>>Welcome back everyone to the cubes coverage here in Seattle, Washington for AWS's marketplace seller conference. The big news here is that the Amazon partner network and marketplace coming together and reorganizing into one organization, the AIST partner organization, APO bringing together the best of the partnership and the marketplace to sell through. It's a sellers company. This is the second year, but technically with COVID, I call it a year and a half. This is the cube. I'm John for your host. Got a great guest, Leah for sale vice president of business development at four square. Leah, thanks for coming on the cube. Look great. Yeah. >>Hey, thanks. Thanks for having me here. >>So four square, everyone, and that has internet history knows you. You check in you'd become the mayor of a place right back in the day, all fun. It was a great app and I think it was competitor go sold the Facebook, but that was the beginning of location data. Now you got Uber apps, you got all apps, location, everywhere. Data is big here in the marketplace. They sell data, they got a data exchange, Chris head of marketplaces. Like we have all these things we're gonna bring 'em together, make it simpler. So you're on the data side. I'm assuming you're selling data and you're participating at the data exchange. What is Foursquare doing right now? Yeah, >>Exactly. So we are part of the data exchange. And you mentioned checking in. So we, we are really proud of our roots, the, the four square app, and that's kind of the basis still of our business. We have a hundred million data points, which are actually places of interest across the world 200 countries. And we are we're in the business of understanding whereplace are and how people move through those places over time. And >>What's the value proposition for that data. You're selling the data. >>We are selling the data and we're selling it. You can think about use cases. Like how can I improve the engagement with my app through location data? So for example, next door, as a customer of ours, everyone knows next door. When a new business comes online, they wanna make sure that business is a real business. So they use our places to ensure that the address of that business is accurate. >>So how did you, how do you guys get your data? Because if you don't have the first party app, you probably had critical mass of data. Yeah. But then do other people use your data and then re contribute back in kinda like, well, Stripe is for financial. You guys are plugging in yeah. To >>Apps. A great question. So we still do have our consumer apps. We're still proud of those. It's still a basis of our company really. Okay. So, but we take that data. So our first party data, we also, for all the web, we have some partners integrate our SDK. And so we're pulling in all that data from various sources and then scrubbing it and making sure we have the most unique. >>So you guys still have a business where the app's working. Yep. Okay. But also let's just say, I wanna have a cube app. Yeah. And I want to do a check in button. Yep. So rather than build checking in, could I OEM you could four square is that you >>Could, and we could help you understand where people are checking in. So we know someone's here at the Hilton and Bellevue, we know exactly where that place is. You building the Cub app. You could say, I'm gonna check in here and we are verified. We know that that's the >>Right place. So that's a good for developer if they're building an app. >>Absolutely. So we have an SDK that any developer can integrate. >>Great. Okay. So what's the relationship with the marketplace? Take us through how Foursquare works with AWS marketplace. >>Sure. So we are primarily integrated with ADX, which is sort of a piece of marketplace it's for data specifically, we have both of our main products, which are places that POI database and visits, which is how people move through those places over time. So we're able to say these are the top chains in the country. Here's how people move throughout those. And both those products are listed on ADX. >>So if I'm in Palo Alto and I go to Joe in the juice yeah. You know that I kind of hang in one spot or is it privacy there? I mean, how do you know like what goes on? Well, >>We know somebody does that. We don't >>Know that you do that. So >>We ensure, you know, we're very privacy centric and privacy focused. We're not gonna, we don't tell anybody at you >>Yourself it's pattern data. It is. >>Okay. So it's normalized data, right? Over time groups of people, >>How they, how are people using the data to improve processes, user experience? What are some of the use cases? >>So that example, nextdoor, that's really a use case that we see a lot and that's improving their application. So that nextdoor app to ensure that the ACC, the data's accurate and that as you, as a user, you know, that that business is real. Cuz it's verified by four wear. Another one is you can use our data to make business decisions around where you're gonna place your next loca. You know, your next QSR. So young brands is a customer of ours. Those are, those guys are pizza hut KFC. They work with us to figure out where they should put their next KFC. Yeah. >>I mean retail location, location, location. Yeah. >>Right. Yeah. People are still, even though e-commerce right. People still go into stores >>And still are. Yeah. There's, there's, there's probably lot, a lot of math involved in knowing demographics patterns. Volume. >>Yeah. Some of our key customers are really data scientists. Like the think about cus with businesses that have true data science companies. They're really looking at that. >>Yeah. I mean in, and out's on the exit for a reason. Right. They want in and out. Yeah. So they wanna put it inland. >>Right. And we can actually tell you where that customer from in and out where they go next. Right. So then, you know, oh, they go to this park or they go somewhere and we can help you place your next in and out based on that visitation. >>Yeah. And so it's real science involved. So take us through the customers. You said data scientists, >>Mostly data scientists is kind of a key customer data science at a large corporation, like a QSR that's >>Somebody. Okay. So how is the procurement process on the marketplace? What does the buyer get? >>So what we see the real value is, is because they're already a customer of Amazon. That procurement is really easy, right? All the fulfillment goes through Amazon, through ADX. And what you're buying is either at API. So you can, that API can make real time calls or you're buying a flat file, like an actual database of those hundred points of interest. >>And then they integrate into their tool set. Right. They can do it. So it's pretty data friendly in terms of format. >>You can kind of do whatever you want with it. We're gonna give you that as long as you're smart enough to figure out what to do. Do we have a >>Lot of, so what's your experience with AWS marketplace? I mean, obviously we, we see a lot of changes. They had a reorg partner network merging with marketplace. You've been more on the data exchange, Chris kind of called that out. It's yeah. It's kind of a new thing. And, and he was hinting at a lot of confusion, but simplifying things. Yeah. What's your take of the current AWS marketplace >>Religions? I actually think ADX because our experience has primarily been ADX. I think they've done a really good job. They've really focused on the data and they understand how CU, how, you know, people like us sell our data. It hasn't been super confusing. We've had a lot of support. I think that's what Amazon gives you. You have to put a lot of effort into it, but they're also, they also give you a lot of support. >>Yeah. And, and I think data exchange is pretty significant to the strategic. It is >>Mission. It is. We feel that. Yeah. You know, we feel like they really value us as a partner. >>What's the big thing you're seeing out there right now in data, because like you're seeing a lot more data exchanges going on. There's always been data exchange, but you're seeing a lot more exchanges between companies. So let's just take partners. You're seeing a lot more people handle front end of a, a supply chain and you got more data exchanges. What's the future of data exchanges. If you had to kind of, you know, guess given your history in, in the industry. Yeah. What's the next around the corner trend? >>I think. Well, I think there's a, has to be consolidation. I know everyone's building one, but there's probably too many. I know from our experience, we can't support all of them. We're not a huge company. We can't support Amazon and X and Y and Z. Like it's just too many. So we kind of put all of our eggs in a couple baskets. So I think there'll be consolidation. I think there has to be just some innovation on what data products are, you know, for us, we have these two, it's an API and a flat file. I think as exchanges think about, you know, expanding what are the other types of data products that can help us build? >>Yeah. I mean, one of the things that's, you know, we see, we cover a lot of on the cube is edge. You know, you got, yeah. Amazon putting out new products in regions, you got new wavelength out there, you got regions, you got city level connectivity, data coming from cars. So a lot more IOT data. How do you guys see that folding into your vision of data acquisition and data usage, leverage, reuse, durability. These >>Are, yeah. I mean, we're, we are keeping an eye on all of that. You know, I think we haven't quite figured out how we wanna allocate resources against it, but you know, it's definitely, it's a really interesting space to be in. Like, I don't think data's going anywhere and I think it's really just gonna grow and how people use it's >>Gonna expand. Okay. So if I'm a customer, I go to the marketplace, I wanna buy four square data. What's the pitch. >>We can help you improve your business decisions or your applications through location data. We know where places are and how people move through the world over time. So we can tell you we're, we're sure that this is the Hilton in Bellevue. We know that, that we know how many people are moving through here and that's really the pitch. >>And they use that for whatever their needs are, business improvement, user experience. Yeah. >>Those are really the primary. I mean, we also have some financial use cases. So hedge funds, maybe they're thinking about yeah. How they wanna invest their money. They're gonna look at visits over time to understand what people are doing. Right. The pandemic made that super important. >>Yeah. That's awesome. Well, this is great. Great success story. Congratulations. And thanks for sharing on the cube. Really appreciate you coming on. Thank you. My final question is more about kind of the future. I wanna get your thoughts because your season pro, when you have the confluence of physical and digital coming together. Yeah. You know, I was just talking with a friend about FedEx's earnings, comparing that to say, AWS has a fleet of delivery too. Right? Amazon, Amazon nots. So, but physical world only products location matters. But then what about the person when they're walking around the real world? What happens when they get to the metaverses or, you know, they get to digital, they tend an event. Yeah. How do you see that crossroad? Cuz you have foot in both camps. We do, you got the app and you got the physical world it's gonna come together. Is there thoughts around, you can take your course care hat off and put your industry hat on. Yeah. You wanna answer that? Not officially on behalf of Foursquare, but I'm just curious, this is a, this is the confluence of like the blending of physical and digital. >>Yeah. I know. Wow. I admittedly haven't thought a whole lot about that. I think it would be really weird if I could track myself over time and the metaverse I mean, I think, yeah, as you said, it's >>It's, by the way, I'm not Bo on the metaverse when it's blocked diagrams, when you have gaming platforms that are like the best visual experience possible, right? >>Yeah. I mean, I think it, I think we'll see, I don't, I don't know that I have a >>Prediction, well hybrid we've seeing a lot of hybrid events. Like this event is still intimate VIP, but next year I guarantee it's gonna be larger, much larger and it's gonna be physical and face to face, but, but digital right as well. Yeah. Not people experiencing the, both that first party, physical, digital hybrid. Yeah. And it's interesting something that we track a lot >>Of. Yeah, for sure. Yeah. I think we'll have a, well, I think we'll, there's something there for us. I think that those there's a play there as we watch kind >>Of things change. All right, Leah, thank you for coming on the Q appreciate so much it all right. With four Graham, John fur a year checking in with four square here on the cube here at the Amazon web services marketplace seller conference. Second year back from the pandemic in person, more coverage after this break.

>>Okay, welcome back. Everyone. Live cube coverage here in Las Vegas for Amazon re Mars hot event, machine learning, automation, robotics, and space. Two days of live coverage. We're talking to all the hot technologists. We got all the action startups and segment on sustainability and F pan hero for vet global lead, Amazon sustainability data initiative. Thanks for coming on the cube. Can I get that right? Can >>You, you, you did. >>Absolutely. Okay, great. <laugh> thank >>You. >>Great to see you. We met at the analyst, um, mixer and, um, blown away by the story going on at Amazon around sustainability data initiative, because we were joking. Everything's a data problem now, cuz that's cliche. But in this case you're using data in your program and it's really kind of got a bigger picture. Take a minute to explain what your project is, scope of it on the sustainability. >>Yeah, absolutely. And thank you for the opportunity to be here. Yeah. Um, okay. So, um, I, I lead this program that we launched several years back in 2018 more specifically, and it's a tech for good program. And when I say the tech for good, what that means is that we're trying to bring our technology and our infrastructure and lend that to the world specifically to solve the problems related to sustainability. And as you said, sustainability, uh, inherently needs data. You need, we need data to understand the baseline of where we are and also to understand the progress that we are making towards our goals. Right? But one of the big challenges that the data that we need is spread everywhere. Some of it is too large for most people to be able to, um, access and analyze. And so, uh, what we're trying to tackle is really the data problem in the sustainability space. >>Um, what we do more specifically is focus on Democrat democratizing access to data. So we work with a broader community and we try to understand what are those foundational data sets that most people need to use in the space to solve problems like climate change or food security or think about sustainable development goals, right? Yeah. Yeah. Like all the broad space. Um, and, and we basically then work with the data providers, bring the data to the cloud, make it free and open to everybody in the world. Um, I don't know how deep you want me to go into it. There's many other layers into that. So >>The perspective is zooming out. You're, you're, you're looking at creating a system where the democratizing data means making it freely available so that practitioners or citizens, data, Wrangler, people interested in helping the world could get access to it and then maybe collaborate with people around the world. Is that right? >>Absolutely. So one of the advantages of using the cloud for this kind of, uh, effort is that, you know, cloud is virtually accessible from anywhere where you have, you know, internet or bandwidth, right? So, uh, when, when you put data in the cloud in a centralized place next to compute, it really, uh, removes the, the need for everybody to have their own copy. Right. And to bring it into that, the traditional way is that you bring the data next to your compute. And so we have this multiple copies of data. Some of them are on the petabyte scale. There's obviously the, the carbon footprint associated with the storage, but there's also the complexity that not everybody's able to actually analyze and have that kind of storage. So by putting it in the cloud, now anyone in the world independent of where of their computer capabilities can have access to the same type of data to solve >>The problems. You don't remember doing a report on this in 2018 or 2017. I forget what year it was, but it was around public sector where it was a movement with universities and academia, where they were doing some really deep compute where Amazon had big customers. And there was a movement towards a open commons of data, almost like a national data set like a national park kind of vibe that seems to be getting momentum. In fact, this kind of sounds like what you're doing some similar where it's open to everybody. It's kinda like open source meets data. >>Uh, exactly. And, and the truth is that these data, the majority of it's and we primarily work with what we call authoritative data providers. So think of like NASA Noah, you came me office organizations whose mission is to create the data. So they, their mandate is actually to make the data public. Right. But in practice, that's not really the case. Right. A lot of the data is stored like in servers or tapes or not accessible. Um, so yes, you bring the data to the cloud. And in this model that we use, Amazon never actually touches the data and that's very intentional so that we preserve the integrity of the data. The data provider owns the data in the cloud. We cover all the costs, but they commit to making it public in free to anybody. Um, and obviously the computer is next to it. So that's, uh, evaluated. >>Okay. Anna. So give me some examples of, um, some successes. You've had some of the challenges and opportunities you've overcome, take me through some of the activities because, um, this is really needed, right? And we gotta, sustainability is top line conversation, even here at the conference, re Mars, they're talking about saving climate change with space mm-hmm <affirmative>, which is legitimate. And they're talking about all these new things. So it's only gonna get bigger. Yeah. This data, what are some of the things you're working on right now that you can share? >>Yeah. So what, for me, honestly, the most exciting part of all of this is, is when I see the impact that's creating on customers and the community in general, uh, and those are the stories that really bring it home, the value of opening access to data. And, and I would just say, um, the program actually offers in addition to the data, um, access to free compute, which is very important as well. Right? You put the data in the cloud. It's great. But then if you wanna analyze that, there's the cost and we want to offset that. So we have a, basically an open call for proposals. Anybody can apply and we subsidize that. But so what we see by putting the data in the cloud, making it free and putting the compute accessible is that like we see a lot, for instance, startups, startups jump on it very easily because they're very nimble. They, we basically remove all the cost of investing in the acquisition and storage of the data. The data is connected directly to the source and they don't have to do anything. So they easily build their applications on top of it and workloads and turn it on and off if you know, >>So they don't have to pay for it. >>They have to pay, they basically just pay for the computes whenever they need it. Right. So all the data is covered. So that makes it very visible for, for a lot of startups. And then we see anything like from academia and nonprofits and governments working extensively on the data, what >>Are some of the coolest things you've seen come out of the woodwork in terms of, you know, things that built on top of the, the data, the builders out there are creative, all that heavy, lifting's gone, they're being creative. I'm sure there's been some surprises, um, or obvious verticals that jump healthcare jumps out at me. I'm not sure if FinTech has a lot of data in there, but it's healthcare. I can see, uh, a big air vertical, obviously, you know, um, oil and gas, probably concern. Um, >>So we see it all over the space, honestly. But for instance, one of the things that is very, uh, common for people to use this, uh, Noah data like weather data, because no, basically weather impacts almost anything we do, right? So you have this forecast of data coming into the cloud directly streamed from Noah. And, um, a lot of applications are built on top of that. Like, um, forecasting radiation, for instance, for the solar industry or helping with navigation. But I would say some of the stories I love to mention because are very impactful are when we take data to remote places that traditionally did not have access to any data. Yeah. And for instance, we collaborate with a, with a program, a nonprofit called digital earth Africa where they, this is a basically philanthropically supported program to bring earth observations to the African continents in making it available to communities and governments and things like illegal mining fighting, illegal mining are the forestation, you know, for mangroves to deep forest. Um, it's really amazing what they are doing. And, uh, they are managing >>The low cost nature of it makes it a great use case there >>Yes. Cloud. So it makes it feasible for them to actually do this work. >>Yeah. You mentioned the Noah data making me think of the sale drone. Mm-hmm <affirmative> my favorite, um, use case. Yes. Those sales drones go around many them twice on the queue at reinvent over the years. Yeah. Um, really good innovation. That vibe is here too at the show at Remar this week at the robotics showcases you have startups and growing companies in the ML AI areas. And you have that convergence of not obvious to many, but here, this culture is like, Hey, we have, it's all coming together. Mm-hmm <affirmative>, you know, physical, industrial space is a function of the new O T landscape. Mm-hmm <affirmative>. I mean, there's no edge in space as they say, right. So the it's unlimited edge. So this kind of points to the major trend. It's not stopping this innovation, but sustainability has limits on earth. We have issues. >>We do have issues. And, uh, and I, I think that's one of my hopes is that when we come to the table with the resources and the skills we have and others do as well, we try to remove some of these big barriers, um, that make it things harder for us to move forward as fast as we need to. Right. We don't have time to spend that. Uh, you know, I've been accounted that 80% of the effort to generate new knowledge is spent on finding the data you need and cleaning it. Uh, we, we don't have time for that. Right. So can we remove that UN differentiated, heavy lifting and allow people to start at a different place and generate knowledge and insights faster. >>So that's key, that's the key point having them innovate on top of it, right. What are some things that you wanna see happen over the next year or two, as you look out, um, hopes, dreams, KPIs, performance metrics, what are you, what are you driving to? What's your north star? What are some of those milestones? >>Yeah, so some, we are investing heavily in some areas. Uh, we support, um, you know, we support broadly sustainability, which as, you know, it's like, it's all over, <laugh> the space, but, uh, there's an area that is, uh, becoming more and more critical, which is climate risk. Um, climate risk, you know, for obvious reasons we are experienced, but also there's more regulatory pressures on, uh, business and companies in general to disclose their risks, not only the physical, but also to transition risks. And that's a very, uh, data heavy and compute heavy space. Right. And so we are very focusing in trying to bring the right data and the right services to support that kind of, of activity. >>What kind of break was you looking for? >>Um, so I think, again, it goes back to this concept that there's all that effort that needs to be done equally by so many people that we are all repeating the effort. So I'll put a plug here actually for a project we are supporting, which is called OS climates. Um, I don't know if you're familiar with it, but it's the Linux foundation effort to create an open source platform for climate risk. And so they, they bought the SMP global Airbus, you know, Alliance all these big companies together. And we are one of the funding partners to basically do that basic line work. What are the data that is needed? What are the basic tools let's put it there and do the pre-competitive work. So then you can do the build the, the, the competitive part on top of it. So >>It's kinda like a data clean room. >>It kind of is right. But we need to do those things, right. So >>Are they worried about comp competitive data or is it more anonymized out? How do you, >>It has both actually. So we are primarily contributing, contributing with the open data part, but there's a lot of proprietary data that needs to be behind the whole, the walls. So, yeah, >>You're on the cutting edge of data engineering because, you know, web and ad tech technologies used to be where all that data sharing was done. Mm-hmm <affirmative> for the commercial reasons, you know, the best minds in our industry quoted by a cube alumni are working on how to place ads better. Yeah. Jeff Acker, founder of Cloudera said that on the cube. Okay. And he was like embarrassed, but the best minds are working on how to make ads get more efficient. Right. But that tech is coming to problem solving and you're dealing with data exchange data analysis from different sources, third parties. This is a hard problem. >>Well, it is a hard problem. And I'll, I'll my perspective is that the hardest problem with sustainability is that it goes across all kinds of domains. Right. We traditionally been very comfortable working in our little, you know, swimming lanes yeah. Where we don't need to deal with interoperability and, uh, extracting knowledge. But sustainability, you, you know, you touch the economic side, it touches this social or the environmental, it's all connected. Right. And you cannot just work in the little space and then go sets the impact in the other one. So it's going to force us to work in a different way. Right. It's, uh, big data complex data yeah. From different domains. And we need to somehow make sense of all of it. And there's the potential of AI and ML and things like that that can really help us right. To go beyond the, the modeling approaches we've been done so >>Far. And trust is a huge factor in all this trust. >>Absolutely. And, and just going back to what I said before, that's one of the main reasons why, when we bring data to the cloud, we don't touch it. We wanna make sure that anybody can trust that the data is nowhere data or NASA data, but not Amazon data. >>Yes. Like we always say in the cube, you should own your data plane. Don't give it up. <laugh> well, that's cool. Great. Great. To hear the update. Is there any other projects that you're working on you think might be cool for people that are watching that you wanna plug or point out because this is an area people are, are leaning into yeah. And learning more young, younger talents coming in. Um, I, whether it's university students to people on side hustles want to play with data, >>So we have plenty of data. So we have, uh, we have over a hundred data sets, uh, petabytes and petabytes of data all free. You don't even need an AWS account to access the data and take it out if you want to. Uh, but I, I would say a few things that are exciting that are happening at Mars. One is that we are actually got integrated into ADX. So the AWS that exchange and what that means is that now you can find the open data, free data from a STI in the same searching capability and service as the paid data, right. License data. So hopefully we'll make it easier if I, if you wanna play with data, we have actually something great. We just announced a hackathon this week, uh, in partnership with UNESCO, uh, focus on sustainable development goals, uh, a hundred K in prices and, uh, so much data <laugh> you >>Too years, they get the world is your oyster to go check that out at URL at website, I'll see it's on Amazon. It use our website or a project that can join, or how do people get in touch with you? >>Yeah. So, uh, Amazon SDI, like for Amazon sustainability, that initiative, so Amazon sdi.com and you'll find, um, all the data, a lot of examples of customer stories that are using the data for impactful solutions, um, and much more >>So, and these are, there's a, there's a, a new kind of hustle going out there, seeing entrepreneurs do this. And very successfully, they pick a narrow domain and they, they own it. Something really obscure that could be off the big player's reservation. Mm-hmm <affirmative> and they just become fluent in the data. And it's a big white space for them, right. This market opportunities. And at the minimum you're playing with data. So this is becoming kind of like a long tail domain expertise, data opportunity. Yeah, absolutely. This really hot. So yes. Yeah. Go play around with the data, check it outs for good cause too. And it's free. >>It's all free. >>Almost free. It's not always free. Is it >>Always free? Well, if you, a friend of mine said is only free if your time is worth nothing. <laugh>. Yeah, >>Exactly. Well, Anna, great to have you on the cube. Thanks for sharing the stories. Sustainability is super important. Thanks for coming on. Thank you for the opportunity. Okay. Cube coverage here in Las Vegas. I'm Sean. Furier, we've be back with more day one. After this short break.