The Exchanges

Q is going to be at, you know, South by Southwest. And, you know, so I think that's, I, I do think that having that magical sort of experience is cool. If you were building something like this, and I mean, you built the product, so I'm sure you've thought it, thought about this. How would you actually get to, like, how would you get awareness and in something like this?

A Yeah. I mean, I think, you know, conferences are, are a historically fantastic place to launch products. South by Southwest itself is like known to you. I guess it's not anymore, but it used to be this place where like everyone anticipated the, the next social app to launch. And so, um, it's one of these things where it's like, it has a strong network effect, especially with these social features, which is like, You host an event at a South by Southwest or a Tech Week or something like that. These events, if you're in their distribution system, get tons and tons of RSVPs. We hosted one for Tech Week, 800 RSVPs. 800 people all download your app. Conferences are probably no more than like 20,000 people in the largest sense. So once you have that 800 people, you just do the next conference that these people are going to. That's probably how I do it. Obviously, you know, you're targeting Particular niches. So you may want to start with the crypto community or something, because these people tend to like hop from one conference to another pretty consistently. Um, you may want us to target like the tech community or another specific group of people that tends to show up consistently at these conferences. But, um, yeah, I think that's how it worked.

AI assessment note: “conferences are, are a historically fantastic place to launch products.”

Q All right. Well, what's on your mind? What's idea number one?

A Okay. So I guess idea number one is, goes to this, uh, crappy startup idea that every kid in college has coming out of college. They're like, and the first idea they come up with is what? It's an app to help you hang out with people when you're bored. And all of these apps have failed. Like all of them have failed. Like they just don't work. There's this negative selection bias where it's like the people who actually want to hang out are not the people you want to hang out with and like all of this stuff. But before we landed on the idea that I'm working on right now in stealth, we actually pursued something that is an iteration of this idea that it will actually work really, really well. Uh, and the idea is that instead of focusing on, uh, nerdy loners in big cities that want to hang out and weren't invited to parties as your target audience, you focus on, um, conference attendees, conference attendees. And the idea is that if you've ever been to a conference, whether it's like tech weeks and crypto conference, whatever it is, you know, most of the action is not actually the main conference events. All of the action is the side events. And actually maybe the more of the action is in the, like the, the private dinners and stuff like that, but really the side events are where the action is. That's where all the cool people are hanging out. That's, they're more interesting. Uh, t…

AI assessment note: “idea number one is... instead of focusing on nerdy loners... you focus on conference attendees”

Q you know, you could get to a situation where you're doing one to three million ARR or something like that. And you go to, um, a clear bit or someone like that and you sell the business. What do you think? You know, what are, what sort of multiples? You know, you've worked in the Google M&A world. Like, what sort of multiples are, are some of these businesses getting?

A Not much. So, like, it depends on the approach. Like, the Clearbit acquisition, Clearbit was acquired by HubSpot. And the rumor is that it was not the most amazing price because HubSpot didn't value the existing business. HubSpot is not in a, in a data enrichment business. They bought it so that they can have data enrichment out of the box in their own CRM and have this kind of competitive moat based on that. So they bought it for the capabilities and they bought it for the, for the data, not the business. When you are selling a company, like you need to know what the acquirer wants in your company. The best deals are ones where they're buying the whole business because that means you're getting traditional, like whatever the relevant multiple is based on public comps, other acquisitions and other kind of fundraisers. Um, but if they're not building, buying it based on the business, Then it's kind of like, I don't know, it's totally random sometimes.

AI assessment note: “Not much. So, like, it depends on the approach.”

Q Cool. All right, Brad, what's, uh, what's idea number two?

A Um, all right, so I have two, the next two ideas are both dating related because I'm hopelessly single in New York. Um, and I find that people just kind of talk about, don't you feel like when you're hanging out with people in a certain city, they kind of talk about whatever the, whatever the thing of the city seems to be. So it's like you hang out with people in San Francisco, they're only talking about the latest AI models and stuff like that. You hang out with people in New York where dating is like a sport, basically conversations naturally go back to dating. I have a couple ideas that I think would be super, super killer. The first one is basically a vertical SAS for matchmakers. So the main point is that, like, there are people in every community, and this is like a thousand-year-old job, who play this role of matchmaker, like, particularly in, like, like, we're both Jewish, the Jewish matchmakers, Indian matchmakers, like, you know, any sort of religious or ethnic community, there are strong matchmakers, but what I also find interesting is that, like, uh, there are other communities, uh, and you're the community guys who, I want to hear your thoughts on this, but, like, There are other communities that have emerged or have their own identities that also should or already have matchmaking makers within it. So rock climbing, like you would think that rock climbers would ge…

AI assessment note: “The first one is basically a vertical SAS for matchmakers.”

Q I think, uh, this works. I, you know, I think this works really well for certain groups and certain, um, you know, very specific niches. Um, what do you think are two, three, four, five specific groups that would use something like this?

A Well, I think what's interesting is like the data, the data companies are not incentivized to go after a lot of, a lot of niches, right? So if you wanted to start like, um, you know, a Sri Lankan real estate CRM or marketing automation platform, and you needed to have a lot of information about, you know, the building location and like the number of rooms or all that stuff, like you would need to build that data set yourself or hope that users input it. And the magic of this is that Because you're using LLMs, because you're kind of crawling the web a little bit, or you're finding data sets online, or in other places that you can point LLMs to, is that you can do, you can target almost any niche, um, much better than these kind of like incumbents can. So yeah, Sri Lankan real estate, like, I don't know. I don't know why I thought of that.

AI assessment note: “So if you wanted to start like, um, you know, a Sri Lankan real estate CRM”