Interview with Placer.ai CMO Ethan Chernofsky on the Importance of Data for Retail and Shopping Center Success
Interview with Placer.ai CMO Ethan Chernofsky on the Importance of Data for Retail and Shopping Center Success
Darius 0:01 Welcome to the retail tech podcast. My name is Darius Vasefi. And this is a podcast where I speak with the movers and shakers in the retail and e commerce and anything related to that industry to meet them and learn about what's the latest thing that they're working on.
So, today I am speaking with Ethan ternovskiy from a company called place or AI. I hope I spelled your last name correctly, Ethan.
Ethan Chernofsky 0:34 Yeah, that is Great.
Darius 0:36 Awesome, awesome. Well, thanks for joining me, Placer is a very interesting company. I just recently learned about it from my some of my other contacts, and really love to learn more about yourself and what blazer is doing. So maybe we can just start with a brief intro about maybe yourself, how did you get into this business? And now you know, we're going to workplace or does.
Ethan Chernofsky 1:04 Sure. So I, you know, I come from the technology ecosystem average for startups in the past, specifically, most recently, another data startup called similar web, which is online. So the ability to kind of join in early stage startup I joined plaister, over two years ago, was really attractive at the chance to kind of help be a part of building a company like this, places, location data companies. So what that means, like the simplest form is, you know, you think people vote with their feet, we're showing you how they vote every single day across the United States. very critically, it's all anonymized aggregate data. So the data that we see is used to create a panel. on that panel, we run AI machine learning algorithms to make estimations, retail visits anywhere across the US. And then we present that data in a wealth of different reports in our dashboard. And we kind of provide that service to our customers, we also have a bunch of free tools that are available both on our website at you know, place your data.ai a section called the square, which is kind of totally free tools. And then we also have a free version of our premium product that you can also sign up for at place. Right.
Darius 2:20 Great. So yeah, I was, I've been playing around with the website, it looks really interesting. And I think I need to sign up to get the data about the location that I was looking for. So
Ethan Chernofsky 2:36 yeah, I mean, we hope so. But I think I think the key is, we really have a, I think, a deep understanding of the fact that data like this can be really, really valuable. And it can have a huge impact on the way organizations make decisions. And very critically, the decisions that are getting made in the brick and mortar retail world are not. They're not trivial. They're actually, in fact, many cases, the most significant when you think of the costs that go into choosing where to place a store, or how to operate within a specific market, or whether to buy a shopping center or not. These are really costly, significant decisions. And the ability to leverage data as a mechanism to improve the likelihood that each decision is correct, is a really significant piece of the puzzle and an area where we believe we can have a lot of impact.
Darius 3:30 Yeah, I think we all know by now, or we should know by now that data is the new oil, or the oxygen of running businesses. So that's should be a known fact, for anybody who's in business in today's world, especially retailers, and e commerce players. So that is really critical. Let me ask you a question about a, you know, something you said, What do you mean by anonymized? What does that mean? And how do you actually do that.
Ethan Chernofsky 4:01 So as a as a data company, you kind of have a choice in terms of where you sit on the spectrum. So there are companies like, you know, Facebook, where they have your data, and you they're using it to target you as an individual, right? So they want Ethan to get the best possible ads. So it increases the likelihood that I click on them and then eventually buy things. And and so to do that, they need to know a lot of information about being we don't, we don't need that we're looking at things at a macro level. So what we want to do is understand the movement patterns of certain devices, enough so that we can make estimations on the movement patterns of theory all people. So when we say anonymize, it means that no personally identifiable information is coming into our system. And by having that level of privacy focus, we're able to ensure that we're not just regular in from a regulatory perspective, we're not just GDPR and ccpa compliant today, but we're ahead of where the right He is going. And we put in a lot of efforts and focus to ensure that our technology, technological infrastructure is done privacy by design. So it's built to ensure that we can stay compliant and stay committed to user privacy, while still enabling the type of impact that we think we can make with our technology.
Darius 5:22 Okay, so but you do have a way of tracking that individual? Like person, right, or or user across their diff, their journey, I guess?
Ethan Chernofsky 5:37 Yes. But then again, the question is, what do you do with it? And how do you what information do you take in? So in theory, if I want to target there's, you know, if I'm an advertising platform, and I want to get Ethan to go into a Starbucks, I love Starbucks. And I walk past one. And I want to make sure that when Ethan walks past a Starbucks, he gets hit with an ad of like, Hey, get $1 off your blueberry muffin. That's, that requires me to have information on the specific individual using this specific device, right. If in theory, though, you're only focused on those macro levels, and you're only using the data from a as a panel to then run your estimations on top of you don't need that information. And so if I don't need that information, what I want to understand is that a device went from point A to point B to point C, but I can take all of these other steps to ensure that I never know anything more than that. So I don't know who the device belongs to, I can blur things, once it enters into any degree of like, residential zone, so that I can't know where that where someone is home location is, you can take many, many steps to ensure privacy. So that you don't even need to enter into that mass, I think it's one of the really important things within this wider conversation around data is that it's not a choice of like data or privacy. Obviously, there are some people who say, I don't want anyone to know anything about me ever. And that's totally fair. And there are people on the other side of the spectrum who say, I don't care, let them see everything. But there's a very large middle ground where you can find a very strong way to protect consumer data and consumer privacy while still enabling solutions to provide resources for businesses.
Darius 7:18 Okay, so just to do a quick reset to the room, this interview is being recorded. And it's on clubhouse. And I will add it to my website, retail tech podcast, in a few days after we're done. So, I mean, the concept of data, and privacy is, of course, top of mind for all of us, you know, as consumers ourselves is, you know, very important for us. On the other side of the picture. The other thing that's really important is the idea of personalization. So how do you so you don't really get into the personalization side of the business, you, you capture this data, you provide it to retailers and shopping centers, and you know, hedge funds, or whoever that uses the data to show them is it core traffic basically, is what you're trying to provide or anything else.
Ethan Chernofsky 8:22 It's like Google Analytics for the real world. So you're trying to show what's actually happening offline. And there are a lot of stakeholders who have a huge amount to gain or lose by understanding this information. We're not in the personalization game at all. And it's because of that privacy focus that we discussed. So you have to make a decision as a company where you want to in your attention. And there are companies who say, you know, hey, we want to be in this personalization game. And ultimately, you know, at least I'm a believer that that that helps. Like, I don't I don't have a problem with that. But there are people who are and there's a whole different level of privacy concerns and considerations to have, if that's your focus. For us, we are for looking at those macro trends. So how many people visited Starbucks nationwide? The week of august 2? That's a question we want to know how many people visited a specific mall? And what that might mean for retailers who are deciding where to put their next store? Those are the types of questions we're trying to answer. So that macro level data is what we're attempting to create and then provide in a really accessible way.
Darius 9:29 Okay. So, I mean, that's definitely, you know, a key piece of, you know, making a decision where to invest your resources and money, I guess, for for companies. So if you have this data, and you have it in real time, so that's the other part of it. I think what you do is you provide I mean, this data can be captured. In the past it was captured, but probably took months to get it right. Even if there are,
Ethan Chernofsky 10:05 there were places where you could even wait weeks for report. And you would get just the report, you wanted the idea. And we have a, you know, three to four day lag so that we can run our algorithms. But what you're talking about is near real time access to what's happening in the offline world, and kind of in unlimited about queries that you can ask. And what that allows you to do is, you know, again, in the past, imagine, you requested certain data, and you would have to wait weeks for it to come. But then when it came, and you were diving in digging in, it wasn't answering enough of the questions that you needed answered. And so what do you do now, you're kind of like stuck you to then go through a process and wait another two weeks. I think one of the important elements of being a sass platform is what you is that you enable people to dive into the rabbit hole, and really kind of dig into any question that they have, in the moment it during that like eureka moment of who what am I looking at this. And I think that's where it gets really exciting. A lot of the more creative and interesting solutions or utilizations of the product that we see. come from those spur of the moment who I have an idea. Let me open up the platform dive in and it's all available at my fingertips right away.
Darius 11:23 All right, awesome. So I have a good friend of mine who I respect a lot that's going to join us you probably know her as well, Denise. I don't know if you know Denise or not, but she's in the shopping center. Business. Hi, Denise.
Unknown Speaker 11:41 Hi. darious Hi, there. You've been. Hi, Denise. Hey, I, we have talked and then Witten, who was on your your podcast last week actually works for my husband, Steve. So on. Yes, in small world and enjoyed getting to know, dairies and learn about his product. And I listened to your your session last week about shopping centers. And I thought what would be interesting maybe to share with people is, is the traffic patterns that you're seeing from comparing 21 to 19? Not necessarily 20, where we're seeing, you know, large returns to the shopping centers and the better ones.
Ethan Chernofsky 12:25 Yeah, absolutely. And, you know, Denise is referring to, you know, Ben Whitney trademark, who was kind enough to join one of our webinars last week, we talked about the mall recovery, you know, to a whole podcast in a while up and when but that's for another time. There, I think what's what has been really fascinating when we look at retail and the retail recovery is, I think not only when you look at the numbers, you have to consider the conversation that was happening. You know, just a year ago, in the midst of the pandemic, one of the things that we kept on hearing was that consumer behavior, if given enough time to change and kind of bake in, was going to change forever. And so I think some people would say 60 to 90 days, some people a little bit more. But if we saw a shifting shopping behavior for too long, then things weren't going to go back to normal. And we were going to create this quote unquote, new normal, etc. And yet, what we've seen is that kind of this recovery periods, I don't know that there is such a thing as post COVID, at least in the near term. But this recovery period for retail has shown us that the havior is looks a lot more like it did pre pandemic than in the height of demand. And so we are seeing a really strong recovery at balls, a really strong recovery in brick and mortar retail, casual dining restaurants, I mean segments, some segments that weren't doing well prepared to talk to your balls were doing well before the pandemic. And so the fact they're doing well, as you know, as we start to recover, at least from a retail perspective, makes sense. But casual dining, a lot of these chains were struggling very significantly, pre pandemic, and yet, we're seeing visits come back in mass. And I think what's interesting is that we were in many cases reminded that we like certain things that how exciting going to a restaurant is and that, you know, as much as we might complain about having to the grocery store, when we actually have the choice of do I want to buy something online? Or do I don't want to walk through a store and kind of decide when I want, we're very often going to choose that offline experience. In fact, more cases than not, we're going to choose it. So it's been really interesting to see how resilient consumer demand has been, and how resilient consumer behavior has been an outage driven it has been by routine and patterns as opposed to, you know, the shifts that we saw in the midst of the height of the pandemic.
Darius 14:57 That's a that was a great question Denise. So I definitely actually recommend if you go to play sir.ai I think they have the webinar is called the mall update 2021. I watched it last week. And that's where I did some of my notes from getting to know place AI better. So yeah. So what what are you seeing that is? Is there anything that you're seeing? That's kind of like surprising?
Ethan Chernofsky 15:28 I mean, a lot. I mean, a lot of things have been surprising. And again, it's a surprise means like, what did you expect, and then therefore, kind of what delivered so there's some sectors that surprise in a really positive way. So I think when you look at like home improvement chains, like Home Depot, Lowe's Tractor Supply, the the ability to kind of leverage the pandemic to kind of drive this extended interest in do it yourself, was really incredible. And it is much as like, it felt like a very strong alignment of trends that drove this. The fact that it lasted as long as it did was hugely significant, I'd say even more. So. Even now, though, the numbers are not the same as they were a year ago, there's so much higher than they were in 2019, that it's created this extended buzz around, you know, to what yourself and upgrading our homes and making that home improvement experience stronger. Another area that surprised me has been casual dining, I didn't expect it to come back strongly. I thought you were going to see QSR do really, really well. And it has, I thought there were some segments that were going to bounce back very quickly. But I, I didn't think that a lot of these sit down restaurant chains, were going to see a strong comeback, I thought that maybe they would, you know, continue with some of the struggles they'd see pre pandemic. And that kind of resiliency of consumer demand has been an incredibly surprising in this space. And so the last one is with fitness. Now, to be fair, I had a lot of belief that fitness was going to bounce back, I just didn't expect it to bounce back as fast as it did. So if you look at Planet Fitness as a chain nationwide, they have more visits, they have more visits in July than they did in July in July 2021 than they did in July 2019. Which means that even though in the height of the pandemic, we were talking about the death of the gym, and the fact that we were all just going to move to our peloton bikes and stop going to fitness centers, they've seen a really strong rebound, people are proving with, with their kind of actual actions that they want to be in the gym. And it's driven this really incredible rebound in that space. So that's it, there's the present.
Darius 17:43 Yeah, especially the last one is kind of a surprise. For me, it might be a little bit price sensitive. So I know of some gyms close to where I live that are more, I guess priced higher. And they're not doing as well as the types of like Planet Fitness. So. So
Ethan Chernofsky 18:03 surgery, I think it's part of it is because of who is going to where you were to think like gyms are still operating at a disadvantage in the sense that there are some people who want to go to the gym from their house, right. And so those people are probably going back and driving a lot of this return. But there's a lot of us who were choosing the gym based on where we work. And if our work patterns have been disrupted, even some one that's going to impact gym visits. So as much as a lot of the recovery we're seeing, it's it's happening, even though some elements of these businesses are still being hurt. So it's in many cases, more impressive than we're getting a credit for. And the fact that we're seeing recovery, this soon, even with so many lingering elements that are that are hurting these brands only makes it stronger.
Darius 18:55 That's very interesting. I'm wondering, can you do like aggregate? I guess analytics on your data? So can you say for example, because I know, one of our clients is a shopping center. And there is actually Gold's Gym in there. And I'm wondering if the gyms in shopping centers are doing better or not? Is that the kind of data you can get? So
Ethan Chernofsky 19:21 yeah, so in theory, you can see a gold gym location. And you could take, you know, let's say there's 30 in the state that your friend shopping centers that you could look at, you could break them down and slice them and dice them however you'd want and see which ones are recovering faster. So there are because of the level of granularity we go to which is looking at data at the property level. You can build it up however you'd like. And that could be, you know, on a specific case like this, where I want to see every Gold's Gym in a state and I want to put it into my own categories. And it could be I want to look at a chain. You know, I want to look at Starbucks in California versus New York. And it could be that I want to look at a specific Starbucks on the corner of, you know, Main Street and 17th Street in, you know, any city in the US. So that level of granularity exists. And because it exists, it creates all that customizability at the top level.
Darius 20:16 That's awesome. That's that's really I mean, the context is, because I mean, we get a lot of like, industry wide data. But there's so much detail in that large, I mean, that high level data that that's where, like, really, we're spending your advertising money really makes a difference. So I think this, this is really great. It's a
Ethan Chernofsky 20:42 combination, and I apologize for kind of cutting you off there. But it's it's a combination, because I do think sometimes when you look at you need all levels, right? But if you if you're not, if you don't have good data at the property level, how are you going to have good level, a good data at the chain level? If you don't have good level data, like a mall? How are you going to talk about all malls? And so I think there's has to be a lot of focus made on that the granularity enabled in order to create highly high quality insights at the top level?
Darius 21:20 Yeah, absolutely. What's the what kind of businesses do you typically work with? Is it like small businesses, really large businesses, everybody.
Ethan Chernofsky 21:33 So I mean, it's across the spectrum, we have, I mean, we have early stage companies who will use our kind of free tools. And they'll use that process to kind of improve the way their businesses operate, we work with large retailers and shopping center owners who have you know, hundreds of properties across the country. And then we'll work with kind of smaller groups, but because imagine, you know, you and I start a pizza shop together, right. And we want to make sure that the other pizza stores that we open succeed, just as well as we have, this data can be hugely valuable. But if I'm running an Insights Team at a major retailer, being able to look at my load data, compared to all of my key competitors, is really valuable, because it provides me kind of a contextual analysis. I mean, one of the things we talk about a lot is that like, growth or increases in traffic, they don't mean all that much out of context. So you know, if I tell you imagine you and I are running competing grocery stores, and we were down the block from each other, and I tell you that my visits have gone up 10%. You don't know if that's good, or not just because they're up 10%? If you're some kind of 50%, I'm not doing all that? Well. If yours, it might have gone down 5% for years have gone down 20%, I'm doing great, because this is wider context, it's affecting me. And so the ability to have contextual data has also been a really significant piece of the puzzle.
Darius 22:58 Yeah, that reminds me I've probe an example you can tell me if this is relevant or not. So I was at Irvine, at one of the major malls in fashion Island, actually, I forgot the name in Orange County. It's a very high end shopping center. And I noticed that there was Lululemon on one corner, and then Atlanta just opened up, maybe about five doors down. And there is two other one, two other athleisure brands, just like right in that same area. And that was like really interesting for me, is that how they're all capturing a gathering in the same place? And how does that work on a competitive level?
Ethan Chernofsky 23:46 I think what's what's really fascinating is that a lot of times, things that don't feel like they should work together work really well together. So you know, for example, we were once doing an analysis of, of QSR restaurants. And one of the things that we found was that very often, proximity to other QSR restaurants is a really good indicator of success for a specific location. sense because like, if I know you know, if I love McDonald's, that doesn't mean I want McDonald's every day. And if I find that meal really valuable, and like you know, something good for me, then maybe I want McDonald's one day, and then chick fil a The next day, and then in order the next week, but it doesn't mean that sitting next to a quote unquote competitor is actually a bad thing. And so you touched on something that's really important, which is, data is a really important part of the feedback loop of telling us when our assumptions are wrong, when our assumptions are correct. And very often, it's a really helpful piece of the process. We have this objective resource that you can kind of test ideas against.
Darius 24:58 Yeah, well, I can just tell you, I'm a data nerd. And for data nerds, I think your your application is going to be just complete time suck. It's going to take over my life, I need to be careful about getting into the
Ethan Chernofsky 25:13 you know, I mean, I do I hear you, I hear your pain. It's something that I that I'm kind of involved in as well and I, but at the same time, it's
Darius 25:23 I you know, unmuted in a good way. It's like any Yeah, no, no, I
Ethan Chernofsky 25:27 think that the interesting thing is, you, it's important that it, you know, philosophically, it's important that at some stage, if your job, you're working in a research position, I think it's good to go down these rabbit holes, sometimes like, obviously, you know, there are times people log into the platform, and they're looking for a very specific answer to a very specific question, and they need to go out and put it into action quickly. But I do think some of our most some of our greatest power users are the ones that do take the time to just go down the rabbit hole and ask weird questions and try to think about things differently or to look at, you know, other companies in other regions and see what's working for them. Because I think one of the coolest things you can do is take inspiration from other ideas. And I'll give you an example. If you looked at the retail recovery, in the spring of last year, Best Buy was like a fascinating case. So not essential retail, obviously, strong byline pick up in store opportunities, strong curbside pickup. But there was this question of what are things going to look like when we recover, especially with this, the wider level of economic uncertainty that existed at the time. And what was really interesting was that invest, buy reopen, they didn't reopen fully, they reopened with appointment only shopping. So you had to call ahead book a time and then come in, to go to Best Buy. And that's how they kept their numbers down. And what's fascinating about that, that kind of approach is that one, when the brand did reopen their doors, the recovery was incredibly fast. But to that appointment, shopping works in a lot of different cases, because think what it does, it says that the person who's coming to the store has booked a time needs to have a clear reason for wanting to be there, and therefore is likely a much higher intent buyer, meaning that I'm going to have less people. But if I now figured out a way to make sure that the people that do come have a much higher likelihood of buying a product, and I can focus on them to give them a great experience to do so. And that idea can work equally well in in shopping. So imagine if you're running a department store, you know, why not have, you know, Monday through Thursday, between 10am and 4pm, which are off peak hours, we're gonna have appointment only shopping, and we're going to walk you through the store, we're gonna help you find the things you want and give you this great experience that couldn't work at your peak hour has been an off peak hours, allows you to bring in a flow of high tech customers where you can give them an incredible experience. So there's so many ways to kind of look at what's happening across the retail real estate landscape. And take inspiration and find ways to apply those great ideas here business.
Darius 28:18 Yeah, that's that's actually a very important part of my my work personally, is really understanding and almost like guiding and preparing people to shop for a lot more efficiently for more considered purchases, not not staple here. This is just, you know, basic items that you know, you can just go on Amazon and just order it and not think about it. But the other part of the purchases, the larger ones is like how do you how do you match the right consumer with the right retailer and the right location, so that they can actually get the best out of their time? The most?
Ethan Chernofsky 29:06 Yeah, yeah, absolutely. I think ultimately, what you're looking for is how do you ensure that every business is in their best or ideal environment succeed? So that could be you know, which brands do I have the best co tenancy with? So if I'm a, you know, talked about the lemon, if Allah Lu lemon is, do I do better or worse when I'm sitting nearby a Starbucks or when I'm sitting near a gap or an Old Navy? How do I compare performance of experiential locations versus non experiential locations? How important is it? The demographic mix in the wider area are not so important at all? All these types of different factors can be broken down, to understand what are the factors that drive success so that every time you put Reduce store somewhere you maximize the likelihood that you're going to succeed.
Darius 30:06 Yeah, that's very interesting. Now, just to go back to working with different types of companies, so is is Pacer as SAS company? Or is it usage based pricing? How does the pricing model work?
Ethan Chernofsky 30:22 SAS company. So the overwhelming majority of our customers, customers use us. They pay a an annual subscription, and they use this as much as they want. And then, you know, that's, that's a really nice element for us. Though we do have data feeds, we have a API in beta. So there are other ways to kind of consume the data, but it is primarily a SaaS product.
Darius 30:44 Okay, and then but you do have a freemium product as well, right to to let people test and get a taste of the product before they actually subscribe.
Ethan Chernofsky 30:56 Yeah, so I think there's there's two pieces. One is we have our freemium version of the actual paid version that kind of just gives a taste and can be very helpful for brands that have lower needs. And then we also have a series of free tools on our websites, we're constantly launching new free products with almost the same regularity that we launch paid products. And a piece of that is, I mean, not the same, we thankfully, were able to launch quite a bit more premium version. But I think there's we have a team that works on our free tools and launching new ones. And a big part of the reason is, we recognize that I think there's two pieces that are important to us one, we really believe that this data is important, we believe it can make offline retail better. And if you make offline retail better, you don't just make consumers happier, which is a significant piece of the puzzle, but you make those businesses more sustainable, which means the jobs are more sustainable, which means the communities that they serve, they're able to serve for longer. So we really believe in what they can do. And that means providing it not just for those who have the money to afford it. And so we have all these free tools. And then the second bit is like you this is a real community. And I think we were embraced very strongly by the retail real estate community. And so being part of it, and contributing to it, whether it be students who clearly don't have the means to kind of access our platform, or be entrepreneur just getting started in the space, we want to make sure we're providing the capacity to be more data driven with decisions that have to do with brick and mortar retail.
Darius 32:35 Yeah, I think that's a really, really great and positive way of providing value. Before you ask people to give you money, I mean, that's the best form of marketing. So really, kudos on that.
Ethan Chernofsky 32:52 Not made that generous, I just, we just call the email people and we don't even tell them about the product, just like give us money.
Darius 33:01 All right. So now what about on a global level? So you probably have customers all over the world? Correct?
Ethan Chernofsky 33:09 So we have, we only have I mean, meaning we have companies that are based all over the world, but our data is us only at the moment. Okay. And so we are focused fully on the US the real key decision for us was, let's build out the best possible platform, the best possible product, and then we'll take it to other places, but our focus is 100%. On how do we build an incredible product.
Darius 33:34 Okay. Now I'm taking a look at the some of the products and I think I don't know if these are free products or they're freemium. So this one called the brand tracker is seems very interesting. What does what does brand tracker,
Ethan Chernofsky 33:52 it looks at? I think it's 100 200 some odd brands at their nationwide or state level data across the country. And it's completely free. And it looks at their I think it's its monthly data year over year, maybe it's we did it year by year. But it's a it's, again, completely free on our website. I think it speaks to what we were talking about before. It's a really valuable tool. We know some really amazing companies, large companies that use use that on a regular basis. And it speaks to this question of like, in some cases, we shows people they're like, Why are you giving this away for free? Or like because it's it's it's part of the ethos and remembering that it's a big piece of the puzzle for us.
Darius 34:34 Yes, is very interesting and this information that I see so I'm checking out the page. And it's loading with Costco on a nationwide level. And it's giving me data for the last 90 days. And it's showing me it so that way basically this graph is like the traffic right at Costco on a nationwide Level foot traffic changed compared to two years ago.
Ethan Chernofsky 35:05 Yeah. And you can switch anything to compare to last year, it's just not as interesting. Because of last year was so strange. But yeah, you're looking at 30 days back and the comp to like on a daily basis to 2019. Or if you toggle about you can change it to the last year.
Darius 35:23 It's very interesting. Very interesting. So. So this is on on on the different brands, and then then industry trends. So that's another tool.
Ethan Chernofsky 35:37 Yeah, it's a way of aggregating up that same data. So to look at it from a category level, so because we have all those chains, we have all those locations, we can group them together as a categories, you can look at dining overall apparel overall. But I mean, I think one of my favorite tools is, is one that we just launched, which is a recovery dashboard, which looks at any zip code, DMA, hundreds of bits, even some business investment districts, at the county level, to understand where retail traffic is, and where even, you know, in domestic tourism traffic is how many people are coming from from far, you know, from far away versus how many are coming from real close. And to get a sense of how different regions are recovering in this, you know, wider period that we're experiencing.
Darius 36:27 That one's not on the website yet. I think so you
Ethan Chernofsky 36:30 probably have to lie. No, it is it's it is a two if you look at that. So if you go to the to the square, it's called the recovery dashboard.
Darius 36:40 Products solutions. Okay. Well, I'll find it. But I mean, really, I mean, oh, the square I see it, yes. Okay. Awesome. I mean, this is really impressive. Just to tell you, I see I talk to a lot of companies, I have a company myself, we're a start up, of course, a lot smaller. But just the the number of tools and services that you're providing for free. It's really impressive. I mean, it's really valuable. Yeah, yeah, I appreciate that. So. So Ethan, what are you thinking, as far as let's talk a little bit about the future. So what I think what this data typically shows us the past, right? So how do we translate this data into the future?
Ethan Chernofsky 37:31 Well, I think that's the magic of it, right? It's, nobody knows what the future holds. And so all you can do is, is look at the past, try to make an understanding of what that might mean. And also, what's really exciting is you and I could look at the same data and come to very different conclusions. So this, the cool thing about about data like this, is that in theory, it should, it should enhance what we can do creatively, but it doesn't remove the need for kind of human creativity and interesting ideas and decision making. And that's why we kind of really, I think one of the most exciting elements of our job is that we get to analyze this data every single day, we get to kind of think about what it might be moving forward. But then we get to look at other people who come to very different conclusions, looking at the exact same numbers, and that conversation can be as fascinating as any other piece.
Darius 38:29 Yeah. So what do you think about the evolution of the data industry as a whole? moving forward? I mean, look, I mean, things are moving very quickly, I'm sure a lot of what you do to be able to provide this data to a user. Probably 99% of the heavy lifting is on the back end that we don't even see. Yeah, how is that improving? How's that changing?
Ethan Chernofsky 39:02 I think there are two really interesting shifts that are taking place one. There are more companies in this space, which makes the need for talent at all levels, but certainly on my kind of the back end side, very significant. And it places advantages in ecosystems that are very good with data. So our r&d and product teams at Tel Aviv and that's because it's a it's a data hub. So it's it's a great place to find that type of talent and empowers us to build a really strong business for kind of our needs. I think the other side of it is what's going on, on the actual internal business side. So there is a growing recognition that data is not valuable at all, if it's not accessible. So it's like this, you know, if a tree falls in the forest, there's no one there to hear. It doesn't mean because If you have the best in the world, but it's unusable, who cares? And so accessibility is becoming a greater and greater focus. And one of the things that we take a lot of pride in is the fact that our product is really easy to use. And it's easy to come to conclusions with. And we are working to make it even easier and bring even more robust kind of concepts and insights into a simple, easily accessible platform. Because we want our data to help drive decisions. We don't want it to just sit there or you know, it's wonderful that we do it. But if you can't actually bring it to the hands of the average employee of an organization, it doesn't have the same level of potential impact.
Darius 40:44 Yeah, I mean, I mean, that's, I think that's some of the things that I'm always wondering about, like, you know, when you look at a product, there's a lot of work in the backend, and how is that actually changing? And one reason that I look at it is that for our own, you know, company, we have an app that does live stream video. And when the user looks at it, well, it looks really interesting, simple, maybe, you know, it's a live stream video, and shopping and things like that, but we are dependent on so many other players on the backend, and how they improve the experience that will actually help us like, the phone, the hardware itself, connectivity, the video, you know, just the streaming side of it. I mean, there's like so many other pieces of it. So, so that the backend that the I guess the the gears that run the business are very interesting for me.
Ethan Chernofsky 41:43 Yeah, absolutely. I think it's, I think every level of a business, whether it's the technology side, or kind of the go to market side or anywhere in between. There's a lot of complexity, it's really hard to build a great business, it's just very difficult doesn't mean it's everything requires rocket science, like it's, it's much more complex to think about, you know, great algorithms or how to, you know, leverage data effectively. But it's, everything's hard. You know, what I mean? And I think one of the having that recognition that nothing's easy that you have to invest and work at everything and hire great people and make sure you invest in them is a really big piece of building a good business. You know, in the end,
Darius 42:29 yeah, having having an idea about a great feature or product is just the beginning of the tip of the iceberg. Putting the team around you're actually doing it is really the hard work these days. Yeah. Absolutely. Awesome. Well, thank you so much, Ethan. I know it's getting pretty late for you. I really appreciate your time and look forward to hearing the amazing growth. And that that plaisirs having.
Ethan Chernofsky 43:00 Thank you so much for having me. It was great to be here and have a wonderful rest of your day.
Darius 43:03 Awesome. Thank you. Take care.