August 20, 2021 – On today’s podcast, we welcome special guest Will Marshall, CEO of Planet Labs. Planet Labs is a leading provider of daily data and insights about the Earth and is currently going public at a $2.25 billion enterprise value.

On the show, Will discusses:

  • His background at NASA and some important missions they accomplished
  • How Planet plans to become the “Bloomberg Terminal for Earth data”
  • Planet’s business model and competitive advantages in the marketplace
  • What made dMY Technology the right merger partner
  • And more

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Transcript:

Welcome investors to the Absolute Return Podcast. Your source for stock market analysis, global macro musings and hedge fund investment strategies. Your hosts Julian Klymochko and Michael Kesslering aim to bring you the knowledge and analysis you need to become a more intelligent and wealthier investor. This episode is brought to you by Accelerate financial technologies. Accelerate, because performance matters. Find out more at www.Accelerateshares.Com.

Julian Klymochko: I’m very excited to have Will on the podcast today. And Mike, I think it may be the first time we have a literal rocket scientist on the show. So probably our smartest podcast guest ever so, Will welcome to the show. I thought I’d kick things off by going through some of your pretty extensive background, noting that you were a former scientist at NASA. Do you want to talk about your early interest in science, physics, your path to NASA and ultimately Planet Labs?

Will Marshall: Thanks very much. And it’s a pleasure to be here. And yeah, so I started as a space scientist, studied astrophysics and then quantum physics for my PhD, and ended up working at NASA Ames Research Center on a number of missions, but mainly what was called small satellite technology. So, we pioneered small satellite technology on behalf of NASA. And we were doing a few missions. I was lucky enough to be involved with two lunar missions LADDIE and LCROSS, these were two missions. LCROSS was looking for water in the south polar moon and water never been found there before. And we actually literally hit down in the middle of what was more or less a load of a regular with icy particulates in it. So, we discovered a boatload of water on the moon in the form of ice. And people hadn’t discovered that before. And pioneering, that was a low-cost mission from NASA’s perspective, well under a hundred million dollars, which you may think of that as very expensive, but typical NASA missions, you know, over a billion dollars. 

Julian Klymochko: Wow.

Will Marshall: And so, it was considered low cost, but then we were trying to pioneer technology to reduce costs and miniaturized satellites in particular. And what we were noticing was how Moore’s law was transitioning technology as so fast with processes and radios and accelerometers and sensor systems were getting smaller and smaller. And we were like, okay, how can we make smaller satellites do the same thing as the big ones? And we flew a few phones into space. We call them PhoneSat, and we had amateur radio listeners pointing their amateur radio antenna at these phones as they flew around in orbit and took little pictures with their camera phone.

And then we’re like, wow, if this worked and it did, we were like, well, maybe we could leverage the consumer electronics to build satellites much, much more compact and more efficient. And that led us to this idea of, well, what can we do if we put a lot of satellites? Where we could do something like much more frequent earth imaging, and that’s what led to the birth of planet, because what we realized was, we could do a lot of, lot of help for how we steward the earth with we had a lot more rapid imaging. I’ll talk about that, but that’s sort of the quick, quick summary.

Julian Klymochko: So, prior to getting into the founding of the company, I wanted to touch on one more thing at NASA. It seems to be like a dream that every kid has, either to go into space or work on rocket ships and stuff like that. What was the coolest experience that you drew from that? 

Will Marshall: Well, I mean, we were very, very lucky to have relative freedom to start missions relatively young in our scientific career. This lunar mission, when we send this probe and we actually got the data back from the moon successfully and we discovered the water there. That was the highlight of my time there. I mean, that was a big deal for the scientific community. We didn’t think that there was water on the moon and it just turned out, this prior 73 missions to the moon, which many of which had looked for water and were just looking in the wrong place. And we just discovered it in these creators, in the south pole where the sun is never shines basically. They’re in craters and they’re in crunch, have been in shadow for 2 billion years and it was 40 Kelvin in temperature. So, it was really cold, minus 230 degrees C, really, really bloody cold. And there we found all this water and other light hydrocarbons and all the things necessary to build human settlements. So ultimately that resource discovery was really cool.

Michael Kesslering: And you talked a little bit about from the technology side that the founding of your company became possible. So, from that perspective, from that technology aspect seems like there was a product that you were going to be able to launch, but can you talk a little bit about that decision to leave NASA to now go be an entrepreneur. That’s a very difficult transition, even if you’re well capitalized, there’s a certain amount of your identity wrapped up in that. Can you talk a little bit about that and then as well, you know, how you plan on being the Bloomberg terminal for the earth data? That was something really from a finance perspective an investor’s perspective really jumped out to both Julian and, I am sure.

Will Marshall: Well, I can’t wait to talk about that, but just quickly on that. Yeah, I mean, look, it wasn’t hard for us as a team to decide we wanted to go there Michael, and leave NASA to start Planet because the stars were aligned. What we realized was, what was possible in terms of putting up a lot more centers, we had the necessary tools for, the society and the economy needed that data. And, yeah, we were there ready to do it. And then we were in Silicon Valley already. So, we could find access to the capital. We had friends that had already done this sort of thing. Some of them were gone to NASA. Some of them are gone to Apple, or some of them have at some startups, but, you know, we knew that sort of show. And so, we went and found our first VC check. We didn’t leave NASA with capital. We found capital after we started building the satellites, literally in our garage, which is, you know, what one is meant to do in Silicon Valley. We really did it, clean the leaves out of the garbage in the morning and then start building the satellites. Anyway, in all seriousness, it wasn’t though, just because it was a cool technology. It was because we realized that this data that we could gather could have tremendous applications to the earth economy. So let me take us more terrestrial for a second and yes, Bloomberg Terminal for earth data. That’s how we think of it, because what we are doing is, we have two hundred satellites, one hundred and eighty of them image the whole earth every day, all the land mass of the earth at about three-to-five-meter resolution.

So, you can just about see a tree. You can see a house, you can see a road, you can’t read number plate or, or see you identify a person, but you can see the macroscopic object. We are seeing the entire earth every day. So now we have fifteen hundred images on every point on average, on the earth surface documenting all the change and every day tracking new changes and I’ll get into why that is super important, to a lot of economic factors in a second. Secondly, we have twenty-one satellites that can zoom in at fifty-centimeter resolution up to ten times per day. So, this is the dataset we have, but why is that interesting? Okay. So let me talk about just a few applications. Firstly agriculture, so twenty-five of the land mass of the earth is agricultural land, and they are trying to do what’s called digital agriculture or precision agriculture.

This is where they’re trying to improve crop yields. In any given area of land, it turns out with our satellite image. It’s not just a pretty picture of the field. We with one of our spectral bands can tell crop type and crop yield. So, we can I say three-by-three-meter box it’s wheat, and it’s doing this well. We know the yield. In fact, we can predict the year. We know when they’re going to harvest. So, we can help them improve agricultural yield by telling them when to add fertilizer, when to add water, when there’s blight in the field, this can improve crop yields by twenty to forty percent in the developed world. I mean, and that is a big industry and they need daily data to help this precision agriculture practice. I can give a number of other examples in that sort of what’s called digital transformation space.

We’re helping a lot of governments do that, like local and state government do law enforcement, like regulatory enforcement, you know, like speed cameras, catch people and send them a ticket. Well, we’re doing that, but for illegal swimming pools, you know, people have to have construction permits to do this or here in California you have to have permits to do weed growing. Even if you can do it legally, you still have to have permit. And some of the counties have used it to enforce, and they just send them bills in the mail. Super-efficient way of keeping on track of those regulatory enforcement. And then I’m not sure how I morally feel about that.

So, there’s a lot of government applications. We work with companies like Google that improve their maps online. So, this is how the maps that you see online are staying up to date. They do something really powerful whenever they see something change, like a new road or a new building, or any hint of that. Like if people are suddenly driving through the middle of a field, because they see the cell phone signals through the middle of a field, they’re like, hang on a second, maybe there’s a road there. And then they automatically task on our high-resolution satellites, take a picture of that place. And they automatically pick out the road or the building from that, and then they update the map. Okay, so this is how the maps stay up to date. Otherwise, they quickly go out of date.

And so, there’s a wide variety of use cases. And the general theme is twofold. One is digital transformation. This is where big data and AI are helping various industries improve their efficiency. The second is sustainability. So, every company is trying to measure is ESG targets. Every country is trying to measure its emissions. And how do you do that? How do you do that in a uniform way? How do you do that without, you know, going into every house and checking everything? You do that with satellites, we have a base map of what everything’s, again, if you’re a company trying to measure, we work with Georgia Pacific as an example, that’s trying to ensure that the wood that they source for their paper comes from a sustainable forest. They know where that is, but they didn’t know if it’s sustainable. So, they use our data to check that it’s being sustainably managed. That’s the kind of thing, so ESG supply chain tracking for the E in ESG, is going to be really huge for companies and you can’t manage what you don’t measure. Plant data is the source of measuring all those things. And so, as companies and governments get more into sustainability, where sort of a cornerstone data set that enables them to make that transition.

Julian Klymochko: I really wanted to dig into that because it appears you’re a mission driven company. I see the words ESG and sustainability just throughout your investor presentation, was that, you know, is that a key opportunity and a key mission for the company?

Will Marshall: Well, the two things I’ve just mentioning to you, sustainability transitioning, digital transformation. These are no minor economic opportunities. 

Julian Klymochko: Right. 

Will Marshall: These are multi-trillion-dollar transitions of the global economy. So, it’s solidly both. It’s solidly we started planet with an intent to help bring about a sustainable economy.

Julian Klymochko: Right.

Will Marshall: And it’s a massive business opportunity because this, they need this data, you know, the economist quit, data’s the new oil. Well, there’s some problems with that analogy, some good things about that analogy, but certainly in the sense that data powers, like ours. Powers lots of industries and refinement of it makes it better. But those industries take that and it fuels them to be more efficient or whatever machinery or what have you. There’s some sort of analogy with data, our data is useful for agriculture, for energy, for finance, for insurance, for so many sectors, is powering lots of those sectors. And in that sense, it’s an extremely powerful commodity to have. And we have a very proprietary, the only challenge with Bloomberg data analogy, and I’ll come back to that now. So, we are feeding our data feeds. So, some ag company subscribes to an area or Google as I said, picks off or changes the maps, and that bit. You subscribe to an area; you get a data feed based on your interests. And then those data feeds go into people’s workflows and just like Bloomberg, those workflows, those data feeds enable them to make smarter decisions where the agriculture smart decisions, counties doing that regulatory enforcement, Google making its maps up to date, it’s enabling smarter decisions. So that’s what Bloomberg does, is just focused on the financial data sets, right?

For the financial services, we are focused on earth data. It’s a bit different in that it serves a lot of different vertical markets. And the other big differences is based on a proprietary data set. You know, we have two hundred satellites up there collecting all this data. It’s really, really hard, to put up two hundred satellites. And for anyone else to catch up, we would take many, many years. And even if they caught up, they couldn’t go backwards in time. And a lot of our users use to go back in time to see what happened over time to train their algorithms and so on. And obviously you can’t get back in time, I’m in a physicist and I’m pretty sure we haven’t got time machines yet.

Michael Kesslering: So, you talked a little bit about the different verticals that you have, and anyone with imagination can think of different verticals and use cases of how businesses can use this. And so, you’ve found your product market fit. You have the product itself, the technology itself, I guess, how do you go about taking that from a cool technology, a cool product, into something that the businesses are using, and especially with regards to you talk about it being a truly proprietary and unique dataset. How do you go about pricing that and how do you think about that from a pricing theory perspective?

Will Marshall: It’s a great question on the pricing, especially. Look because it’s a new capability and no one’s priced it yet. What we do is, we price it very simply. It’s based on area and its basically volume of data. So, if you pick an area and how frequently you want to touch it, like every day, every week, every month, and you want this many hectors or this many kilometers per squared, and then we just charge it and there’s volumetric discount, think about it as simple as that. And by the way, we sell each data feed multiple times. So, the marginal cost, by the way, for us of selling, you know, people think, oh, satellites, they must be really, really expensive, low margin. We’ve got very high margins as a business. And the reason is, we can sell each data feed multiple times and incremental costs of selling the data feed the second time is next to nothing.

But anyway, you were asking about pricing. And so basically using this polymetric pay, the good thing is no one else is producing this data set. So, in principle, we could charge more or we could charge less and flood the market and get market position. And then, you know, we have lots of options at our disposal on pricing. We are doing what, you know, a lot of value-based pricing with our customers today. But, you know, it’s based on a very simple model of area imagery and how much you use, but we want to really much focus it on how it provides value to the users. And you were getting that with the first part of your question, which is how do we turn this from a cool tech into a business?

So, you know, it’s taken us a few years, and, you know, it took us about six or seven years to build and launch all these satellites. And then the last three years we’ve been building that business and, you know, it’s not simple, right. And what does it mean? It means calibrating all the data sets and making it easy to pick, it’s making that Bloomberg tunnel. I don’t mean a physical terminal. It’s a website, you know, is a gooey interface and classic API is that you would use for any modern business that automate all of this in the backend. Like in the end, you can set up your data feeds, your area of interest, your analytics that you build on top of it and so on for your needs, right. And so a lot of what we have building on top of this, you know, fifteen hundred layers of imagery for every part of the air surface is machine learning and added insight and simple ways of digesting and integrating that data into your workflow, whether you’re an ag company or the government, or you’re that mapping company, or on and so forth.

Julian Klymochko: So as this data gets integrated into customer’s workflow, could you describe more of how you guys generate revenue? I understand you have a subscription model, and could you also discuss some of the operating leverage as you guys scale?

Will Marshall: Yeah, I mean, look, the really [Inaudible 00:17:12] subscription model over ninety percent, so just last year, we did just over a hundred million of revenue and just over ninety percent of that was recurring revenue, mainly subscription-based business. So yes, people are subscribing to this area over this much time, and sometimes it’s like that, they can add on more stuff on top of that, a bit like maybe you do an AWS, you know, and you get your both discount because of your minimum commit. And then it’s on top of that. The margins just get better with time because the more data we sell. So, our margins last year inclusive of the cost of the satellites, we’re sixty two percent on the bulk of our revenue, the planet scope business, which is seventy three percent of our revenue.

So that’s including the cost of the satellite. So, you know, including amortization and depreciation of those assets, and that’s a big deal, right? Because again, most people think of the satellites as being really expensive. Our Capex, next year is just shy of ten percent which, you know, for a heavy use satellite launching rockets business, you might go well, you wouldn’t have expected that. And that’s because we’re selling. And so, in the future, what are we aiming to do? We are going to leverage this data more and more. We’re going to sell it to more clients. And every time we sell it, you know, basically gravy every time, right. And were going to add value added services on top of the data to enable more clients, to be able to use it.

So, at the present day, it’s mostly folks that have geospatial expertise, you know, big ag companies, governments, and mapping companies like Google have geospatial experts, but we can’t expect everyone. And a lot of other people will get value out of that in principle. So, a lot of what we’re doing next, firstly, is we’re adding lots of sales and marketing efforts, because we can’t deal with all the inbound requests for our data right now. But the second thing is building software to make it easier and easier to use. So, you can imagine that we can make it simpler, and then we can enable it to be useful to the hedge funds, to the insurance companies, to the energy companies, to the many other companies that can’t use it, because they don’t have people with PhDs in computer science or satellite imagery to digest it.

And so, we’re making the tools. Let me give you an example of that. We have a machine learning model called train your own model. Basically, you can say I’m an interested in these kinds of features. And then it will go and find those features in the rest of the world for you or in your area of interest. So, you can imagine how powerful that is. So, you can make it bespoke to the things that you’re trying to find. We’ve already done that for click classic objects, that a lot of people want. We automatically find roads and buildings and ships and planes, but say you were interested in tennis court, we haven’t got that yet. Say you’re interested in silo bags, actually we do have that one, but like, you know, say you’re interested in a particular feature. We can help you to train that. And then you can run that model for yourself. And that’s going to enable a lot more people. That’s going to enable that hedge fund or that insurance company to do their job, whereas today they can’t. And it’s mainly that people who use special expertise getting value out of that data.

Julian Klymochko: So, over a hundred million dollars in revenue from over six hundred customers. So, I’m guessing average customer is a couple of hundred thousand dollars in annual revenue. So, you guys have developed the business, grown it to the point where you are now going public, at two point two five-billion-dollar enterprise value by merging through special purpose acquisition company, dMY Technology Group IV. Can you talk a bit how this deal came together? Was it inbound? Where are you guys seeking to go public and go big time?

Will Marshall: Well, we did get a lot of inbound. I think my CFO was batting off about ten spacs a day at one-point, peak load, but it was pretty high. But we wanted to go public when we were ready to go public and our board very thoroughly consider this, our management team and our board has done these things before. And we would like checking in and making sure that we ready and it got to the point where it made sense. And then we were assessing our options. Niccolo de Masi had knocked on our door over a year earlier than we consummated the transaction. And we sent him away to be honest, but he came back and he was very keen on the data business. And we were very keen on him and his colleague Harry, because they knew data companies, they knew about hardware companies, through INQ, they become [Inaudible 00:21:55] Genius Sports, they really saw the big picture perspective.

They saw Planet as not just the satellite company, but the state of company and the software companies, and it’s all three, right? But they saw the fact that it’s a data business, right. And that’s the core. And they saw the value proposition to sustainability, and they all saw that how this is going to have a lot of retail interest. And they were like, okay, this is cool company, right. And so, it was a good match, both ways. We were ready and I’m really excited about going public actually. We’re ready at the right scale. We’ve scaled our business. We retire the risk on our technology. The satellite are working, you know, [Inaudible 00:22:33] are working. We’ve got lots to do, lots of growth, but this is the right time to go public. Have more capital to invest in sales and marketing, to invest in going up the software stack to have more evaluated services so that we can help other companies. And hopefully also be more well known. A lot of people when I meet them, potential customers, they’ve never heard of Planet. We have a lot of inbound, but like still a lot of the world hasn’t heard of Planet who could get value out of it. And that was going public enables you that. And of course, at the same time we did a pipe and I’m very pleased that BlackRock is leading our pipe because of course they care a lot about ESG and that transition of the community to measuring environmental goals. And we have my, you know, Google coming back in, we have Mac Benioff investing in a big way. And he he’s basically like, he wants to be in everything to do with sustainability. He’s investing in some really cool stuff.

And he said to me that everyone I speak to in this sustainability space needs Planet data or is using it already. Basically, our data is, as he puts it, all roads lead to Planet when it comes to sustainable, either have or need our data to make that transition. So, he thinks this is the bet of the century for, you know, sustainability. And of course, I happen to agree, but it’s, just you know, a bit self-serving to say purely myself, but since he says it, I feel more inclined to.

Julian Klymochko: I’m sure he’s right. I mean, many investors will tell you that these days that ESG and sustainability are massive areas of growth and not only from a business perspective, but also a personal values perspective. So, we touched on a lot, the founding of the company, the development, the business model, and now going public with the two and a million-dollar dollar pipe financing and funding the growth of the business. One thing we didn’t touch on is competition. Who are some of your competitors? How do you differentiate and what makes Planet better?

Will Marshall: In our case, there’s not really much competition as it turns out, because we’re really the first player to put up a fleet of satellites to do a daily scan of the earth or anything like that. There are a couple of companies that already have earth imaging satellites. There’s not like we invented that concept, [Inaudible 00:25:00] Airbus and a couple of others, and a couple of other new starts trying to do that as well. But no one’s got anything like the scale of satellites. So, they’ve all got a few satellites and they can only cover say one or two percent of the land mass of the earth per day, different applications sometimes. But in any case, the kind of applications we’re going after like agriculture, if you only cover one or two percent of the world every day, and agriculture alone is twenty five percent or forestry is another twenty five percent.

All the urban areas and suburban areas is ten percent, you can’t do those applications. You can’t do maritime. You can’t do a lot of applications if your area coverage. So, our area coverage is what enables us to do the applications that we’re doing. And no one has anything like that. If they propose such a mission, if they had perfect funding and a perfect team that was already bonded and already knew how to build lots of satellites, which is not many teams, maybe they could get it done, like catch up to where we are today in five or seven years. And so, we have a fairly good margin from which to exploit this data, get it out there, test the market, grow the market whilst if anyone wants to copy us and, you know, and then of course, it’s our prerogative to keep on innovating on the technology, to have the best data and the best platform that people want to use that delight our customers that add value to them and ultimately help the planet. So that’s our job to continue to push as far as we can.

Julian Klymochko: It sounds like you’re well on your way. So, Will I want to thank you for coming on the podcast. One last question, going to throw out a fun one for there. Since you are the resident, the space expert, what are your thoughts on extraterrestrial life, UFO’s, UAPs, do you believe in any of it? 

Will Marshall: Okay, so whereas it at NASA, one of my friends was on the hot phone that got all the UFO calls, ninety six percent of the [Inaudible 00:27:01]. If I remember him telling me why, I mean, basically almost all of them are just misunderstandings of basic astronomical objects, of course. No, I don’t think it’s very likely that UFO’s will visit the planet, but I think it’s very likely that there’s life in the universe. And in fact, I’ll make a prediction for you. I would predict we will find life off earth within ten years.

Julian Klymochko: Oh, wow. That’s quite the prediction. So, there you have it folks. Will from Planet labs calling for perhaps some alien sightings over the next decade, but we shall see. What investors should know, DMYQ is the ticker symbol for dMY Technology Group for the spec that is merging with Planet. The deal should close, I believe later this year. So, looking forward to that, and once it is closed, what will be the ticker symbol? Is it PL I believe?

Will Marshall: Yeah, that’s right. DMYQ is the ticker symbol of the SPAC vehicle. And PL will be our ticker symbol on the New York stock exchange. And I think people are going to love this, right. You know, they’re going to see the data technology, data in its relevance to a lot of different vertical markets. They’re going to see those margins. They’re going to see developments to sustainable economy, and it’s just fun as well, right? I mean, we’re taking pictures of the whole earth every day. Data is often, by the way, in the press, because we’re exposing things going on around the planet, like just last week, it was in the New York Times with pictures and found a bunch of nuclear weapons silos in China that no one had discovered and we discovered ecological things like, you know, things in the forest, in the Amazon, you name it, we’re just discovering stuff. So, it’s just a fun story to follow and the pictures are beautiful. So, there’s, lots of side of it, but I’m confident about our prospects and excited about it. So, bring it on. 

Julian Klymochko: Sounds great, as are we, so we’ll wish you the best of luck as you pursue, you’re going public journey with Planet and we’ll be watching and wishing you knew the best. So, thank you very much for coming on the show today.

Will Marshall: Thanks a lot Julian and Michael. 

Julian Klymochko: All right, cheers. Bye everybody.

Thanks for tuning in to the Absolute Return Podcast. This episode was brought to you by Accelerate Financial Technologies. Accelerate, because performance matters. Find out more at www.AccelerateShares.com. The views expressed in this podcast to the personal views of the participants and do not reflect the views of Accelerate. No aspect of this podcast constitutes investment legal or tax advice. Opinions expressed in this podcast should not be viewed as a recommendation or solicitation of an offer to buy or sell any securities or investment strategies. The information and opinions in this podcast are based on current market conditions and may fluctuate and change in the future. No representation or warranty expressed or implied is made on behalf of Accelerate as to the accuracy or completeness of the information contained in this podcast. Accelerate does not accept any liability for any direct indirect or consequential loss or damage suffered by any person as a result relying on all or any part of this podcast and any liability is expressly disclaimed.

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