The Exchanges

Q here in a second, but I want to fast forward to today for a second. Yeah. People that are listening right now going, I want this thing. How cheap is it to get started? I assume you have a free plan and if that confirm if that's true or not. And then secondly, of your paying customers, what's the average customer paying per year to use this technology today? Yeah.

A Uh, so we have a startup program for small companies. We just view the product for free. Like we don't try to monetize at the low end of the market. Um, because that's just, you know, we're nickel and diming. We want to align sort of our price point with a growing company that's seeing value. And that's where we sort of start our pricing. Um, our average ACV is, is, you know, at the, at the, you know, two segments that put the enterprise segment aside, but at the sort of mid market commercial segment, it's about 10, 15,000 dollars. Um, so So that's, that's the sort of average amount customers are paying us there. At the high end of the market, this goes well. Yeah, per year. Yeah, per year. At the high end of the market, this goes well into the few 100,000. Um, but that's, you know, where, you know, there's millions of users and enterprise customers.

AI assessment note: “at the sort of mid market commercial segment, it's about 10, 15,000 dollars.”

Q Wait, wait, against how many downloads? I want to get the conversion rate of activated. So how many total downloads? Okay.

A Uh, so, uh, well, there's, oh, against, I think we had about a hundred, so about 20% of the people that have, like, you know, signed up with GitHub, set up trials, et cetera, had, you know, set up accounts. Yeah, super good early on. Um, and there's just, like, highly targeted, right? Like, five very specific keywords. It's not, like, we're not pretending that that's scaled. Um, but, Of those 20 customers, they had done already 20,000 onboardings across them. And I went and looked at what we had been able to observe in that. And there were hundreds of thousands of mapping decisions that we had tracked and hundreds of thousands of data correction decisions across these customers. And I had this like light bulb moment. I like went, when I tried to convince my co-founder to join me, I was like, this is the Tesla opportunity of data. At no point in history has an ETL product had this level of volume of access to subject matter experts.

AI assessment note: “against, I think we had about a hundred, so about 20% of the people”

Q is under eight million and a hundred million in funding. How do you, as a founder, I think they'll agree with you. Like it's good to have a war chest right now in this economy, but also like this is expensive for me from a dilution perspective, unless you're just really good at getting super high valuations because the story you're telling, but how do you think about that balance?

A I think it's a massive market, and I think the willingness to sort of accept capital has to, has to come alongside with the size of the market. This is something that we believe is one of the largest addressable markets in the world. Every single company has to exchange data, and this doesn't matter if you're applying for a bank loan, you're a home builder placing orders at Home Depot, or you're a SaaS company. Everybody has to exchange data because that's just how business works now. So when we look at this sort of market opportunity for us, there's no Back pressure saying, Hey, you're not going to be able to fill these shoes. Right. And then the question just becomes how quickly I think in a different market where you're, where your addressable market is, is lower. There's a lot of discipline that should be exerted and thinking about the capital.

AI assessment note: “willingness to sort of accept capital has to, has to come alongside with the size”

Q What are those? What are those? What's one, two, three.

A So oftentimes with our customers, there's a starting use case. That's really simple. It's we need an import contacts button in our application or something like that. Import inventory, import something, right? And then there's more places in that product where they may want to import. So that's an opportunity to expand across there, but almost every SAS company starts opening up an enterprise motion and they start dedicating months to onboarding these customers. And that process oftentimes has 5000 plus hours of services To go through that customer's data, get into the system. So that's where we are able to sort of have both the like PLG sort of button in your application and an expansion motion as you start opening up these enterprise deals. And that is, allows us to have those conversations to track with their business model and make sure that we're sort of serving additional use cases across the org. With the rollout of what we're codenaming X here is a preview of what's coming in the next few weeks. We're actually taking all of the fundamental building blocks that has enabled these two Successful products that our customers use and opening them up to our customers to build whatever they want on top of that. So all of the core APIs, all of the training engines, yours as building blocks. This will open up another set of use cases where customers oftentimes don't have, their u…

AI assessment note: “So oftentimes with our customers, there's a starting use case... And then... With the rollout”

Q Okay, okay. So that's like sort of a six to ten million dollar post-money valuation way back then? Yeah. Okay. And then what did you do?

A Then we did a, we grew for about seven months. Uh, we got preempted, uh, did a seven, six, 7.6 seed with two Sigma. Um, then we got preempted about seven months later again. That was entering twenty-twenty. Yep. Uh, entering the pandemic, uh, new territory. Got preempted again, um, in later that year for our series A, which turned into a thirty five million dollar series A, uh, led by scale ventures. Um, and like, but because both of these are preemptive, we, you know, amassed capital, um, in a way that like gave us an incredible amount of runway. Um, and we, you know, our focus was not to try and burn that capital as quickly as we could. Focus was to make sure that we, you know, had plenty of runway. Not an opportunity to innovate as, as much as we needed to while creating a category. And this is maybe the one thing that I think gets lost in on a, on a lot of sort of business models is category creation is incredibly expensive because unlike, you know, innovating in a, with a new CRM where you can, all of your sort of education, your customers is clearly done and you get to be better, right? You get to differentiate yourself. Telling people like, Hey, this is something that you've exerted services on our spreadsheet templates too far before. And there's now a product with this, you know, the alternative flat file is not another product. It's not an ETL system. It's something y…

AI assessment note: “we grew for about seven months. Uh, we got preempted, uh, did a seven, six, 7.6 seed”

Q Yep. This is amazing. Okay, so again, I don't want to bury the lead here. Can we take 500 customers times 15,000 minimum ACV? That would put you guys north of eight million in ARR today, right?

A Um, definitely putting me on the spot on a revenue metric. Um, so we, we grew, our first year we grew from, uh, zero to a million, um, which is just incredible journey. Um, then we went from a million, uh, uh, 2019, zero to a million. Um, the company starts early 2019, 20, 20, uh, yeah, 20. Then we went a million, uh, no, we're actually like, we're, we're a year off here. Uh, so 20, 20, zero to a million, um, 2019, uh, Sorry, 2021 last year, a million to just shy of four. And this year we're shooting for a two to three X. So tracking in that range, I'm not gonna be specific about where we're at right now, but you're, you're, you're thinking about it, right?

AI assessment note: “So tracking in that range, I'm not gonna be specific about where we're at”

Q Fair enough. All right. That's the book. Number two, is there a founder you're following or studying? Just one you really respect.

A I think right now there's the, the founders that are most interesting to me are founders that have been through a number of different market conditions and have, have figured out the sort of the balances of each one of those, uh, sort of eras for their, for their business. Because in a high industry of a bull market, you do need to think about the success of your business in terms of top line growth and, and more of a bear market. You have to shift that. And that's a complete sort of mental model shift. Um, so I think there's a couple of companies that have done that well. I think we saw DocuSign go through a number of eras as a company. Um, we've, we've seen a, some of the more sort of mature growth companies have been able to go through a lot of that. So I think the founders I'm sort of paying attention to and are my advisors fit in that category.

AI assessment note: “the founders that are most interesting to me are founders that have been through”