Download podcast transcript [PDF] here: How CompStack CEO Michael Mandel Used the Value of Information to Create a Real Estate Tech Company that Raised 16.5M! TRANSCRIPT Time-Stamped Show Notes: Resources from this Interview: Leave Some Feedback: Connect with Eric Siu: Disclaimer: As with any digital marketing campaign, your individual results may vary.
Full Transcript of The Episode
Eric Siu: Cool. Great. How do you guys make money? What's the business model like?
Michael Mandel: Sure. The way it works is we have two sides to our platform. We have CompStak exchange, where commercial real estate brokers, appraisers, and research people within real estate brokerage firms share information on CompStak. They earn credits for sharing that information, which is like a virtual currency. And they can use those credits to get other information back out. And then we end up with a comprehensive database, of all ... In this case, the least comps of the market. We now do other information as well. And then we sell subscription access to that database to commercial real estate investors, and lenders, primarily. Our customers are people like Wells Fargo, and J.P. Morgan, and Blackstone, and BlackRock, Tishman Speyer, Brookfield, what have you ... Major institutional real estate investors, and lenders pay for access to our data, and they use it to make their real estate decisions.
Eric Siu: Great. And so how did you I guess ... How are you pricing this right now? And how did you even come up with a pricing model? So two questions.
Michael Mandel: Coming up with a pricing model was an interesting challenge. We basically looked at the way other real estate data was priced. Or other real estate data services were priced. And a lot of it was per seat, but the problem with per seat was that when you're just starting off you can only sell a couple seats at a time. And when you're providing data you run the risk of it being used as a quote "librarian tool"... Where you've got one person who has access to the data, and they share it with everybody else ... And so the way we priced is we basically said, well what are the most expensive real estate data products priced per seat? For a minium number of seats. Initially, we did it for two seats, but we actually priced it even higher than that, and we said this is the minimum price to get in. For just originally it was just New York City, and then we expanded to more, and more markets throughout the country. But we've always actually been priced on the higher end of real estate data tools, but that's a function of the fact that our data is incredibly proprietary. No one else has the data that we do, and can sell it.
We felt that we should be a premium product, and we just went out there with that pricing, and people bought it. We continue to tweak our pricing model every day, and make sure that it fits the use cases of our customers, and meets the value that they're getting out of it, but there wasn't an exact science to it. It was ... We tried to make it as scientific as we can, but it wasn't easy.
Eric Siu: Cool. Yeah, kind of the assumption is that ... If so and so is paying this X amount, and we're delivering this amount of value. We should be able to charge this much, and then it kind of just worked, and you guys are tweaking from there, right?
Michael Mandel: Exactly, yep.
Eric Siu: Got it. So how much on average are you guys charging right now? Just so I have an idea.
Michael Mandel: For our core enterprise product, an average contract size would be about fifty thousand dollars. But our contracts range anywhere from low five figures, to high six figures, on the enterprise side of our business. And then we also do API integration deals, and partnership deals, and those are all six and seven figure deals.
Eric Siu: Got it. It just basically depends on the size of the company, right? Ultimately.
Michael Mandel: Yeah. Well, it's a function of. There's a ... We actually have a pricing matrix.
Eric Siu: Interesting.
Michael Mandel: That takes a lot of things into account. We built a calculator, and the calculator takes into account the size of the organization. The type of the organization that it is. Which markets they want access to. And how many markets they want access to. As well as the number of users. And basically, you plug in all that information, and it spits out a price.
Eric Siu: Love it. Okay. So your sales people if they're on the call they just use the price of the matrix. Spit something out, and boom there's the quote.
Michael Mandel: Exactly. Yep.
Eric Siu: Got it, okay. Love it. What other kind of numbers can you share around the business state? Growth rates, revenues, customers, things like that.
Michael Mandel: Sure. Well, our revenues have roughly doubled year over year. We are growing very, very well. Our user base tends to roughly double year over year, as well. And our database as well ... Our data growth has been pretty close to that. It's pretty exponential growth. We don't give out specific revenue numbers, but we're really happy with the growth that we've had, and we've been able to bring in some major institutional customers.
Eric Siu: Got it. Yeah, BlackRock ... And then who else did you mention?
Michael Mandel: I mentioned BlackStone, Tishman Speyer, Brookfield, Wells Fargo, J.P. Morgan, people like that. They're major institutional real estate investors, and lenders are our biggest customers.
Eric Siu: I love it, and I think they probably ... I mean once they buy in ... They probably aren't gonna go anywhere for a while, right? And these are probably annual contracts?
Michael Mandel: They are annual contracts. Some are multi-year contracts. Yeah, no they are very, very sticky. I mean our ... We have negative net churn. Our expansion of these contracts substantially outpaces the charter of the contracts. They tend to be very sticky. And like I said, we were lucky in that we provide a data set that no one else has. Provided that we continue to grow the database, and show good value up front. The value tends to only get better with time.
Eric Siu: Yeah, and I think I remember ... I remember you talking about in another talk about how you guys have a crowdsourced model. How does that work exactly? 'Cause you mentioned in the past people would just kind of share information. You'd call people last minute just to not look like a scrub at a meeting, but how does a crowd source model work? I guess even going back how did you even come up with that?
Michael Mandel: Sure, well ... The idea really just came out of the way that I was used to doing business as a broker. When I was a broker I would trade comps with other brokers, and they would give me other comps in return, and it was basically ... It wasn't an exact one for one, but it was roughly that. You know? And the idea came out of just trying to take that offline experience, and move it online. But we tried to improve on it, and make it more fair and equitable than it was offline. Our members earn credits for submitting data to CompStak. The credits are like a virtual currency, and the number of credits they receive is tied to the uniqueness of the data that we received it before. The comprehensiveness of it, so how complete that deal record is, for instance. And the recency ... Is it a recent deal, or is an old deal. And the better the data they provide, and the more comprehensive. The more credits they earn. And they can use those credits to get other data back out.
But it ends up being roughly one for one. For every lease transaction you put into CompStak you can get one lease transaction out. For every sales transaction, you can get roughly one sales transaction out. And then the credits can also be used for property level data, and things like that.
Eric Siu: Love it. This kind of reminds me of data.com is a good example ... Where you give contact information, and you get one back ... Kind of thing. It seems like that's how it works. I love it. What's interesting too ... I guess in the venture capital world there's a couple companies out there like CV Insights, Mattermark, all those. And they all basically ... They aggregate a ton of data, and they sell it, right? There's something to be said about these kinds of businesses. I guess this leads to my next question. You guys have raised roughly about twenty-one million dollars, right?
Michael Mandel: Well, we've raised as of right now sixteen point seven five million in equity, and three million in venture debt.
Eric Siu: Got it. Okay, great. What are you doing with all that cash raised right now? What's it mainly going towards?
Michael Mandel: We've spent most of that cash.
Eric Siu: Oh, okay.
Michael Mandel: At this point most of our ... Most of our operations are covered by our revenues. But we have a data team that is responsible for getting these ... This data into the system, and cleaning up the data, and we have data scientists that create insights from the data, and help also maintain our data quality. We have our exchange business development team, which is responsible for building up that exchange of members, and building relationships with commercial real estate brokers, and appraisers, and research people. And getting them to share data on CompStak, and they're responsible for launching all of our new markets, and getting those markets going. Because we have to launch every market individually, one by one. And get the exchange going in every market, one by one. We have our sales team, which is responsible for selling the end product on the enterprise side. We have client success for maintaining those customer relationships. We have marketing. We have tech, obviously, and product. And that's basically it. Finance.
Eric Siu: Cool. Love it. Yeah, so for you guys how did you go about acquiring ... Let's just say your first hundred customers?
Michael Mandel: Sure, well it's really just been a function of well, we have SDR's, and we have account executives. The SDR's field a lot of inbound interest, which is driven by our marketing efforts, and just brand recognition. And then they field a lot of inbounds, and they also do outbound calls, and emails. Those leads get passed on to our account executives, and our account executives go to a lot of conferences. Follow up on leads from the SDR's. Create their own opportunities. And do a lot of in person meetings, and a lot of phone calls. But most of our contracts have some in-person component to the sale.
Eric Siu: Got it, okay. Yeah, I mean what do you say to those people that come to you and they're like, Michael, I love it, but I'd just like to try it for a month. I'll pay you this amount. How do you make the argument that ... Maybe this is early day Mike selling this ... But, it's how do you make the argument that it's no, you guys have to do an annual contract instead of all the people that want the one offs?
Michael Mandel: Well, we'll do like a one week trial.
Eric Siu: Okay.
Michael Mandel: And we'll let people try it out for a week, and if they say we want a month, or two months, or three months. We just typically say, no. Unless there's some really, really, really fantastic reason for it.
Eric Siu: Right. And what's an example of a fantastic reason?
Michael Mandel: That would be like if they're bringing on one group of people ... It's a potential fifty user contract, and there's ten people in one market who they're bringing on now, and then we're gonna make ... We're gonna do meetings with different offices, and we're gonna onboard each of them, and give them each a one week trial over the course of a month or two.
Eric Siu: Okay.
Michael Mandel: Generally, our feeling is you can see the value of this in a day. Certainly, a week. We'll give you a week so that you can find time to ... Try out the trial if you need that, and you can see the value in it. But we also will give you an in person demo, and show you the platform, and show you the data that would be interesting to you in the platform, so you can find the value off the bat.
Eric Siu: Love it. Okay, great. I think the point being here is that not everything is set in stone. Sometimes you make exceptions if it's gonna be a potential whale deal. Sometimes it's okay to do that right? You talked about kind of the first hundred customers. Sounds like a lot of sales. SDR's, AE's. What's a unique thing you're doing today in terms of customer acquisition? If anything?
Michael Mandel: Probably the most unique thing is that we've been doing a lot of API deals as of late. API, and data partnerships, and integrations with other software platforms. It's the end of the quarter, we just signed two big API deals today, and those are much more complex, and they take a lot longer to close, but they're large six and seven figure deals, so they're worthwhile, and they ... It's become an increasing larger area of our business. We've been finding that for some of these big companies ... And some of the more sophisticated customers ... They've got internal platforms that they're working with, and they know how to work with API's now. And the landscape has changed with a lot of these enterprise customers. That they actually have in-house capabilities to know what an API is, and how to use it. And then also, because our data is so unique. It tends to be complimentary to a lot of other companies in the real estate technology, or real estate data space. And so we found ways to partner with other people's platforms, and integrate our data into their platforms, or integrate algorithms, or derived data from our platform into theirs.
Eric Siu: Okay. What's an example of a company that would like ... I guess an example use case of somebody integrating with your API?
Michael Mandel: Well, so there's different ones. From one that we've probably made the biggest splash with as of late, has been a partnership we signed with Moody's. Moody's is one of the world's largest credit rated agencies. They also have a division called Moody's Analytics, which is effectively a technology company that sells ... A technology, and data company that sells analytics, and builds really interesting products in a lot of different spaces. One of those spaces being commercial real estate. So our data is being used in a risk product that they have called Commercial Mortgage Metrics, which is called a loss giving default model. It's a platform that helps lenders understand the probability of defaults of a commercial real estate asset, and they use our data to inform those algorithms. And then we're building new products together with them that can use our data in new creative ways, and that's pretty exciting as well.
Eric Siu: Yeah, that is exciting. I'm assuming for those deals a lot of custom work, like you mentioned, but I have to think that your pricing matrix probably doesn't work anymore? And you have to do a lot of custom pricing, so how do you price these?
Michael Mandel: Yeah, they're really difficult. The way we structure them is we basically have three screens for them. We look to see does this partnership provide ... It depends ... actually ... There's two types of API deals, right? There's the one where we integrate ourselves into some other company's product, and then there are the ones where we provide an API to a customer, right? If it's a ... If it's integrating into somebody's product the screens are ... Does this integration provide a lot of distribution for us? Does it provide a lot of revenue for us? And does it potentially cannibalize us? And so, if something provides a ton of distribution for us. We maybe will look for less revenue. If it has a high cannibalization risk then either we won't do the deal, or we'll ask for a lot more money. That's one aspect.
And then the other kind of deals with existing customers. Those are even trickier, because we price per seat. And so how we structure an API deal with a customer that could potentially be using us on our platform, and be buying seats that doesn't cannibalize that seat growth over time? Because we've seen some of our contracts grow by ... We have exponential growth as we've added seats over time, and we don't want to just give somebody API access that could potentially cannibalize that seat growth. And so sometimes we'll only offer them derived data, or access to our algorithms, or something like that. And we bench mark these deals against previous API deals we've done in the past. The first few were just somewhat of a crapshoot, and then over time we got a sense of what the pricing could be, or should be, and benchmarked our new deals against those.
Eric Siu: Got it. I think this ties back to my point earlier. There's no one size fit all, when it comes to deals like this. Sometimes you have to think about getting creative, and that's certainly what you've done, so I love it. Just a couple more questions here as we wrap ... Work towards wrapping up. Tell me about one big struggle you faced while growing this business.
Michael Mandel: I think the biggest struggle is tying data growth to revenue growth. One thing that was a hard lesson learned on the job was that the ... A high growth VC-backed company looks for a hockey stick kind of growth, right?
Eric Siu: Right.
Michael Mandel: But for a data company, the hockey stick is different. The ... I don't know what you'd call the bottom part of the hockey stick, but that part is much longer on a data company. And perhaps the exponential growth on the long stick part of the hockey stick is maybe even steeper, for a data company. But you have to have a lot of data, and the data has to be really relevant, and once it is you can sell that data over, and over, and over again with very, very good margins. But you have to build up that data, and build a tremendous database, first. And that was a hard learned lesson because we'd been building up the database for years, and ...
Eric Siu: How many years?
Michael Mandel: Well, we've been at it now just about six years.
Eric Siu: Okay.
Michael Mandel: And we actually have seen that inflection point in the hockey stick at multiple times because we actually have to hit it on a market by market basis.
Eric Siu: Huh.
Michael Mandel: Every market has its own inflection point, but it's been interesting to watch as that's happened, but I think you know, the other thing is once you create a formidable database. You have an incredibly high barrier to entry, and incredible margins, so it's worth it in the long run, but you have to really account for that earlier on as you're building the business, and understand that you're building a data business, and what that means as it relates to what you should expect ... For the amount of capital you have to invest, and the amount of revenue you can expect over the course of time.
Eric Siu: Love it. Okay. Well, what are you ... What are some good habits that you've fostered? I guess we can even talk about daily habits in terms of how you structure your day ... How does that look?
Michael Mandel: I wish I had better habits from structuring my day. I do my best. As CEO, I get pulled in a lot of directions, and into a lot of meetings. One thing I do, frankly, is I have ear plugs in my desk, and if I need to focus on something I put in the ear plugs. You know, to focus on something. I do a lot of work on the weekends, and at night. A lot of the stuff that involves some real thinking, and do a lot of meetings during the week, and just try to put everything on my calendar, so that I don't miss anything, and I kind of live and die by my calendar. That's sort of the name of the game for me.
Eric Siu: Yeah, you seem like a true grinder. How many ... What time do you usually get into office? Or better question, what time do you usually start work on a weekday? And what time do you stop working?
Michael Mandel: Sure. Well, I don't put in the same kind of hours that I used to because I have a six month old, and a three year old. I get in ... We're in New York, so things seem to start a little later here. I get in nine, nine thirty. I used to leave the office around nine, nine thirty. Now, I leave the office more typically around seven thirty. Maybe. Or if I can I try to get out a little earlier, and make sure I'm home for bedtime, but it's not always easy, and then I ... I tend to do some more work on the couch at home.
Eric Siu: Cool. Yeah, we're getting close to your seven thirty time. I'm gonna hit these last two questions, and then we'll let you get on your way here. What's one new tool that you've added in the last year that's added a lot of value? For example, could be like Evernote.
Michael Mandel: Yeah, on the sales side we brought on InsightSquared, which is an analytics platform that is built on top of sales force. And that's been really, really cool. That's one that's probably in the last year, but along those lines ... Big fan of Periscope, which we've been using for several years now, which is awesome from a business analytics standpoint.
Eric Siu: Great. Love it. Okay, so Periscope, and InsightSquared. Have heard incredible things about both of those. What is one must read book you'd recommend to everyone? Could be entrepreneurial. Business. Could be fiction.
Michael Mandel: Must read book. Good question. Right now, I'm reading the new book by the Moneyball guy. His name is totally escaping me. Michael Lewis. And all of his books are awesome. The new book is about Danny Kahneman, and Anton Twersky. The guys who created behavioral economics. Those are interesting books. I don't know if it's the absolute must read, but it's a good one.
Eric Siu: Cool, yeah. Often times it is just whatever is top of mind. We'll add that to the show notes. First time I've heard about that one. Mike, this has been great. What's the best way for people to find you online?
Michael Mandel: Well, I'm a ... My twitter is CompStakCEO. My LinkedIn is MMandel, and people can also email me. I'm just [email protected]
Eric Siu: Awesome. Mike, well. Thanks so much for doing this.
Michael Mandel: Awesome. No problem. Thank you.
Speaker 2: Thanks for listening to this episode of Growth Everywhere. If you loved what you heard be sure to head back to GrowthEverywhere.com for today's show notes, and a ton of additional resources, but before you go hit the subscribe button to avoid missing out on next week's value packed interview. Enjoy the rest of your week, and remember to take action, and continue growing.
Download podcast transcript [PDF] here: How CompStack CEO Michael Mandel Used the Value of Information to Create a Real Estate Tech Company that Raised 16.5M! TRANSCRIPT
Time-Stamped Show Notes:
Resources from this Interview:
Leave Some Feedback:
Connect with Eric Siu:
Disclaimer: As with any digital marketing campaign, your individual results may vary.