Transparency in Commercial Real Estate Data with Michael Mandel

About Our Guest

Michael Mandel

https://www.linkedin.com/in/mmandel/

Michael is the Co-Founder & CEO of CompStak, a marketplace for commercial real estate information. CompStak uses a crowd-sourced model to gather real information that is hard to find, difficult to compile or otherwise unavailable. Our first product is a marketplace for the exchange of commercial lease comparables. Users add the comps they have to find the comps they need. CompStak was born out of Michael’s experience as a commercial leasing broker in Manhattan. He has been recognized for his success as Grubb & Ellis’ National Rookie of the Year in 2007 and Real Estate New York’s 30 under 30 in 2008. CompStak has been featured in The Wall Street Journal, The Real Deal, Forbes, Bloomberg, AG Beat and more.

Resources mentioned

LMRE website www.lmre.co.uk

UKPA website www.ukpa.com

Compstak website www.compstak.com

Michaels email michael@compstak.com

Insights from this Episode

• Data in its most granular, basic form has been used in the industry forever – Michael Mandel
• The idea behind CompStak was simply to move that that trading of information from offline to online – Michael Mandel
• It was years before we started entertaining partnership opportunities, the reality is that you need to be focused on your core business early on – Michael Mandel
• It becomes like a virtuous cycle where more data leads to more insight, and then continues to make it more important in the industry – Michael Mandel
• You need to get the fundamentals right before you start looking at those data on the fringe – Michael Mandel

Episode Transcript

Louisa

Hi everyone and welcome to the Propcast, my name is Louisa Dickins, co-founder of LMRE and board director of the UKPA, and I shall be your weekly host. Each week for 30 minutes, we will be connecting the VC, PropTech startups and real estate professionals globally, and assist in bridging that famous communication gap we tall love talking about. So, sit back, relax and enjoy the show. Hi, everyone, and welcome back to the podcast. Today we will be talking about transparency in commercial real estate data. And our guest today is Michael Mandel, co-founder and Chief Executive Officer of CompStak, so welcome to the show Michael.

Michael

Thanks for having me.

Louisa

And now those are listening CompStak is a US founded real estate data analytics company, leveraging crowdsource commercial lease and sale transaction data and property information combined with AI driven analytics. Compstak’s 30,000 members provide data covering the entire US, and it’s paying customers include the world’s largest real estate investors and lenders, which I’m sure you know some of these names, it’s JP Morgan, Blackstone, Brookfield and many more. Additionally, CompStak has grown a strong data partnership business through data license and API integrations with firms like Moody’s, Realpage and the list can go on, just check out the website after the show. And now since launching CompStak in early 2012, Michael has helped navigate the company through tremendous growth with over $30 million raise hundreds of markets launch. And your team must be well over 100 people now Michael, and offices in the big cities, New York, LA Chicago, Atlanta, and the list goes on.

Now Michael has also been named 30 under 30 by Real Estate New York and the rising star buy the Real Deal. And I’m sure some of you have also heard Michael speak on the future of commercial real estate, real estate technology and data transparency before, and his speaking engagements include talks from the ULI, Wharton School, Columbian University. Michael is also a star and has appeared on Fox Business, public radio and featured on Wall Street Journal, Forbes and various other notable publications. Hopefully this gives the audience a good flavor of your background, Michael. Now, rather than me talking let’s hear a little bit more about you to your journey to founding CompStak.

Michael

Sure, absolutely happy to do it. And thanks for the very nice introduction, it makes me feel like I’m a very big star. So yes, by way of background, before starting CompStak I was a commercial real estate broker, or in the UK I’d been an agent. And I worked for Grubb & Ellis, which is now part of Newmark. And I did office leasing transactions in New York City, and I also did data center transactions throughout the country. And the idea for CompStak came out of my experience as a broker. In that I was trading data with other brokers all the time, in particular commercial lease comps, so detailed records of commercial lease transactions. And I was trading this information with other brokers over the phone, via email and in our weekly Monday morning meeting where we’d all sit around a big boardroom table and talk about all the deals taking place in the market. And it occurred to me when I was in one of these meetings, just the whole process was a waste of time, because I would be frantically calling up other brokers that I know on Sunday night at CBRE or at JLL or Crispin, or whatever the case may be so I could bring comps to the table on my Monday morning meeting. But mostly, people were talking about hedge fund deals and law firm deals and bank deals, and I was mostly representing tech companies and different neighborhoods where it wasn’t relevant.

But at the same time, when I am working on a deal I would want to know about the relevant deals at that time. And so the idea behind CompStak was simply to move that that trading of information from offline to online, so that our members who are brokers, appraisers and research people within real estate brokerage firms could share information on CompStak, earn credits for sharing that data, which is like a virtual currency, and use those credits to get other data back out. And that way you can actually get the specific comps you need, when you need them, and when they’re relevant for the deals that you’re working on. So that was the original concept and we continued to grow from there.

Louisa

And that was what I had a big question about, how do you almost like monetise your product? And how do people get stuff back? Your customers will get all the data but you as an owner with the premium content, how would you monetise it, but that makes a lot of sense in terms of tokens?

Michael

Well, there’s no monetary value to tokens or to the credits on the exchange side of our platform. So actually, you can’t buy credits, you can only earn credits by submitting data. The way that we make money is by selling subscription access to the data. So we effectively have two sides of our platform. So there’s CompStak exchange, where the brokers, appraisers, researchers, share comps and get comps out. And then we have CompStak Enterprise where we sell subscription access to that data to banks, private equity funds, sovereign wealth funds, hedge funds, pension funds, insurance companies, institutional real estate owners, flexible office, space companies, you name it. And so they pay for access to our data, and the data we’re selling them, it’s lease comp data, sales comp data, property data. And then we have an analytics suite that sits on top of all of those data sets, and lets you get more insights from it.

Louisa

So anyone can go on and put this data in and that’s how you create complete transparency in data?

Michael

To some extent. It’s not anyone, so only people who are commercial real estate brokers or agents, appraisers, valuers and researchers within real estate brokerage firms. Anyone else would have to pay for access to the data.

Louisa

Okay, cool. So that’s a good vetting process behind it as well. And since you grew in 2012, how has this whole data platform changed? As your brand grows as well, you must be storing so much data, you said how it varies from of the brokers to hedge funds who are using this. How big is the data platform now?

Michael

There’s several million comps in the platform, there’s a couple million properties, there’s something like I think 25 billion square feet worth of transaction data, give or take something like that. So there’s a lot of data. It’s growing exponentially. I think last quarter, we brought in about 250,000 comps and that includes recent deals and a lot of historic deals. And the crazy thing too, is that the data that we bring in from our members, this is information coming in in Word documents, Excel spreadsheets, in the body of an email, we get PDFs, we get scanned PDFs, we have people send us pictures of post it notes, it’s crazy. So we’re bringing in really like dirty unstructured data, we have to make sense of it to get in the system and get a live on the platform.

Louisa

Yes, that’s a big old task. So who’s doing this, is this data scientists who are looking at analysing this data, how are you converting it?

Michael

So it’s a combination of things. So when we first started, it was just a team of people, well originally it was me! But after that it was a team of people in our New York office who were manually reviewing every comp, then that team grew. And we from there found that we’re just bringing in too much data, we couldn’t do it all manually. So then we built a heavy amount of machine learning and AI on top of the process, and other technology methodologies around normalising and cleaning up the data, where we could automate a lot of what the analysts were doing, we could learn from the decisions that they were making, find, patterns in those decisions and make those decisions in an automated fashion.

And so now, something like 80/90% of the data that comes through gets processed in an automated fashion and then the remainder gets reviewed manually by our analysts. I should say there’s still a good amount of work setting up the data, for it to even get into the system, whether it’s manual cleanup or some of its using optical character recognition and even deep learning. And we’re looking at the logos and files and using the logos that are on a file that indicate the quality of the file based off of where it may have come from, the brokerage firm that submitted it or things like that. Natural language processing, and all sorts of stuff like that. But also now we’ve built a process and we’ve actually built our own team, we just recently incorporated and set up an office in Belgrade, Serbia. And we have a team of people in Serbia that work with us who manually review data as well and work in conjunction with our team in New York.

Louisa

Oh, wow. And to truly going global. And now Michael, are one of our earlier guests on I think it was Season Two of this podcast was with the well-known founder LD of Cherre, who I see CompStak has partnered with. At first, I thought and maybe naively I would see that as competition, can you tell us a little bit more about the partnership and how your businesses complement each other?

Michael

Sure absolutely. Well, what’s somewhat unique about CompStak, particularly in the latest iteration of the PropTech and real estate data, is that we have a quite a unique proprietary data set. And so a lot of the other data companies out there are focused on how they analyse data, bring different data sources together and make sense out of that data. And we do some of that in house as well. But we’re really actually complimentary to a lot of those companies, because we’re one of the data sources that they would want to pull in for their clients to allow them to make better sense of their internal data alongside market data. And so in the case of Cherre, that’s where the opportunity lies, that maybe they’ll bring in data from one of their clients, maybe they’ll bring in some other external data sources, maybe it’s economic data, employment data, credit card data, whatever the case may be, and leverage our transactional data for leases and sales alongside that. And so effectively, the way it works is if one of their clients is a CompStak client and has basically signed an agreement with us to have access to our data, that will allow those clients to leverage that data within the Cherre platform.

And more broadly as we think about partnerships, because of the uniqueness of our data set, we’ve been able to structure similar deals with a lot of different firms too. The most notable recent one was a deal we signed with, with Trepp. And Trepp is the leader in commercial mortgage-backed security data and loan data, and so we’ve been able to pull in some of our aggregated data into the Trep platform for all of their users. And then for Trep users who have CompStak accounts, they can see our very granular leasing data within Trep. And that’s really helpful, when they’re looking at the CMBS and the properties that go into a package of loans. They can actually see the underlying data within those properties to better understand the risk of those of those loans. And there’s the security effectively, right. So I think we ended up being complimentary to a lot of companies out there. And we’re actually about to announce a very big partnership, where we’re bringing in a new asset class into CompStak where we’re bringing in a partner’s data into our platform, which we’re very excited about. I’m not ready to announce it yet.

Louisa

I’m looking forward to that, Michael, very exciting! I will have to wait see. Is that coming out in 2020 or 2021?

Michael

Well, we may announce it in 2020, it probably won’t be live on our platform until 2021.

Louisa

Awesome, exciting times ahead.

Louisa

Now for some of our listeners, they vary in terms of what they do from startups to the real estate guys, to finance. Now for some of the founders maybe listening in an earlier stage to what you are, any advice? What would you say the right time to start looking at the partnership model?

Michael

Not too early, honestly. It was years before we started entertaining partnership opportunities, the reality is that you need to be focused on your core business early on. Now some businesses as core to their business, they rely on partnerships for that business to succeed but that’s tricky, right. If you’re like a proven successful, serial entrepreneur that’s built a reputation, then maybe you can pull that off and get into bringing partnerships into your business day one. But if you’re not, and you don’t have a lot of credibility, the big companies that are probably the most valuable for you to partner with, they’re just not going to want to waste their time with you. And from your standpoint too, when partnering with other companies it can create a lot of distraction from focusing on your core stuff. So I would say for most people, probably better to wait and do it when it really makes more sense. It’s tricky for us, because we have startups approach us every day who want to use our data and partner with us in some way. And even today, we have robust API’s that make it a little easier to do these deals, but at the same time they can still be distractions. We have other things we got to worry about and other work we have to do. So you have to really be thoughtful about it, if you jump into all of them, you’ll end up burning too many cycles on these things.

Louisa

Yes, I definitely echo that. I think our business LMRE, our day-to-day job is recruitment and helping businesses, startups scale and hire. But outside of it I’m looking at different partnerships and associations, I’ve got one with the PropTech Collective, or the podcast, but it gets so easy to get distracted. And then before I know, I spent three hours talking to people on a podcast, two hours drawing up an association agreement, and then my founder Brad’s is just like, “Lu, don’t you realise we run a recruitment business? You just spent two out of five days this week not doing the job!” But it’s definitely I think, timing is comes into it and managing your time as well. So let’s go on to a big topic, we’re saying this podcast is on the transparency of data, when did you see data start becoming super important? Cash is king, as everyone always says, but data really is king and cleaning up. When did you start seeing more of a movement?

Michael

Honestly, in my mind, data has always been critical. The whole basis for CompStak was around the fact that before PropTech was even a term, I was using data every day and doing transactions on a day-to-day basis. I think that a lot more of the maybe excitement and it’s funny actually, I was on a panel just a couple weeks ago, and somebody asked me when did data move from the back office to the front office? And I said, no the data was already in the front office, it’s been moving to the back office. When I was a broker I was a front office person, but I needed to use comp data every day of the week to get deals done. I think that it’s actually now where we’re seeing companies build out data science teams, and robust research teams, where they’re trying to leverage bulk data in a lot of different ways and get insights from it.

But like data in its most granular, basic form has been used in the industry forever, maybe it was traded over the phone, or in meetings, or informally, but was it’s always been very, very critical. Now, though, I think it’s become table stakes. It used to be I think that it was relationships first, data second, I think it’s now data first relationship second. And you have to be on top of your game in the market. And there being more data and there being transparency and data actually creates more need for data, because as more people are using it and the market becomes more efficient, you need to have access to it to know where things stand. And so it becomes like a virtuous cycle where more data leads to more data leads to more data leads to more insight, and then continues to make it more important in the industry.

Louisa

Does more data ever mean more problems in terms of us keeping up and making sure it’s clean? Like all the data on your platform, certainly a number one priority is making sure that it’s good data on and you’re filtering it through non stop. Surely there’s quite a few obstacles ahead of us in terms of data?

Michael

Oh, absolutely. Data in the commercial real estate industry or the property industry, as you guys call it, is just very messy and completely inconsistent. Every market is different and when I say every market, I don’t mean every market by virtue of country, I mean every market by virtue of a tiny, local level. In San Francisco, rents are quoted per square foot per year. But you go right over the line from San Francisco into the greater Bay Area, and rents are quoted per square foot per month. The terminology and the structure of data, the way people think about it varies dramatically across the industry. And so yes, having more data creates lots of problems and challenges to overcome.

The other aspect of it too, is I think there’s been an obsession in the industry in the last few years around alternative datasets. How can I determine the value of a property based off of its proximity to parks, or the number of incidents of robberies nearby, or the credit card payments of x, there’s a million different data sets. And some of them are really interesting, and some are not as interesting. But I think that there’s been almost an over indexing on these alternative data sets because the reality is, there are data sets that are fundamental, and then they’re called alternative data sets because they really are alternative, they are not the fundamental data sets, and you need to get the fundamentals right before you start looking at those data on the fringe. So we’re focused on fundamentals, leasing data is absolutely core, because it drives the income of the property. And investment grade assets are valued on an income approach and so understanding the income is absolutely critical. Sales transaction data, what the property sold for it, it is critical. We’re focused more on those datasets than on the alternative data sets, although I do find those interesting, but I think there has been a little bit of over indexing in those areas.

Louisa

Well, we’ve got another asset class which is going to be added to a dataset, so we look forward to that happening. And now we’ve nearly gone through a whole podcast without mentioning the COVID word, what’s the what’s the biggest disruption you’ve seen COVID cause in the market then? Focusing on the US market.

Michael

Well, it’s a million different disruptions. On a personal level, I’m doing this podcast from home, and I’d rather be doing it in the office. But I would say, in the data that we track retail has been the most impacted. That’s no surprise there, retail has been destroyed. Certainly offices impacted meaningfully, even industrial we’ve seen in a lot of markets, industrial rents have even gone down a bit even though industrial has been viewed as being very strong in the market. So there’s nowhere without impact, but it’s also creating interesting opportunities for different firms. We’ve seen an increase in interest from hedge funds that our data because they trade on instability in the market and they’re trying to capture value from this. So it’s hard question to answer, because it seems like just about everything has been disrupted by COVID.

Louisa

Yes, it’s a very good point, it’s very broad. I was on a panel the other day and they said, what trends are you seeing in the PropTech space? And I was like, well there’s plenty different verticals we can go into but I’ll just say data and sustainability to keep it brief. Michael we are coming to the end of the podcast and for our listeners tuning in, how can they connect with you? If they’re, brokers or agents, hedge funds, how do they connect with CompStak and with you?

Michael

Well, can certainly email me. I’m Michael@Compstak.com and I’m happy to respond and chat. I’m also on Twitter @compstakceo and I’m on LinkedIn and Facebook and all these other things as well, so whatever works is fine with me.

Louisa

Michaels it’s been an absolute pleasure chatting on the podcast, and I am looking forward to catching up with you after the show.

Michael

Sounds good, thanks a lot I appreciate you having me.

Louisa

Thank you for joining us this week on the podcast and a big thanks to our special guests. Make sure you visit our website www.lmre.co.uk where you can subscribe to our show, or you’ll find us on iTunes and Spotify. We’re all good content is found. While you’re at it, if you found value in the show, we’d appreciate if you could rate and review us on iTunes. Or if you simply just spread the word, be sure to tune in next Tuesday and I’ll catch you later.