[Music] Welcome to Making the Great, the podcast that explores what's driving the decline in graduation rates between funding rounds and what it really takes to scale adventure back software startups successfully with realistic options to exit. I'm Tom Glassen, CEO at Scalewise and each week I'm going to be joined by founders, investors and some of the best go-to-market leaders in the world to unpack the strategies, Mr Hebs and the mindset shifts that separate those who graduate from those who don't. Expect real talk, actionable go-to-market insights and honest stories that will help you scale more wisely and thrive in an increasingly competitive market because there is a smarter way to scale and we're here to uncover it. [Music] Today's guest is Harrison Rose, a founder who's lived the full reality of scaling, not just the highlight reel. Harrison co-founded Paddle, taking it from zero to over 100 million in revenue and Unicorn status and now he's back at the earliest stage again building Good Fit. In this episode we go deep on the moments that actually make or break companies on the journey from one to ten million and why most founders underestimate ICP complexity. We also unpack what repeatable revenue really means, why being boring is a competitive advantage and how AI is starting to reshape go-to-market in ways most teams aren't ready for yet. If you're navigating that messy middle or trying to avoid getting stuck there, this conversation will be a perfect guide for you. So Harrison, welcome to making the grade, how are you today? Good, thank you. Yeah, really, really pleased you having me on. Of course, this isn't your first time on this journey. UK founded Paddle, which has become I think a rare UK unicorn. So I'm really excited to dig into the lessons that you're carrying forward from Paddle into Good Fit. And that's supposed one thing we see again and again is that growth is never linear. There are usually a few key kind of good-and-market inflection points that either unlock the next phase or perhaps quietly create problems later on. And from the outside, it looked like Paddle just navigated those moments unusually well. But looking back now, what were the real inflection points on that journey, the moments where those decisions either unlocked growth or could just easily have derailed it? Yeah, it's really interesting. Paddle is now, I don't know, 12, 13 years old. I was there from the obviously third day zero for about a decade. In that time, we went from 0 to 100 million revenue, got the unicorn valuation. But we absolutely didn't feel like an overnight success to be fair. Absolutely not. And honestly, I think when we began and maybe we'll talk about this in the context of go to market, which I kind of owned over that period, like absolutely nobody knew who we were for years. Nobody knew what we were doing. At some points, we were growing at like three extra year and a year and people had never, never heard of us. So it certainly wasn't an overnight success. Everyone now is like, yeah, Paddle was great. We know about it for ages, but it really wasn't like that, I don't think. And if I have to think about those inflection points or the moments where things really felt like they were changing, I think what people don't know is we started for the first couple of years actually as a customer facing kind of marketplace. And for those of you that don't know Paddle who are listening, we basically are revenue infrastructure company for other software businesses. So check out the current billing tax payments things of this nature hypothesis was a little bit different. We basically recognize it was really hard to sell software. And our first view was that marketplaces make it easier to sell stuff, right? They bring new customers they handle the payments. They just pay you out your commission at the end. And so we started as a marketplace and ran at that for two years with basically no revenue. My co founder used to joke we'd have made more money going door to door trying to sell software than the view of this marketplace. Like it was a complete disaster. So there was a big inflection point where we dropped the marketplace and went B2B. What happened was folks who are on the marketplace basically started taking the check out links on their pro listing page and just sticking them on their own websites because they value the infrastructure that enabled them to accept these payment methods and currencies etc. But not the customer facing marketplace at all. So that was a real big moment for the for the business and hard for some very early investors who thought they're investing in like a big consumer face. And kind of brand. That was a big thing. We then started executing pretty well and actually started growing and bringing in revenue. I think I got to more that the next big inflection point was probably bringing in our first set of leadership. So we got through to about series B with no real management or leaders, which is kind of mad. Like it was ignorance having never done it before. Like I was in every single deal for four years. Like I played every single role and after about four years we brought in a VP sales VP success and had a marketing. And that was just such an unlock the two VPs we hired one of them. You just mentioned Abin was with us and grew in entitlement role but both of them were the so fortified years up until about a hundred million dollar valuation. And they were amazing and I just built such a trust and kind of loving relationship with the both of them. And then the final inflection point I think was probably we acquired profit well with the latest fundraise. And that's actually when I think people started to notice paddle like we've got to like high tens of millions in revenue and people still didn't really know much about it in the UK. Certainly not in Europe in the US. The one we acquired profit well which was just very big brand. Profit well and price intelligently people really started to take notice. Couple with some great work from Andrew Davis who we heard as a CMO who did like the first payment in space and stuff like this. But we really invested in brand quite late and suddenly everybody knew paddle and everyone always had in reality. I think there was a bit of a step change overnight quite late stage. But yeah, they're probably the few that stand out to me if that's what you're after. Yeah, I've got so much there to dig into Harrison but I'd love to just touch on the leadership point because that can often be a make or break moment for companies. So we see so many companies that come to us at scour eyes where they've made that wrong leadership hire normally a sales leader hire or a marketing leader hire. Super interesting that you waited till series B to to make those highs but it sounds like they really worked out. So what was important for you in terms of what were you looking for in those those first leader hires. And how do you think it became so successful I suppose. Yeah, it's really uncommon right like not only did they last four years and go from low millions in revenue to 100 but average tenure of the VPC sales. Maybe not success of like 18 months right so first time we got someone in for four years I hide him again to like he's due to good job. And I think it's a super interesting question. I was talking about it to some folks recently like I think one maybe to start with the sad like when we went out to hire our first VPC sales having been running revenue alone really was some individual contributors account executive STRs for four years. I was so excited I was like oh my god I can't wait for some adults to turn up and just tell me what the fuck I've been doing wrong with all this time and just fix it life. I can finally afford or I've been told a me give him permission I should just be hiring someone better this than me. And honestly it was one of the lowest points I had like we went to market and it was just really really hard to find great talent to be honest with you. Yeah, it was really tough I was like oh my god maybe this is this isn't completely super easy to find. And we eventually did I think having played every role within the sales process I was an SCRS and our thousands of emails I was on every single end of the initial call for many years I was in I was the solutions engineer and every deal not realizing all these things were both bad and good. So to be fair are varying different different times it really did help us deeply understand what the sales process looked like the nature of the people these people were going to be managing what skills they were going to need in order to manage higher coach. Run these sales processes I think I I fell I was so close to it that it was really clear to me on who and what profile I needed to succeed which was very helpful. I think if I were to do it again we probably did wait too late like we grew faster much faster when we we did find those adults in in the room. And that being said I think the most common mistake that people make and I'm sure you're this is the people hire too early right it's just like I'd encourage people to wait and it be painful and your growth be slowed. Because slow growth that you then accelerate is something your business can stomach and handle and survive on the wrong higher to early can kill your business or say you back many years. And so that was probably more by luck than judgment because we didn't know what we were doing as children and one woman higher some of these folks but I do think it's up there for success in it at least in the long term. Yeah I think you're completely right Harrison you make a really good case for family led selling for longer than is comfortable I think and most founders that we know and not commercial leaders that's not their background you know their technical or product leaders and they just want to delegate that problem of sales and go to market too early. And actually there's so much value as you say in really understanding you know what it takes to sell the type of profile the personas you know building that early playbook you know that really helps to sharpen what you think you need and it sounds like you exactly right in terms of hiring Adam now going back to that early focus because a common trap. And yet the kind of you know one maybe one to two million stages is trying to serve to broader market to early obviously there needs to be some kind of testing and early iteration of that ICP but but I think companies often feel that that focus can feel like a constraint even though it's usually the thing that enables scale eventually you served a huge market of paddle. How did you narrow focus early on and what did go to market actually like in the in the early days compared to then maybe how it evolved later stage yeah it's interesting like I think when we started paddle yeah.
Yeah, we could basically power any software company out there with the checkout. Right? And we were replacing whatever they were doing today with our own checkout and broader, kind of what we now call revenue for structure. But yeah, when we began, like, nobody knew who we were, and nobody knew what we did. So as such, absolutely everything was outbound, and not only outbound, but like Stone Cold outbound. Like, absolutely no idea who these people were. The most credibility we had was that the main name was quite expensive, like, honestly. That's a basic, well, two children with quite inexpensive domain name, not a lot of funding, like funding in Europe at that time was not what it is today. We'd probably raised, I mean, our siege check was like two of two of two K, and most of that went on the domain name, if not all of it. And we also were operating under a very different model to our competition. We were operating at what was called the merchant and record model. Like, I won't bore your listens with it because I'm sure they don't care. But it was a very adjective sale and very different to how people were thinking about selling that their software. And so whilst nobody knew who we were or wanted to talk to us, we had the ability to sell to every stuff I could be in the world, but they check out yet at that time, I was a one person commercial team, right? So the question I asked myself was like, where do I start? Like, I've got a really limited amount of time. Like, how do I maximize the use of that time? And one of the benefits, I think, having been doing this quite young and for the first time, was I just approached things from first principles because I had no experience in what going to market looked like. And so what we did was we mapped the market at every software company out there that we could sell to that actually was quite quite complex. And it's not easy to find software companies. They don't neatly fit into industry filters and things like this. And we wanted to gather as much info on them as we possibly could in a systemic kind of systematic story way. And then prioritize my time on those that I felt were most likely to yield results. We did have some constraints which are helpful, right? They had to be software companies. They had to have a checkout. It did start to narrow our focus. We got opportunities to move into physical products and stuff along the way that we turned down, which was a great move. But yeah, it was all about getting a deep understanding into the entire set of folks we could sell to really understanding every single one of them in the market at a very deep level. So we could really pinpoint the folks that we could adopt a very challenging sale to being like, you meet the exact profile that should care about my solution. And here's why it was very, very, I mean, is state as quote these days, like hyper relevant kind of targeting a messaging, but at the time like our investors were amazed about this approach that we had. And a lot of what we were doing really was the precursor to good fit, which I kind of know running today. Amazing. And was there a moment where you realized your initial ICP or maybe go to market assumptions were wrong? And how did you course correct? I was at a dinner list and found us the other day. And I was like, how many of you have been told to focus on your ICP? And it's just like family enough fucking all of them. Like everyone raised their hand, right? And yet, like how many of you feel you really have a hand on your ICP, fun enough, every single person raised their hand again, right? And it's like, it's not because they're not being told to focus on this. Like they, they've I could know it's everywhere. It's in every article, right? And yet people don't do it right. And I think it's because people massively under appreciate its complexity, but also the impact it can have on your success, right? And when I think about why people have been unsuccessful about this historically and why I think we were successful about it, a paddle is because I think people historically haven't had the depth of insight into those they're selling to to truly understand what's great about those they're having the most success with and what isn't great about those that they're not having success with, right? This stuff shouldn't be academic, right? It's not, I mean, you may have to start with a hypothesis, but very quickly it turns into data-driven experimentation and iteration over and over and over again. But that's only true if you have access to the data to do that, right? So a paddle, if you ask me what is my ICP, I could give you a pretty generic one in the early days. I can say we sell to software companies post series A who are product led, right? Product led being a proxy for the fact that they have a checkout. That's still a tighter answer than most people give, which is like we sell to industries A and B with employees size Y, right? Like still not great. But instead of that, what we actually did was we'd map the mark of every self-accompany in the world, right? We had a huge amount of insight on them and also the people we were who are applying to us who were creating ops with who we were winning, right? And it allowed us to run analysis, like correlation analysis, on what was the difference between the people who had the higher win rate or the higher ACV or whatever metric we were looking at versus those that didn't. And you start to realize two things, like one, ICP isn't binary. Like people think of it as like ICP or not and it's just mental. What's actually true is there's lots of different attributes with lots of different weights of importance that contribute to a company's overall level of ideal, right? And any company in the world is it somewhere along the spectrum of I do not know, right? And two, you realize that data points that people usually talk about in the context of ICP like industry and stuff like this. Just absolutely don't fucking correlate anywhere near as highly a stuff that's really specific to you. And what we got to is that we learned things like companies that were getting a high amount of traffic say like 25% of traffic outside of the home market, especially when they didn't support the currencies and languages of the traffic they were getting were great for us because we can tell them you're getting loads of traffic outside of your home market. You don't support the currencies and languages for these people. We can help you do it, right? It really tied into our value proposition that we got there through analysis and iteration and it also becomes very actionable. Everybody kind of needs to be working on that basis to truly get a handle on this stuff. But it's not actually like some academic exercise in front of the whiteboard. It's like you need a lot of insight into people and then run real trade driven experimentation over time. They're not at the best successful. No. God. Richness in that answer, Harrison, just the fact that you're taking such a data driven approach to the ICP development and iteration. And I know that's a core part of what you're doing at GoodFit now. But I suppose a question that I often get asked and that I challenge our clients around is when is the right time to expand that ICP? Because we talk about going uncomfortably narrow and there's a lot of value in that. But at what point should a company be saying to themselves, right, okay, we need to now expand either geographically, segment wise. Like how do you think about that and when does that make sense? I think we learn the lesson, probably the hardest possible way at paddle to be fair. So we were constantly zeroing in on who was most likely to buy like eventually. And I think it's still true today. The very best fit customer to paddle was software companies that are living to sell internationally because we really help with the complexity of that. But actually in the early days, our ICP was actually desktop max software. We were growing a 300% year and a year for a number of years selling into that group of folks. We really differentiated with them. We have like trials and licensing SDKs loads of very specific stuff to serve that type of customer. And the years are like focus, focus, focus on these accounts and these accounts only are win rates were astronomical. Our NERR was like 140% or something. But we always knew the market wasn't huge, right? Nonetheless, we raised this big GC series B, right? Book's been growing at 300% plus year and a year. I hired Adam a VP sales a bunch of sales people literally within about three months of that happening. One, it became the worst year of growth we had for a long, long time, even as the numbers got much bigger. And it was because I had this realization of just like, oh shit, like we can't find any more desktop Mac apps that we haven't spoken to in the last six months. So what the hell is this VP sales is set of sales people we have going to do, right? And we had to make a hard pivot to selling to to SaaS companies, which again, sounds mental now is like how big is SaaS and look how it's grown. But at the time, desktop software was still pretty prevalent. We had to pivot to that because one, it was a growing industry, not shrinking one. But it also had huge cross functional ramifications, right? We went from building SDKs for Mac app developers and trials and licensing to like recurring billing management, right? That requires a hell of a lot of product investment, marketing, positioning, coaching salespeople, how to sell these people as new personas, objections, competition, everything, right? And it was because we were too focused on just selling into the folks who are having success with without really having an understanding of the size of the market and how it's evolving of time. So to combine the two points that we talked about today around kind of ICP and market mapping, I think my advice would be for any company out there, know how many accounts are actually out there that you can serve that are qualified, know how many accounts within that Mac market are ICP. And I think about that as prioritization. It's not binary. Like how would I prioritize the accounts within this market? Absolutely direct your dollars and your resources at the highest ICP lowest hanging fruit. That's where you're going to get your growth, your highest ROI, right? But over time, you probably do need to just strategically expand your market in parallel so you're not not quite sure. But at the start of your planning cycle, if you're aware of how many accounts are out there, what you're kind of assumed or usual conversion rates are, you kind of can work out how far are we going to get to selling into this segment or this group, right? And if that number isn't the required number to go out and raise or reach whatever that next step change in growth is for you, you probably need to already be thinking about how you're going to move into a new group, right? Like this stuff does come out and is planning, oh, I issued to some degree. And again, easy to say for me with hindsight, but trust me, we didn't do that. And it completely fucked up. First year after the series beat. Yeah, learn from my mistakes, I guess. You can see the pain though, like, good fit does all this stuff now because we did it so badly, right? But yeah. Oh, man. Yeah, I can see the pain, but I can also see the motivation to solve the pain, which we'll talk about more in a moment. But we spend a lot of time with companies that have that early traction. They've got real customers, even strong product market fit. Yet they seem to kind of not stall, but their growth really slows around that two, three million ARR. And from the outside, it looks like maybe they're still progressing, but internally things are really starting to creak. And they just haven't got that scalability or repeatability where they've not found those growth.
levers from your perspective, what separates companies that are able to build that predictable, repeatable revenue engine from those that maybe hit that plateau and start to slow? It's fun because when we were talking about this in the past, you were saying, between two to three, they start to plateau before that they're good and I'm like, I'm living this, like going through it with good fit, so I need to practice what I preach about. I think the most common problem that I see, like, and I imagine you see different things, right? You're so hot on leadership and and the culture and some of these playbooks, but like, I actually think the problem might come really early, right? And I think the problems actually start right at the start as you're going from their final-led sales process. They actually only show up at two to three million. And I think it's because in the early days, founders, or sometimes your first commercial hire, but usually the founder and it should be, they think it's their job to go out and prove that someone is willing to pay for their product. They're probably not wrong. They're probably the first box that you need to tick, right? Is there a job to prove that the product can make money and there's a problem in this to pay for it as well as keep the lights on, I guess, right? The problem is, if they have some success, they win a customer too. They're like, great, this is working, this is what I'm going to do and they continue down that path. And it seems sensible. Some of us are giving me five grand. I'll go find another person who's willing to give me five grand by hook up by crook, right? And often through network, investor interest, you name it, they find a way. Founders are very resourceful, relentless people, right? And then they think it's their job to go find another five or another 10 her willing to pay, right? And once they've got to some arbitrary number, 10 customers, 15 customers, whatever it is, half a millionaire or an embrace a series, I don't know, the numbers are really matter. They then think, what? I've clearly got going to market fit here, right? Like, I've got 10 customers, I've got a bunch of revenue. I can probably hire someone else to go do the same for me. I've just raised my series, and why high someone will get serious big, great. But what they fail to recognize, I think is as a founder, like they know the product best, they know the market best. They own the roadmap. So in the conversations of someone's asking for something, they with confidence and credibility, you can say, yeah, we'll go build that. They have found a privilege, I think is probably the all encompassing kind of way I'd phrase it. And I think this is in stark difference to those that don't get stuck, because they then go hire a bunch of people who don't have found a privilege, can't create pipeline in the way that they did. And just ultimately full flat on their face, and they're actually starting from scratch, despite the revenue being a certain level to have gone to be able to raise the A. They're actually just starting to build that play bit from scratch, right? And the experience of those that grow through A, B, whatever, one to five million successfully do things very differently. And I think this is also a bit of a second time founder privilege for some folks too, is that it's not their job to convince someone to go and buy their product, right? It's actually their job to work out for a way for others to repeatedly sell their product without the founder in the room. Like, don't find a way to win 10 customers find a way someone else can win 10 customers, right? And that's a huge, huge distinction. And often I've talked about that in the past around like sales execution, like they need to be able to sell without you there. But I think it's also true for pipeline too. It's like there needs to be some stream of pipeline that can feed more people than just use the founder. And yeah, like if you actually focus on that, it's much more likely that you're not going to get stuck between one to five. If anything, getting to one may become harder than getting to one to three or whatever. And this is how people close their second million much faster than their first is because they've actually worked out their repeatability and there the people that go on the good growth curve. That's how I kind of see the difference or the biggest difference, I guess. Such good advice. Just switching gears a bit. I said, like after a journey like paddle, many founders, I think choose advisory roles or investing or maybe hanging out on the beach and whatever few deliberately go back to day one again. We've talked about good fit at high level a few times, but can you just tell us what you're building, like where the idea came from and what it's been like, starting again from scratch after paddle. Yeah, I mean, you've got a bit of a flinder for the idea, right? Like we were growing paddle and growing pretty quickly at my VP, Rebox, who actually hired as a manual researcher, if they did to start with, which is an interesting story in its own right was basically just asked to go and start good fit and I joined them along the way. And in terms of what we're so we've always is a lot of the problems that you just talked about, right? Like we're here to go map your market of qualified accounts, give you a deeper level of insight into this accounts never before, but that's often where a lot of companies will stop, but most people don't know what to do with a massive data set full of loads of insight. So it's actually turning that into something that people can go to market with very effectively will help them run the analysis and who they've been winning or losing in order to identify what is true about Moza having success with to be able to prioritize who they're going after in the market, who they should distribute to the reps, who they should run their ads at. It's like operationalizing that data set and the analysis into go go to market, basically, it's what we're doing a good fit to keep it keep it short. Why do it again? Great question. I rested with it for a long time, right? Like I'd been running the reason they step out from paddle as I've been running in my whole adult life, like we started to Christian line really working together, like 1617 paddle was probably 18, but we'd been working on stuff before. And at some point, your whole identity, friendships, great way you live your life becomes so intertwined with this thing that like I was Harrison app paddle.com not Harrison, the entrepreneur even, you know what I mean, or anything else like friendship, suffer, relationship, suffer. And I was just like, we'd just raise a series, the, you know, it's like, feel like I've seen this journey for like I probably like to do something a little bit different. And I refer to the lot on how I wanted to spend my time and it was two things that attracted me to good feeling. I'm not sure I'd have done anything else. I did get off of opportunities, but it was two things. One, I got the opportunity to work with my best mate on a business quite frankly, like Alex, I hired at paddle and he became my best mate. He was my best man at my wedding last year. And the opportunity to build a big business with your best friend is a difficult opportunity to pass up quite frankly. And then two, I reflected a lot on what I enjoy and a lot of it was growing myself, both professionally and personally and also growing others. And I kind of recognize that businesses are probably the playground through which I can do that most effectively. I did it consider doing coaching quite heavily, particularly for young founders about to go and mad journeys that I don't think people necessarily equip them for particularly well. And maybe now be the next one, but that was really the why. I love that. Yeah, there's something just very powerful and meaningful about building something with a good friend. I'm very lucky that I have the same with Gavin at go wise as well. And you intentionally bootstrapped good fit, you know, for several years before raising your your VC route last year. Why did you choose to start that way? What did it enable and what eventually changed your thinking to go down the VC route? Yeah, I guess for two reasons, I kind of off the back of a 10 year journey with with paddle, right? And when you raise money, like, I think this is increasingly getting understood by founders, but like you're making a commitment to work on that business for a decade, at least the life cycle of fun probably. Not only that, but return the fund, right? Like this has to be a billion other opportunity. Otherwise, the economics of that model just don't work. And I was like, I think this can be an absolutely colossal business. That's not a problem. It's just like, I'm not sure I'm ready right now to necessarily make that commitment in good faith to a set of investors who are all very, very willing to fund good fit from the day that it kind of began. So part of it was that. And then the second part was, I mean, we didn't need it to be fair. Like we, Alex was in a very fortunate position that based on the market education we've been doing on how we're doing things at paddle to run to be small group in Europe that there was literally a queue of customers lining up ready to give good fit cash from the data we began, which meant that it could be self funded, right? And when you don't need to take the funding and you're not sure whether it's the right long term solution for your advice, everyone to not take it until you either one is required. And then you should consider all different types of sources of funding to be fair. The two only ones you're ready to commit to turning this into a category leader, billion other company doesn't make sense to take the funding. So they were the two reasons. My god, it wasn't without his learnings and challenges. They're talking to me. That was a rationale at the time. Oh gosh. It's so interesting what you say because the whole VC model is built on the power law and the expectation that as you say eight out of 10 in the fund probably aren't going to work. One or two will return the fund and be break out successes. But so many founders just seem to think that the VC path is the only path if they've got a B2B SaaS company. What advice would you give to those founders that are thinking about whether to bootstrap versus go down the VC route? And how should they ultimately make that decision? Yeah. One just to be clear, I've got nothing against the model. I'm so grateful for the people that funded PADO because we couldn't have done it without funding. There was a huge development cost up front before we could sell anything perfect for the VC model. And ultimately, especially the early investors, they basically funded Christian and I's education into how to run a business. Why even looks like we have absolutely no experience. It was like the equity funded to MBA kind of fired. So super grateful for them and the model. I'm nothing against it. But I think I mean, we've also since taken VC money from the same folks, right? But I think if I were to evaluate it, it's two things. One is the scale of your ambition and the scale of the opportunity in your business pick enough to be able to return to build a billion on business. And honestly, that's not the case for a lot of folks who have raised in the past. And then they run out of market size and then things become difficult, growth can slow or they struggle to get funding because someone along the way realizes that this may not be quite a big enough opportunity for it to make sense. And I'm obsessed with market mapping and market sizing.
even more than the investors and they're not always spotting that early enough and then you get start half by through, right? So that's one thing. And then I think the other is, if you don't need it, like don't take it necessarily, it has to be a net gain. Like I wasn't sure when we first started, part of whether we'd actually grow faster if we had the VC funding, like in the early days, coupled with some of the other considerations, like we didn't need it, so we didn't take it, right? Like it's just totally cool. And but yeah, it's like, know what you're signing up for, ensure that you can actually deliver upon the promises you're making to your VCs and also only take it if it's going to accelerate your growth room and prove your outcome. And if you want to run, you can still build a business into the tens of millions in revenue without taking funding. You might take some other sources of capital and build a colossal success. You also might build a billion other company without funding in which case, great for you, you've got a hell of a lot of equity that you can eventually sell. So they're the ways I think about it. It's pretty, pretty objective to be fair. And the market is gone a bit crazy from a VC standpoint, certainly where AI is concerned. And we're seeing now companies achieving, you know, breakout growth rates and high valuations that we've probably not seen in in over a decade. But AI is also, I think, moved from experimentation to something that's actively reshaping how go to market teams now operate as well. Often faster than, I think a lot of leadership teams can keep up with. I mean, I host a monthly Pavilion dinner and it's fascinating to see how these CROs and CMOs are evolving their thinking around AI and how they use it within their teams. It's moving at such a pace and you're right at the forefront of this shift. How are you seeing AI reshape go to market today? And what do you think will matter most as we look towards, you know, the back end of this year? I think we're in such a privileged position and good fit because as a day of provider, as the data's often the fuel for whatever AI that we're trying to power our data's feet fed into the agent that's creating the messaging or creating the customized landing page. So we get to see the output use cases like a lot. So it's just been fascinating to see the incredible things folks have been out to achieve with AI. I think at the moment we're seeing AI largely used to increase productivity either internally or externally with in teams like is either automating something like I'm not sending a lot of email or creating stuff much faster like the actual messaging for that email or that assets for ads or a landing page or whatever. I think where it's headed and where it's going to have the biggest impact is when it stops just making us more productive or producing more output. And now as she starts making decisions for us like informing how we go to market because AI can compute a hell of a lot more shit in one go than a human can. In the same way that I guess that I paid media has become very programmatic over time. There's not single individual deciding which places they're going to put their ad on which websites anymore like we can just do that more intelligently these days. I think going to market might go more of the same way. So for an example, if I feed an agent or AI like here's every account in your market with loads of context on every single account in your market, like here's 100,000 companies and hundreds and hundreds of data points on them not only now, but how those data points have evolved over the past, I don't know, seven years. One already that's a level of context that human brain just can't, can't, can't hold off right. And then here's every single company that's ever applied to us and what their profile like at the point they're applied or every company was called created not with one lost their LTV whatever. And here's every single channel of touchpoint I have available to me. And here's my ACV LTV and desire a cat payback right AI is going to do a much better job than a human to work out to say if there's something like for this account, it closely matches the profile of X that came before you had success with. We'd encourage you engaging with these personas based on who's in the organization and who you had success with in the past. We suggest you ping each of these personas on these different channels based on your previous success or whether most likely to respond based on previous data. One of those channels is ads. We suggest that in the spending of X based on the expected outcome from that company on Y platform. And we've created the assets fee for that ad. And another is email and we think this sequence is most likely to resonate with the personas in a question. That's quite impressive when it's applied to one account. But you can actually just apply it to your entire market at any given time all the time. And I think this is the future that we're trying to take us towards with good for it. Right. The starting point is the quality of the data to be fed, to actually do the analysis or create the assets to create the messaging. As we move from just creating stuff to informing how we go to market, I think it's going to yield much better outputs and an experience. And I actually think it can transform the experience of both the cello, which is where we spend a lot of our time as go to market leaders. Like how do we do be better at selling? I think that the buy product might be actually a better experience of buyers. Like right now people feel fucking swamped with just crap. Because right now we're using AI to just create a lot of stuff as opposed to direct that stuff at the most relevant people of the most relevant time in the most relevant way in the way that they enjoy and respond to. Like good selling should you could match good buying experiences right. And I think as as AI starts to do more of the decision making, that's where we're going to see the biggest bumper. But maybe a basic example right like at this point in time, I could hire an SDR, Shreya of Uni, tell them kind of my ICP and be like go find some companies that we should sell to you based on the information. They're not going to do as good a job as me with a data set to be able to just pick out 10 accounts and they should sell to you right. It did this complete different experience. But yeah, that's that's kind of how I think about it if that makes sense. Gosh, yeah, I mean, I love the picture that you're you're painting both for buyers and and sellers there. But what does this actually mean for going to market teams do you think? Like how will teams look in let's say 12 to 24 months time? What fundamentally changes? I mean, is this the end of the SDR or something else? Yeah, I don't think so. Like within that time span, I think definitely not like I'm being asked a lot of my fundraising is just like do we think AI is going to buy and sell basically we've been forward. We're in a forged position whereby it just it doesn't matter to us to be fair. Like I can feed a human a bunch of contacts on who they should sell to. I can feed a AI a bunch of contacts on who they should sell to or I can feed a procurement bot, a bunch of information on a set of products. I think it should buy based on other companies that have been successful that have come before it right. Like there's lots of possibilities for us. I think in the short term, no, I think where the biggest change I actually see, I mean, we're definitely going to see smaller teams higher output or all of the things you'd expect. I think we're going to see people working on problems and tasks that humans are better suited for than the net AI much more so. And again, I'm still not at the point where I'm seeing machines capable of actually engaging in the sales process. I think a lot of the stuff is still very top of funnel heavy. So only and it will continue to be over the next 12 to 18 months. I will see how far down the value chain AI can can get herself involved and just place folks. But at the moment, it's very much in the top of funnel. But where I think there's going to be a really interesting change is not being talked about much is like people often think about threats to displacing some of the more junior roles that we have. I think that the influence I'm interested in is actually the clash between the CRO and the CMO. And like I think AI is influencing top of funnel faster than bomb the funnel. Right. And who's going to own that? Right. Like in the the earliest signs you see of this pre AI, we're just like, should the SCR's role in the marketing or should they roll into sales? Right. It's actually this problem times 10. Right. If if I can give either a CRO or a CMO, you know, here's 50 grand, go drive as much problem as possible via whatever means the one email ads, AIS, the R's, I don't care events, people in person, I don't really give a shit. Like who who owns that? The CMO or the CRO. And I think there's going to be that's going to be interesting to see how it plays out, right? Like and ultimately, I think it's going to be the folks who are most savvy at interpreting data and then utilizing it to go to market effectively with the combination of both humans and AI that are most successful. They're like this convergence of power of the CRO CMO, I think is very interesting, particularly at the top of funnel because CRO is a meant to only have a new end to end, right? And then how capable will they are they to really focus on the officer acquired at the top end of that? I think it's a bit fascinating. Yeah, that is interesting. And are there any roles that you think become more valuable in go to market, not less as as AI adoption increases? I've seen this emergence of the go to market engineer a lot, right? Which I think is quite interesting. I don't think it has a long shelf life though, which is maybe a bit of, of course, a lot of inflammatory. I don't think many of us say that. Like they've spotted the right problem, which is in order to go to market really well, like you need one, that the first problem they tried to solve is actually gathering that data set that I've been talking about, right? Like data lives across all sorts of different sources. You need to prompt AI in different ways to get that insight. And it's a very technical problem today. Great products will make that problem not technical. So you don't need to go to market engineer to do it anymore. And an increase in me is automations and workflows become more and more user friendly. Again, I don't think technical skills that's going to be required. And so that's been a role that's emerged, but I don't think we'll last if products do their job right. And I think actually, yeah, you're going to see much more empowered. I don't know where it's going to live. Like revops, CMO, like where people have as leaders had to hire folks to do work, I do think they're going to be able to do more and more themselves utilizing some of this technology and others. And yeah, between zero, revops, CMO, I'm not sure to be fair, but I think the shelf life of some of these technical roles of the go to market actually is limited.
because I think the reason they exist is because it's so complex to get some of this stuff to work, which the answer isn't, let's hire someone really technical to make it work, it's like, why don't we just fuck you make it easier? And again, I'm not going to talk about some of our competitors, but like that's a big differentiator. It's like, I know that I'm going to use this thing, and it can produce really great outputs. How many people do so in a sustainable way over five years, or the sales team of a hundred people? None of them, right? No, I completely agree. I completely agree. The Go-to-Market Engineer role is probably one of the highest in demand roles at the moment. I think I picked up a post on this on LinkedIn recently, but actually it's not solving the right problem. It's there because of the complexity of things like clay and NATN and building those workflows, and actually really the solution to that is just better products that. Well, yeah, I don't wake up trying to cobble together datasets, I just want one, but to me, really, we want to put those agents and that power in the hands of a layman, a user like me, that is non-technical, and that's definitely the direction it is going. What do you think of some of the biggest misconceptions that founders and Go-to-Market leaders have when it comes to AI, and it's role in the revenue function? Yeah, that's interesting. I think I certainly see the early sage, I think, misused. As I said, I think people are most affected by using it today for skating stuff, like automating stuff, and you can only really automate what you know is working, which means I think it's application in some of the early sage is just quite difficult. I think it has some really good ones, but one of the ones that I think people struggle with is that people just think it can do more of the work in establishing product market, fit in Go-to-Market, fit in its actually able to. I think a number of companies who have seen this in the turn have been missold. Oh, yeah, yeah, just buy my product to help me kind of hear your targeting. I'll go find you a bunch of pipeline, a bunch of business. These AI-SDR pitches of a couple of years ago were just too broad. They're actually can be really good at very point things within that process, but they were selling themselves as their silver bullet to just immediately finding Go-to-Market fit. The advice I'd give early sage founders is AI isn't going to work out product market for you. You need to understand the audience and customers who have a common pain and are identified in the first place. You need to build a solution for them. You need to work out how to communicate the benefits of your solution to those people. I can help drawing sight from conversations. You still need to go have those conversations. Also, you'll probably have a 25 AI is only as good as the size of the data set you're feeding it. You have to just go do this stuff and work it out. There's a bit of a misconception, I think, but folks have right now. Agreed. Absolutely. I suppose just to wrap up from everything that you've seen across the paddle and good fit and just a border ecosystem, what do you think most improves the company's chances of successfully making that leap from series A to B? Yeah. I think we've covered some of that, right? I think it's not only in bringing in revenue, but a peat or wafer others to bring in revenue. I generally think that's the biggest difference between those that scale through that very quickly versus not. I think in the context of that, make sure you invest in the right leaders at the right time. They're the folks that saw through that phase. Unfortunately, there's very different problems as you go from B to C, right? Suddenly, your problem is a multi-market, multi-products, different, different rabbit holes, but those are the ones, I think, from A to B. I've done it once. I'll see if I can do it again. Maybe I'll have some more lessons for you in a year's time. We'll see how it goes. Well, Haras and I have no doubt that you will successfully make the leap and graduate. This has been an incredibly generous and thoughtful conversation. We've covered a lot from the inflection points and scaling paddle, the reality of starting again with GoodFit, the trade-offs around bootstrapping and VC, but what I've really enjoyed is your perspectives on AI and how that's fundamentally reshaping go-to-market and how I share a lot of those views. Thank you so much. Thank you. I know that this is going to resonate deeply with founders and leaders that are navigating that journey from one to 10 right now. So, really appreciate your insight. We're definitely cheering you on from the sides with GoodFit, really, really looking forward to see how that journey pans out and thanks again for coming on Making the Red. Thanks for having me. Yeah, a great speaker. Amazing. 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