Why AI Won't Fix a Broken Real Estate Business

Transcript

Host: Michelle Castle. Lightly edited for readability; sponsor segments removed.

For those not familiar with your work, what's your main focus?

AI and automation services within the real estate sector. We help on the direct mail side in terms of removing the overhead and friction that often drives for people. There's a lot of moving parts, especially when you're doing north of 30 or 40,000 pieces a month. So we help solve that problem, from data segmentation and aggregation through targeting, enrichments, all the way through delivery.

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 they're able to understand inside the business, and uncover gaps — whether that's in sales training and performance, or lead management and follow-up. All the things that sort of drive to the bottom line at the end of the day.

How did you build White Space Solutions?

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 I was very early in on everything that happened with AI — to the point where I was negotiating with my CTO to get the team to adopt some of these tools, because I saw the power they offered specifically in the coding context.

Around that time I started taking real estate very seriously, started to grow my own portfolio as a path to wealth — probably like most people that read Rich Dad Poor Dad and got swept up in that vision of building a big portfolio.

And then while I was working for the fintech company, after we launched the product we had to scale it, and funny enough direct mail was one of the most effective ways to do that. We built a credit card product, issuing credit cards across the US, and we had to build an internal program to enable that nationally. So we were doing two, three, four million letters a month across the US slinging credit cards.

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 led me to start what became White Space Solutions. On the direct mail side, obviously very prevalent in real estate — people's ability to market direct to sellers, do that efficiently, and get to a three, four, five X or better ROAS. I was able to leverage my engineering and technical background to help solve that problem, especially as it relates to the data and optimizing for response rates.

The second piece was what I call applied AI — sifting through the noise that can often be the hype train, but really understanding where the core value lives in terms of how these tools can be used effectively within a business. I built out a service offering catered to the real estate industry, because I feel like it's often underserved. A lot of the technical platforms out there are maybe not at the most cutting edge, so I saw an opportunity to help close that gap.

What have been the biggest challenges?

One is the speed at which the technology is changing. You've got to stay on top of it and find the things that are working. The thing that might not be working today, tomorrow could be working. In order to provide the most valuable solutions and services you have to understand where things are at. And everyone wants an edge — these tools can offer you an edge, so you have to be an early adopter to start incorporating some of these things.

Other challenges: the market's tough, especially in real estate. I've seen this in some of my clients where cash conversion cycles start to extend. AI can't solve all of these problems. That becomes a challenge when interest rates are fluctuating, things aren't selling as quickly, and there are serious headwinds. Those have domino effects across the board — from my client through to me to anybody working within the space.

And the third obstacle is just that building and growing a business is always a challenge. Hiring, client retention, quality of service delivery. Building out a service-based business is challenging, but it's a lot of fun, and I enjoy learning the ins and outs of different businesses and how some of these tools can apply and add value.

What does the service model look like?

On the direct mail side it's essentially a managed service — sort of like your typical agency model where we manage the campaigns from start to finish. It's a done-with-you model, so we really emphasize transparency. We give our clients full access to the platforms we use, largely white labeled, but we've built an integrated solution across the tech stack that makes it easy to use. That usually ends up looking like a monthly management fee, anywhere from maybe $1,500 to $2,000 a month. And then we pre-negotiate mail costs with all of our vendors and pass that through to our customers. Mail's typically 60 or 65 cents all in.

On the data side we work with a number of vendors. Some clients come with their own data provider; others we have a handful we like to work with that work really well with our platform, which lets us automate things.

On the technology side it really just depends. We do things that are project-based where people want one or two problems solved, and we'll scope that out separately. Others are looking for someone in a fractional CTO type role. I wouldn't claim that I'm a CTO, but a lot of times clients will install me on a monthly retainer where we'll tackle a series of problems over the months — whether it's integrated systems, actually using AI within some of their workflows, or getting their team up to speed on how to leverage these tools in their day-to-day work. We'll map out a plan and work through it as time permits.

As an investor yourself, do you use these tools in your own business?

Absolutely. We run 20 units out of state in Chicago. That's not a huge portfolio by any means, but for a solo operator — I have one virtual assistant that helps oversee things — in order to keep a team lean you need efficiencies in place.

On property management, the VA helps with communications and coordination. This past year we had several significant tenant disputes come up, and that's much more high-touch. You have to analyze the situation, dig deep into the laws and regulations and 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. Whether you're using ChatGPT or Claude, they have several skills available where you can consolidate all of the ordinances and laws and then use that as a sounding board as you start responding back and navigating through whatever the issue is, understanding both sides of the equation. 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 made sure the tenants were treated appropriately and taken care of.

Second is underwriting — exploring new deals. If you've ever read an OM, you know it's often a 6 to 10 page PDF that's very hard to sift through. You have to extract rent rolls, P&Ls, financials, put it into your own model, and then try to ascertain whether this is going to be a viable investment. With AI now you can 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 you get to an answer faster on whether or not to move forward. And then you can even have it compose the LOI or the purchase agreement. It compresses a lot of the timelines of the tasks you'd normally have to execute and enables you to move much faster.

Third, back on the property management side, one of the things we're looking at is building out voice AI so we can cover inbound off-hours and even during-hours calls from tenants, whether it's a maintenance request or an inquiry. We run some Airbnbs as well — that's super high touch, and to the extent we can put an AI agent in front of that it helps flatten a lot of the time my VA would spend taking those calls. The voice agents are really powerful now, and once you equip them with the appropriate APIs to actually talk to your systems, they can handle most tasks.

Who's the ideal client?

Our ideal customer profile is folks doing 50 or more deals a year. Typically they have a team of 10 or more people. At the smaller scale, the optimization you're usually trying to get out of these tools — whether on the direct mail automation side or leveraging AI tools — I think you can kind of figure it out. Once you start to get to a bigger team size and larger deal volume, that's where you need more sophisticated tech and tooling in place.

Same goes on the direct mail side. If you're sending five or 10,000 pieces a month, you can get away doing that on your own. When you're doing 100,000 a month and you're trying to keep track of every campaign, every segment, every month, for every creative, the data complexity in order to understand what's happening becomes much more challenging. That's usually where we're the best fit, because we're able to help solve those problems when it becomes painful to manage.

Is there anything your services don't solve?

We don't solve broken businesses.

That's the danger with a lot of the excitement that has come out with AI. It's not a silver bullet — and the shiny object never is the silver bullet. It's not going to fix all of your problems. If you have a broken business model, a broken process, a broken team, these tools aren't going to fix it.

Sometimes what I see is owners will chase the shiny object hoping that's going to solve the problem. You really have to focus on the core fundamentals. Once those are dialed in — you have a solid team, a solid process, a solid offer with consistent output — then you can layer on some of these tools, whether it's AI or marketing automation or whatever it may be, to put the fuel on the fire and amplify the output of the team.

What are you most focused on next?

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. My goal is to double if not triple the volume we did last year, really standardize our offering, and reach more people. We're on a good track so far.

How do you normally find clients?

So far it's honestly been almost all word of mouth and 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 to fuel the growth we're looking for. But so far it's been a lot of word of mouth and an emphasis on providing a lot of value and over-delivering. That's proven out — when people feel that and see that within their business, they tend to refer you to others.

Where can people find you?

We have two websites: whitespacesolutions.ai, where you'll find all our stuff around AI automation technology, and remaildirect.com, our direct mail automation offering for real estate investors. Or you can always email me directly at jason@whitespacesolutions.ai. I try to be active on the socials where I can, but direct email is probably the best.