E669 | Harrison Rose, GoodFit: How AI Is Rewriting B2B Go-To-Market

0:00Welcome back everyone to another episode of the EUvz podcast. Today I'm delighted to be joined by Harrison Rose, founder and CEO of GoodFit. Harrison previously co-founded Paddle, scaling it into one of the UK's fastest growing software companies, and now is building GoodFit, an AI driven go-to-market data platform that just raised$13 million, Series A led by Notion Capital. A former investor is of course Robin Capital, and I am a big friend of Robin, so I wanted to give a shout out here. Today we'll dive into how he's applying his GTM learnings to this new venture, what the rise of AI means for commercial strategies and what this all means for the European ecosystem.

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2:22Tear down this wall. It's more than just an ally. This is a union of values. Let's start acting. This show is not investment advice and the hosts of this episode may be invested in the funds and companies featured. Welcome to the pod. Thank you for having me, mate. Yeah, yeah, really excited. So Harrison, let's just level set with everyone that might not know GoodFit. Talk to them. What is GoodFit all about? yeah i mean good fit is a data platform for go-to-market teams basically so we help you map your market of all the qualified accounts so you can tell to out there we configure a bunch of insight against every single one of those companies in your market help you recognize which of them are those you should actually be spending your time dollars money effort on and then even scientists suggest which of the ever-evolving new exciting go-to-market strategies you should actually deploy in order to go and capture that demand and turn it into revenue tell us about paddle because you had an aha moment at paddle so let's just get that out of the way as well yeah so good fit was kind of born out of some of the the needs that we had at paddle i guess so i'm not sure it was an aha moment as such like we we started paddle i had a co-canical christian when we were like 17 18 and because of that we hadn't worked anywhere else we had no context on what good luck like what came before what was status quo like i've talked in the past about that being like a real blessing and a curse.

3:50Like the blessing is that you approach everything from first principles versus how things are usually done because you just have no reference point, quite frankly. The curse is you sometimes spend weeks and weeks trying to solve something that has actually just already been solved a hundred times before and you don't need to reinvent. So like it has pros and cons. But in the context of GoodFit, I was kind of the commercial leader, commercial co-founder at Puddle. But when we started, nobody knew who we were, never knew what we did. And we operated on a quite different business model, actually, to the market was expecting.

4:20It's called the Merch to Record business model. For those listeners that don't know, Paddle, we're like a revenue infrastructure company for other software businesses, like checkout, recurring billing, payments, things like this. But we basically had the ability to serve every software company in the world that had a checkout. So a pretty big market. I was like a one-person commercial team. So that first principles question I asked myself was like, where do I start? Like I could sell to any of these software companies. and so approaching things from first principles i kind of was like well let me get a list or let me map every software company out there that i could sell to let me gather as much information on them as i can in a systematic way so i can prioritize my time on those that are most likely to like most likely to yield results because i'm a one-person team right now because there was no way i could work kind of large portions of the market and those same principles applied to go to market today they're kind of the same principles on which we built GoodFit from, but we got more and more sophisticated around this go-to-market kind of data engine that we built a paddle to fuel our own go-to-market up until the point that we recognized that was a product in its own right and have started GoodFit.

5:23And I can tell that story as well. It wasn't necessarily an aha moment as much as we were just approaching like, how do we go to market in the most efficient way possible? And the starting point for that was data. And that was really the genesis for what eventually became GoodFit, if that makes sense. Yeah. Then tell me a bit about the customers that come and use GoodFit. What's the profile? Because I imagine that go-to-market is very much a startup problem and startup verb, so to say, or it's something that if you go to a normal company that's outside of the tech arena, they don't think of it as such.

6:00They think of themselves as salespeople and so on. So talk a bit about that, how it works. i mean we don't necessarily make the distinction like whether you're going to market we talk about go-to-market strategies a lot whether you're deploying like ads uh we'll talk about programmatic go-to-market a little bit later i think whether you've got a sales team that are cold calling like all of these things need to be fueled by data like you always need to ask who am i selling to like why and also how which is which of those strategies you're deploying and that's true whether you're like i don't know trying to find true in every industry that's selling quite frankly, whether you're trying to sell, I don't know, as an agency to go and do some web development or a classic B2B SaaS product.

6:39And that is the vision for GoodFit or the mission. We always want to answer who you should be selling to, why and how for any company out there. We do focus on B2B tech companies. That's largely just because they're a little bit farther down the education curve, which I think is what you're alluding to. They tend to have a little bit more robots thinking, even if they don't necessarily have the function. They're a little bit more educated on what are the jobs to be done to go to market effectively, if you like. But we serve companies in B2B tech, and it's tech more broadly. I kind of think of it as the same kind of market that investors would invest in even today, which is kind of broadening, I think.

7:14But it does tend to be companies that have some level of go-to-market that are already established. And we're really helping them turn that into a predictable machine, something that's optimized and working really, really efficiently and effectively, as opposed to helping folks go from zero to one. I think over time, it's something we'll do more and more with like clear and what the product and how the needs differ when that's your challenge, as opposed to how do I make this thing bigger, better, more effective. But it just tends to be the established kind of B2B tech companies with a sales marketing function that tend to come and buy GoodFit today.

7:47Tell me, Harrison, a bit about the, like you had the founding journey with Paddle and now you have it with GoodFit. what's different this time around because obviously first time you were testing a bunch now especially with a company that does go to market as as your product i imagine that go to market is something that was quite easily uh approached for you yeah i mean completely different like i can't emphasize enough that we started that business it's like effectively children not having done anything before and every single thing that we could have possibly done was new and like there's some really stark stories of that like i remember raising the series a and people asking like what what's your culture like and christian and i being like so what's culture like we didn't know what that is and like the journey we went on there and the culture that we eventually built was something i'm so proud of so i can't emphasize enough that the the experience is fundamentally different it's certainly a lot easier i'd say second time around again having having made some mistakes, albeit not easy, easier, but not easy.

8:51I'd say the market piece is something that's really interesting though. Like we had a queue of customers lined up ready to buy GoodFit before it even started. I can talk a little bit more specifically about that founding story in just a second, which is very different to Paddle. Like, as I said, when we started how known and knew that we were, we had no credibility. We'd not built a unicorn. We'd not already established ourselves as thought leaders in go-to-market and built a network of revenue leaders who wanted to replicate what it is that we've been doing. Like that experience Vince is very different and was certainly a lot harder because yeah, we weren't selling to our peers into a network that we'd established.

9:23And a problem that we really knew, like Paddle like GoodFit came out of a personal need. So we started this because Christian was trying to sell software himself and realizing that he was spending as much time on the infrastructure to sell the software as he was building the software, which was kind of the idea behind Paddle. It was born out of and it's the same for GoodFit, albeit we were much better positioned to take advantage of that experience, that network, that credibility second time around for sure. Tell me a bit about selecting investors. I was chatting with Ichazo from Notion before coming on here.

9:54I said, do you want to join? And then she said, no, no, Harrison will do great alone. I'll let him take the spotlight on this one. So tell me a bit about picking investors this second time around versus the first one. What would you say are the crucial things to pay attention to yeah so it was very different so at paddle we were we raised money from the day zero before we began like krish and i were kind of playing with some ideas of what would become paddle whilst i was at school he'd actually left already and we raised for an angel investor and then went on that path thereafter i think by the time i stepped back from full time we'd raised 300 million dollars it was your classic vc counterpart journey so with good fit i actually joined a little bit into it having begun so my old vk of revops at paddle actually left paddle and started good fit a little bit before i joined and we could talk about that if you want but we were bootstrapped as i said we had a queue of customers lined up ready to buy good fit before we began notion in particular actually had paid particular attention to to the unique way in which we're using data and go to market and we're encouraging us to educate the rest of their portfolio on it And that eventually became him encouraging Alex to maybe leave Padawan and go turn this into a product.

11:04Very happy for him. I hired him straight out of uni, but on an amazing, amazing story of his own. Was devastated. I lost my right hand and VP of Red Ops in the business. But have eventually joined him along the way. I was telling him, I'm like, it's not normal that you have a queue of people lined up ready to give you tens of thousands of dollars before you've even begun. Like, it's incredibly abnormal, in fact. but because of that luxury and because he was a one-person scene for quite a while as he was kind of working out what the product looked like very clear on the problems he wanted to solve but not necessarily sure on what the solution looked like good fit was bootstrapped for for four years and then our first round of funding we've just closed and announced in the last month month or two led by notion obviously i've got a great relationship with them since they led the series b at paddle back in 2017 but yeah we actually bootstrapped good fit for a number of years before having just raised.

11:49And again, much more optionality in terms of investors we could choose second time round, having had some experience under your belt. But I always wanted to pick Notion there because generally, I think they were the investor that understood this problem, showed the most interest in it from the earliest days, were powering most of their portfolio in terms of go to market. And my relationships with the partners there are so, so strong. and if you can establish that trust with someone and feel like you can go and be fully authentic with them you're going to run your business much more effectively quite frankly like in the early days of paddle i had a lot of imposter syndrome like as a young founder but being able to do the second time around with someone that i trust and believes in me like i don't know it just really elevates that that experience i'd say talk about the decision to also because yes you got notion but you also got a group of solo GPs, all friends of mine, actually.

12:46Common Magic, Adrena. Who do we have more? I saw another name. Gideon. So, yeah, Gideon from Adrena, Sarah from Common Magic. We've got Robin from Robin Capital. We've also got an Ovia in Wraith. We've got Salaka as well. So a few different folks, yeah. Tell me about their decision to put together the syndicate, so to say, behind the round as such. Because you could have, I'm sure, picked anyone. on yeah we didn't even speak to to an investor who's quite interested in doing that whole thing so like i think it's a couple of things right like notion they were the lead but i think we're quite willing to do the whole thing and then different questions come up right like again to walks then do you want this person to own such a large portion of the cap table and is this is this healthy in terms of running the business like if you have an investor that's talking to you like that like already that's a great sign this is a great investor because they're thinking about with business not just their own ownership like awesome already what a great sign and was no surprise to me and two and like it was a pretty chunky round as i said we really wanted to this this step change would be structure vc back is quite a big one for us so we did want to raise a reasonable amount of money to facilitate that change because because it really does require quite a lot but i think i was also conscious of like echo chamber like i've known notion for a long time they've known me for a long time they know how i like to go to market i have been a go-to market advisor for motion for a number of years like i think there's a bit of danger of just per chamber really that's good governance yeah it is good governance too exactly and network and experience and just different perspectives right it was like that that was the main the main thing and each person it sounds like you know them that we've brought in is a phenomenal operator advisor like pet persons having in your corner.

14:30So that's kind of how we got there. Then tell me about that decision to me to do a 12 million year round. Like, and I think there's two decisions. There's the first one, which is bootstrap for four years. That's not what everyone chooses to do. So let's talk a bit about that and what that enabled you to do when you think it's a good fit and when you'd say, well, maybe do take money early. And then after that, let's talk about the decision to do a chunky round, as you called it. Yeah. so the the boost reposition as i said there was a few things right alex actually started before me right so he left paddle his story is amazing he joined us somewhere to like manually research and gather data for the sales scene that paddle won a hackathon in like three weeks and it's like i can turn this into something completely systematic and promising engineering heavy as opposed to human heavy immediately after that he kind of came became a right hand in the business and we built this go-to-market data engine together which would become a good fit he left a little bit worth of ARR in less than 12 months.

15:27It's like a one-person team. It was the good times, don't get me wrong, on COVID. He also churned most of it as a one-person team, not really knowing what he was doing. But it was really clear there was real problem market fit, as I'd describe it, in what it is he was doing. And he probably just needed a little bit of help and experience to come in and turn that into a business, which is when I joined him. But as I said, that gives you the luxury to be able to bootstrap. We were selling data at the time, like candy. People were just desperate to get what it is that we were offering. And when you're selling high-value contracts with a relatively small team it gives you the luxury to be able to bootstrap and then when i joined him being completely candid with you there were a few things in my mind like one one was just like curiosity like i'd never run a profitable company before and i wondered what that would look like turns out really hard uh that's what i say as hard as running a company valued at 1.4 billion dollars i think just despite much smaller scale and the other was I mean I'd just been on a 10-year journey like I'm really conscious of the commitment you're making to VCs when you sign on the dotted line for VC money that you're about to go and try and return their fund and build another 100 million dollar business I wasn't sure we were necessarily ready for that or we were committed to that and then over time as we were working together as we saw the market explode around us as go to market has fundamentally evolved and changed in the past couple of years we just became so excited about what we could do that it made sense we got some acquisition offers that we were very easily turned down.

16:54And all of this became real obvious to us that we should turn this into something big. And Notion was the obvious choice to do so given the relationship that we have there as the leader at least. It would be helpful that you talk a bit to the audience about the decision to raise capital from VCs, because I think it's something that there's quite a few too many founders, and honestly, also VCs and angel investors that are not mindful enough about. I think a good investor is very mindful of what it takes to go on the journey and also a good founder. And the good investor would also make sure that the founders understand, but I see it too often not being the case that these conversations are being had.

17:33So talk about that decision and where you see me, because I imagine you talk to a bunch of other founders out there that are struggling on the journey or trying to figure out their route, and then they look at you as a bit of an inspiration having gone for years without. Yeah, I think you need to be really, really clear on outcomes, right? We were bootstrapped for a while because we weren't sure on what outcome we wanted to shoot for and it gave us optionality, right? We could continue to run the business profitably. We could raise some debt, for example, to get a bit of an injection of capsule into the business and keep 100 % ownership between Alex and I.

18:09Or we could go VC back knowing that you're basically committing to build a colossal business over probably a longer period of time. And we weren't sure which path was right for the business in terms of fit, because not every business is actually VC backable in terms of its potential outcome. We should also acknowledge that. I think increasingly we were sure that we were, but I wanted to get into business and ensure that was the case in the early days. And two, you need to align with your investors and what outcome is the issue. Some angels are happy for you not to build a massive business and deliver a relatively quick return at whatever multiple.

18:38An institutional VC investor probably doesn't care about that type of outcome, right? And so I think it's all about determining what do you want for your business in terms of size, scale, time horizons, even, and then thinking about what options that allows for you and then executing on that, right? In our case, given the way in which we saw AI transform and go to market, we were like, this category has never seen and potentially will never see in my lifetime quite as much change and disruption as we're seeing right now. And we have the opportunity to fundamentally change the way in which every single B2B product in the world is bought and sold moving forward.

19:18Like that feels like a pretty fucking chunky problem that's exciting for us to go and solve. What's the only way to really able to do that? The only option really becomes to raise your seat, right? but I think it's being really honest with yourself and your investors about what outcome are you shooting for in what time horizon and who makes sense as a result, quite frankly. And then let's talk about this AI disruption of go-to-market because I completely agree with you that this is one of the places where we can definitely see a huge explosion in opportunity. So talk about that disruption, what you're seeing, maybe also talk a bit to where you're seeing people getting it wrong.

19:53It seems like everyone's thinking that now you can automate a lot of your outreach and AI is going to make it all work. And then you realize once you get into the nitty gritty, it's actually not that easy. This is what we were observing ourselves over the past few years, right? Like where good fits on up 10, 20, 30 customers paying us high tens of thousands a year and making sales seems more efficient, more productive. Like suddenly the things that we can actually deliver for these companies, like the opportunities were exploding, right? Like where data historically could be used to supply the sales team with a less qualified accounts to go and work.

20:28Now every single element and every single decision to go to market can start to be influenced by the combination of data and AI. And I think it's how those things interplayed, which is really, really critical to deliver the great outcomes, maybe start to jump ahead to some of the issues that I think some people are having. I think the biggest thing that I'm seeing is our usage of AI in go-to-market is incredibly narrow right now. People are using AI actually just to automate a lot, as opposed to necessarily do things better, which I think is the biggest distinction that we're going to see over time.

21:04So right now, AI is kind of effectively, I think, being used at least by good folks to get richer data sets than they've ever before to inform the gen AI that they're using to produce a message or produce a landing page or an ad or whatever, or enrich accounts better than ever before to get better insight before you go and do an activity. But I think where we'll see AI really start to impact go to market most profoundly is that AI will start to inform how companies are going to market better than ever. And this links to a little bit of the vision that I have for GoodFit. I want to take every account in your market, analyze every single one of those accounts versus your historic performance.

21:43Secondly, both of those things better than ever before as a result of data and AI and start to do things like recommend for every single account in your entire market, the expected value or spend you could afford on every single one of those 10 ,000 accounts in your term, what channels are most efficient to contact them with, if it's ads, how much, is it email, is it call call, is it events, and what combination of those things do we think is most effective, most efficient in order to get that company to engage based on how they've performed in the past. Like if I asked a human that on a single company right now, it's a really, really hard thing for them to be able to work out.

22:15Right. If I'm like, here's a company, what is the most efficient and effective way to get in front of them? What is a unique combination of touch points that's going to deliver the best results for the lowest cost? Some of them are looking like, obviously, I can't work that out. Right. But suddenly, when you can do that across all 50 ,000 companies in your addressable market, the quality and the effectiveness and the efficiency of what we're going to be able to deliver is much improved. But also, as you start to feed that data, which is required to deliver that level of insight, analysis and insight into like the, what I call the execution layer, then the next set of tools are actually delivering the touch points, delivering the ads, delivering the message, whatever it may be.

22:52Like, Gen.ai can do much, much better stuff fed with really great data, right? And I think this is where some of the disconnect is today. Like people are jumping straight to execution layer and AI to just automate stuff. But they're feeding their gen AI, creating the message or the ad or whatever, just a bunch of really crap stuff, basically. And thus the results are you're just automating more bad stuff as opposed to doing anything differently or anything better. And everyone's like, this isn't working. And they say, well, you're actually just doing more bad. So no shit. And I think this is the trap that most people fall into.

23:28Tell me, Harrison, because now we're a bit in the weeds of what GoodFit really is and what GoodFit really does. Like you described here, the go-to-market motion all the way from the beginning of getting the data, scoping out who you target, getting the data to be able to target them well, all the way to in the end, actually approaching and getting them through a sales funnel and closing. What do you do on this part? What is GoodFit doing right now and where are you working towards being able to handle this? So today we're at the start of every go-to-market action that you take. Eventually I want to be at the end and then the circle around the whole thing, right?

24:05So every single go-to-market strategy, motion, campaign, whatever, starts with who the hell am I selling to? Why? And then eventually how, which is also somewhere we're going to start to improve. The start is like, who am I selling to and why? Whether you're running a cold call campaign, an ad, a direct mail campaign, inviting them to a breakfast, that's a go-to-market strategy. And we're here to answer that question for every single company. And the way that you do so is that way back to the first principles of Paddle is like, what is actually my qualified list of accounts that I can sell to?

24:36And against every single one of those, I need a huge amount of insight configured to me, unique to me, that really helps me understand which companies are great or not. And that really does need to be configured to you in order to be useful. and then with that you can start deploying go to market much more effectively analyzing your performance much more effectively like the starting point is always the quality of your data so we're here to map that market enrich it with insight configured to you analyze what great customers look like and then today we feed that into your as we call it execution layer of choice but once we've worked out this is a tier one customer versus a tier two we feed your tier one customers into your outreach your code calling tool your abm platform or whatever and that's where you'd execute.

25:17Maybe your tier three, you'd run what we call programmatic go-to-market app, which is a much more automated means of go-to-market with less humans in the loop because your expected return from those accounts is lesser than the tier one. So they require a different approach, right? So we're starting to inform who you're selling to, why and how, but the actual execution is taking place elsewhere. Now today, huge amounts of dollars have gone into this execution layer, like a new sales martech tool seems to emerge like every week, which is why there's a greater emphasis, I think, for revenue leaders on telling them how, like which of these things to actually use or what combination of them.

25:50But then there's also nothing at the end of this process to be like, we have observability into every single one of these channels, touchpoints, customers that you've been selling to. We know their sales cycle, their ACB, on what channel they responded, how long it took. And then taking that to inform that next set of activities. Like there's not really anything close in the loop super well right now. So the vision is to become kind of this decision hub, this mission control for go to market, determining who you're selling to, how and why, as opposed to actually doing the execution, like sending the email or the tool to run the cold call.

26:22I think there's plenty of that in this space. There are very few people informing what goes into those tools and why, and then what next based on how it performed. So that's kind of what we're doing. And today we've been winning based on the data, just to be clear, we supply the best, most configurable datasets in the world to feed some of these systems. They increasingly will be advisory on like what to do with the data in order to drive the best go to market and this is where ai really transforming some of our capabilities if that makes sense all right this is hugely interesting tell me why do you like is it purely because there's so much competition in the execution space that you don't want to touch that and you just think the opportunity in itself on the on the data side is so big that for you having an api that that integrates into salesforce or whatever people use is sufficient it's really interesting i want to never say never to be honest with you uh i think there's a chance that we could do it at some point in time because if you're deciding which companies why and how if you start owning now you could probably potentially do a pretty good job of that too right so maybe one day i think honestly my view is that the execution is going to become increasingly commoditized like i i don't think it's super complex to build a product that can send along email or run a bunch of cold calls.

27:37I think that's increasingly not very defensible, to be honest with you. So that's just an investment thing of just like, does it make sense for us to build this thing when we could just integrate with it, to be fair? The other is that I have, and VCs don't always agree with me on this. I'm like, I have a feeling that the way you stand out in a go-to-market motion or the way you're successful is that what is the unique recipe of that execution layer that you're going to deploy that helps you stand out to a prospect, which gets them to engage with you. And I think that could just continue to proliferate the different options that we have there.

28:12And no tool is ever going to be able to encompass all of them very well. And we don't need to. If our data is fed into them and we get the data fed back, we just need to continue to inform what goes in and make that process really easy. And that's easier and easier with NDP. You get integrations, all this type of stuff. So maybe we'll get there, especially if we see that become a really common recipe but I'm not sure. Yeah. Tell me Harrison how you think about pricing so to say and batching of customers because I imagine there's a there's a point where this is valuable like enough per client per potential like me so I'm a creator I love a billion subscribers like it would it be something that I would ever use or do you need to have you need to justify a x dollar amount spent on research per client?

28:57And for that reason, you need to be looking at this type of... Yeah, that's a great question. So two things need to be true. Like one, the market probably needs to be big enough for this to be complex. Like if you're only selling to like 50 companies, like you can probably manually work out what's the best way to get in front of them and do a bunch of research into them, right? It's probably less than a thousand. You maybe should just do this manually. When it starts to get above a thousand, I think it's really hard to do this stuff without making it a product. The other probably is ACV as well.