Strategic Techniques In Solving Business Problems | Roger Smith & Zain Jaffer

TermSheet is a cloud-based platform exclusively built for the real estate industry that marries your workflow with your data. Our two product suites, Productivity and Intelligence, provide your team with all the tools and information they need to execute deals faster and more efficiently.

TermSheet makes it easy for real estate teams to analyze, visualize, and act on any data by automatically synthesizing information once trapped in spreadsheets, PDFs, and folders.

TermSheet’s powerful productivity tools help real estate teams execute deals more efficiently through seamless collaboration, streamlined workflows, and a centralized database.

---

Strategic Techniques In Solving Business Problems | Roger Smith & Zain Jaffer

It's always evolving and this is why I said to try to learn what the priorities are for the people on the other side. Hopefully, the company is organized enough where the priorities are clear. The priorities should trickle down when it comes to how goals are set by a company. The CEO's goals trickle down to the executive team, which trickle down to the VPs and eventually to the front-level people. Why don't you start to go beyond how is my product being used? Do you start to focus on what your problems are? What are your strategic priorities? You realize, "This isn't a strategic priority for this company."

They're competitive with the same strategic priority. "I'm playing chess. I'm thinking beyond what product features exist. These guys are trying to solve a bigger problem." This is an expansion opportunity for us that matches our vision. Eventually, I did this. I'll give you one quick anecdote. We were trying to diversify our revenues as an ad platform beyond iOS being at the mercy of Apple. We also wanted more channels to be on Android and Google. We partnered with Amazon and Microsoft and knew that for them building a third-party developer ecosystem at that time was a priority.

We worked on that to the point where I finally got a meeting with Satya Nadella, the CEO of Microsoft. Once you realize you're solving a problem and building a product and that product gets visibility in the company, suddenly, you're not just a CRM tool and a data management platform. You are the way they run their business and achieve their strategic priority. The world changes for you once you talk to customers differently.

How did you go about doing that, out of curiosity?

We talked to big companies. We knew they wanted to get into the app space and we wanted to build a product that would diversify us. We're thinking, "How do we grow beyond iOS and Android?" Amazon and Microsoft candidly where potential acquires for us too. They’re big companies. You figure, "We're hearing that they want to develop a developer ecosystem. Let's talk to them and try to see what they're doing. This is a strategic priority. This SVP's neck is on the line because this guy's being tasked with building a developer ecosystem. Why don't we come and help them?" We asked, "How can we help you?"

It turned into you investing in this initiative. All types of things happen here by then. This is how you do corporate development. If you want to get your company acquired or you want good acquisition opportunities, you need to develop a corporate development arm or initiative where you will partner with large companies in your below strategic projects. This is tough because it might not be a long-term thing for your company like the strategic project. Suppose that a strategic project can make a difference for the acquirer, it’s interesting. I might not even tell them about that acquisition. We had a discussion and it's far along in the past.

I wouldn't say it's confidential. It's smooth and irrelevant. We had conversations about some of these large companies investing in our company being part of our next growth round. That's how we did it. We eventually took a lot of money and co-development. It would subsidize our development. We used all of the resources that Microsoft and Amazon both had. We were piggybacking on their sales terminals. We were invited on stage and at conferences. That's because we were pitching our company as a solution to a strategic problem.

That's funny you say that. We're going through a pilot. This is not even a decision-maker thing. This is, who was under pressure to solve this problem and experienced it the most? We need to do anything and everything going back to the viewer doesn't scale thing. If we can buy this person groceries and deliver them to the house and that makes their life better so that they can more effectively do their job, that's what we need to do. We need to make his life or her life better so they go off our products that were a key part of the way they work. They can't operate without us. That's what we're living and breathing. It's interesting to see that holds true.

In an earlier segment, we were talking about not being distracted and focusing on a core problem. This isn't a distraction. This is product development. When you're asking what someone's problems are, what the strategic priorities are and you're seeing that resonate across different client bases and you go build that out, that's how you run a company and do product development. I was trying to scare everyone when we talked about how you shouldn't have a top-of feature and how it can blow up the code bases.

If you're doing this based on what you think is needed and you don't have a core yet, you were fumbling together trying to hack something together. How many times have I heard and once I fell victim to this and almost noticed a startup, "I'm going to be like Google with Facebook and Clubhouse combined?" No, do one thing well. Once you did that one thing well, then add another thing on top but make sure that you've got customers that are willing to buy that and use that.

No matter what you're selling, at the end of the day, someone has to have a problem that you are trying to either solve or make their life simpler or easier in some way. You can talk about the fact that you have features X, Y and Z. For them to even experience problems X, Y and Z, they need to get past problems, A, B and C. Think about TermSheet. Our whole vision is this data management platform. The idea is that real estate teams across the board have all this disparate data. Whether they've collected themselves, they're consuming it from other places, whatever it is that they're maintaining.

No matter what you're selling, at the end of the day, someone has to have a problem that you either are trying to solve or make their life simpler.

They know they want to do something with it but they don't know how to get started. I talked about the data journey where we think companies will get to. Everyone's at a different step on that journey. Oftentimes when we talk to teams, it's like, "That's cool. I know I want to use my data but realistically, I'm trying to manage my deals and make some sense out of the chaos that goes on my deal team when my managing director asks me, 'What's the status on these ten deals? Has this offer been accepted? Where's the LOI that I wrote for X, Y and Z?'"

That's the problem that they're facing. Our belief is that we can help them solve that problem. Eventually, they'll be able to begin asking the questions. "I have all this data either I've collected from my deals or researched on," which they can leverage to inform their decisions. They know they want to get there. They're not even going to be able to get there unless they can get out of the chaos of daily work.

That's somewhat enlightening when you realize your product is solving so many problems. They can improve their workflows so much more by using a solution. There are even more things they can do. Before, they were complaining, "I had no shelter," now they're complaining, "I'm bored. I want to have some entertainment." See the difference there? It’s different degrees of problems. It's very enlightening because if you have a customer that doesn't use your product yet and you're seeing how they operate, the problems they have is so ancient.

People that use our products have different problems. They're asking to do more with it and operate at a higher level. I don't want to use war analogies or religious knowledge. It's like a crusade. It feels like a holy type of mission that you have. You need a commercial sales team. Your sales team isn't selling something. They feel like, "This customer needs this." It's like where the medics were coming on the scene. Those are technological solutions to make their life easier.

This is why internally, you should always have case studies and show your company, "This customer used us. This is how they operated before and now. Look at the questions they're asking, business decisions they are making, how much more revenue they can make and the feature requests they have." When you go into the field and you're dealing with these other customers who don't know what we do, imagine how much of a duty you have to help them. They're struggling.

When your sales team acts like that, you can never motivate them with commission or salaries. They can be motivated with teamwork and recognition but that inspiration and impact are what will motivate them to be like, "I missed a customer." "You need to listen to me. That's why they'll knock on the door and get that sale for you." It's exciting when you have a part that can even do that.

We call it a journey. You can use the crusade. The idea of the steps that you're going to take to get there is the vision. Part of that is we don't know exactly the end of the journey but we believe that by doing these things along the way, this vision or dream of data-informed real estate investing, buying or whatever that acquisition can become more of a reality than it has been now.

Let's dive into this. What is data-driven real estate investing? What's happening? How are funds and real estate investors managing themselves? How should they be doing it? Walk us through the problem, where you end up and what the solution looks like?

I don't know about you but as long as I've been in this space, the way real estate investing has been done, even at billion-plus AUM funds, has been generally driven by the gut. What happens is an acquisitions person will find a deal and underwrite it. If the financials look good, they'll use data to support the decision as opposed to informing the decision. Fundamentally, you're buying up a business when you think about real estate property and the financials are important.

There's been this idea of, "There's all this data out there." Traditionally, it's been about third-party data. If you think about companies like Placer AI or unit casts that are collecting foot traffic data, you combine that with publicly available data sets like permits and employment data, some might look at tree cover data and satellite imagery to inform, not only at the property level but potentially at the market, the submarket and bigger level to help identify opportunities. Lots of companies are trying it. It's picking up a lot of steam but it's been a process that people have thought about for a long time. It hasn't happened. It's all been gut. You have these worthless documents that are like, "Here's the 1, 3, 5 male population in any marketing piece of material.”

The macro-level data that is in the marketing brochure has been put together by a broker.

It's like, "What do I do with this? That's cool. How does that make my desire not to buy?" The pages have to be filled out, so they might as well put some market data and that's the way it's been done.

When you get in these brochures, there are pictures of the interior, maps and pictures of the local amenities. I don't even have people look at this data but there's also data for the sake of there being data, supporting stuff. Here are the population and the income. These are important but they're supporting rather than informing.

The dream of most people is to say, "I have these models." I'm not talking about AVMs. That's thrown around a lot but these models that can understand my business help me decide whether a particular opportunity that comes across my desk is even worth my digging in. That's one thing. Two, models that are potentially identify regions, whether it be a market of some market or smaller of where I should be potentially looking.

Screaming and opportunity analysis is what you're saying.

Yes. I won't say the names but there are companies, both large and small, who are hiring data science teams. You see it across a lot of the spaces where they're hiring their internal teams to build data links and data warehouses to collect all this data to help build these types of models. I don't know yet if it has been successful. I know they're doing it and making investments in it. If it hasn't been successful, what level has it been?

You can see the 20 other deals that you didn't look at, but someone on your team looked to really help better inform your decision-making.

Most likely, it won't be successful because all of these businesses have a core. It's a fear-reactive move. It's much better to use a third-party expert. Unless there's complete board-level CEO level, complete company level alignment and they're focusing on this as the only thing they do, they'll do it well. Otherwise, in most cases, people are taking a job at a real estate company. They'll do better than they were previously but it won't be transformative versus a specialized vendor.

That's why I like investing in PropTech. There are focused startups that can solve strategic priorities for companies. Moving back to the customer problem, this is a market where there's a lot of froth and people are getting a lot of FOMO when they bet on a property. When we bet on a property, we don't understand how the winner paid.

I've spoken to many winners. Here's, frankly, when it comes down to. "We have a lot of capital we need to deploy. We’ve seen a lot of dry powder. We had a few assumptions in our models. We're assuming that the cap rate might be reduced when we sell the property." You're like, "What?" "In our models of Bluefield, we assume the cap rate is going to be the same where it's going to go up," if you were to reduce the capital and the other thing. "We have a few assumptions around the debt around the interest rate." If your interest rate assumptions are like this and the market moves and interest rates increase or the cap rates go up, you are so screwed.

Those leavers are so easy to model. The truth is most fund managers don't even look at those. All they look at is, "What's the IRR? How do we make this IRR what we want it to be?" This trend is happening too. It's not about 20% gross IRR. "The market's changed. Our LPs want us to deploy capital. We'd be okay with a 10% IRR. It would be okay with a 5% IRR."

This is when this danger is happening. It's turning into fear-based decision-making. You've got models on the spreadsheet that are being fine-tuned. Those leavers are not very solid. There isn't real data backing it up. Gut instinct feels right. "Let me call up my friend who's a broker." This broker said, "That's pretty good." It's ridiculous how our decisions are being made. It's absurd.

One of the things that we've seen and one of our beliefs at TermSheet is there are mountains of spreadsheets that are sitting in a folder somewhere that has a ton of valuable data that you don't have to pay for. You've already created it. Our real belief is we can help teams unblock that data. When you do go look at a property and say, "What are the average rents in multifamily? What is the average asking cap rate or tendency for a bid cap rate," you can begin to build your comps based on your data.

Where we see a ton of value from our platform is ingesting historical data from these groups, so when they go look at a deal, they might say, "We've looked at 20 other deals within a 1-mile radius of this particular property. How did we go get the deal? Where did it trade? What do we underwrite it at? What was the bid at?" More effectively inform the particular investment that you may be looking at. That's where we believe we're unlocking this internal data. You're not necessarily always relying on some report.

It's data that is fundamentally the right way to do it. You're building on how you make decisions. You're creating a decision framework in your company or fund by making decisions appropriately and looking at previous decisions. Any company doing things like postmortems and analyzing what went well, what didn't work well and creating patterns is key doesn't seem to fit in real estate. It's hustling from one deal to the next deal. It’s not, "Is this the right deal for us? How does this compare to other deals we've looked at?" Taking external data, comparing it with internal data and then making a decision that's right for you and your fund’s returns is where real estate will eventually be.

That's what we believe too. It works if the acquisitions person will say, "I remember we looked at a deal years ago down the street. Let me dig through my emails to pull up the OEM." With a platform like us, it's like, "You’re not only going to see that deal but you can see the twenty other deals that you didn't look at but someone on your team looked at to help better inform your decision-making." That's what we're excited about.

Some other person isn't on the team anymore. They left and you don't even know what you don't even know. Whereas if you have the infrastructure in place, you're building business intelligence. This is one of those areas for funds. It can allow them to compete. I used to say having Blackstone level technology and even Blackstone doesn't have the best technology, I've realized. The industry is wide open. I used to think when I first started that these small funds needed to compete with the big funds and have the same technology. Don't make it complicated. No one's using technology, it turns out, in real estate. If they are, it's so primitive compared to where it could be and should be.

The size of the company doesn't matter. Traditionally, you think larger companies and enterprises would be more likely to have this. What we found the size is not necessarily qualitative to their tools or desire for data. Sometimes, it's the opposite, where the larger funds have a bigger problem because instead of looking at 100 deals a year, they’re looking at 1,000 deals a year but they're not doing anything with that data more than the guys looking at 100 deals a day.

Any final thoughts to conclude regarding where PropTech is heading and in your segment specifically? What does the future look like? What concluding remarks do you have?

Honestly, there are too many opportunities in PropTech. Quite frankly, it's hard as an entrepreneurial-minded person to go look at all the inefficiencies that exist in the space and not bash your head against the wall. You're like, "We could solve that problem."

As a VC, I want to invest in every startup that I comes across. It's even harder as a VC because I see all the opportunities. What will your industry look like years from now? How will the funds operate?

I do think that data is going to be a part of it. I don't think it's going to invest in automated, AVMs or anything like that. There'll be more data points that will help teams be better informed. It's not necessarily that it's going to happen automatically. The data that's being downloaded in spreadsheets and called together by acquisitions teams to put together an IC memo for Monday morning pipeline meetings will be more automated because the data will be in the right place at the right time, allowing people to generate these reports but it'd be the right information that they need to make better decisions. That's my belief. It's not going to replace their decisions. It'll be more efficient to get to that point.

Here are a few quick yes or no questions. One, if this is the future, will the fund be smaller? Will they be fewer admin staff?

The size of the company doesn't really matter. Size is not necessarily qualitative to their tools or desire for data.

Yes, fewer admin stuff. We're already seeing it.

Will returns be increased for these types of funds?

Yes.

Doubling down on that comment, does that mean that funds that don't use this will make lower returns?

These funds will be able to do more deals more quickly. By doing that, there'll be able to deploy capital.

When a price has increased, are the funds able to extract the value?

If you believe in an efficient market, then yes.

I was going to say shouldn't return equalize?

Eventually, they will. We're seeing it.

This is how history has tended to repeat itself. People use the dumbest technologies possible to buy real estate and hold it because real estate goes up and up. Having said that, some real estate might go down a lot too.

It depends on when you're buying it. They underwrite it based on some crazy assumptions that historically haven't been true.

What it comes down to is this. The dream scenario is there will be a hedge fund that's able to get so much scale by using data to buy real estate. It means that no longer can our readers who want to break into real estate or own real estate already can play anymore. It's very hard for an individual trader. You can talk about Robinhood and the stock manipulation that happens. The cards are stacked against you. You either have the technology. You become giant and big or you don’t. Aren't there going to be barriers to entry eventually on the real estate funds?

It's happening. Look at mobile home parks. That's a classic example. Years ago, you couldn't touch a mobile home park in an 8% cap. Now, you can't find one above a 6% cap or 6.5% cap. Why is that? It's because the institutional investors have come in and bought everything up. Their capital is cheaper. They can deploy it quickly. Is there an opportunity still in mobile home parks? Yes. Where it exists is $1 million and below parks.

My belief is that opportunities will still exist. They'll just be different. Think about people looking at Airbnb rentals. They’re like, "I can't buy an apartment building because it's a 4% cap. I'll buy an Airbnb." Eventually, there's going to be a fund that only invests while you're seeing it in these single-family rental SVR funds. They're going to start gobbling all those up.

PropTech is going to hold a lot of premises. There'll be more data-focused approaches. Real estate funds are going to be left behind if they don't adopt the technology. The ones that adopt technology are going to get larger and have more scale and data. Prices are going to go up across the board. No matter what happens with cap rates and interest rates, inflation is real and real estate values will increase. People will pay even more for real estate when they realize how valuable it is. On that note, that was a positive note. Thanks for coming to the show.

Thanks, Zain. I appreciate the time. It's good to talk to you.

---

Subscribe to Zain Jaffer: https://bit.ly/2SWhYW5

Follow the PropTech VC Podcast:

Listen on Apple - https://apple.co/2Izoznu

Listen on Spotify - https://spoti.fi/2STWDwq

Listen on Google Play - https://bit.ly/2H7s6c0

Follow Zain Jaffer at:

Twitter: https://twitter.com/zainjaffer

Website: https://zainjaffer.com/

Current Ventures: https://zain-ventures.com/

LinkedIn: https://www.linkedin.com/in/zainjaffer/

Creating the World's First Co-Living Start-Up: https://www.youtube.com/watch?v=K2MQNZnfvOA

Innovative Housing that can change the world! https://www.youtube.com/watch?v=K92fRT04Qjo

Building an Online E-Commerce Furniture Empire: https://www.youtube.com/watch?v=WhznBbYMhhg

About Zain Jaffer

Zain Jaffer is an accomplished executive, investor, and entrepreneur. He started his first company at the age of 14 and later moved to the US as an immigrant to found Vungle, after securing $25M from tech giants including Google & AOL in 2011. Vungle recently sold for $780m.

His achievements have garnered international recognition and acclaim; he is the recipient of prestigious awards such as “Forbes 30 Under 30”, “Inc. Magazine’s 35 Under 35,” and the “SF Business Times Tech & Innovation Award.” He is regularly featured in major business & tech publications such as The Wall Street Journal, VentureBeat, and TechCrunch.