141 Marketing With Quality Customer Data - Ed Carey Nov 30 2022

Greg Bray: [00:00:00] Hello everybody, and welcome to today's episode of The Home Builder Digital Marketing Podcast. I'm Greg Bray with Blue Tangerine.

Kevin Weitzel: And I'm Kevin Weitzel with OutHouse.

Greg Bray: And we are excited today to have joining us, Ed Carey. Ed is the founder and CEO of Audience Town. Welcome, Ed. Thanks for being with us.

Ed Carey: Thanks, Greg. Kevin. Fun to be here.

Greg Bray: Well, Ed, let's start off by just helping people get to know you a little bit. Tell us a little bit about yourself and your background.

Ed Carey: Sure thing. Well, I am talking to you and your audience today from suburban New Jersey, outside of New York City. Grew [00:01:00] up here in the northeast down on the uh, New Jersey Shore, which is a different Jersey Shore than the one on television. Because everybody wants to know if that's how I grew up, and it was nothing like that, but it was in that vicinity. And then lived in New York City for many, many years working in digital media startups.

I went to grad school there, met my wife there, and then moved out to New Jersey with my family many years ago, and here I am at the offices of Audience Town in suburban New Jersey, and excited to be here to talk with you guys. Audience town has been around for, we're coming up on a fourth-year birthday pretty soon. December. Yeah. That's a four-year birthday. So, you know, it feels two or three times that length of time, but it's been four years, and here we are.

Kevin Weitzel: Well, before we jump into Audience Town, I need to know a little bit about you. Just something odd, peculiar, personal that people will learn about you on our podcast.

Ed Carey: Okay. Let me see. Odd. Plenty of odd things. I have two different colored eyes, which is interesting. So, your podcast listeners cannot see that. It's one of [00:02:00] those like unusual things that people recognize sometimes.

Kevin Weitzel: Like David Bowie. Nice.

Ed Carey: Not as stark, but as odd for people who look at me. So, that's sort of a startling thing about me. What else about me? I, you know, it's funny, I guess I'm a founder of a sort of technology company, but I was also an English literature major, and really didn't get into software and data and all the things that this company does until I was much older. I really grew up more of a bookworm, more of someone who really appreciated the humanities and yet here I am a founder and CEO of a software company. So, I think that's always funny how that happens.

Kevin Weitzel: Nice.

Greg Bray: Let's explain Audience Town first Ed, and then we can backtrack a little bit into how you specifically decided to focus kind of in the real estate piece of that. So, why don't you tell us just a little bit about the company and what you guys do?

Ed Carey: Yeah, sure thing. For many years of my career had worked in digital media and advertising technology. Again, somehow made that my career, despite being an English literature major and had been working [00:03:00] inside of cool startups and getting to see how startups get built and grow. Working with major marketing brands and major online digital publishing companies on software and automation and all the things that have changed and automated uh, many industries.

I always thought to myself along the way, Hey, you know, maybe one day I could start a company. Seems fun to be a founder. There seemed to be a lot of industries that could benefit from using software and data. That seems to be the revolution happening. Maybe I'll start something. Not sure what though, but I got my head around the idea that vertical was an easier, lower-risk way to start a company. Meaning do something really specific for just one industry or even one sub-sector of an industry.

So, I sort of learned along the way that that would increase the odds of success. So, I thought, okay, there's gotta be a big industry out there that doesn't really use data and software for digital marketing or digital advertising. I gotta find an industry like that, and if I do, maybe I'll start a [00:04:00] company.

You know, it's funny, the story literally goes, I was sort of on the hunt for an industry that wasn't using any of the products that I had been offering in my career, and then my wife became a real estate agent many years ago now. She came home one day and said, Hey, we're learning all about digital marketing and all of the data that we could use to attract people moving from New York City to suburban New Jersey. And she said I think that sounds a lot like the stuff you do at work. And It was really an aha moment when she called me with that and I was like, Holy cow. This is a family-friendly show, I'm sure holy cow is what I said.

I said, Holy Moly, I need to learn more about that. I went in, I talked to her manager. She, at the time, was at Coldwell Banker. I said, why, why are you talking to your agents about data and software and targeting and analytics for real estate? Like, why are you doing this? He said, Well, because we need to figure out new ways of marketing online. I feel like we're really [00:05:00] far behind and it's like too expensive to do it though, and I don't know how to do it. So, I'm just gonna go back to doing what I've always done, you know, which is to use ILSs and Google and Facebook.

And I was like, That's it. You know, that's an industry that is really big, has a lot of data to sort of play around with and do interesting things with, but it's like shut out from a lot of these technologies and tools that big brands and other industries were already using. So, doing some more homework, I found that, that was the case, and I thought, Hey, this is an industry that seems ripe for change across all facets of the industry. Maybe I could start like some kind of a digital marketing platform for this industry, and you know, I got the courage to do it.

I actually had worked with a bunch of people in the more mainstream digital marketing industry, and they were like, Hey, like I'll do this. Let's do this. This seems fun and hard, but an industry that could use a lot of help. Here we are. Maybe another personal thing is I, I guess, 42 when I started the company. So, also kind of old founder, but the [00:06:00] statistics I've read online are that people in their forties have a higher probability of success than people in their twenties. So, I hope that that is true.

Greg Bray: I think what happens is once we hit our forties, we redefine success differently. I think that's what happens.

Ed Carey: I love that. We have a different, 25 years old, they need a lot of money and glory and we just need to...

Greg Bray: Pay the mortgage tomorrow. Yeah.

Ed Carey: Get paid. I think that's probably true. So, anyway, that's the story.

Greg Bray: Well Ed, somebody's sitting here going, Okay, you do data, but I still don't know exactly what Audience Town does. So, give us like the two sentence, What does Audience Town do?

Ed Carey: Yeah. Well, we are really the only consumer analytics platform of its kind for real estate. Our whole thesis is that real estate's a really big industry. Maybe 30 million people move every year now. It's a 40 trillion industry, but it's still really hard to know who is moving. We launched a company years ago that was really a predictive digital advertising company. We would run all these online ad campaigns for builders, new [00:07:00] construction companies, mortgage companies, brokerage companies, proptech companies, and then we would give them all of these really elaborate analytics reports for free.

They started saying to us, We like your free reporting better than we like your advertising. We were like, Huh, what do you mean? They're like, Well, we get nothing like this. You know, these reports tell us who is moving, when they're moving, their credit scores, their current profile of home, their ownership status, their rental status. It tells us all about the people coming to our website. It tells us all about the people who see the ads, click on the ads, convert on the ads. Honestly, that's like way more interesting than your ad business.

So, we basically went from being a digital ad platform to a consumer analytics platform. So, now our platform is something you log into and you get all these dashboards that tells you all about the people who are coming to your website, seeing your emails, seeing your ads, and really that free reporting has become the business more than the [00:08:00] ad business.

Kevin Weitzel: So, you're only four years old, or coming up on four years of history there at Audience Town. Is it safe to assume that your clients are like Carl the Builder, Bill, the guy that's gonna do a rehab on a bathroom? I mean, what, what kind of client are we talking about here?

Ed Carey: It's still mostly an enterprise client. Meaning it could be either like the in-house marketing team at a builder, like a top 200 builder. They would subscribe to our analytics and use them to measure their site traffic in unique ways, and then they can also use the analytics to power some of their online advertising.

So, instead of us actually doing the ads, we give you the data to do your own ads, but it's still mostly enterprises and then it's marketing agencies. Not unlike Blue Tangerine, who, you know, use the software to try to understand their clients' customer better, and to try to put together marketing plans and marketing channels that will work more effectively.

So, it's not really that local. You know, I think when you're in real estate, people are like real estate agent. Our client is not the real [00:09:00] estate agent. It is typically a regional builder, a marketing agency that does some kind of full service, maybe similar a Blue Tangerine. Or it could be actually the in-house marketing department of a larger builder who will then subscribe to the analytics to learn as much as they can about their customers, so.

Kevin Weitzel: So, a Lennar or K. Hov, somebody like that could gravitate toward your services?

Ed Carey: Yes. Yeah, that's right. That's right. Both of those are and have been customers of these products. Is that on our website? Did you get that from our website?

Kevin Weitzel: Boom.

Ed Carey: Yeah, no, I think those are the types of innovative customers that you want. Both of those companies are trying new ways of engaging consumers online, investing in the online channel and online customer acquisitions. So, you know, those are the companies that are really ahead of the curve in the space to truly try to understand the customer experience as they go through life events that might get them to purchase a new home.

Kevin Weitzel: So, we joke around that I'm the mouth-breathing knuckle dragger of the two of us, me and Greg here. But is it safe to assume that you're taking like that, I don't even remember what it's called, Greg, that U-Haul [00:10:00] report where it shows who's moving where and what trucks are moving only one direction versus another, and then multiplying that times a hundred and then utilizing all those data feeds to power your engine?

Ed Carey: Yeah. Yeah, Kevin, that's a good comparison. It's kind of like that. So, we basically monitor about 200 million people in the US which is almost all adults in the US. We sort of monitor what online adults are doing, and then from there you can kind of deduce who from those 200 million people are predicted to move or are in the process of moving, or who recently moved.

So, that calls that down to about 30 million people. About 30 million people do move every year, buying, selling, renting, and so then you get that 30 million pool of people. You're like, All right, these are the people this calendar year who are going through the home journey, and then from there, you break it down even further. When are they predicted to move? What life events are they experiencing? Where are they in the transaction journey? What is their level of intent? How much equity do they have in their current home? Are they qualified? What are their credit scores? What are their [00:11:00] interests? Do they have an electric vehicle or a gas vehicle?

You know, new construction companies and multifamily companies actually really want to know that. What is their current commute like? And you can really get super granular on those audiences. You can just glean a lot of insight and improve marketing. So, that's essentially the idea though. It's bascially reports. Like, who is really moving and when, and what can you tell me about them so that I can get the message right, choose my marketing channels better?

I've always been fascinated by the world-class lead conversion rates for real estate. They're world-class 'cause they're the worst of any industry in the United States. So, I'm like fascinated by that. They're so bad. It's sub 2%, the lead conversion rates for real estate. It's an industry obsessed with leads. A lot of it is just being done wastefully and incorrectly. They don't really know who their client is and so they just buy leads and spend all this money on marketing channels that don't work and kind of hope for the best. So, hopefully, that can be improved with tools like this.

Greg Bray: So Ed, I gotta go back to, we're monitoring two hundred million people. All right. Tell us just a little bit more [00:12:00] about what you mean by monitoring. 'Cause again, if I'm gonna look at this report, I kind of wanna understand is this just Ed just making it up, or where does this data really come from in the background?

Ed Carey: That's the number one question we get. Where are you getting this stuff from? Yeah, so monitor. I guess that is a little bit of a big brother word. What it refers to is that you know, we're all online all day, every day. You know, the average adult is online something like 11 hours a day. So, it's basically like life is online. You know, we're online right now. All of those anonymous digital signals are being collected. We don't always know that it's Greg and Kevin, but we certainly know that Greg and Kevin both have an interest in a property or in moving.

Those things are pretty easy to pick up. Those signals are anonymously available through various technologies that we license and that we've built, and so you can start to really pick up on those little digital breadcrumbs that say, Hey, this person is experiencing life events, which is why people move. And then you can combine them with other signals such as their existing home profile, which is oftentimes offline data. It's municipal data, [00:13:00] and then we can combine that with other online data signals that could come from habits even on their phone.

You know, so you can start to really tell when people are surfing on Zillow and Realtor and apartments.com. You can pick up on all of these signals and put together, through these sort of anonymous digital breadcrumbs, that this is their offline home profile. This is their online behavior. This is a signal that might come from where they are surfing online. You put them all together and you can start to build a 360-degree view around someone who has all the characteristics of being a home mover. So, that's kind of how we do it.

Kevin Weitzel: So, what you're saying is that everybody has their own, with their computer or their devices, they have their own unique IP address, and that IP address is literally leaving crumbs everywhere. So like, take Greg for example. I know that for a fact Greg's IP address says that he's been looking up how to grow really fat sideburns. I just know it. So, because of that, you know that in 9.5 months, potentially he could be planning on moving to Columbus, [00:14:00] Ohio.

Ed Carey: Yeah, I think it's something like that 'cause you might be thinking, Okay, Greg is looking for these sideburns, and that means that he's old enough that he thinks sideburns and mutton chops are the next big thing.

Kevin Weitzel: And they are.

Ed Carey: You could start to infer this guy is old enough that he is probably downsizing, and then you can kind of string together: business owner, kids have moved out of the house, paid off his mortgage, he's on Zillow every three days frequently, and he's looking at properties in Florida. So, you start to look at life events, property profiles, intent behaviors, and you put these things together. You can get a pretty accurate score around someone likely to move. I mean, we've all moved. We know why we move.

You know you move because of these things. You get a new job, you lose a job, you move because of health issues, financial issues. So, we just try to put those things together through these digital signals and you can get a pretty accurate read on who's moving and when. In Greg's case, it's 'cause he is getting old and he wants mutton [00:15:00] chops and he owns his house and he owns a business and he is ready to go to Florida. So, it's like, you can actually figure these things out pretty easily. Like, your browser alone will basically tell, you know, what you're looking to shop for.

Greg Bray: I was okay with the sideburns, but once you called me old, I'm ready to hit stop. So, I now, now we're done, Ed. We can't be friends anymore.

Kevin Weitzel: Oddly enough, Greg, he described to me. Except, you know, fifties and, you know, looking on Zillow every other day, which I do, and looking for some sort of Tudor somewhere to downsize and upscale in a secondary market. It's crazy, but all that data is there. That's the crazy thing.

Ed Carey: It's all there. We all, and by the way, we all have like gray beards. Your audience just can't see this, but we all have gray-flecked beards. We can be honest with one another.

Greg Bray: Okay. I'm getting old.

Ed Carey: I'm with you, Greg. I'm the same. I'm just like you. I want mutton chops and I wanna move to Florida.

Kevin Weitzel: Ed, was it something that just clicked where you were like, all these data points are there? How can I just accumulate all this, package it, and then utilize this data to where it could be monetized in all [00:16:00] reality for you, but then also advantageously for your clients?

Ed Carey: Yeah, that's right. The story goes a bit like the big, big brands, big consumer brands are already doing this type of customer research and they're using big data and big tech to try to understand their customer really well. So, this has been happening already in the consumer markets for a long time. How do I predict when someone wants to purchase an item? How can I learn more about them through their anonymous digital footprint? How can I use my own CRM and my own website activity to better inform my products and like how much I can sell? So, this stuff has been going on for a long time. All we're doing is customizing it and verticalizing it for real estate.

We started seeing all the available information about consumers that were out there. I guess the big validation of the thesis of the company was like, even to this day, like when I speak with marketing executives in real estate, even operators in real estate, they don't know any of this. They don't know any of it. They don't know the profiles of the people coming to [00:17:00] their websites. They don't know how to connect activity from their email marketing to their website conversions. They don't really know if their web traffic is qualified to purchase their homes or rent their apartments. They just don't know anything about their customer at all.

What that leads to is an industry that stays dependent on buying leads which is a really dangerous place to be. And I think when you don't know your customer, you have to buy leads instead of understanding your customer and marketing to them efficiently, you have to outsource your customer acquisition, and that means you lose connection with your customer, and that means that intermediaries, like Co-Star or ILSs or Google or Facebook, can basically wedge in between your brand and your product and your customer, and that's what's happened across the real estate industry.

You have these extremely powerful entities namely ILSs, but in a more quiet way, Facebook, Google, who have basically stepped in and created a huge gap between real estate [00:18:00] brands and consumers. The real estate companies don't really know their customer and so they just have to buy leads and spend a lot of money from vendors just to get buyers, sellers, and renters.

So some of this stuff is just Hey if you know who your customer is, you can communicate with them directly. You can give them what they need when they need it. You can be a little bit more in control of your destiny. That's a little bit of philosophical, but generally speaking, those are the things that I've seen coming into the real estate. I've only been in real estate for four years. I just came into it and I was like, these companies don't know their customers, and these big powerful companies are getting more powerful every day. There needs to be some kind of check and balance and the way to do that is through just knowing your customer better.

Greg Bray: So Ed, when you think about the kinds of reports and insights into the customer that you guys are able to offer, one of the things that's happening. Like, Facebook is starting to reduce some of the abilities that you have to target, too finally, because of some privacy concerns and discrimination concerns and such. How do we take the data that you're able to provide and turn it into actionable [00:19:00] marketing decisions? Do you have an example or two that come to mind of someone who you've seen do that well?

Ed Carey: Yeah. We're basically now, an analytics and data company. It's one giant set of data that we manage and build and create. We have a customer in the new construction space who subscribes to our analytics and they were studying all of their 55-plus communities across the country with our analytics, and they were learning, trying to learn more about who is in market for 55-plus communities in different areas of the country.

They looked at all these dashboards we gave them. They learned new things about these customers, and then they were like, Hey, we gotta make more of the people coming to our websites customers. Like, how do we get more leads out of them? And so we took the analytics that we showed them in the front-end dashboard and we send them files of data to their Facebook API.

So basically, we can take these same data sets and we can send them to your Facebook accounts. They went in and they logged in to their Facebook ad manager where they go to buy ads, and they took this [00:20:00] data that we gave them about 55 plus audiences. They just plug it right in, and then they buy and deliver ads on Facebook targeted to the 55-plus audiences that our platform thinks is most in market. That is the main way that our data gets like activated.

So, the analytics kind of teach you who your customer is and what they're like, and then you can activate them by us sending you files of data to your Facebook account. We can send it to your Google account, and then you can target those people with your advertising using our data. Hopefully, that's an easy example of how it works.

Greg Bray: Is there one particular metric that you think is the coolest or most important or the one that everybody goes, Ooh, wow, I never knew that. That kind of jumps to mind when people are first introduced.

Ed Carey: Yeah. I think the one that we spend a lot of time on and is interesting to most customers is actually the, when. Meaning like when is someone actually moving? I think part of what leads to so much waste in real estate is that a lot of people will go to a community or property website and they're not really planning on moving. You know, [00:21:00] most people on the big real estate websites are looking at property, are not really planning on moving for a long time or they've already purchased something. It's all a timing game.

We've spent a lot of time trying to figure out when people are moving, not just that they will move. 'Cause you know, of mutton shops, but like, hey, you know, like, alright, when are these old guys with mutton shops moving to Florida? You know, I mean, I look at stuff in Florida, but I'm not gonna move to Florida for five years. How do you really know when?

So, it is the thing that we put in this dashboard. You can like slide this thing back and forth and be like, I only want to use data to know people who are moving in six months or in three months, or whatever the case is. That's sort of unique thing that we built. And then I'm also really surprised by just the really very standard data that people don't have access to, you know, like credit scores. Just knowing that someone has a high enough credit to be able to get a loan, especially in this environment.

Kevin Weitzel: Well, that actually brings up an interesting piece of data. You know, when you're talking about, 'cause I assume you're talking about like Equifax, TransUnion type data. With all the shifts in the market, are you tracking information that can [00:22:00] actually create a qualifying benchmark for a home builder, so they know what kind of client they could have that could buy their product or that can't buy their product?

Ed Carey: It's a good question. I think so. I don't think we've been asked to do that yet, but I think we could. We basically have, to put it in perspective, we've got about 18,000 attributes on those 200 million people or 30 million home movers. So, it's a lot. I think most people will use these tools, one of two things happen. They either go like, the people I thought would buy this home is not it. Or the people who are coming in the front door like are wrong for us and they're not really that interested.

How do I go find and reach more of the right people? And so then they'll come and be like, Hey, you know, a lot of people coming to our 55 plus are actually really young. That's wrong. Our marketing message is clearly not targeted the right way. Can we use your data to try to find people who are right fit for this community?

Greg Bray: So, Ed, when you think about data. I mean, we've got the reports you're talking about. We've got Google Analytics reports. We've got data coming from [00:23:00] Facebook. We've got, you know, Zillow sending leads. All these different sources of information and frankly, there can be that information overload effect. Just that, I've got all this stuff. I don't have time to process it. I don't know what it means. I don't know how to use it and so I'm just not gonna look at it. It's like a pretty graph. It's a nice picture. Up is good, or down is good depending on the, the number.

Kevin Weitzel: Green, good, red bad.

Greg Bray: Yeah. But, but it's like, how do we keep from just drowning in data and not just totally throwing up our hands and not knowing where to go next?

Ed Carey: Yeah. It's a good topic. It's something we hear a lot about and it's something we have to be super sensitive about. I don't have the answer. I think for a company like ours and for companies that use analytics, I think a lot of the topic comes down to like, how do you want to get this stuff? How do you wanna delivered to you and how do you want to see it? Then trying to make it easy so it can be all in one place.

So, for example, information overload is the symptom of our times. You know, we have all this information that I think every bit of is super interesting, but it's not to everybody. So, like what we think [00:24:00] about is like, we have like a front end version that you like, log into and you get a login and you can pull all this stuff. But then what's happening is interesting in, in so far as like companies like Google, you know, for example, just like folded their Google and Looker brands together.

And we're having customers trying to be like, Hey, I don't wanna log into your software. Can you just like send this to me, and can it like appear via API in my own existing dashboards? I think if our mission is to just know who's moving, that's something that we should just do to try to reduce the information load on clients who are really just trying to find specific information. That's how we have to think of that problem 'cause it is something that I think anybody in software has to consider is I already have seven logins.

You know, I gotta log into this, I gotta log into my CRM, I gotta log into my analytics. I got Google Analytics over here. I got an Adobe over here. I got my website over here, and then you show up and you want me to pay for another thing to log into. They're like, ah. That's our answer to it. Right now, you have to log [00:25:00] into it, but I think we're thinking of next year as maybe a time when if the way analytics as an industry sort of goes, they might want to ingest our analytics rather than like log into a dashboard. So, don't know the answer, but it's something we hear about. You know, it makes us nervous, so.

Kevin Weitzel: I'm a firm believer that crazy thoughts can create industries. So, just like when you and I are having a conversation about mutton drops and I happen to mention Bose headphones, and then next thing I know, it's in my LinkedIn feed, it's on my advertising on my Facebook page, and all we were having was a casual conversation and somehow our phones heard us, whatever.

How far off all were we to where we could take the data points that you have where you could literally give me a list of IP addresses and, and potentially phone numbers and emails or whatever, where I could call up Hi, Susan Smith. I see in about four and a half months you're gonna be relocating. I'd like to be your concierge to help you with that process. I truly believe that is a possibility. I know it sounds crazy, but I truly believe that with all the data that [00:26:00] you are collecting, that there is a proponent to move to that direction where we'll actually predictively be able to know when people are moving.

Ed Carey: Yeah, I mean, Kevin, that's a oversell or tease outta things, but we can do that stuff. We're trying to figure out on those crazy ideas like when it is compliant to do that kind of thing. There are a lot of data regulations between what we have sitting on our computers and like what is allowable to do that we're trying to navigate as well.

So, for example, starting early next year, a capability that our technologies can do is actually de-anonymize people online. So, if someone comes to a builder's website, they just come in as an IP address, right? Just, KW123. Using a lot of these identity technologies, you can actually sort of figure out that's actually, Kevin. And then you can figure out that Kevin is having a life event, and that person is predictably likely to move in the future. And then you can call them and say, Hey Kevin, I know you came to my website and I know you just gotta raise at work.

A [00:27:00] lot of those capabilities exist today. In fact, we'll be able to do many of those things in the not too distant future, but there are a lot of regulations around being able to do that kind of thing. Do you wanna get a phone call that says, Hey, Kevin. I understand you're buying Bose headphones and that you know, your wife thinks you're just not listening, and like, it's just like, wait a minute. Wait a minute. So, you gotta be careful.

So, there's whole thing's like SOC 2 compliance. There's a lot of regulation and that regulation is only getting more firm and strict around how data like that can be used, and it's something we have to navigate very carefully. The reason why Facebook ripped all their targeting out cause they got in trouble with stuff like that. We have to be careful, but those things are possible technologically. How you turn them into products and commercialize them with regulation in mind is trickier and more expensive.

Greg Bray: It's interesting that we think it's crazy and intrusive when it's not something we want, but when that perfect ad shows up for the thing that we actually [00:28:00] do want, we don't even realize that we're like, Oh, that was helpful. That was useful. But yet all the things that go in between and the ability for misuse of some of that technology is really a challenging industry opportunity or moment that we're facing. It's gonna be interesting to see how that all plays out.

Kevin Weitzel: I know for a fact this is already happening, buddy, and I'm gonna tell you why. I've never spoken about any kind of suits with anybody. Never, and just like what you're talking about, that ad that just kind of hits you and it's like, Wow, who knew that I needed this? Tweed suits. Nobody buys tweed suits, but who wants one? This guy. I want a plaid, tweed suit, and what do I see? Boom. It pops right in my feed. It's almost like I was just thinking it.

Is it my age demographic? Is it my income level? Is it the, you know how long I've owned my home? I don't know what it is. All I know is that kind of stuff just makes me think that we could have predictive outbound marketing campaigns based off of demographics that feed a certain data set.

Ed Carey: Yeah. [00:29:00] You're absolutely right. I was talking to a colleague going through a home move recently. If you're looking to move, especially in a world where you can work from home, and we're all, distributed more than ever before like the ads you get online for properties, like aren't good. You don't understand the marketplace. Like, maybe you could live in Tennessee and you don't know that 'cause you don't see the ad. Like you don't know.

So, when advertising is addressable that way, using data and signal the right way. Like, it's great. People love it. They really do. They give all of their information online to a lot of companies so that they can get better services that's more personal and relevant. So, Kevin, you're right. I think real estate is not there yet.

If you ever buy or lease a car, you actually have a pretty good commercial experience. You know? It's like, Oh, like a Volkswagen? Try a Honda. Yeah, you know what? Maybe I will. Like a Toyota? Why not try a Subaru? Yeah, okay. That's a little bit cheaper. When you go to like buy stuff houses or look at things online, you have no experience like that at all. You don't know what's possible, and so it actually [00:30:00] creates a more difficult experience, I think. I would love to know about new construction communities in different parts of the country to potentially move to. I just don't know about. Like, where do you even, how could you know? And so good advertising done well can be a great service to consumers, but in real estate, I haven't seen it. Yeah.

Greg Bray: Well, Ed, we appreciate you spending so much time with us today. As we kind of wrap up, is there any last pieces of advice or thoughts you wanted to share with our audience that we didn't have a chance to touch on yet?

Ed Carey: I feel like I've shared too much already. I just think that moving homes is so unique for people and it's so hard to do. Transactions are hard. Knowing where to move is now hard. You know, whatever happens in the real estate markets, Covid has changed things forever, and I think you can't make decisions about marketing real estate without data and good information. I'd love to see the industry get to a point where they stop just marketing the property or where the property is and think more about the people that are actually marketing too and what their needs are and what their fears are and what their desires are. I think if they do over [00:31:00] a period of time, real estate marketing can catch up to the present.

Greg Bray: Well Ed, if somebody wants to learn more about Audience Town or connect with you, what's the best way for them to reach out?

Ed Carey: Audiencetown.com, of course.

Kevin Weitzel: Boom.

Greg Bray: Awesome. Well, thanks again, Ed, and thank you everybody for listening today to The Home Builder Digital Marketing Podcast. I'm Greg Bray with Blue Tangerine.

Kevin Weitzel: And I'm Kevin Weitzel with OutHouse. Thank you.