Why AI Won’t Fix a Broken Real Estate Business | Jason Macht on Automation That Actually Works

Jason Macht (00:00)
We don’t solve broken businesses. you know, I think, I think that’s the danger ⁓ with a lot of the excitements that has come out with, you AI. It’s, not a silver bullet and you know, the shiny object never is the silver bullet. It’s not going to fix all of your problems.

Michelle Kesil (00:02)
Right?

Hey, everybody. Welcome to the Real Estate Pros podcast. I’m your host, Michelle Kesil. And today I’m joined by someone I’m looking forward to chatting with, Jason Macht of White Space Solutions, who provides AI automation and automated direct mail services to investors. And he is also a real estate investor himself. So excited to have you here today, Jason.

Jason Macht (02:16)
Yeah, thanks for having me. Looking forward to our conversation.

Michelle Kesil (02:18)
Awesome, let’s dive in. First off, for those not familiar with you and your work, can you share what your main focus is?

Jason Macht (02:25)
Main focus is AI and automation services within the real estate space. We help on the direct mail side in terms of just removing the overhead and friction that often drives for people. There’s a lot of moving parts, especially when you’re doing, call it north of 30 or 40,000 pieces a month.

So we help solve that problem from everything from like data segmentation and aggregation through segmentation, targeting, enrichment, all the way through delivery.

So that’s that side of the business. And then on the AI side, we focus on enabling business owners to leverage these tools within their business to drive better outcomes, drive revenue, improve the insights that they’re able to understand within inside the business and uncover gaps, whether that’s in sales training and performance or it’s lead management and lead handling and follow up.

⁓ all the things that sort of like drive to the bottom line at end of the day.

Michelle Kesil (03:26)
and is this operation nationwide?

Jason Macht (03:29)
Yeah, we have clients across the US, everything from West Coast to East Coast.

Michelle Kesil (03:33)
Awesome, and so how did you create ⁓ these platforms?

Jason Macht (03:38)
Sure, so ⁓ I was an engineer by education. I spent most of my career in product management. I worked for a fintech company where I ran a team of engineers. And ⁓ so I was very early in on everything that happened with AI. ⁓

to the point where I was sort of negotiating with my CTO to try to get the team to adopt some of these tools because I saw the power that they offered ⁓ specifically in the coding context. So that was my exposure on that front. ⁓ Along those, ⁓ around that time I started to take real estate very seriously, started to grow my own portfolio as a vehicle to sort of…

a path to wealth, probably like most people that read Rich Dad Poor Dad and ⁓ kind of got swept up with ⁓ sort of that vision of building a big portfolio. So that started my journey on the real estate side. ⁓ And then along the way, while I was working for the FinTech company, after we launched the product, we had to scale the product. ⁓ funny enough, direct mail was one of the most effective ways to do that.

We built a credit card product. So we were issuing credit cards across the US and we had to build an internal program to ⁓ enable that across the nation. So we were doing, you know, two, three, four million letters a month across the US slinging credit cards. So fast forward a couple of years, I had the opportunity to work with some real estate investors, particularly in the wholesale space. And one thing led to another and it kind of led me to start what

became white space solutions. And so the idea there was ⁓ one on the direct mail side, obviously very prevalent in the real estate sector of people’s ability to ⁓ market direct to sellers and then do that efficiently and get to a three, four, five X or better ROAS. And so I was able to leverage sort of my engineering and…

technical background to help solve that problem, especially as it relates to the data and optimizing for response rates, et cetera. ⁓ And the second piece was on what I call like applied AI and sifting through the noise that often can be the hype train of AI. ⁓

but really understanding like where the core value lives in terms of how these tools can be used effectively within a business. And so I built out sort of a service offering tailored to that catered to the real estate industry because I feel like it’s often underserved. I think a lot of the technical platforms out there are maybe not ⁓ the most cutting edge. And so I saw an opportunity to help close that gap.

Michelle Kesil (07:04)
Yeah, amazing what have been some of the biggest challenges and obstacles in this process.

Jason Macht (07:10)
the biggest challenges and obstacles. I would say, ⁓ one, just with the industry, ⁓ whether it’s the speed at which, ⁓ in the context of AI, the speed at which ⁓ the technology is changing, you gotta stay on top of it and find the things that are working.

The thing that might be not working today, tomorrow could be working. And so you got to really keep up with it because in order to provide the most valuable solutions and services, you have to understand where things are at.

And at the end of the day, everyone started to be competitive, right? Everyone wants an edge and these tools can’t offer you an edge. And so you have to be sort of an early adopter to start to incorporate some of these things. And so, you you have to be able to keep up with it. Other challenges or obstacles, you know, the market stuff, ⁓ especially in the real estate or has been, and I’ve seen this even in some of my clients where, you know,

cash conversions cycle start to extend. AI can’t solve all of these problems. So that becomes a challenge when interest rates are fluctuating, things aren’t selling as quickly and there are like serious headwinds and those have sort of like domino effects on.

across the board from the client through to me to anybody who started working within the space. And you can see this, ⁓ the rippling effect sometimes. And then the third obstacle I would say just like building a business, growing a business is always a challenge, right? Hiring, ⁓ client retention, ⁓ quality of service delivery.

⁓ All those aspects in building out a service-based business is challenging. But it’s a lot of fun. And I enjoy learning sort of the ins and outs of different businesses and how some of these tools can apply and add value at end of the day.

Michelle Kesil (09:02)
Yeah, amazing. And so how do these platforms work? Is it like a subscription or what does it look like?

Jason Macht (09:10)
⁓ in terms of our service offering. So on the direct mail side, we have, it’s essentially a managed service, sort of like your.

typical agency model where we manage the campaigns from sort of start to finish. It’s a done with you model. So we really emphasize transparency. We give our clients like full access to the platforms that we use, largely like white labeled, but we’ve ⁓ built an integrated solution across the tech stack that makes it sort of easy to use. And so that usually ends up looking like a ⁓ monthly sort of management fee. It’s anywhere from maybe 1500 to 2000 dollars a month.

and then we pre-negotiate ⁓ mail costs with all of our vendors.

So we pass that through on to our customers. So mail is typically 60 or 65 cents ⁓ all in, which is great. ⁓ And then on the data side, we work with a number of vendors on the data side. some clients will come with their own data provider. Others, ⁓ we have a handful that we like to work with that work really well with our platform allows us to automate things and ⁓ provide a really nice integrated solution across the board.

how things that work ⁓ on the direct mail side and then on like the technology side, it really just depends. We do things that are project based where people might just want ⁓ one or two problems solved and so we’ll scope those out separately. Others are really looking for someone in that like, I might even call it like a fractional CTO type role. I wouldn’t claim that I’m a CTO, but ⁓ I can, a lot of times what I do is,

clients will sort of install me on like a monthly retainer ⁓ where we’ll tackle a series of problems over the months within the business to sort of ⁓ step up their technological capabilities, whether it’s integrated systems or it’s actually using AI within some of their workflows or…

getting their team up to speed on how to leverage these tools and their day-to-day work. And so we’ll map out a plan and then work through that ⁓ as time permits.

Michelle Kesil (11:55)
Yeah, amazing. And as an investor yourself, how do you like do you utilize these platforms for your business?

Jason Macht (12:05)
Absolutely. I mean, I have, you we run 20 units out of states in Chicago. That’s not a huge portfolio by any means, but, for a solo operator, I have one virtual assistant. It kind of helps like oversee things. But when it comes to sort of every stage of it, in order to keep a team lean, you need to sort of have, you know, efficiencies in place. And so

Everything from top to bottom, would say, property management. So for example, the VA that I have helps with communications and coordination. in this past year, we had several significant tenant disputes come up. And so then that’s much more high touch. You have to analyze the situation. You have to dig deep into

into the laws and the regulations and the ordinances to understand what you as a landlord ⁓ can and cannot do. And same for the tenants. ⁓ This is a great use case for AI. So whether you’re using ChatGPT or Claude or a model of the sort, they have several skills available where you can actually essentially consolidate all of the ordinances, the laws, and then use that as a sounding board as you start

responding back and navigating through whatever the issue is and understanding both sides of the equation. So that’s been instrumental in helping us navigate several challenging ⁓ tenant disputes this year.

and making sure we didn’t overstep ⁓ any boundaries, acted within our rights, and also make sure that the tenants were treated appropriately and taken care of. So that’s a really useful ⁓ use case for, I would say, underwriting, so exploring new deals. ⁓ If you’ve ever read an OM, you know that it’s oftentimes like a six to 10 page PDF that’s very hard to sift through.

and to have to extract rent rolls, P &Ls, financials, input it into your own sort of model, and then try to ascertain the answer of, is this gonna be a viable investment or not? ⁓ With AI now, you can actually just import those PDFs directly into the model. You can build your own skill sets around.

how you want to underwrite that, what to calculate, what to look for, so that you can get to an answer faster of whether or not to move forward with that or not.

And then you can actually even have it compose the LOI or the purchase agreement, right? So it’s able to compress a lot of the…

the timelines of the tasks that you would normally have to execute and enable you to move much faster. So ⁓ that side’s really, really useful. The third side I would say would be just on the property, back to the property management side. One of the things we’re looking at is actually building out voice AI so that we can have them.

sort of cover inbound, off hours, and even during hours ⁓ calls from tenants, whether it’s a maintenance request or an inquiry. ⁓ We do run some Airbnb’s as well. That’s super high touch. And so to the extent that we put an AI agent in front of that, it helps deflect a lot of the time that my team, my VA would spend sort of taking those calls. And the voice agents are really powerful now. And then once you equip them with appropriate APIs to actually talk to your systems, it can handle most tasks.

So those are, I don’t know, three quick examples I would say of how we’re seeing them be used in the real estate ⁓ sector and how we’re actually using them firsthand.

Michelle Kesil (16:24)
Yeah, amazing that you’re able to leverage technology in that way.

Jason Macht (16:27)
Yeah, it’s fun to watch how far things have come along.

Michelle Kesil (16:30)
Yeah, absolutely. And so who is kind of the ideal client? Is it suited for all types of investors?

Jason Macht (16:38)
We’re generally like our ideal customer profile. would say, know, they’re they’re guys that are doing or girls that are doing, you know, 50 or more year 50 or more deals a year. Typically, they usually have a team of, know, I would say 10 or more people. You know, once when you’re at the smaller scale, like the optimization.

that you’re usually trying to get out of some of these tools, whether it’s even on the direct mail automation side or even leveraging some of the AI tools. mean, I think starting out, if you’re like a smaller team, you can kind of figure it out. Once you start to get to a bigger team size, larger deal volume.

That’s where you need ⁓ more sophisticated tech and tooling in place is kind of what I see. And same goes on the direct mail side. If you’re sending five or 10,000 pieces a month, you can get away doing that, I think, on your own when you’re doing 100,000 a month and then you’re trying to keep track of every campaign, every segments, every month for every creative, the data complexity.

in order to understand what’s happening ⁓ becomes much more challenging. And so that’s usually where we’re best fit because we’re able to help solve those problems when it becomes ⁓ painful to manage.

Michelle Kesil (17:50)
Yeah, that makes sense. Is there anything that your services don’t solve?

Jason Macht (17:58)
We don’t solve broken businesses. you know, I think, I think that’s the danger ⁓ with a lot of the excitements that has come out with, you AI. It’s, not a silver bullet and you know, the shiny object never is the silver bullet. It’s not going to fix all of your problems.

Michelle Kesil (18:00)
Right?

Jason Macht (18:18)
And if you have a broken business model, a broken process, a broken team, you know, these tools aren’t going to fix it.

And sometimes what I see is ⁓ owners will sort of chase the shiny object, hoping that’s going to solve the problem. But you really got to focus on the core fundamentals. And once those are dialed in, you have a solid team, a solid process, a solid offering with a consistent sort of ⁓ output.

then you can layer on some of these tools, whether it’s AI or marketing automation or whatever it may be, to sort of put the fuel on the fire, so to speak, and sort of amplify the output of the team.

Michelle Kesil (19:01)
And what are you most focused on solving or scaling to next?

Jason Macht (19:05)
Most focused on solving or, I mean, my goal this year is to help more people, help more investors and evangelize how businesses are thinking about and integrating AI into their business. And so my goal is to double, if not triple in terms of like the volume that we did last year, ⁓ this year, and really.

sort of standardize ⁓ our offering, add more value for what we’re able to do, and reach more people in terms of what we’re able to provide. So that’s our goal this year. yeah, I’m excited. We’re on a good track so far.

Michelle Kesil (19:47)
How do you normally find your clients?

Jason Macht (19:50)
So far it’s honestly been almost all word of mouth in referrals, which I feel honored and lucky to have been the case. This year we’re just now starting to step a little bit more into marketing. So we’ll be doing some in order to sort of fuel the growth that we’re looking for. That’s one of the main priorities this year. But so far it’s been a lot of word of mouth and just, you know.

an emphasis on providing a lot of value and over delivering. And I think that has sort of proven out that, you know, when people feel that and see that within their business, they tend to refer you to others. And so that’s worked out well. And then, yeah, we’ll continue to sort of do more out bounds in digital marketing this year to kind of spread the word even further if we can.

Michelle Kesil (20:36)
Yeah, amazing, that’s great that you’re able to use relationships to grow your business.

Jason Macht (20:41)
Yes, very fortunate.

Michelle Kesil (20:42)
Well, we begin to wrap up here, someone wants to reach out, connect, and learn more about what you’re up to, where can people find you and connect with you?

Jason Macht (20:53)
Yeah, so we have our two websites. There’s whitespacesolutions.ai. That’s where you’ll find all our stuff around AI automation technology. And then we have remaildirect.com. That’s our direct mail automation offering for real estate investors. Or you could always email me just directly at [email protected] and ⁓ you can find me there. And I try to get active on the socials where I can, but ⁓ direct email is probably the best.

Michelle Kesil (21:22)
Well, I appreciate your time and your story. Thank you so much for being here.

Jason Macht (21:26)
Thanks for having me.

Michelle Kesil (21:27)
And for those tuning in, if you got value, make sure you’ve subscribed. We’ve got more conversations with operators like Jason who are building real businesses and we’ll see you on our next episode.