The Exchanges

Q Okay. So you switch everyone over and then at some point you become the GM and president in addition to leading product. What was sort of the story there?

A So I was talking about how the kind of COO of the LiveRamp business became the head of product for Axiom. When our founder CEO, Orrin Hoffman, left, which was about a year after, a year and a half after the acquisition, Travis, who was the CEO, became the, the CEO of LiveRamp within Axiom. And then he did that for about, I guess it was 2015, two years, and then decided to go found another company. And at that point in time, me and our current head of sales Became like co-general managers for the LiveRamp business, and that was the point in time as well where Axiom was starting this process of figuring out how to divest the legacy business.

AI assessment note: “me and our current head of sales Became like co-general managers for the LiveRamp business”

Q Can you give a, just a few of the questions that you find most illuminating in those conversations?

A So the first thing we'll do is we ask them, okay, tell me in your own words, what did you buy? Obviously it's a little weird because, you know, it's my company. I just sold it to you. Of course I know, but that anchors them on the purchase. And then the next question is what would that enable you to achieve? So we're immediately taking the conversation away from your product and we will never talk about your product in the rest of the interview. To their goals. And they're probably going to tell you some basic functional goal. Like, you know, I needed to, you know, get this all in one place and stop using spreadsheets or whatever. And then we need to explore more around that because there's probably more to the story. So like, why is that so important to you? Who else cares about this outcome? So ask some questions and probe and just really try to get a sense of like, what are all the layers to their goal? And then the next thing we need to do is map the customer journey. So we'll say, okay, do you remember the first time you started trying to do X? Oh yeah. You know, it was two and a half years ago and my boss put me on this new project and blah, blah, blah. Okay. What did you do then? And then we're just going to go through that journey. Well, first I Googled this and then I tried this product, but it didn't work. And we just go through that whole journey. And I'm listening f…

AI assessment note: “tell me in your own words, what did you buy?”

Q For the founders that end up running their businesses at scale, do you think it's somewhat random luck in the sense of the organization can actually handle those peculiarities? Or do you think they tend to go into different phases and maybe mature in some way?

A No, I don't think they mature. I think they, uh, discover an organizational trick. One of my best friends, John Rubinstein, was, uh, uh, Jobs's, uh, head of hardware for, you know, both at Next and then at, uh, the reinvention of Apple. And John, I think, was representative of Steve Jobs growing up. Jobs was still insane, but, but the second coming of Steve Jobs had an organizational level of world-class executors. Tim Cook, John Rubinstein, Avi, et cetera, were all people who could take that craziness and filter it down to an organization that provided a level of stability. They were an impedance match. You know, between crazy whatever to competent management, and that's what Jobs lacked in his first incarnation at Apple. There was no filter. There was no level of operational excellence between his mouth and then the direct people he was trying to manage.

AI assessment note: “No, I don't think they mature. I think they, uh, discover an organizational trick.”

Q So continuing on down the journey, you sort of begin with this idea of building context through talking to other folks in somewhat similar, maybe dissimilar marketing roles. Then what happens?

A So yeah, after the listening tour, I again re-anchored myself on what do I know about our business strategy over the next 12 to 18 months? And what do I believe that this person really needs to get an A on? And what are their skill sets that I'm saying, hey, this person doesn't Isn't an A plus at this one thing? Let's say PR, for example. That's okay, because we have other strengths on our existing team that will make up for it. And then I just ensured that Joe and I were aligned. And then I spent a ton of time trying to curate who was interviewing. Was it cross-functional in nature enough? And then just preparing for my own interview assessment.

AI assessment note: “after the listening tour, I again re-anchored myself on what do I know”

Q What did the company do to start to think about what are the next few products and or business units we might want to create?

A I think the most important thing, as you begin to think multi-product, if you're a product that has Initial product market fit for a core. What else does that specific user want that would make their job better? Like the classic line of your B to B user wants to get promoted. What is the thing you can give them that helps them do so? And when Stripe was thinking about the second products, one of the like easy angles for that is who is our buyer? It's that developer who's like integrating payments early on. And like, what could you give them that same buyer to make their lives meaningfully better? And so that's how Radar, the fraud product came about, where it's like, well, all these people are taking payments on cards, and you know what sucks about doing that? Fraud. Let's, let's give them a tool, uh, that can make that a lot easier. And given that we had that focus, that our user was the same person who was buying payments, we were able to really, um, similarly narrow down the set of features that made a difference for that User. Certainly there's other dimensions that you can think about as you're trying to go multi-product. One is like, does going multi-product allow you to unlock a net new user base that you weren't targeting before? So that was Stripe Connect was the other kind of early multi-product bet that really worked out for the company. And that was, hey, we've been…

AI assessment note: “And when Stripe was thinking about the second products, one of the like easy angles”

Q Maybe sort of on a, on a similar point, what's gotten vastly easier in the 18 months that you've been building the company from an enabling technology perspective?

A Code generation works super well now. So when we take these prompts to code, there used to be so many gotchas where the code wouldn't actually work, whether the API is not well supported or it makes a couple mistakes here and there. And now It's hard to break the system. It's hard to just put anything into that prompt and not have code that spit out that runs and does exactly what you want it to do. If I had the product in front of me, it would be hard for me to come up with an idea that wouldn't work in the system, which is really, really cool. And that was certainly not where we were at a year and a half ago, where if you weren't on a kind of a predefined list of things we knew very, very well, uh, it wouldn't work. So we used to, for example, have defeated a bunch of contexts of Here are all the possible workflows somebody might want to build and here's the code. Here's what it looks like. You might want to use this code as like a reference point. And then as long as what you're trying to do was somewhat similar to the workflows that we provided as context, it would work fairly reliably. But as soon as you went off the rails and you want to do something crazy creative, it would just fall over and it would just get stuck. And that doesn't happen anymore. Now you can be as creative as you want, touch as many applications as you want. Internet search capabilities built into the…

AI assessment note: “Code generation works super well now.”

Q What are some of the examples when you think about the products you've worked on of you could not have landed on that thing if you did not embed and go deep in that way with customers?

A Yeah, one of the most striking examples from Verkata was panic buttons. We didn't know if they were even necessary. You know, it was a category that was kind of controversial whether or not they even needed to build those. And I went on site to a customer that was a payday loan customer. I actually spend time talking to their cashiers that spend all day behind a layer of Bulletproof glass. Every single one of them had been held up at gunpoint at some point while working at this company. I asked them about, you know, their day and what we could do to make their day better. And I was thinking about this from their perspective of what new products could I build. And the thing they said to me was, the ATM is in the lobby on the other side of the Bulletproof glass. Is there anything I could do To move the ATM to be closer to the door so they don't have to spend so much time in the unsafe part outside the bulletproof glass because they're worried that something's going to happen to them when they walk out the door and they have to empty the ATM. That was their biggest fear was being in the lobby and having to cross this hallway. And that lived in their head as the most important thing that, that they wanted from us. And then we're having this conversation of whether or not you can carry around the panic button or if it should be mounted to the desk. It's like, of course you have to c…

AI assessment note: “one of the most striking examples from Verkata was panic buttons.”

Q And what was the original thing that they explained that they were up to?

A So they had been working on a school yearbook business. They'd been running that for about three or four years. It was built in Adobe Flash, if anyone remembers what that was. And they had built out a decent business. I think it did two or three million dollars in revenue. They'd really started to corner the yearbook business in Australia. But they had this bigger vision. It wasn't just yearbooks. They wanted to bring design to everyone. And it really fascinated me because I'm a graphic designer by background. I also have a computer science degree. That's how I ended up building digital products. And I'd always been really interested in creative tools, helping people unlock their innate creativity, which a lot of us don't realize we have. And I'd built a lot of tools over the previous 15 years that did that. Campbell was a really pointed expression of that. Being able to bring visual design to people who had never even thought about tackling it before was really compelling. And that's what Mel wanted to do. So we started exploring what that meant and Burrowing into some of the vision decks you'd put together, thinking about what product we wanted to create, and that's really where Canvas started to flourish.

AI assessment note: “It wasn't just yearbooks. They wanted to bring design to everyone.”

Q Were there other things like that that you figured out in watching and talking to those early customers that were trying out the product that were a big part of the, the early success?

A Definitely. We started seeing who Really got into the products. I mean, we couldn't launch the all singing, all, all dancing version of Canva on day one. You need to, you know, pace yourself. You got limited resources. You got limited time. So you need to put out a product that's polished enough that people feel like they can use it and trust it. You also need to get it out quick enough so that you're getting feedback and responding to it and helping you find your direction. Through some of those early user testing sessions, both the in-person ones and, and then the ones that we did online, we started to see that there was this rich vein of social media marketers who just got really excited about Canva. So this was 2013. Pinterest had come out like a year or two earlier. Instagram was just becoming popular. Twitter was a thing, but it wasn't particularly visual. More and more people were now adding images into their Twitter posts. And it was just the right moment where people were starting to having to scale their visual content needs. And there was this type of user who was helping people with their social media, helping businesses figure out their strategy, produce content that engage people. So these social media managers needed to create a lot of content. They couldn't afford to go and get someone to do it. And most of them were actually individuals. So they were running th…

AI assessment note: “we started to see that there was this rich vein of social media marketers”

Q What about maybe the inverse of that? Like, were there a few moments that were Particularly difficult or hard other than the normal trials and tribulations of, of making a startup work?

A In terms of the product, it's mostly been smooth sailing, like you iterate, you put stuff out, you see what works, you see what doesn't, you're kind of used to that. There was this one period where we decided to rewrite our entire editor code base, which was particularly trying. The reason was it took us like close to two years to do that. And in that time, we essentially launched nothing. We didn't put out any new functionality. We couldn't respond to customers with like, here's a improvement based on what you've said. It was really, really trying for us as a, as a team, as a product. So that was really hard. So we've kind of vowed never to do a huge rewrite like that ever again.

AI assessment note: “There was this one period where we decided to rewrite our entire editor code base”

Q So, you mentioned this a little bit, but when you reflect back on that sort of first chapter of MemSQL, What are the, the things, the most tangible things that you learned there, and the types of things that sort of are still part of the way that you think about building and running companies?

A Yeah, I think, um, I'll tell you a few things that I learned, and also some things I took for granted. Um, so, some of the most important things I learned, one, I think you have to be extremely paranoid when you're building software about quality, and What I mean is, it's actually like super, super hard to build a product that actually works and people actually use. It's pretty easy, and now I would say even like easier to build a prototype, but the craft of actually taking something from 95% to 99% or a hundred percent is very challenging and not something they teach you in school. Um, and there was one guy at MemSQL named Adam, uh, and he was a pretty senior database engineer from Microsoft, and Anytime someone broke a test or anytime a customer ran into an issue, he wouldn't brush it off. He would pay attention and he'd find the relevant engineer and kind of force them to pay attention to it. And I think being extremely paranoid and that level of diligent about quality is not only important, it's just existential. Um, and so I, that was one of the probably biggest learnings for me. Um, I remember when we were selling a big deal at Goldman, The managing director pulled me aside. I was like, 23 at the time, and I, you know, I was, I had no idea what, really what I was doing, and he was like, hey, we're about to make a really big investment in your software, and if it crashes, …

AI assessment note: “one, I think you have to be extremely paranoid when you're building software about quality”

Q Did you do that just by filing off all the rough edges or were there in those first six months, really important phase shifts that happened in the product that you were building toward?

A Yeah. So the first six months we built Very little interesting technology, and I remember talking to, I won't name any names, but, um, VCs and stuff, and they're like, hey, you know, what are you building here that's durable, and what, you know, what, what are you building, what's your moat, and, ah, what's gonna stop, um, people who are now writing AI code from just rebuilding brain trust, or how come customers aren't gonna build this internally, and I just didn't care, cuz I was talking to customers, and They didn't care, and so why would, why would that matter? Um, what started to happen really interestingly last summer is that Notion, who was way far ahead of everyone in terms of real adoption of their AI products, and really pushing the boundaries of the latest models, they had, and they also had more people working on AI, um, they were, like, searching for stuff and trying to dig through the logs that they had in Braintrust, In a fairly unique way. So normally when you're working with observability products, you try to do very structured queries like, you know, user ID equals Brett or whatever. Um, and in AI, primarily because there's so much text floating around one, you have these enormous rows. So every span in brain trust land, which is like a row of something that you'd log in brain trust, the average size is 50 kilobytes. In traditional observability, it's 900 bytes…

AI assessment note: “the first six months we built Very little interesting technology”

Q To wrap up, and it may have been somebody you already sort of talked about. When you think about getting a company in a product market fit and early company building, Who, who's taught you the most, and was there like a particular tangible thing that they imparted on you?

A Honestly, I think there's two people I'd point to, um, and these were the first two people that invested in BrainTrust and really helped us. The first is Alana, and I think that she grew up, um, learning a lot about sales from her dad and then worked in product, and I think that she's super technical, so if you're a nerd, you can, like, communicate with her easily, um, And it doesn't feel like you're talking to a, uh, someone who's too salesy or something, but she deeply understands the importance of getting the right people like customers and, um, candidates around a company to make them successful. And she has very high taste for those things as well. And I, I, I just don't think that comes naturally to a lot of the people that have the skills or gifts that would enable them to create a great product. And I think the meta point here is if you can create a great product or you're very technical or whatever, you need to like almost surrender or make yourself vulnerable to people that are wired a little bit differently and they are wired around people or wired around markets and sort of benefit from making them a really important part of your company. Like the way that she works with companies is so oriented around the people that she gets around the company early on. That is just a very unnatural thing for people, for, for especially people like myself who are super nerdy. So I…

AI assessment note: “Honestly, I think there's two people I'd point to”

Q Do you think in your experience, when a manager gives feedback like that about being more strategic, that there's a few things they're generally trying to communicate? Or is it truly like a long tail? It could be 60 different things that that manager is trying to communicate.

A It's probably a few things for the individual that they're giving that feedback to. So the problem is, if you're the operator hearing that, You're not sure what those things are. But for the manager saying it, yeah, I do think that it's a couple situations that have shown that manager that, hey, this person could be thinking more strategically. And so a couple examples of what it could be, you know, I see operators sometimes be too zoomed in to the project or the task in front of them without considering organizational context. So that could be an example of you're not really thinking Strategically, you're, you're focusing on the how of getting this exact thing done, but you're not thinking about how does this stack rank amongst other things that we're doing? How does this impact other things or how is it impacted by other things? So that's one way of, you know, what be strategic could mean. Another could be thinking more about what, like choosing what to do versus just the how. If you are used to something being fairly scoped and defined by the time it arrives at your desk, You're thinking about, well, how do I get this done? How do I bring this to fruition? Whereas the next level that your manager might be looking for is you doing the shaping. You saying we should do this, not that. And here's why. And here are the trade-offs. And here are the risks involved. And choosing wha…

AI assessment note: “It's probably a few things for the individual that they're giving that feedback to.”

Q So what, what did that look like for you when you think about your own arc of your career, and like the first couple things that you've done, and now the last couple things that you've done? Like, how has it become more aligned with sort of that set of ideas you were talking about?

A Yeah, so I'll give an example where I worked on this skill or on this weakness, I would say, until it was not a blocker for me, but then intentionally started choosing roles where this was not a core need. So I used to be pretty disorganized and bad about operational details. And early in my career, this was pretty prohibitive for me because I was in a brand management role. And had to manage multiple launches for multiple SKUs with different launch timelines, production timelines, et cetera. It's a physical product. And it was really overwhelming keeping track of all of it. I dropped a ton of balls and I realized that if I am to advance to the next level where, you know, as a manager, I might not have to manage all these details myself anymore. I'm never going to get there because I'm never going to get promoted if I'm so bad at managing all these different details. And so I put concerted effort into learning to become more organized, to become better at project management to a point where I could keep track of different projects and where they were and could communicate upwards and keep the appropriate parties aware of what was happening. But I knew that this was never going to be a strength of mine, that to this day, logistical details very much stress me out. I tried to outsource it as much as possible. I still dread doing things that require a lot of Logistical detail, esp…

AI assessment note: “I literally changed career paths after that role.”

Q What's the last thing that annoyed you that turned into something you put out on the world that was interesting?

A Everything, almost everything I write about, the root is something that annoys me, and then I turn it into something much more positive, because the frustration part isn't always, you know, isn't always the best angle, but one that is more literal is I did a newsletter article and then posted this on social as well about, no, I don't want to hop on a call, and so this was about how many of us default to live conversations when they don't need to be live conversations, and it actually wastes everyone's time, and how You know, if you're not sure how you want to write a message and you're not clear on your idea, I, as your colleague, do not want to be taxed listening to you talk, you know, meandering for 30 minutes as you figure something out in real time. Like, take five minutes, think about it, and then if you really can't come up with an answer, fine, let's hop on a call, but don't make that just your default. And there's obviously many good reasons to hop on a call. Brainstorming, you know, situations where showing your facial expressions or tone of voice matters, discussion, etc. In my experience, many of the day-to-day interactions we have aren't that. Like, it's a simple question or, you know, sharing information, and you can do that in writing in a much more scalable way that respects the other person's time. So that was an example of something where the beginning of that …

AI assessment note: “I did a newsletter article and then posted this on social as well”

Q So how did you go from this teenage Minecraft business to starting owner?

A When I started focusing full time on building games, which was what happened when I dropped out of high school halfway through 10th grade, it was first scaling the Minecraft servers up and then using that community of millions of players to Build my own mobile games. I started to feel very conflicted. There were certain things about that experience that I loved. It was so much fun day to day, and it was a great environment to learn software engineering and growth marketing in. But what I started to hate about it and hate about my life as I thought about my future was I felt when I looked forward three, five, 10 years of what my life would become focused in gaming, that it was basically scaling What I viewed as this negative impact because I was obsessed over how to get millions more players to ultimately waste time on my games so that I can make money. That's what you do as a gaming company. And that felt wrong to me. It, it didn't feel like something I wanted to spend my life doing, but I also felt kind of trapped because I didn't have a plan B. I was literally a 10th grade high school dropout. Didn't even finish 10th grade. And I knew there had to be some way to use that skill set that I built in Software engineering and growth marketing to actually help people, but I wouldn't know what that way would be until about a year later, I built the first version of Owner for my mom'…

AI assessment note: “I built the first version of Owner for my mom's dog grooming business”

Q So, as you sort of started to figure that out in month six and nine and 12, and this is all pre-pandemic, did it now start to feel like people were lining up at the door, or was it still a slow grind customer by customer?

A It felt a lot better than the cold outbound stuff. To me, it felt like people were lining up at the door, but I wouldn't truly know what that would feel like until a year and a half later, When we executed that post-pandemic pivot and added the online ordering module to our product. That's when things went hyperbolic. I thought it was great that we had a few dozen customers that had come to us from the inbound stuff, because somebody that had spent months grinding the outbound stuff, that was awesome. But what was really great was when we lost that online ordering product in May, we had hundreds of demo requests every week. We had so many demos that I had to create group demos to fit all the restaurant owners in that wanted to chat with me. Where I'd bring a group of three or four restaurant owners that had requested a demo, and I'd show them all the software together from, this was such a grindy period of the company, from like, seven a.m. Pacific, 10 eastern, to seven p.m. Pacific, I was in demos all fucking day that had booked inbound, and it was group demos, a lot of them. So three or four restaurant owners together would be seeing the software and then signing up. That was what real people lining up the door would feel like, and that's what real product market fit feels like. I had a very weak version of product market fit, if that. With the old dine-in focus website build…

AI assessment note: “To me, it felt like people were lining up at the door, but”

Q tried to sell to local restaurants and businesses that either got stuck and they themselves kind of got capped at X millions of revenue, or just the whole business was always upside down. What have you sort of figured out in maybe a more meta sense that might be useful to other people that are specifically thinking about other things that they want to do for this specific customer segment?

A To summarize my thinking on how to make the Very brutally difficult economics work of serving local business owners and restaurant owners. It comes down to making sure that the LTV to CAC ends up being very favorable, well over three. And the way you do that is both dropping CAC through finding resourceful, creative ways to distribute the product and maximizing LTV through delivering so much value in the product that you're able to charge a high price for it ultimately. We're doing both at Owner. On the dropping CAC, we've got not only this massive content marketing machine that is developing a large community of restaurant owners that trust us and are learning from all of the resources that we're putting out there for free, which then ends up making them want to become customers, but we've also got now our AI grader and AI website generator that makes it so that restaurant owners, in a matter of minutes and for free, Can start to experience the benefits of growing their sales through owner before they give us any money at all, which ends up giving us customer acquisition costs in the future that look more like Squarespace or Shopify with lifetime values that are even greater than toasts over time because the attach rate is so high once you earn the trust on free products. On the ensuring lifetime value is very high, that comes down to figuring out what the dollar ROI is on ado…

AI assessment note: “It comes down to making sure that the LTV to CAC ends up being very favorable”

Q So walk through what was the set of insights that you landed on before you actually built or shipped the first product?

A Yeah. So on the plan sponsor, the small business owner side, you hate wasting money, right? At least, at least I did at TaskRabbit. So if you're going to offer a benefit, you want people using it. So again, that participation rate, why are they not using it? I'm paying 20 grand a year for this. Nobody's using it. Nobody's getting the benefit. Nobody understands the benefit. So that was one. And then the other one was like, people need to understand that small businesses can afford a four or one K if it's done properly, just because you don't have assets doesn't mean they won't build over time. Right? Like that's the whole point. So, and then make it as easy as possible. So for us and ADP and Sequoia, like our payroll and our four one K weren't even integrated and it came from the same company. And that was just like mind blowing to me. Why am I validating Contributions after every pay run. Why, why am I doing this? That should all be handled in the data set in this product. Um, and it wasn't, and that's kind of the way it is even today with some of the larger legacy companies. They still haven't figured out that you need to have this seamless integration. The small business owner doesn't and isn't qualified to administer a for one K. Um, and, and part of our first product was building these. 360 degree integrations with forward thinking payroll companies like Gusto. And that wa…

AI assessment note: “So that was one. And then the other one was”

Q Then did you have a, uh, AUM style fee as well?

A Yeah. So early on, we didn't have any asset based fees whatsoever. So it was zero. That was really important to get to, but we were losing money, right? I had to pay the custodian. So that was really important to understand. What I didn't understand early on is that custodian, not only were they charging a very small asset-based fee at the time, but they're charging a transaction fee. So when you had certain things happen in a four one K you want to take a loan or a hardship withdrawal or a distribution of some sort. You got charged essentially a distribution fee. They mailed out a check, right? Like that cost them money. They charged us money. We had to charge money for that. The experience that really brought it home for me was actually a, an early participant was in a car crash or had a flat tire or something and needed money and they needed it immediately. And guideline was charging them, I think, a hundred dollars to get a distribution because that's kind of what we were getting charged. And that was really important for me to understand. So somebody is coming to guideline who they trusted to like save for retirement. Now they need help. And we're going to charge them a hundred dollars to get it. Uh, just felt really terrible, quite honestly. So we started charging a small asset-based fee on the entire platform to cover all transactions. So that's what we do today. We char…

AI assessment note: “So we started charging a small asset-based fee on the entire platform”

Q Did you figure out the integration insight before you started the company and raised money?

A I didn't. That came after, obviously I knew, I had known about this problem with ADP cause I was experiencing it myself at TaskRabbit, but I couldn't figure out the angle to make Gusto care or make my first payroll partner. Care that I was going to go do this. And eventually we figured that out. And that was really important to understand. But one of the things that I didn't realize until after the fact, and Gusto actually told us this. So payroll in the United States is incredibly fragmented, right? They have high churn. It's 25, 35% on the higher end of their annual logo churn. So when you take that into account and you attach a four one K or an integrated four one K solution to the payroll product, it cuts it in half. Right. So their LTV doubles, which is fantastic for them. Right. So now I'm starting to think this is why they're going to care because I'm going to cut their churn in half when they attach a integrated for one K and now I can start paying them as well. Right. Like the long tail of it with that integration, it gives me operational scale. I can actually start giving them money. Now I'm giving them, I'm giving them money for essentially maintaining an API. Right. That's a hundred percent margin business for them. So that makes it really exciting. Doubles the LTV and I pay them. Now I'm starting to understand like, hey, this go to market motion has legs. Now I hav…

AI assessment note: “I didn't. That came after, obviously I knew, I had known about this problem”

Q So then maybe you could talk a little bit more about those few weeks. So you had the lunch and you kind of explored a bunch of ideas and said, okay, that's interesting. You were then whiteboarding in those, like, what, what did you actually do to go from the higher order insight to something you would actually ship to someone?

A We worked out kind of the early object model and you know, what we wanted to be able to keep track of. How we wanted to communicate with people and when the important moments were, you know, in a, in a mobile app user journey to be able to create that strong early connection and then ongoing engagement with people. And interestingly enough, the early version of app boy actually was a lot more opinionated and a lot more rigid. We built a number of game mechanics. We built out a user profile. I had cross channel communication from the very beginning because, you know, when you try to solve a more Fundamental problem like that. You realize that actually, unlike a lot of companies that are built to just be, oh, we're going to be a push notification service, or we're going to do email marketing. Like they all start on a single channel. We were just trying to solve a business problem. And so we knew that we needed to be cross channel from the very beginning. So we had four different message types. We had push notifications, email. We had a newsfeed before there was a Facebook newsfeed. I used to call it a mini blog inside your app, but it was it's proper now and was the, the hat boy newsfeed. And then we had our slide up message. We had a user profile. The early version of Appboy actually let the user interact with the profile itself because it was meant to be like a profiling system…

AI assessment note: “We worked out kind of the early object model and you know, what we wanted”

Q Kevin, maybe you could talk a little bit about what were you doing before you got involved with Braze and like how did your app boy at the time and what caused you to join? What was going on at the time?

A I was working at Accenture doing consulting in the energy trading industry for a number of years prior to Braze. It was actually a fascinating industry. I am like as far as one can possibly be from it right now, but I sometimes still think about how it was really interesting, like You know, you can go and trade like a strong wind over Texas. This is a financial instrument that exists out there. And from that experience, I got the chance to work very closely with a very, very old school legacy enterprise software that was being used in ways that were wildly productive for these energy companies. And that sort of planted the first seed in my head of, I mean, you know, kids don't grow up thinking, man, I really want to do like enterprise SaaS one day. But from working with this technology, seeing how successful it was, um, I definitely got that idea that there was a huge amount of promise. And then that combined with observing from, you know, a completely different place, a completely different state from where Bill and John were, the rise of mobile, I was very, very keen on figuring out a way to get to a place where I could both sort of pursue the fact that I saw a lot of opportunity in enterprise SaaS, and also make sure that I was sort of catching these early side of Of the mobile wave that was blowing up. So Bill and I actually know one another from college. We were fraternity…

AI assessment note: “I was working at Accenture doing consulting in the energy trading industry for a number of years”

Q I want to wrap up, uh, by asking the question that we always do, which is basically who in your career has had the biggest outsized impact?

A This guy named Nick Merrill, who was, I worked for Hillary Clinton for almost four years, um, the years of like, 2013 to through the campaign in 2016. And he was my mentor and manager actually throughout that entire period of time. He has probably had more impact and influence on me than almost anyone except my parents, uh, because it was a very formative stage of my life. It was like the ages of 19 to 22 or something. And, you know, he, I think he in many ways taught me how to be an adult. He taught me how to contribute. He taught me how to work in a professional environment and make an impact, and I learned a lot from his example. And, and more specifically, like, He was always, you know, on the Hillary Clinton campaign in particular, a lot of ups and downs, a lot of crazy things happening every day, and he was able to be extraordinarily level-headed through all of that, and taught me a lot about how to do that in my current circumstances, which are frankly way less stress and way lower stakes than a presidential campaign.

AI assessment note: “This guy named Nick Merrill, who was, I worked for Hillary Clinton”

Q One of the passing comments you made a little while ago was You invested a lot in brand early on. What does it actually mean to invest in brand early on?

A So first of all, I think we benefit from the fact that the company's name is Clay. And so that lends itself to many things that make it much easier to, to build a brand around, right? And so what does this mean tactically? Well, tactically it means we hired a claymation artist who we worked with part-time for many, many years and is now full-time at Clay. And we have a full-time claymation artist who's building imagery and, and art with Clay. Uh, online, right? But we also have a lot happening in real life as well. And so we try to bring a lot of this brand creativity in real life as well, because we, we are trying to stand out from the normal kind of tech audiences, right? So for Dreamforce, as an example, our team put on a spa day and which is pretty atypical for a SaaS event at Dreamforce. And the intention was, how can you like relax and wind up for a really depleting few days at conference? And so how can you bring this energy and creativity in brand, both in your digital presence and in your in real life presence? And that is something we invest a lot in. And there are several people at the company just focused on that. We think it pays long-term dividends. It's not a short-term investment by any means. Last point on this, on the brand thing, is when you look at other B to B software, no one invests in it. And so when you have something that no one invests in, And everyth…

AI assessment note: “tactically it means we hired a claymation artist who we worked with”

Q What else were you doing in early customer reverse demos?

A Well, let's do one together right now. So let's say you signed up For the waitlist, I would click a checkbox in Clay. That checkbox would trigger a workflow in Clay that would send you an email. That email would say, hey, book some time with me and actually come prepared for this conversation with a data set you want enriched or a problem you want solved in this. You would show up to the call, and ideally you would have a CSV or some data you want enriched. Alternatively, you might not, but we'd spend the 1:05 minutes coming up with something. We'd come up with a problem for you. So that, I'll just, let's, let's spitball an example. So you could say, you know, to pull from our earlier one about Kansas City, it's like, okay, let me get List of all the plumbers in Kansas City. I want to know what year they were founded. I want to know and that I want that because I only want to sell into, you know, plumbers who are founded more recently because they'll be more amenable to buying software than much older plumbers. I want to know which ones are well reviewed. I want to get the owner of the plumbing company and I want to get their content information. Remember, my goal is to blow their mind, right? So my goal is to solve that problem in 30 minutes. And I think that is a bar that most software companies cannot achieve. Can you solve someone's entire problem in 30 minutes? And have th…

AI assessment note: “Well, let's do one together right now. So let's say you signed up”

Q You mentioned that one of the unlocks was positioning, was repositioning the product for enterprise and landing with sort of the insertion point, which is enrichment. How are you thinking about then going from landing in enterprise with enrichment to other use cases to ultimately sort of expand?

A I would say for us, that model is So success, basically customer success is almost as important, if not more important than the sale itself, because we're usage based and because we have a very methodical plan led by Jess on our team to start with enrichment, make sure the data quality is high, and then build use cases on top of that, on that strong data foundation, each of which, by the way, uses credits. And so that could mean keeping your CRM enriched, but that could also mean like using clay to automate outbound at scale, Automate your inbound at scale, like Anthropic used us to automate all their inbound at scale and triple their enrichment rates on that and finding way more leads through that. Verkata was using us to come up with new growth ideas to personalize web pages at scale for ABM efforts, you know, doubling their ad targeting rates. And so basically it's like, you have a good data foundation and it's like, how can we work with you to come up with growth ideas across outbound and inbound and you're in and expanding your existing customers. And we are partnering with you to grow your business. The consequences of that is they grow their business. They also use more credits, which also leads to a bigger contract, and so it's a win-win across the board.

AI assessment note: “start with enrichment, make sure the data quality is high, and then build use cases”

Q And did you go about them in any particularly interesting ways?

A So I think the honest answer is that now we go about them, I think, in particularly interesting ways, and we can talk about those. At the time, it was more brute force, and it was more just regularly putting out the content and diligently doing that with some discipline. And getting other people to do it as well. And these would be the, the agency owners or customers and things like that. Now we have turned that into a machine that I think is actually pretty interesting. And what I mean by that is I think that so much of our business is a loop and there are so many feedback loops and we have now tried to create feedback loops in many parts of the business. And so from a content perspective, it's like, as an example, we have, you know, 50 different clay clubs hosting community events all around the world from Bangalore to Sydney to Toronto. And Things that they, these amazing people do is they like share play tables and there's content that comes from that. We take that content and we can like put that in a LinkedIn post and we can combine those LinkedIn posts and put them into a blog post and combine the blog posts and put them into a guide. And you can have this loop where you can keep repurposing the content that I think is super powerful and can compound over time. Our growth marketing team led by Bruno has done an amazing job at enabling the rest of our community To, uh, to…

AI assessment note: “At the time, it was more brute force... Now we have turned that into a machine”

Q Whenever you think about the moment the company was started, what was like the story, the two years before that, what was going on?

A I had been working in data for a very long time. I, you know, my, my core skillset over the course of my career has been quantitative. I had practiced that in a bunch of different ways. Like I had been at Deloitte Consulting and did large IT projects and data stuff as a part of that. And Went to the startup side of the house and, uh, ran data team at Squarespace and very nascent data team. And then I, I joined an analytics tech vendor called RJ metrics. And I was an early user at Squarespace of this company, RJ metrics. And, um, we were supposed to be what Looker became. Uh, the thing that RJ was never, and I don't think would have ever been able to, uh, anticipate was The cloud, the rise of the cloud for data specifically. And, uh, so I remember experiencing this in, in 2014 or 20 15. I got to use a product called Amazon Redshift for the first time. And as a, as a long time data practitioner, I was just very immediately within writing a couple of queries. I was like, oh, this is going to change everything about my profession.

AI assessment note: “I joined an analytics tech vendor called RJ metrics... I got to use a product called Amazon Redshift”