When you’re building and scaling a real estate portfolio, it’s easy to assume that more data equals better decisions. In this conversation, I sit down with Kevin Shtofman to unpack why that isn’t always true. We talk about how institutional investors think about data, how individual investors can avoid costly blind spots, how to use AI as a strategic partner instead of a shortcut, and what it really takes to build trust with capital partners. If you want to scale with more clarity, stronger systems, and smarter decision-making, this is a conversation you’ll want to listen to closely.
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Hello, everyone. Welcome back. I’m Adrienne Green. And today we’re here with Kevin Shtofman. Here we focus on how real estate entrepreneurs can break free of the grind using leverage, support, and smarter strategies. And Kevin, I know you’re going to talk about that a lot. So as we get started to ground the conversation for listeners, how does your work intersect with real estate investing today?
I mean, I’m living in it.
With my day job, I’m the head of corporate development for a software company that sells into large real estate institutions. So think sovereign wealth funds, the real estate arm of a bank, the real estate arm of an insurance company, publicly traded REITs. And then outside of the day job, I’ve been slowly, methodically building a real estate portfolio myself with a handful of friends.
Love it, love it. Which would you prefer to talk about first?
Oh man, let’s start with the first 15 years of my career, which is the corporate side. And then we can go into the most recent six, which is how I basically turned it into a hybrid role.
Okay.
Love it, love it. So let’s start with the corporate side. I know that we’re really going to talk about data. Now, investors are always surrounded by dashboards, reports, and data. But where do you see investors confusing having data with actually making better decisions?
I think most people, when they put something in front of their face to look at, they care more that it’s visually pleasing and appealing for an investor or regulator than they do that it actually answers a real question. So what often happens is they’ll just say, look at this pie chart, look at this, look how rents have gone, look at foot traffic. The real value is actually when you take pieces of data and put them together so that you get some sort of inference and result you wouldn’t get from any report you might buy. So a good example of that is when someone’s looking at sales comps on their own, what might a property sell for in the market today or what have they been selling for recently, that on its own is not very valuable. You might think it is, because you have a certain budget and want to acquire property for X, but that does not really matter unless you understand what the underlying net operating income is of that asset and what comparable lease rates are for similar properties nearby. So you need that triangulation of sales comps and lease comps and actual NOI in the building before you can infer anything related to due diligence and whether this property is worth looking deeper into.
Right.
Right.
Yes, I totally get what you’re saying. I think that’s a fabulous example of it. I’m also thinking about your initial point of, we can see what properties are selling for in this area. Also, if we’re looking for a short term rental, can we look at the difference in terms of sales price and gross or net operating income for three bedrooms versus four bedrooms versus five bedrooms in this area? Where are we going to get the most bang for our buck within this market in terms of types of house for the specific strategy?
My answer would be as you get closer and closer to home or as you get more micro in your focus, the deeper you need to be in the details of data. A lot of our clients are large sovereign wealth funds or banks. They are looking at macro trends. Who’s moving from one market to another? What markets are adding more jobs? Where is there less weather related risk?
Right.
Right.
But when it comes to you or me individually or some of your listeners that are building a portfolio, if you’re looking for a particular house, it’s not just the neighborhood and the school district it sits in. It’s not just the property condition. It’s actually doing an inspection of the home. What deferred maintenance sits inside the house? Where are the surprises that probably aren’t on the MLS listing that you’re looking at, which has beds and baths and expected sales prices and rent? It might be when you get in there, are you going to have to redo electrical work? Is there any problem with the foundation? Was there a previous weather related accident on that home before you owned it? And therefore, when you buy it and have to put a homeowners insurance policy on it, the premiums will be higher because there was an incident before your time that did not involve you at all. Knowing that means if it’s an extra $3,000 a year in insurance premium, that’s an extra $250 a month in operating costs. Are you going to be able to justify that or make that up in the rent when you’re running the property?
Right.
Mm-hmm, right. Sometimes your average real estate investor may be worrying too much about macro trends when there are specifics about that house that are more important to how their return is actually going to be, how great of an investment it’s going to be.
Yeah, as your pool of capital grows, you can probably afford to average out risk and think more macroeconomically. But for most of us trying to build portfolios on our own, piecemeal and grow from the ground up, you need those first couple deals to be really profitable. You need to know so much because there are so many details we miss and we learn doing our first couple deals that the maximum amount of detail you can have about a property, the better off you’re going to be in terms of revenue versus cost versus risk.
Now, from your perspective, because we can have data on everything, we can have data on the minutia. I’m curious, what are the highest impact decisions in a real estate business or for entrepreneurs where better data is going to materially change their outcomes?
Well, it totally depends on the property type.
If we’re talking about a single family home, the most important data is going to be school district information, demographic information, supply information, and the reason for that. And then corporate relocations and hiring. Because what you want to know is, are there a lot of people that are going to be moving into the area that might be candidates to buy or rent the home that you’re buying?
Are you moving the lever on supply in the area? Are there a lot of houses that are being remodeled right now? Are the schools over capacity and thinking about increasing the neighborhood footprint or building a new school that will handle that new demand? We’re dealing with this in Dallas a lot. We’ve been fortunate to get an influx of people and companies and so there’s a lot of argument about that kind of stuff. Also, hiring data is very helpful to understand because if the right jobs are open with the right salaries for people that could then afford the home, that’s good data to know. Some of that data will be irrelevant if you’re looking at buying a retail strip center. Then you care more about foot traffic in that area. Are you actually getting enough people walking by your strip center to test and stock your brands? The health of a potential tenant becomes more important. What brands are popular and growing with consumers? What brands are falling out of favor and not getting people in the door to sell goods? Some leases might have a base rent component, but they also might have a percentage rent. The more money they make, the more money you make as the landlord. It completely depends on the property type in question, which data set is going to move the needle with regard to how you maximize rents and minimize costs.
Mm-hmm, right. You give a great number of specifics there, which is really helpful. If you’re doing any of these investment types that he’s talking about, pay attention. Write that down. I think there’s also the macro principle of before we look at 123 Main Street or 456 Banana Street, we need to step back and say, what is the data that’s going to be helpful for this asset class that I’m pursuing, and how can I get that data? So that you’re not just being reactive for that specific property, you’re being intentional beforehand to set up a situation that’s positioned for success with your data. What I love is you have a foot in both worlds, this corporate institutional side and as an investor yourself. What pro tips would you have, specifically in terms of operations first? What pro tips for operations would you think individual investors could use or learn from the institutional side?
First, AI. I know it’s the buzzword. It’s what everyone’s talking about. But at my corporate job, I have teams that I can collaborate with. People that can help with marketing, finance, vendors and accounts payable, collections and receivables, leasing analytics. When you’re a company of one building your own portfolio, you will not have an analyst or an AP clerk or an accountant. You might hire a service for that, but all of those expenses cost money. My advice is to be using the LLMs that can help you produce documents so that you’re not spending a lot of time on operational minutiae day to day. Having AI help you produce a standard rent collection statement or a way to process invoices that come in from vendors. Crafting communications that go out to tenants when rent is due. Creating an email inbox dedicated to work order requests. If somebody needs something done, a light bulb change or the toilet is clogged, having an easy way for tenants to send a quick email to communicate. More sophisticated investors will have portals where all this gets automatically logged, but when you’re a party of one and don’t have a lot of money to spend on software, having the LLMs help you create these documents and this initial flow so you can appear like a more professional organization at first will help you get started. By doing that, you’ll figure out where the holes are in your workflow. There’s nothing like trying to automate a workflow to learn all the little steps that go into it and where it fails.
For people who are at that solopreneur stage of their real estate business right now, you have tools like ChatGPT to use. When I got started in 2013, I remember having to create that initial lease in Microsoft Office. I had a few different leases that friends and some of my husband’s coworkers who were real estate investors gave me. I used those to make one master lease that was our style and vibe. That took forever. The tools now make those things so much easier and higher quality. You look more professional from the start. I love that.
And you can really treat those LLMs as a virtual colleague that happens to have a couple of PhDs. The value is not going in, asking for something, having it spit it out, and going about your day. The value is having a back and forth conversation with that LLM. I typically use ChatGPT for research, Claude for financial modeling and document building, and Gemini because we’re a Google shop to sift through emails and Google Drive files to give recommendations and reorient my day. When you’re doing that, the best action is to ask for something and before you make the ask, say, what do you need to know in order to give me the best result? The LLM will say, here are all the questions you need to answer. You answer the questions you have the information on. If you don’t, you go hunt down that information. You may use a different LLM to hunt down that information to automate and populate it. Now you have two LLMs working together. It sounds overwhelming and complicated when you first start, but this is 30 minutes a day for a week. You won’t be a professional after that, but once it becomes a habit, you’ll be gold.
Right. It’s funny because we’re here in Vietnam and there’s a big cafe culture here. We’ll go work from cafes. If somebody was looking over my shoulder, they’d know ChatGPT is my best friend. It’s there all the time. Now, when people are getting started, they have to get into systemization, procedures, using technology, and using data. What else would you say in terms of the systems and procedures piece that you would recommend for solo investors based on what you’ve seen on the institutional side?
One of the big common problems at large institutions is they often don’t have the same definitions across departments for critical terms. Property might mean something different if you’re in acquisitions versus leasing versus accounting versus capital raising. That becomes more complicated if you invest in multiple property types across multiple geographic regions, maybe for multiple fund mandates for different limited partners. As that complexity grows, so does the pressure to have a common definition at the corporate level on what is unit, what is asset, what is occupancy. When you’re a solo practitioner, you won’t have this problem at first. But it will be important if you’re leveraging your own capital now and later want to get a loan from a bank or an angel investor. You want to know the type of information they’re going to need whenever they ask so you’re not spending a lot of time hunting it down. If you’re getting a mortgage on a house or a retail property or an industrial warehouse or office building, what type of information do you need to provide every month or every quarter? Having all of that information easily stored digitally where you can add to it and have an auditable footprint will help you later. Businesses get audited all the time. If you’re being an investor, you’re starting a business. You need to have all of that data in a place where you can store it, easily access it, and define it. That is paramount to do at the beginning.
As you described that, it reminds me of something I think about with my own investing. Back in my bachelor’s in business, I had a professor who would help people with their resumes. She would say somebody has to be able to look at your resume and see the story. You have to put the pieces in there where it’s a story and not random threads. I think about that with private money lending. When a borrower comes to me, I need to see the story from them. They need to sell me on the story of the property they want the loan on. If I’m going to get investors to be a part of my lending, I need to show them the story of what they’re investing in. What wisdom would you give to people about making it a cohesive story? How can they use that data to really show the story to a bank or capital partner?
You first need to know what that capital partner requires to make a go or no go decision because not everyone is the same. Directly ask, I’m evaluating a potential property for investment. What would you need to make a quick decision other than my track record? Assuming you trust me as a person, what do you need to know about the property? You’ll get that feedback. AI will tell you everything you’re going to need up front. On the flip side, they need to know why they’re not just betting on the horse but on the jockey, you, to run the process. What is your operational background? What’s your history? Why are you going to execute whatever the underwriting assumptions are about that property? Are you experienced in property management? Do you have good relationships with vendors? Are you aware of the pitfalls about that property type? There will be standard data pieces like expected net operating income. You’ll build a P&L and balance sheet for each asset. There might be questions about cash flow. Are you distributing checks every month to an investor or taking on a loan with interest only payments and a balloon at the end or amortizing it? How long are you holding the asset? Are you building payoff into your return or is it about cash flow? All of those detailed data points are important when telling the story to a capital provider. Most people do not care about the IRR multiple you’re telling them because they’ll be skeptical. They want to know if they can trust you to get close to the numbers you’re representing. The numbers matter less than trust in the person running it. Once you’ve built trust, they’ll want to know more about the numbers. Then they’ll dig into unlevered yield on cost, expected equity multiple if you sell in three versus five versus seven years, risk of getting the right tenant at the rents you’re projecting. It starts with you, your background, and methodology, then goes to the specifics of the assets.
Now, Kevin, you talk about all this data and these terms. Is your background in finance or something data focused?
Kind of.
I started in financial management out of Texas in 2004. I spent three years in wealth management. I was at A.G. Edwards and then Morgan Stanley and all the deals I worked on were real estate deals. I’ve been doing real estate for a long time. I didn’t dig deep into financial modeling until I got my MBA from 2008 to 2010, which was during the financial crisis. There were not going to be banking jobs to go back to, so I pivoted to a big four firm doing technology consulting for real estate companies. That was the only part of the market growing because deals weren’t happening. Everyone was entrenching and needed to improve operating margins, and technology was the way to do that. I learned technology, probably initially kicking and screaming, but now I love it and embrace it. It was an odd journey.
I am a detail oriented person and like numbers. The challenge for many real estate investors is they are not naturally detail oriented. They are decision makers and extroverts. For people listening who feel like this is a lot of data and particular detail, what is your wisdom for those who are not data types? How can they hold their own and do well as investors when it’s not their natural skill set?
At the beginning, use AI. You can literally tell it, I’m not detail oriented and don’t know all the particulars of this asset. What are investors going to ask me for that’s important? You’re having a back and forth conversation, trialing with it, recording the information so you have data at your fingertips. Eventually, once you have a couple of properties, you’ll hire for that role. You’ll hire a detail oriented analyst or fractional accountant whose role is to be in those meetings and handle details. You’ll go out, tell the story, and raise capital. Until you get to that point, have AI be your thought partner as you pull together the story and information.
I love that tip. AI has been helpful in financial analysis and providing wisdom. I would add that many real estate entrepreneurs cannot pull their own data because their accounting isn’t up to date. One of the first steps is making sure your numbers are current so you can evaluate accurately.
Now, as we wrap up, I want to talk about your personal investing. What are you excited for in your investing journey in 2026?
It’s transitioned. I was excited about stealth storage for a long time. We had a couple properties. People say they’ll be responsible with their belongings and not buy too much stuff, but they do and hold it forever. That has been a great asset class for the last 10 years. More recently, I’m bullish on senior housing. This is probably not for someone’s first property because the capital commitment can be large. The demographics support it. As the older generation becomes empty nesters, once kids are in college or grown, many want to find a new community and retain connection. They don’t need nursing home level care but want active living community. I think demographics are pushing toward that being a huge demand driver. It might be early in 2026, but getting ahead of the curve and finding existing properties to renovate or land to build a community over the next few years addresses that need.
I love that. I’ve seen it in a few places. It’s not the hot thing right now, so getting in early makes sense. I think about how fun dorm living was in college with friends right there. Senior living can give that opportunity at another stage.
On the other end, in Dallas we’ve invested in a concept. The first club is called Stone Throw and the parent company is Roster Clubs. The thesis is private clubs are usually made for parents and not for kids and families. There’s a hole in the market for clubs that prioritize the entire family unit. Keep kids happy, excited, and safe so they have fun, and parents have freedom to have their own time. In many communities, you’re not building new country clubs, but you might repurpose an asset designed specifically for families. I think that part of the real estate universe is going to grow in the next five years.
We’ve seen social clubs becoming more common, but not kid friendly. That resonates.
Be on the lookout for those.
I remember when we moved to Chattanooga in 2020, we toured a club reopening. It was great, but our kids would need a babysitter every time because there was nothing for them. It was a non starter. Any other future tips to look out for?
Industrial outdoor storage was exciting for a while. You may have missed the boat if you haven’t invested. That was a smart repositioning of equipment yards. There will be other niches like that. There’s a lot of capital at the top looking for safe assets. Competition for traditional real estate is high and cap rates are pushed down. As an individual investor, look at emerging categories.
I love that. Kevin, if people want to learn more about you, what’s the best way to connect?
Find me on LinkedIn. I spend a lot of time there. Search for Kevin Shtofman.
Perfect. Thank you so much, Kevin, for coming on. This has been an amazing conversation. If you loved today’s episode, subscribe and leave a review wherever you’re listening or watching, and join me again next week.