What's called now rev ops. Right? So where do you see most rev ops, real leaders trying to also kind of over complicate or [00:15:00] over engineer their tech stacks and while they, they could, you know, just simplify it instead.

Jonathan: Give that question one more time.

Mehmet: I will. So I'm saying like with, with, um, with what's happening and people trying to eliminate, like where do you see most rev ops leaders, uh, kind trying of over engineering tech stacks, uh, instead of going and simplifying things. So do you think like, just because, you know, they think like the more systems and the more procedures and the more things they do, um, you know.

Kinda, I don't know, save their jobs or is it like, because they, they, they think the more systems is the better results. Uh, while, you know, I've seen like people talking about simplifying the tech stack and simplifying the processes. The, my question in another sense, like why we feel like still rev ops is, is kind of.

Shown as a complex, uh, [00:16:00] process? 

Jonathan: Yeah, I don't think it's a, uh, I've worked with many, many amazingly talented and strategic rev ops leaders. I don't think rev ops leaders are the problem. I think they're. Um, the receiver of, of requests from a CRO, from sales, from whatever, like, here's the reality of what happens.

You'll have different teams who buy different technologies for different reasons, and there's no one central person connecting the dots to make sure the systems, the tools are working in conjunction with the rest of the team. So you have CS that buys five different tools. You have marketing that buys whatever tools you have sales that buys whatever tools, and there's no one in the center making sure they connect dots.

Rev ops is that person. So they, it's not their fault. There's a bunch of systems they're trying to make sense of all the chaos that's happening. So I think that it needs to have more, not necessarily governance, but at least a, a say in what happens and be involved with it. Because rev ops to me, and enablement too, for that matter.

Should be that central mechanism to make sure that whatever marketing's doing is connecting to sales, it connects to Cs. That would make [00:17:00] sure the system as a whole is working and they don't usually, and it's not because they don't want to, it's because their teams are off going to do their own thing and there's no centralized.

Way of thinking, and I think AI is one way to force people in a good way. I say that forcing because it requires data from different technologies and the process to make sure it functions well. The challenge is that most rev ops people are not AI experts, so they're, they're not, they know systems, they know process, but they don't know ai, which is a little bit of a, a.

A wrench in the, in the, in the engine. Um, so I think a lot of people just need to be aware of what AI can do, but the skill is rev ops all the way they know how to work it. They gotta get update on AI that can do the rest. 

Mehmet: Right. So we know like the also, uh, Jonathan, that there are like teams still living, uh, in spreadsheets and, uh, you know, chasing, uh, whatever, CRM, Salesforce, HubSpot, whatever that [00:18:00] hygiene.

Uh, so if, if they are like little still stuck there where, where they should start?

Jonathan: It's a good question. Um, uh. There's two ways of thought around this. Like there's the bottoms up and then top down. So top down is what I told you before. We have a strategic initiative and then kind of go backwards from there and figure out, um, figure out what the problems are. Um. That it's harder work to do, but I still think it's the most worthwhile place to go because you could go bottoms up and you can give everyone chat GBT licenses, which can have good results.

But the problem is it requires on someone's skill of prompting, you don't know what's going on. 'cause it's a black box and everyone's chatting with their own AI somewhere. Um, and then the, like, if, if I gave a sales rep, let's just say they committed themselves and became an amazing prompter, which, which would be awesome.

Even at that level, they don't have the height or the view to understand like what else is happening across the team and what could be cross-functionally given to everyone else. So I still think it requires [00:19:00] someone in the center kind of making sure that's aligned to initiatives. Now with that being said.

The, um, the lowest hanging fruit, in my opinion right now with AI is anything that has to do with time. So we spend so much time with little piddly do stuff like, for example, a sales rep. All the studies in the world show that most people spend 25 to 30% of their time actually doing something that's revenue generating.

All the other 70% is spent wasted on trying to find content, CRM, data entry, internal meetings, updating everyone else. Like there's all this wasted time. If all someone did was hyper focus on how do I automate and make my team as efficient as possible, if that's all they did, they'd have, um, light years of a difference as as a result.

So one of our customers is Kyle Norton. Um, and, and he uses momentum as well. He, he uses a bunch of different techs. We're one of, we're one of his core technologies that helps automate, but he, his team used to have like a million [00:20:00] dollars per person, um, like revenue or quota, I can't remember is, but now he does it's three times that same person, three times the output.

And all he did was just look at what their day-to-day is and say, how do I automate as much of this as possible? Um, and that's one way I think people don't go to. They think I can just buy an AI and it's gonna solve all my problems. But Kyle did the unsexy work of figuring out what's the process, what's the tasks, what data is connecting, what's not connecting?

How do I make this as easy as possible for my sales reps? And now he's getting three times the output, which in and of itself becomes emote because it's hard work to do for your specific company, and the more you're willing to do it. The faster you can go as a result, which you can outcompete people because for your competitor who has, you know, 30% of their time revenue gen activities, and you're doing 70, you're three timesing their output.

So it's just, it's understanding that doing the hard work is very worthwhile 

Mehmet: right. Now. Another thing, and [00:21:00] Jonathan, I, I'm not sure if it was like a, uh, a, a, a coincidence or how this happened, um. I was curious to know how what we call the GTM playbooks are, are also going, uh, to change or actually they are changing as we speak, right?

They are, yeah. Yeah. So, so, you know, there were. No one thinks that we used to do so both from, I would say, um, interest, you know, generating activities, you know, a company does or whether it's like. How we drive the whole process over there. And I did some research and honestly, I use ai, but again, I, I crosscheck the, you know, all the statistics and I was not shocked, but, you know, uh, some, some numbers, you know, like was a little bit surprising that they are so high now.

[00:22:00] As people working in, in, in the sales organization. So our goal, of course, you know, we know we, we need to find customers, the right customers. Yeah. Do the sales and, and, you know, close that loop. Now, one thing which stuck with me as now from buyer's side, things are changing also as well, right? So, so buyers are using themselves, AI to find.

Solutions now with this, um. Different conditions, let's call them this way, that they were before H HR GPT or uh, Gemini, or whatever tools you are using, wall things were different. So we used to have, you know, the non playbooks, let's say. Gated content. Um, you know, we used to track like certain metrics, so Right.

How AI is changing, you know, these playbooks [00:23:00] today, like what kind of new playbooks we should, we should have there and which kind of metrics really we should be as sales organization laser focused on. 

Jonathan: Yeah, it's, it's a good, it's a good question. Um, what's funny is I still feel like there again, if you go back to first principle thinking.

There are concepts and core principles that still apply even in the AI native world. It's really understanding how do you apply AI as a result, or what's the impact of it. So a classic example of something that's major shifting right now is regular SEO or how people search with a EO. So Google's done a ton of crazy things.

One is the Google overviews, and now they've limited AI's ability to look at different results from search results. To 10 versus a hundred. So that means anything on the first page is more, more important now than ever. Then you have all these disparaging tools. You have chatt, you have Gemini, you have Claude, you have perplexity, you have all these different [00:24:00] tools who all work a little bit different from each other on how they search for content.

So it's one changing how people are making decisions on tech or products or services that they're buying. And also changes the strategy for the people like myself who are trying to figure out how do we make sure that we pop up when those conversations are happening. So that's definitely a major shift in the marketing world.

But there's also things like, I would say I wouldn't do any differently before, like if I was charge of a marketing team or for our company 10 years ago, I'd still be doing the same concepts I'm doing now, which is I'm major focused in on who am I talking to? It's important to them. How can I provide value to them so that whether they work with me or not, they trust the brand.

They trust me, they trust the content, and they're getting value from me as a result of it, you know, so. I dunno if, I dunno if that answers your question, but to me it's all about first principle, thinking of where you're at, what you're trying to provide. And then it's all about where the heck is your ICP at?

Where do they hang out? And [00:25:00] go there and figure out ways of how you can provide value to that person or individual groups of individual individuals so that they can trust you as a brand and, and be more involved with you. And I wouldn't change that if I had AR or not. 

Mehmet: Yeah, absolutely. But how also this, um.

Should be, or is it being reflected on, you know, I think majority of the teams, they do it on Monday, some they do it on Tuesdays. These pipeline reviews and these, uh, for, you know, like how this should be, be now, you know, which direction should, should be taking today should, you know, as I said, it should be, I still asking the same questions I was asking.

Two years or three years ago, um, or, or, or, or things are changing and I need to question my team on different things than, than I used to ask about before. 

Jonathan: Yeah. I'll, I'll give you, I'll give you two different ones. So the current state is when, when you do pipeline reviews, most of the time it's a [00:26:00] glorified Salesforce or HubSpot data entry.

Party. Mm-hmm. Because all you're doing is watching someone enter data. So the, it's not really a pipeline review, number one. And so in the new world with like momentum, all the data's there. So our pipeline reviews are very strategic sessions, like they're brainstorming and how do we win the deal? They're not data entry.

Parties, you know, so that change in and of itself is way different. And the metrics you're able to talk about and ask about are way different because you have the data. So that's just number one. And those metrics, by the way, are not anything new. They're just what we've been wanting for the last 10 years anyways.

There is new world though, of like AI signals where when you think about this world of when you have like third party data from, um, whatever technology you wanna talk about. Third party from clay, from ZoomInfo, from whomever, and you have signals from, um, product releases and PR and overall market trends and all this sort of stuff, and you mix that with first party data coming from conversations, you get signals of different things.

[00:27:00] Those signals, I think, are very, extremely powerful and I think that pipeline reviews will shift ever so subtly so that it'll become more about what is the combination of signals that's happening inside of each deal versus what is the usual. Play, which is exit criteria of the sales process. So an example would be like, um, if we have signals, like if we're going to a key target account and we have external signals from whatever sources that are telling us, like, Hey, they're looking into competitors.

Hey, they have this problem they just talked about at their last financial release of the quarter reports. Hey, this person just got hired. Like all these key signals that get mixed. And then we mix that with our own first party data of saying, we know this about our ICP, we talked to these three people inside the company.

We know they're primed and so we know how, how to target them. Then the larger pipeline review will be asking about what is the signals looking like for each account, and then for all of the accounts at. In aggregate. So that's a way different conversation. Very, very database, but extremely important because you'll [00:28:00] be running your deals differently when you have this collection of signals coming from different sources that you can make better decisions on.

Mehmet: Makes sense, makes sense. Jonathan, now I gotta ask you also from your experience, like what have you seen, like the most underrated automation, uh, that people, they think it doesn't matter, but you've seen like it delivers like the. Best or like outsized impact in, in, in the whole process. 

Jonathan: Uh, it's really dumb and easy, but it's the bread and butter of momentum.

It's just CRM data entry. There are, I'll tell you many reasons why. Um, there's like multiple layers. So we have asked humans to be the source. Like, let's just think about it from a different point of view, from CTO, from product, from marketing, old World, is we needed to have information on why did a customer buy, why did we lose?

What's the product information, how they like it, right? And all the information came from the salesperson or the CS person. And then we got ci. So CI would come up and say, [00:29:00] Hey, we now have all these calls in the massive library, but no one has time to watch all that stuff. So again, they still have meetings with the sales rep or the CS person saying, why did we win?

Why did we lose? What's the product feedback? And of course, that information's biased because the sales rep's not gonna say, I sucked on that deal. They're gonna say it was pricing. It was timing, you know, so you get this, this, not that their opinion doesn't matter, it absolutely does. But they have, they have self-protection mechanisms, which I don't blame 'em.

I'd have the same thing. I did the same thing when I was a sales rep, you know? Um, so the, the data you have in the CRM, which most people aren't used to having is so important. And it sounds so dumb and trivial, but it is so vital. Lemme give you a few examples. There are 38 unique types of fields in Salesforce, something like that, that a human can put in.

I don't mean 38 text fields. I mean 38 unique fields. Mm-hmm. Check boxes, pick lists, multi pick lists, bullion percentages, all these things that a human has to do. Most technology can do some sort of automation to [00:30:00] like maybe 30, 40% of it, but that still requires 50% of it or more to be done by the human. So just the time of doing it, number one, is a problem 'cause you don't have revenue gen activities.

Secondly is the data. So. They always can't remember. I think 'cause most sales reps are going from call to call to call to call. And so the data they're putting in is okay. But if you have an ai, they just auto updates things every time. Then the sales rep has better data. They can go back and say, oh yeah, I had this conversation and they said this thing that AI gave me from last time.

You know? Then you, when you look at that from both one layer up of a manager and they have 10 reps who have 10 calls a day, that's 700 a week, whatever the case is, that's a lot of fricking calls to keep up on. So now AI can consume it all and then automatically give to the sales manager both how are they doing in performance?

What's the product feedback we have? What's the, what's the analysis and intelligence I have in my patch? And then you go a layer above and say, VP of sales, you have 15 managers. Each one has seven to 10 reps. You have all these calls happening. Now you have an idea of, of a [00:31:00] pulse of what's happening across the board.

And you can dig into any, any deal you want to without ever talking to a human, which is like insane. All because you have data inside the CRM and it all starts with manual data entry, deal to deal call to call. So there's all these consequences that happen as an effect, but no one talks about it because no one's experienced it.

So it drives me crazy because I'm like, you guys, you need the data for AI to do its power. And if you don't have that data first, everything else is just like it. It doesn't matter. But once you have the data there, you can do some really, really cool stuff, both for AI and then for humans. 

Mehmet: Does 

Jonathan: that help?

Hopefully. 

Mehmet: Yeah, 

Jonathan: absolutely. 

Mehmet: Now regarding, okay, so, so. You, you mentioned something important Jonathan here about, and, uh, by the way, uh, especially in case of lost deals, traditional answers in the, uh, win, uh, lose comments in, in Salesforce. So we, we know what we used to put like, right? So, [00:32:00] uh, when dark missing features, you know, these kinds of thing and yeah.

To be frank, as you mentioned, like sometimes we feel like we need to be defensive and this brings, you know, the, the, the following. Now with like, with what you're doing at Momentum and with this automation and AI in place, um, what do you think the skills that we need to. Provide, uh, training for, or maybe, uh, I don't know, like, um, they used to take us to different also workshops.

They, we, we used to attend like these different, uh, you know, of course other than the medic or MedPAC or, you know, all the framework that we have. But what, like other skills you think, you know, sales reps would need to be trained on so they can also, uh. Get out of, of this old mentality that. [00:33:00] Spend your time hygiene in, in Salesforce or like whatever, CRM use and this and that, and make sure like this is updated because I, we, we used to hear this a lot and, uh, I didn't do statistics, but I can say in, in 15 years I spent with.

Either as a sales rep or as sales engineering, helping other sales rep. So I can say like majority of the conversations with, with the managers is, Hey, did you make sure that this is updated there? And sometimes you feel, you know, there's some skills. Missing even with the, with the traditional ways of doing things, like with the data entry and all that.

Yeah. Now AI is gonna change this. So me as a sales rep, how should I be prepared skills perspective to deal with ai. 

Jonathan: It is a good question. All kinda depends on what tools you have at your disposal, you know? Um, but to me, again, it comes if, let's just think about it from another point of view [00:34:00] of where we're going.

At some point the sales rep is gonna be not doing all the piddly do stuff they have to do, like, like data entry, like certific content, all this other stuff. And they're gonna become more of what they're supposed to be in the first place, which is a quarterback of deals and relationship builders. So to me, the core skills that people need to have is about emotional intelligence, um, strategic thinking, um, negotiation.

Conflict management, all these kinda things are very, very human, where you have to like deep dive and double down into, because let's just say for example, you have seven your sales process and you can automate the first three with ai. 'cause AI does a discovery, AI does a demo, AI does the stuff, and then hands it off to a human.

That's a whole different world where. The pe the skills of people needed are gonna have to be the same as they are now, but deeper inside of those skills. Like if, if for example, we have a team of, of, uh, if the whole market should, could automate the first three stages of the sales process, [00:35:00] then they have to be really freaking good at negotiation because that's what they're gonna be doing day in, day out, you know, so it, it's not necessarily gonna change anything.

It's gonna focus the skills more than anything. Right. 

Mehmet: So. It's back to basics. I call it Jonathan probably, right? So, yes. Uh, uh, so, so this is the thing that what any, uh, account executive or uh, sales rep should be doing day in, day out. Um, talking to customers, being in the field, I gotta tell you one joke and, um, you know, uh, it's not a joke, it's something fact, but they, they, they start to use my, um, a term that I, whenever someone.

We used to see these emails or someone say, Hey, have you updated the CRM? Have you updated, you know, the intelligence system that we are using? I said, guys, let us go sell. And now all my friends, they use this whenever they see emails. [00:36:00] Whenever they are working, they say, Hey, as me said, let us go sell. We, we don't want more, you know, systems to fill in and, and people are hungry for that now.

Jonathan: They, I'm 

Mehmet: Can I ask you something probably related to this? So. I was telling you before we start the recording, I focus al also on, um, in addition to, to tech executives and, you know, like, uh, uh, tech companies. Part of people who are close to my heart are founders and tech entrepreneurs now. Mm-hmm. For them, Jonathan, from your perspective and you know, when does it make sense to them to start also implementing?

Um, these systems and of course start to automate it in their journey. Like, uh, is it like when they start to hire, let's say a VP of sales? Is it when, when, when the team reach certain, uh, number of, of, uh, people [00:37:00] in the sales organization? So what is the tipping point to start actually thinking about these processes and start automate them?

Jonathan: Um, I now, it doesn't matter where you are now is the time because like things are moving so fast. Like, I know it sounds overwhelming, but now is the time. There's no, there's no too small or too big to start. It's now so. I believe personally, the smaller companies who begin now to do these kind of things can sit scale more efficiently than bigger companies.

Bigger companies are gonna have a major pain because they have all these processes, all this red tape, all these people they have to whittle down and get to. They're gonna have a lot of pain going through this 'cause there's more process. Smaller teams have a gift 'cause they don't have as many people, don't have as many processes.

They can become fine tuned, really good by automating the. Jeebies out of all the stuff they can, you know, because the challenges right now, I'll give you an example. We have a framework called or OAR, which means optimize, amplify [00:38:00] reinvents or re retransform. Optimize all is all about time. Most large companies who have processes, it's about how do I optimize the time.

Next one is amplify so that you have, uh, AI doing things that is beyond just a time thing. Like for example, when you have an AI that can automatically analyze and then coach team members, that's an amplification of a human skill. It's not a time saver. Does that make sense? It's amplifying it. And then reinvention is thinking about what if we could totally reinvent this, where instead of rev ops doing territory planning, I have an AI do it for me.

Mm-hmm. So the entire thing is reinvented, you know? So the challenge is bigger companies have to start with time savings. 'cause most people can't just like revamp and change, manage the whole thing at once. 'cause that's a lot of change to happen with humans and most people aren't equipped to do that. But with smaller companies, 'cause you have smaller amount, you can start with reinvention 'cause you haven't built all the processes and, and the chains, so to speak, to get you where you need to go.

Like bigger companies have all this crap, they gotta get off of them to automate. Smaller companies don't. [00:39:00] So that's why I'm like, you need to start now. 'cause no matter what size you are. Your competition will, someone's gonna be saying, I'm gonna do the hard work now, and they'll be, have the dividends long term that you're not willing to do.

It's the hard work of planting and seeding now that will have major fruits in the future that people will say 10 months from now, I wish I would've done the hard work now to get rid of the they are 10 months from now. You know? So. Hopefully it helps. Yeah, absolutely. Yeah. Start yesterday. I tell people.

Yes. Yeah. Uh, but, but you, if I can add to that though, I wouldn't want people to be stressed. It's like, just focus on what's right in front of you. Um, one workflow at a time. Mm-hmm. And then making sure you have in the back of your mind, does this workflow point to revenue? Like, for example, it would be ai, there's a lot of tools out there that can auto-create emails for you.

Mm-hmm. Is that gonna be the biggest lift on revenue? Maybe, maybe not, but I would ask that question of, is this AI thing that I'm doing, auto-create emails, whatever, will that have an increase [00:40:00] in my revenue or my pipeline, or whatever metric you're looking at? If the answer is maybe don't do it, it has to be like, heck yes.

This is awesome. And once you find those, heck yes, use cases, do one at a time, and after a while they start to stack on top of each other, and that's where you see a lot of results from. 

Mehmet: Great, Jonathan. I know, and I'm transparent with my audience. We're recording on the fifth of, uh, November, and today you had a book launch.

Uh uh. The book is called Ignite. The GTM Leaders Playbook for Building, uh, insurmountable Competitive Advantage with ai. Tell me a little bit more about the book. Like what, what's, what, what was the motive and um, you know, what leaders can expect from it. 

Jonathan: Well, a long story short, my CEOI was up on Saturday nights, like in June or something last year, and I was geeking out at midnight with ai.

'cause I, that's what I do on weekends. I just play with AI all weekend. Um. And my CEO is three hours ahead of me in Argentina, and he messaged me on Slack. He's like, Hey, you up? I'm like, [00:41:00] yeah, I'm up. He's like, Hey, I have an idea. I wanna write a book. I'm like, okay, cool. I thought he wanted me to write the book by myself.

I'm like, I, I'm happy to. I dunno why I'm gonna have time. Um, I. Thankfully though, he came to me on Monday, he's like, no, I don't want you to write the book. I want to get contributors to write the book. I'm like, great. I love it. So we, we have a, we are blessed to have, um, an amazing network of advisors and customers and different people we're talking to who are leaders in the space of G TM and ai.

And so we found 28 to 29 people that we interviewed over two months. Mm-hmm. Um, had half hour to hour conversation with them all, and then we took all those learnings and things we got and found, found patterns of what they're doing to a framework that we now call intelligence architects, which is about really balancing how do you get human talent and power and balance it with ai and more and more.

It's not about saying, how do we get AI to replace humans? It's really about saying. What are humans really, really, really good at? And how do I amplify that? And what is AI really, really good at, and how do I [00:42:00] use both at the same time? And you need someone in the middle, usually leaders now, who understand both instead of thinking, how do I replace the human?

They're thinking, how do I amplify what the human's already doing and how do I get all the crap off their plate so I can have AI do it in the meantime? And all the leaders in the book talk about is their own angle of how that happens throughout the customer's journey. So from pipeline all the way to cs, they have just different thoughts on.

How do to make that happen? And we put it together in a framework so you can kind of apply it to different parts of the process. So anyways, I'm really excited about it. I can talk about this all day long. It's a lot of fun. 

Mehmet: Yeah. And like, you know, great, uh, work. Uh, and uh, congratulations on the launch, Jonathan.

And by the way, thank you. Uh, this theme of, uh. Having this collaboration between, uh, humans and ai, uh, kept repeating again and again and looks like, you know, GTM is not different from any other domain or, you know, uh, expertise [00:43:00] because, you know, when I have CTOs and I ask 'em about the AI in coding, same thing.

Like, uh, you talk about, uh, AI in engineering. Outside of coding, same thing like, and I think GTM is not different. And I tell people like, use it with, you know, it's not there to, and don't rely a hundred percent on it because still you are required there. You need the human touch. And at the same time, like.

Make sure that you are utilizing it, because if you don't do right, someone else, someone else is going and, and, you know, gonna use the AI and, uh, you know, leverage what AI is capable to do now. Exactly. Uh, I don't like to do these predictions things, you know, but, uh, it's hard right now, dude. It's hard. No, no.

Yeah, I stopped. But a question that I discussed with something someone, you know, not long ago and. I was saying that some, I'm not saying like they will not exist, but they will be there in different form [00:44:00] and you know, CRM is one of them. 'cause I was saying like, Hey. If, if my emails are stored somewhere, if my messages with customers are stored, stored somewhere, um, if I can go back and I can, let's say I took notes even with using pen and paper the old way, which I do by the way.

Mm-hmm. And then I, you know, maybe scan them with a phone and put them on a Google Drive or OneDrive, whatever that is. My theory is like, why do I still need a CRM? Because probably the AI will have a, um, all these sources in one place, and then I don't have really to go and create an opportunity, and then I go and, uh, start to update this opportunity and say, Hey, like, uh, you know, Jonathan messaged me and he said, let's meet next.

Tuesday. Mm-hmm. And then, you know, I go out again, I say, Hey, like, um, Jonathan said he's waiting his, uh, [00:45:00] colleagues to come back from vacation to, to take the demo. You know what I mean? Right. So, so I was telling them the data is there. Why do we need to take it somewhere else? Am I thinking too much futuristic about, you know, no, no, no, no.

Jonathan: You're right. Like this world. And I don't wanna speculate because again, I have my own thoughts in this like. When, when, again, you think about the concept of why we have a CRM in the first place, it's made for humans to enter in data, literally, and it's also, I'd say the second. The second part is it's meant to have humans enter in data based on a business process because Salesforce is built around the sales process.

Right. You have the opportunity stages. That's all built on the sales process stages. So, um, there's an interesting world where there is a possibility to where if you take out the need of human putting in data and you can have AI understand the process and be able to update the more you need to go, it then has the question of do we need a CRM still?

So [00:46:00] it's a very good question. I dunno where it's gonna go. Like, my hunch is, is that the new world in the future is gonna look way different to where. Either Salesforce and HubSpot gonna have to majorly change how they're doing things, or it's gonna go to a world where it's just not needed as much. I don't know where it's gonna go, but I think it's a fascinating thing about, again, first principle thinking, why do we have a CRM in the first place?

And do we, do we have to use that to do what we need to do? And the answer is no. So, but the, the problem and the challenge is that most people are like, we're at momentum. We use Salesforce. Because it's, the technology's not there yet to say we can just rip out Salesforce and not use it anymore. 

Mehmet: Yeah. You know?

Right. It's not there. Yeah. The future 

Jonathan: state is, that is a possibility, which I know Salesforce isn't dumb. They know this. So like, they're gonna be, they're gonna be aware of this and make sure they can be the, the chosen place for people to go. And it makes sense because they have all the interactions, they have all the information, they have this huge cloud thing.

Like they're, they're set up for it. They just gotta make sure they can, they can do it, you know? So always be the question of if that's a focus for them. 

Mehmet: Yeah. And, [00:47:00] and which part of the sales process do you think, you know, can be overtaken by ai Jonathan? Completely, totally. Like no human interaction. 

Jonathan: Yeah.

Good question. It depends on the industry and products. Um, I, I think that there's on a lot of different ways it could go, you know, um, yeah, it, it really depends. And it also depends on how nitty gritty it is. 'cause like, as. If AI gets more and more and more out there, if everyone has access to the same tools, the one difference is the human.

That's the difference. It's gonna be the genius of the human in, in the middle of it. So I don't know, to be honest with you, 'cause like let's just say for example, strawberries. If you're a strawberry seller, you're probably gonna be eradicated. 'cause AI can do the discovery, it can do the fulfillment, it can do the questions, it can ask you stuff, it can sell it all.

Like even real estate. I see a world where, let's just imagine future. You have like a Jarvis type experience from Marvel, and you have this hologram where you can walk into a house and AI can [00:48:00] answer every question you want, take you through every room. The question is, do I need a real estate agent anymore?

Mehmet: Mm-hmm. No, 

Jonathan: like it's the same thing with like Waymo, like Waymo's here, and it takes out humans from being. Lyft, Uber drivers. You know, it's like I never thought I would take a car with a stranger, let alone with no driver whatsoever. But I did and I have. So it's like we don't know yet. We don't know as buyers and consumers what we do like or don't like with ai.

So the whole linchpin in this is assuming that people are just gonna love working with ai, and I don't think we know that yet. We don't know where we're gonna like AI or not. So they may wanna buy a house from ai, but they may wanna have a human. I know it's like, this is the weird thing, like AI could literally do all of it.

The question is, do we want it to, that's the question. 

Mehmet: You know, I, I've seen you repeated this multiple times today, Jonathan, but I believe this is. As much as, uh, people, they think it's deep, but it's also simple first principle, right? So in my opinion, right, [00:49:00] so because we need to try things like we, we will never know if we don't try.

And to your point, like yeah, if, probably if you bring someone, um, and tell them, yeah, to use any of the technologies that we have today. Uh, 20 years ago they tell you, no, hell no. I'm not doing this right. But you, because they are afraid. They, they don't believe, you know, and, and I always tell people, like us as a humans, we have this self, uh, mechanism of kind defending the status quo.

We don't like to try new things. Then people like you lose nothing by trying, and yeah, if it doesn't work, throw it away. If it works, fine, that's good. Let's double down and see how we can make it better. And this is, I think, how, when, when we talk about GTM, and this is why, you know, I'm, I'm little bit kind of have a people that don't agree sometimes with me.

I tell them like, you know, especially when it comes to playbooks, Jonathan. And now they're saying, yeah, like let's [00:50:00] digitize this playbook with AI and telling them guys, okay, you can try, but you need to find like new ways of doing things. Because I think AI have opened a lot of, uh, possibilities on both sides for the buyers as well as the sellers.

And we need to think in a new, from new perspectives. And I think what you're doing with momentum, like also like. Combining all these things, all these sources, I call them, uh, sources of truth because you know, in my opinion, I'm not sure if the in the future this will be possible. And I know like there will be some privacy things there, you know, probably, yeah.

Yeah, so I believe, you know, if a sales rep have kind of a mic, you know, and even from the tone that the customer is, is using when speaking, I if there's camera, which is not possible, but maybe there'll be another way, maybe, maybe at the. Time being, we can describe like, hey, like he was nervous, you know, [00:51:00] and maybe she was like, uh, her voice was like a little bit not happy.

And then all these things that we would be able to feed it to the AI and AI would tell us. Okay, you know what? Like probably, uh, if it detects, let's say, I said the deal will close in three weeks from now, but based on all these descriptions from messaging. From emails, I mean messaging, uh, even what the sales rep is telling me or whatever, he have devices that captured that.

No, still there is work to be done. The deal is not done yet. There's more, more things to be done, right? So this is where I, I imagine things would be going in the future. Uh, but to your point, we need to think first principle. So, um, yes. It's a, you know, really, uh, engaging discussion with you, Jonathan, today.

Uh, but, uh, if, uh, before, before we close, like, uh, [00:52:00] usually I ask two, uh, traditional questions. Anything you want to leave us with today? I mean, anything maybe I should have asked you and you wanted to highlight it. I didn't do that. And of course, where people can get in touch and know more. 

Jonathan: Uh, no, you did a great job.

So thank you for that. Um, the best place to go is momentum.io where you can get a copy of the book. We have a 200 plus prompts library if you like to do prompting. I wrote all of them, so if you wanna use some prompts I wrote personally, there's all there. Um, and then there's the gtm ai academy.com where I just teach of how to do this kinda stuff as well.

But, um, nothing but a pleasure to be here. Just appreciate you very much. 

Mehmet: Great. Thank you very much, Jonathan. So the links will be in, in the show notes, and thank you very much for the time. I know how busy it can get, especially on a book lunch day. Yeah. So thank you again for, uh, giving me the time today, Jonathan.

And this is how I end my episodes. This is for the audience. Uh, guys, if you are new here, thank you for. Joining. I hope you enjoyed. Please subscribe and share with your [00:53:00] friends and colleagues if you are one of the fans. That keeps coming again and again, thank you very much for the support. Thank you for the feedback.

Thank you for pushing also the podcast in the Apple Top 200 podcast charts. October was fantastic. We were at the same time, uh, simultaneously in the top 200 charts. I think we crossed 11 countries by the end of the month. This cannot happen without you guys. Nice. So I really appreciate that. And as I say, always stay tuned.

We have a lot more coming. So see you very soon. Thank you. Bye-Bye.