David S. Rose, one of the most prominent angel investors in New York, says angel investing is about to change for good. David has founded half a dozen companies, but his latest, Gust, is a SaaS platform connecting entrepreneurs to early-stage investors. With a new product, Gust Launch, David aims to help make algorithmic investing possible on a large scale, while standardizing the tools for entrepreneurs to get started on their companies. Once companies begin sharing their data, investors will continue to demand it, David says.
Want to make your own company more data-driven? Learn how Indicative can help.
3 Data Insights from David S. Rose:
1. Analytics is the future of angel investing
Making decisions based on big data, rather than gut feelings, makes for successful investors, David says. A new product, Gust Launch, aggregates company data to easily compare how they perform against others in their industry, without publishing actual earnings. David says that a large dataset of this nature will allow angels to engage in algorithmic investment — automatizing their investments based on how new startups compare to unicorns’ growth trends.
2. The most valuable investment data comes from the earliest stages
David wants new startups to use Gust Launch from their inception so the platform can measure their full lifespan. With these data points, Gust can build a huge database of information, based on everything from credit card statements to analytics. David knows that with more data points, the insights will be more accurate, providing a more valuable service to investors who want to know where companies stand.
3. More data means early-stage startups have more to prove
The barrier to entry for starting a company is diminishing. It doesn’t take much capital to start a website, research competition, or do the basic planning to get your startup off the ground. But this also means that early-stage investing is happening later and later down the development process. David says that angels now look for more proof of concept than ever before, including analytics and sales data. The more data available for angels to base their investments off of, the more necessary it becomes for new companies to keep track of these numbers.
Andrew: Today, we’re interviewing David S. Rose. I’ve had the good pleasure of knowing David for probably 20 years. He is one of the seminal figures in the New York startup ecosystem. He is the chairman emeritus of the New York Angels, and probably the most prolific angel investor I know in New York, including as an investor in a company that Jeremy and I co-founded, called Indicative. He’s also the founder and CEO of Gust, a SaaS platform that connects startups with investors. David likens the ease of fundraising on Gust to applying for college with the Common App. So far, half a million companies have chosen to fundraise on Gust.
We will start our conversation asking David about how data can inform angel investments. Later on, we’ll discuss about how Gust is changing the investment landscape.
David, thanks for joining us.
David: It’s my pleasure.
Andrew: David, we talked about before, the idea of this podcast is to really drill down and understand how certain verticals are being completely disrupted by the use of data. And I’d love to talk with you about your perspective on angel investing. Let’s go back to your earliest investments and talk about how they were made. And then we’re going to transition and talk about how you’re thinking about investments now and your use of data in how you consider and evaluate your investments.
“A fundamental change in investing”
David: Sure. I think this is a very timely podcast, because the question is very timely. What we are seeing, is a fundamental change in the world, and business is part of the world, so it’s a fundamental change in business, and investing is part of the business, so it’s a fundamental change in investing. What we are seeing is the exponential advance in technology. It’s the whole Ray Kurzweil Law of Singularity, technology is doubling every 18 months, Moore’s Law kind of world. And what this means is that as everything is increasingly moving to technology, because it is tech-based, it is therefore monitorable. Because it is monitorable, you therefore have data, whether primarily gathered or as data exhaust as Josh Kopelman would put it. And so now, you have a world for the first time in history, in which everything comes down to data. And so, therefore historically, if you look at any kind of decision, what to do, where to sell, what product to offer, whether to invest, how much to put in, anything, and probably even down to whether you should get married, right? I mean, every single decision that anybody, any human has ever made is, it boils down to, I have certain inputs and that input can be my eyes, it can be a gut feeling, it can be my experience, it can be whatever. And based on those inputs, I’m going to make a decision.
Andrew: Let’s roll back a little bit. What are the criteria? When you started investing, what were the criteria by which you analyzed an investment?
David: Well, ultimately angels are the earliest, earliest, earliest outside investment in a company. The very first cash for any kind of startup comes from the entrepreneur, him or herself. Because if you don’t have the vision and the faith to invest in yourself, it’s not going to earn. Nobody else is going to invest, right? So that’s, you know, sight on the scene, you’re the first cash in. The second cash then comes from, if once you’re out of cash, people who are investing not because it’s a good business or if they know anything at all about it, but because they know you and love you. That’s your friends and family, right? They’re not making a considered investment decision even if they think they are. They’re making a love, passion decision. They are investing to help you, because of you, they trust you, whatever. So after that, comes angels. Angels are the first outside arm’s length investment. And we as angels are looking to invest in the company in order to make a lot of money. Now, we invest at the earliest stages, often or always before anything is proven because if it was proven it will be a later stage investment. So at the early stage, companies are just starting. Now, just starting is getting later and later in the process. You get an idea, and then a business plan, and then the basis about being a product and so on and so forth. Today, it is so relatively expensive to start a company that you’re starting later in the process. So you probably have a product, you probably have customers, means you can have revenues or whatever. And so-
Andrew: So you’re evaluating, so you look — and full disclosure, David is an investor in Indicative, the company that Jeremy and I co-founded. You’re looking, in the past, you looked at the founder, whether or not you believed in the market space, but there wasn’t a great deal of due diligence, right? You weren’t-
David: Correct, because the company was so new and so little, right? There was no history, no track record of anything. Because even if it was operating, you had no access to that data, because it wasn’t being tracked. And so historically, angel investing has been very much of a gut- Is this industry going to grow? Do I think this team, is this entrepreneur I’m going to back, is this is Andrew Weinreich or this is some wannabe?
Andrew: So, has that changed? Has that idea at the earliest stage, where there’s not a great deal of data to ingest, because you were betting on a founder and the founder’s description of a market opportunity. Has that fundamental proposition changed, or is today there’s some data that you’re assessing, you’re running the background of the entrepreneur through some algorithm, or you’re evaluating? Is anything different today for that early stage investment?
David: Yes. What’s interesting is that there is a real difference today and what’s coming down the pike is something much more exciting and even much more different. So, let’s start with today. Historically, you were looking at, because it was an idea, there was nothing to track at all, you were investing really early stages, because an entrepreneur couldn’t start their company without the investment. So all you have to go on was the pitch direct and the entrepreneur, right? And we knew over time, we came to realize that at the earliest stages are so much dependent on the entrepreneur, it was called betting the jockey, not the horse. You almost didn’t care what the business plan said, if you were betting on the right entrepreneur. And in reality, that has actually held. So that today, that still continues. I want to bet on Andrew Weinreich, one of the world’s great entrepreneurs, right? And so, that’s still a really important part. But what has happened is because it has gotten almost paradoxically, so much easier to start a company, companies that are coming for angel investing actually, for the first time, have something, you have a product done. You got a team. And you could be a dispersed team.
Andrew: And the reason for that is because the cost of development has plummeted so dramatically over the years. Is that right? Or it’s just the expectation of entrepreneurs is greater?
David: No, absolutely. It’s not just the question of development. It’s basically everything, development operations, team building, the ability to have a remote team. All kinds of stuff, right? Every part of the process of starting a company has gotten less and less and less expensive, which means that it’s available to more and more and more people, which means that you have a larger group of companies to choose from and the companies that ultimately are that, one to two, three percent of the companies that get invested in by angels are companies that have gotten a lot farther down the road than they start, which means they actually have customers, they have product, they have visitors.
Andrew: So what’s the data you ingest? If we just take those three areas you talked about. There’s product, there’s customers, there might be revenue, but still we’re talking about, from an angel’s perspective, it’s still incredibly early on. And in order for the data to mean anything, you would need to somehow or another compare it to other startups. I mean, maybe you can-
David: Correct, but also, historically, the data wasn’t there. Historically, a company was so young. It hadn’t gotten, and you couldn’t start it until you had the money. Since the company has not started, there was no data anyway. It wasn’t available, right? So the only thing you had to go on was with your gut take on the entrepreneur, on the business, on the market, so on and so forth, right? Now, because companies actually have gotten started, you can now look for the word that is so critical to investors and such a nightmare for entrepreneurs which is traction. So, you will now hear from every entrepreneur, every early stage investor, they’re looking for traction. Historically, the company couldn’t have traction, because it couldn’t get started without it. Now that you can get started without it, traction, which is a very loosey-goosey term, is the key. And what we mean by that is to say, okay, you’ve now managed on your own or with friends and family to get something into the market to get something out there. People have seen what you have, people have tried what you have. So, now let’s look for the T-R-A-C-T-I-O-N. And traction can mean anything from, profitable revenues to revenues, to number of people visiting your site, to number of people converting in your funnel to retention, to NPS scores, Net Promoter Scores, to anything. Because once you actually have a company that is doing anything and interacting with customers, assuming you instrument that appropriately, you can now track things. And the traction that we want to see is something that is in the market and it’s interacting with users, and like the wheels on our car, gripping the road and moving forward, that things are moving. How do you define traction will differ for every company.
Andrew: But are you saying that today the traction that the analyst, that the angels, I’m sorry, not the analyst, the angels are looking for is measurable much the same way in 1995 or in 2000, the series A investors, or the series B investors could look at traction? It’s not that there’s more data, it’s just that the the stage at which the angels are investing is later from an operational perspective.
David: No. It’s actually a double whammy. It’s a double barrel thing, right? First of all, companies are coming to us, because it is cheaper to get started, companies are coming to us at a later stage, or at least the ones that get invested, are getting invested at a later stage. They have more that they are doing, right? The fact that they are doing more, means they’ve actually interacted with the market which they didn’t do before. So now you have a company that has a interacted in the market, that’s number one. Number two is the fact that, because the market interaction is now all in every single case, happening online in ways that now can be actually instrumented as a standard of course. You know what your Google Analytics are, you know how many people have seen your- what your CPM are. You know what your CPA is. You can track things, you know, with all kinds of current software, you can track things like your customer acquisition cost and your lifetime value. And your Net Promoter Score, and your conversion rate. And these are things that would have been very arcane even you know 10 years ago and required specialized custom kind of stuff. But today, with all of the, the fact that anything you do online, in the cloud, everything you do is going to be in the cloud and digital, and anything you could do digitally is going to be, by today, default instrumented. Then all you need is the analytics software on the other end to be able to track all this. So companies are more fast. They are more instrumented. You have more access to the data and that’s now therefore expected.
Andrew: So, if we were to carry this forward and you were looking at investing in, and I’m going to come up, very antiquated example, if you were interested in investing in a pet food company that was selling online, wouldn’t you need- I appreciate the fact that today if you had the benefit of looking at a perspective investments, Google Analytics, and you didn’t have that perspective 10 or 15 years ago you’re obviously better off today. But, where you’re taking us is, in order for you to turn this into a science, you really would need to see every single pet company, right? Because what you would want is, this presumption that there will be a winner or several winners, and then you would want to stage compare the CPA, the lifetime value, the churn, across all the startups in that space.
Andrew: Is that where you are taking us?
David: Yes, but you’re actually halfway there. That’s the halfway part. So, right now if you take a look at things like that that Jason Lemkin is doing with his SaaStr Conference, which has grown out of nowhere to be one of the most important conferences in the industry, 10, 15, 20,000 people come to San Francisco every year, all in the SaaS business. You now have metrics that all the major VCs are putting out, and all the cloud guys are putting out, so you can see today what the benchmarks are for the winners. Right? All the guys that were the unicorns and the near unicorns, the ones that gotten investments, they are publishing a lot of those metrics out there today. In terms of the time to, X percentage on whatever, and your LTV and CAC and all those track numbers.
Andrew: And they are publishing that where they are today? Not where they were, when they were-
David: No, they’re publishing that historically. So I think, I mean there are a bunch of benchmark surveys-
Andrew: Got it. So benchmark is you’re now in a position to stage compare these startups to what a unicorn would be.
David: Correct. And so, a good part of SaaStr, of the conference this past year, was saying these, VCs are saying, okay, here are the profiles of the last 25 unicorns, right? Here is how long it took them to get to this, get to that, get to something else, have a million customers, their first series A, whatever, right? And so, if you whoever startup you are, are matching these metrics, I’m going to take a serious look at you, right? So what you have today is everybody is being instrumented, number one. And you have the metrics and the winners, number two, right? And then taking a larger swath of that is the step that you were going to, which is a step and a half. But where things are going to beyond that is really, insanely interesting. And that’s the kind of stuff that we’re working on here at Gust. Because as you might know, actually I know you know, we have a product called Gust Launch, which was announced at the end of June. And so, Gust Launch is a company, it’s a service. It is a software service, a SaaS platform designed for high profile entrepreneurs that lets them press a button, and set up and run their entire high-growth company. So we incorporate them in Delaware, service their registered file with the IRS, set up their bank account, their credit card, their payment processing system, handle their accounting and bookkeeping and handle everything, integrate everything. Do it automatically, and starting at a price of 99 bucks a month…
What Gust Launch is that I was just describing, we introduced literally at the end of June. And it’s this company as a service for all these startups that now want to get started, and what we do is automate the entire process of starting up a high growth company. And because we are doing that and at scale and automated, it literally is a fraction, it’s one-tenth the cost if you were trying to do it yourself by going to law firm or anything else. We’re working with most of the major law firms in the country. It’s a truly a disruptive plat-
Andrew: I’m curious- It sounds terrific. I’m curious whether or not, when we go back to tracking and using data to predict the success of a startup-
David: That’s exactly where I’m going. And that’s why it’s so cool, because on the one hand, what you have is a disruptive platform for entrepreneurs. Start your company this way, it’s 10 times faster, 10 times cheaper, 10 times quicker than any other way, right? But the data exhausts from Gust Launch. Having done that, you now have automatically from day one, your entire company, up and instrumented from before you even started. Every bit of your cap table, every credit card charge, everything on your bank account, all of your payment processing, all of your Google Analytics indicative of everything is all tied together, automatically from the very beginning.
Andrew: So, let’s take an example. Let’s imagine that- I want to go back to the Unicorn’s and you having the data. And I’m wondering whether you’re going to say, okay, Uber has exposed from inception their traction on revenue, their traction on page views — well I say pageviews, they were an app exclusively, so their traction on traffic were repeat customers. And I’m wondering whether you’re going to tell me, you’re going to define a vertical, and maybe that vertical doesn’t have to be so limited as ride sharing, but maybe it is, maybe it’s ridesharing. And then if a company participates in Gust Launch, and you are able to ingest all of the data from the successful acceleration of Uber and Lyft, whether you can tell me, ‘Andrew, your startup is doing 10% as well as Uber was, or in fact you are outperforming Uber between year two and three, but you underperformed between year one and two, is that, is that-’
David: Exactly. The answer is, yes, exactly. And that’s why I said you were going halfway there, Right? And so, that’s the halfway point. Say we’ve now benchmark all these winners, We now have total data. We, acting as your agent, have total data for you, that we can give you on how you track against these benchmarks, right? That’s great. But the next step, the last step, the insanely cool step is that once you now have all of these companies instrumented from the very get-go, on a platform that is the only logical way for them to get started, because it is better faster, cheaper, and so on and so forth and you do this at scale, and you have hundreds and thousands, and tens of thousands of companies starting and operating on a totally instrumented platform, what you then have is real-time analytics of everything on the entire industry. And now, you can begin to apply cash at that, not as an additional piece of data that you’re looking at to make your personal decision. You can begin to automate it. And that’s where it gets really, really insane. And so I’m not going to pre-announce anything right now, but all I can tell you is that, imagine doing this at scale where you have hundreds or thousands of companies being started in real-time every month, every few months, and now you have investors who are prepared to say okay, we know what good metrics look like. We want to invest in companies that actually have revenue, where they have a better than three to one LTV to CAC ratio, and so on and so forth. So as long as the company is on this platform that’s being instrumented, the minute it actually hits those numbers, and those begin to show up, hey, bingo, we’re prepared sight unseen to invest in that company on these terms. And so, what we will have is automatic investing across the entire industry, and that’s where things get really exciting.
Jeremy: David, using Andrew’s example, how do you get Uber’s data into Gust?
David: Well, so first of all, in terms of the big ones, the big unicorn’s and so on. The mega-successes, those are all published, those are all the data now, right? So,
Andrew: But they’re not published from the perspective of, let me share with you Uber’s Google Analytics, maybe that’s not the best example but don’t you need that? I mean, if we’re just blue-skying here.
David: But again the question, what can you get right now? You can do, there are published analytics on major stuff, right? Length of time to everything from to a certain investment length of time, to a certain customer intake or whatever, right? But the advantage of doing stuff with Gust, with stuff like Gust Launch, we’re automatically getting this data from everybody. Now it’s got to take away for a while for the unicorns to wind their way through the system, and maybe you don’t get unicorns, maybe you get gazelles who are really fast-growing kinds of things, but once you have this in a system which is automatically acquiring a hundred percent of the data for a company, and you’re tracking everything from its financial data to its product data to its investment data, and you run that out for some period of time, six months, a year, two years, five years, pick a number, right? You now have accumulated an extraordinary amount of data from many companies that are going to fail, and a few companies that are going to be rocket ship successes, and many companies somewhere in the middle, and now, you can begin to do things with big data analytics across a much larger data set, and begin to do those automatic investments.
Jeremy: David, are you putting that information that is public into Gust now, or is that something that you’re going to be doing in the future?
David: No, that’ll be future stuff. So right now, it’s the early days, the product just launched the end of June. So you’re now beginning to become the creator on the platform, now the cycle time for companies to get creative and grow is much faster than has been historically. So you’re just now seeing company begin to get product on the market and so on, and so, give this 6 months, 12 months when you begin to see companies really going out for their outside investment rounds, and so on, and the ones that have developed traction, have real traction, and then you’ll be able to have all these metrics on platform. And whether or not they are interested in publishing them, that’s okay, as long as you have an anonymized data that you can now benchmark, you could begin to both see how you’re doing yourself against your cohort, the industry, your region, whatever. And investors can begin to make automated decisions without having to see your confidential data, which gets really fascinating.
Jeremy: David, why would a company like Uber be motivated to share their data with Gust?
David: First of all, the important thing here is not getting unicorns ex post facto to share of their data, it’s to get everybody to share their data from day one, right? And because it’s going into the platform-
Andrew: Your point is that the next Uber would have. It’s not that you’re going to get Uber to backdate, or to-
David: No. You get the published document from the existing guys that you use for gross level analytics, and you’ll get the detailed stuff from everybody going forward which can be kept anonymous without publishing it per se, but still used for benchmarking.
“Once the data is out there … investors are going to demand it”
Andrew: So, your vision of the future is at some point, we get to a place where people that want to invest in startups, you would say to them- I’m curious whether you even say to them, ‘Tell me the verticals that you’re interested in,’ or whether you would simply say, ‘I’ve assessed the risk profile of all of these investments, and here’s what you will return barring some-’
David: Listen, you’ve guys know analytics as well as anybody on the planet, and so once you have a startup with every single thing instrumented, I mean every single thing from the every dollar invested to every dollar of revenue, to every dollar spent, to every employee, to every everything. When you have 100% data and you can begin to do it- When you have it on one company it’s really interesting. When you have it on 1,000 companies or 10,000 companies, that’s big data, that’s scale, right? And then you can apply all kinds of AI and expert systems, and then you can interface that with human beings at whatever level you want and say “Okay, what’s your thesis? Is your thesis the Internet of Things will be really big?” Okay, fine. So what are you looking for in Internet of Things company? What kind of benchmarks are you looking for? And you can do it that way or you can play a totally automated hand and say okay, it doesn’t matter what industry you’re looking to invest in, you only want to have companies that have got traction, that have gone from you know, their first 100,000 in revenue within six months and then scale on an ongoing basis, month or months from that, or however you want to define it. So you can add the human being in it or you’ll be able to ultimately sit back and let the machine do the work.
Andrew: I understand if I’m a startup, why I would want access to all this data. I also understand why I’d want access to your best-in-class services for my startup to access. But if 99% of startups under-perform their projections- 99.9% of startups under-perform their projections. Why would I want to make my data available to the outside world? Or is your perspective that this is going to be forced upon you entrepreneurs. You’re now going to be assessed in this larger context whether you like it or not.
David: The answer is the latter. Yes, it’s going to happen because once the data is out there, people, investors are going to demand it. It’s happening today. I mean no investor today is going to invest without asking for your revenues, you’re tracking, your conversion rates, so and so.
Andrew: But are investors astute enough today to say, you know, on the angel side, how granular or how sophisticated are you seeing angels with appreciating-
David: Nah, listen, Angels today are not as sophisticated as VCs. That being said, they are getting in with platforms that are making more and more of the data available, it doesn’t take a rocket scientist just to look at a chart and look at a graph of three companies and say this one on this platform has got more than the other one. But the point I’m making is that the data will be available because as you do more things like us Gust launch that are automatic and making the data available to the company, without the company publishing its particular data saying, “Hi, this is company X Y Z and here’s my data,” it will be the other way round. You can anonymize the data for the company and the company can say okay, let me be searchable by an investor who was looking for a company with these metrics. And so investors will be able to invest on metrics and analytics, without knowing the company until they’re ready to make that investment. And so it’s going to turn things upside-down and be really fascinating.
Andrew: Will you look at other data points, you know for example if David Rose is an investor, he opens up his network, that increases the likelihood of success that’s got nothing to do with the founding team, it’s got nothing to do with the fundamentals of the business.
David: Sure. But again, you keep in mind, when I say everything is instrumented, I mean everything is instrumented. Remember, because Gust Launch is running your cap table, the system ultimately knows — and obviously this is totally confidential, you are not going to block your captain with anybody — but what the system can ultimately do for you as the entrepreneur is effectively bring the score to the table, “Hey, you’ve got David Rose and Andrew Weinreich investing in.” These guys each have records about them which therefore score them higher than X, Y or Z. The point I’m making is that with everything instrumented from the beginning, lock, stock and barrel, things that are tangible, numeric, things that are even relationship-based or network based, whatever, you will have the ability to make investments on purely statistical means and only at the very end of the day say oh it’s company X.
Andrew: I got you. I have two more areas I want to pursue, and see if Jeremy wants to ask anything before we wrap. One is, is it in Gust’s future to set up a fund?
David: I’ve been asked that many, many, many times. And do I want to venture, or certainly, I mean angels has now got a fund and seed invest has now got a fund-
Andrew: But all of those funds are predicated on the intuitions of the principals. What I’m asking you about is not whether Gust will set up a fund-
David: A: I never preclude anything and B: I don’t comment on unannounced products. That being said, I don’t see Gust itself necessarily setting up a fund. I absolutely, positively see Gust’s technology and data and the platform being used to facilitate funds.
Andrew: To facilitate algorithmic investing. So you are envisioning a future where investing in startups becomes really, almost like program trading. Am I taking it too far or is that-?
David: No, you’re not. Remember with programmatic trading online, you can only do that at a certain scale because there are only 5,000 publicly traded companies in the whole United States of America. On Gust today, we are adding between 10 and 12,000 companies every month onto the platform. So today with 500,000 companies on Gust, there are 100 times as many companies on Gust today as there are totally traded public companies in the United States of America. So now, as you run that through over time with Gust Launch with companies being incorporated here, you have that, so the minute you get to a 1000, 2000, 5000 companies on the platform, you now have the ability to do all kinds of stuff you couldn’t even do with public algorithmic trading.
Jeremy: David, are there any trends that you can tell us about that that you can already see?
Andrew: I mean we appreciate you having launched this holy grail. But just with the existing data, are there trends you can- for people listening, if you’re thinking about investing, this is what David Rose sees through, across this band of tens of thousands of startups?
David: The interesting thing is that at this early early stage, you can’t really draw data from those because don’t have those. Remember we only launched this thing in the end of June, so we have hundreds not thousands of companies in the platform now. And those companies themselves are just brand new companies, just getting started. But what I can tell you looking at this as an investor, and that’s the whole theme of this podcast, which is that analytics is the future. And whether the analytics are in and of themselves, the way you’re going to invest with an algorithmic fund, or whether the analytics are letting you fine tune and hone down every year, that’s what this is. But it’s not going to be taken for granted. It is today frankly, any investor investor looking at any company today, the very first thing they are going to do is say, “Show me your analytics. Do you have traction? What’s your acquisition cost?” and all the things that were leading edge five years ago or even three years ago, are now today taken for granted. So we are in a data-driven economy today and that’s just going to double down and get more more and more so.
Andrew: David. This has been fantastic. Thanks for your time.
David: It’s been my pleasure. Thanks a lot.
Andrew: Thanks David.