NY Launch Pod: Welcome to the New York Launch Pod, the New York Press Club award-winning podcast on the most interesting new startups, businesses, and openings in the New York City area. I’m your host and New York attorney, Hal Coopersmith. In this episode, we are speaking all about AI. You may have heard about ChatGPT, our Guest Drew Fabrikant has come up with Scout an AI platform that started out with real estate agents but has become a lot more. But before we go to the episode, we have a sponsor RezCue, New York State’s premier residential rental compliance platform for landlords, property managers, and even real estate agents. Rental laws in New York City are difficult to manage and RezCue helps you follow the law. If you are a landlord who wants to keep up with inflation, you need RezCue. For example, you may not be able to increase your rent by the amount you thought RezCue helps solve that problem and a whole lot more. Go to rezcueme.com and enter in some simple information and rescue will take care of the rest. That’s rezcue me.com or R E Z C U E M E.com. And with that, let’s go to the interview. So what’s wrong with tipping?
NY Launch Pod: So what is Scout?
Drew Fabrikant: Scout is a platform that helps people get in touch with their ideal customers 10 times faster using artificial intelligence and data.
NY Launch Pod: Well, you just said a lot there. Can you explain it to me like, I have no idea what’s going on.
Drew Fabrikant: So what Scout helps people do is it helps them find their ideal customer. It then helps them figure out what to say to them, and then it automates the actual outreach. So it’s really kind of like a Swiss Army knife and you can use it for whatever you want, but most people use us right now to help find their ideal customer and then figure out what to say to them and then reach out to their email.
NY Launch Pod: Is there a particular business that you focus on for an ideal customer?
Drew Fabrikant: We do. We work with about 95% residential real estate agents and brokers right now.
NY Launch Pod: And how did you get into this area?
Drew Fabrikant: Six years ago, we built a lead generation tool for residential real estate agents, and we were helping them acquire buyers and sellers, and then we would use performance data to send that lead to a residential real estate agent. And what we realized was that the, the biggest problem in residential real estate wasn’t exactly getting the leads, but it was helping the real estate agent really perform at a much higher level, but also helping them become more informed, right? Take that knowledge set that they had about a particular person or home or neighborhood, and be able to apply that on a massive scale. There are tens of thousands of people that live in a particular area. A real estate agent has to be very knowledgeable about that area, but also those 10,000 homes. And what we realized was there was a data play there where we could take that data and we could actually help that real estate agent scale that knowledge. And that’s kind of how we started down this path was really just by helping the agent to become more knowledgeable.
NY Launch Pod: And how does the platform work Right now? You’re focusing on real estate agents finding their ideal customer. How does that actually work?
Drew Fabrikant: So the first thing that we do is we use predictive data analytics. So we have a huge database of hundreds of millions of Americans and all of the homes around the country. We know bed square footage. We know when they were purchased, what the appreciation of the home is. we take all that information and then we
NY Launch Pod: Nationwide? All the homes in the United States?
Drew Fabrikant: All of the homes in the United States of America. Yeah.
NY Launch Pod: And where does that exist? Is that on a local level or that’s just someone knows something about my house?
Drew Fabrikant: Oh, well it comes from a bunch of different places. It comes from the local level, but then we have a lot of other data sets that we integrate. So it can come from MLS data, it can come from self-reported data, it can come from Department of Finance and we don’t just stop there at residential real estate. We also have data that we acquire through other means automobile data as well. So we take all of this data , hundreds of millions of rows, and then we have about 600 data points on each one. That allows us to create ideal customer profiles. So we can determine, well, maybe somebody’s a prospective mover, maybe, they fit the age range, maybe they fit the family size, there’s more people in the household than they have bedrooms, things like distressed assets. So we have access to all that information and then what we’ll do is we will boil down that list and we’ll provide lists of contacts that would be suggested to reach out to. So essentially scoring an entire neighborhood for who is the most likely mover.
NY Launch Pod: And how are you getting agents to use this platform?
Drew Fabrikant: Agents need help, right? They need a ton of help. They need to save time. Our value proposition to them is, you can describe who your ideal customer is, we can actually find them for you. So if you tell us what you’re looking for, we have the data to do it. We have the contact information, we have everything that they need. If they have the contact information, we can help them score who is the most likely consumer or the ideal consumer for that. So what we’ll do is, we’ll tell real estate agents about this, how we can help them save time, how we can help them increase their business and automate the entire process. We have a number of communities that we do it through built on Facebook, LinkedIn, and also just good old-fashioned networking.
NY Launch Pod: And these are people reaching out to purchasers of property or sellers of property?
Drew Fabrikant: It can be either or. You know, we have mostly sellers because that’s where the data is the strongest. It’s kind of harder to grab renter data, it’s more ephemeral in nature, but for the most part we’re able to identify likely sellers and then those people obviously end up becoming buyers after they’ve sold their homes.
NY Launch Pod: About how many customers do you have right now?
Drew Fabrikant: Oh man. So when we opened up the wait list for this, we probably had two to 3000 people on our wait list within the first three months. We’ve launched our beta just a couple of months ago and have on boarded about 170. We’ve got a couple of agreements with call them, national or regional brokers who have two 3000 real estate agents who are rolling out to right now. So, we’re growing pretty quickly.
NY Launch Pod: And of these people in your beta test, how have they seen their revenues grow?
Drew Fabrikant: 95 x r o I plus
NY Launch Pod: Sounds like a good investment in 95 x.
Drew Fabrikant: It’s a pretty good investment when you’re selling something like residential real estate, it’s a pretty big windfall at the closing table and we’ve had agents sign up in day one, they’ve gotten customers, so we’ve executed outreach for them and the agent gets an inbound, Hey, this is so amazing. How did you know, like all this information about my home? I was actually just thinking of selling, can we schedule a call? Can you come by; can you let me know more information? So some agents have actually landed listing agreements day one of campaign one. So like 90 days later they’re realizing actualizing, you know, 60, 70, $80,000 depending on that home value. And, and at that point, they sign up for three years.
NY Launch Pod: And how do agents reach out to owners with the data?
Drew Fabrikant: So that’s where GPT comes into play. So everybody knows about open AI these days and it basically writes your outreach for you. The problem with that is that it’s not very informed about the specifics or kind of the context in which you’re using this data. So what we’ve done is we’ve built a bunch of AI models that get fed into, into GPT and we write the outreach for the actual real estate agent. And it’s a combination of kind of knowing what the consumer, the recipient wants to hear, plus some data feedback loops. We’re able to actually see the response rates so we can tailor our language for the outbound. So for the most part our software can speak real estate agent almost better than the real estate agent can.
NY Launch Pod: So it’s reaching out by email?
Drew Fabrikant: Yeah, that’s the first channel that we’re using, email automation and obviously we’ll be able to do this through SMS or LinkedIn. We actually have some integrations with robots that will pick up a ballpoint fan and they’ll write an outbound, uh, postcard to somebody. But we’re starting with email.
NY Launch Pod: I was wondering if there was going to be mail involved because you actually know the person’s address.
Drew Fabrikant: Yeah absolutely. There’s still nothing like a handwritten card.
NY Launch Pod: So one of the things that I think about when you talk about AI and all the things that you’re doing and all these integrations and how you know about every single house in the country is it’s a little bit scary. Should people be scared?
Drew Fabrikant: I think no more scared than they are of their information kind of already being out there being targeted by advertisements that are irrelevant. I would say they should probably be happy that they’re being targeted with relevant information. I kind of dread going to the mailbox these days. I weighed it the other day, I had something like 18 pounds of junk mail that literally just went straight into the recycling bin and when you think about, you know, how irrelevant that stuff is and the toll it’s taking on the environment, just from that perspective alone, when somebody actually sends me something that is relevant to me, it kind of makes me, I guess smile a little bit that they did their research.
NY Launch Pod: What happens when every realtor starts using your platform and everyone is relevant?
Drew Fabrikant: Uh, hyper saturation, then we kind of become snail mail and everybody dreads getting a hyper personalized inbound. But we actually take a lot of precaution against that. So we implemented limited exclusivity in the platform. We implemented a batching and throttling system that actually limits the number of outbounds that any individual can actually send. So we actually do our best to make sure that we’re not saturating the market or hyper saturating the market or we’re kind of letting somebody get over their skis
NY Launch Pod: Before that. What is the ultimate goal and success look like for Scout?
Drew Fabrikant: Well, the world is changing very, very quickly. I think in no less than six to eight months, you and I are probably going to be having email correspondences with each other where our emails will then brief us on what happened. The technology that we’re building around it’s going to do for the world. What I think Google initially did and when Google came out, nobody ever had the excuse to say, I don’t know anymore. Great. What GPT is now doing is it’s eliminating the excuse to say, I don’t have the time. And when I think about that, it’s going to make everybody incredibly more productive. And I think that Scout will be able to sit at the center of data, but also context and workflow automation. So the actual delivery of that content. The internet changed a lot over the last decade. It used to be a place where you could get just data. Fast forward to the last couple years, you have to contextualize that data. What Scout is doing is actually automating the contextualization, but also the delivery. So how do you have very personalized conversations with people that you either know, limited information about or nothing about in a very personalized way. That’s really what I hope that Scout can do for everybody.
NY Launch Pod: Well that is a wonderful note to end things on. Drew Fabrikant, thank you for stepping on to the New York Launch Pod and sharing your time with us. How do people find out more about you and Scout?
Drew Fabrikant: You can look me up. I am on LinkedIn, Drew Fabrikant. You can look up Scout www.trustscout.com.
NY Launch Pod: And if you want to learn more about the New York Launch Pod, you can follow us on social media @nylaunchpod, or visit nylaunchpod.com for transcripts of every episode, including this one. And if you’re a super fan, Drew, are you a super fan of the New York Launch pod?
Drew Fabrikant: I’m the biggest fan.
NY Launch Pod: If you are the biggest fan like Drew, or even if you’re not, please leave a review on Apple Podcast and is greatly appreciated and does help people discover the show.
