Transcript
Rob:
Hello everybody. This is Rob coming to you live from the Berkshire's. Peter is on vacation this week. I have a special guest. Adam Ferrari. Adam has a PhD in distribution. Computing was a founding engineer and CTO of Endeca technologies has 14 core patents related to search and navigation for eCommerce. Endeca was founded in 1999. Powered the search navigation and merchandising of Walmart, Home Depot, Target. hundreds of others before being acquired by Oracle. For $1.1 billion in 2011 fun fact, Amazon tried to acquire Endeca in 2005. Well, before that, because in decades, technology was so far advanced for the era. And what I am interested in talking about Adam today is technology. What has happened in e-commerce tech in the two thousands and in the 2000 tens, what is, how has retail technology investment evolved? How does that impact brand manufacturers? So we're going to get into the tech details. We're going to get a lot nerdier than we typically do on this podcast. And I am very excited for that. So Adam, welcome to the show.
Adam:
Hey Rob, great to be here and thanks for having me on.
Rob:
Let's start from the beginning. Let's tell all the Endeca stories. This is one of those great e-commerce stories that now is ancient news and very few people talk about, but the lessons from the Endeca era, I think resonate to today for anyone who is thinking about search on Amazon, on Instacart or home Depot on Granger on any of the major sites that are out there. So can you give us the 10,000 foot overview of what Endeca was, why it was important, the environment that it came up in?
Adam:
Yeah, absolutely. And it's, um, it's wild to think back that far. Um, just how, just how primitive things were. I mean, when Endeca was starting, we didn't, we weren't clearly focused just on e-commerce. It was really kind of really looking at things like auction sites where, you know, it was, it was more generally about search, but rapidly. We got drawn into e-commerce and it was, it was a lot about the timing of the thing. I mean, at that point you had in the late nineties, somebody who really, really bad, you know, first-generation e-commerce, um, experiences that were, were stood up and you could do rudimentary shopping, but it certainly wasn't convenient. It wasn't easy, you know, you landed on a site in those days, boy, like navigating it. You'd go in there, you'd try to search for something and you'd get a zero results page and endeca. But the core thing that we came up with in those early days was this idea of faceted search. Um, you know, the idea that it wasn't just about keywords, but you also had structured attributes in product data that you could use to, to, to navigate by. So for example, I might want to zoom in on products from a given brand or products that have a given color or let a given feature. And, you know, that kind of interactive search was a lot more productive, especially actually you can go back. I mean, one of the things I like to think about from those days is just how primitive the tech staff was. Um, search was no exception. You know, if you look at an ecom site surf in '99, they were probably using a document search engine, like a Verity or Samuel similar to the search. It was crazy. There weren't a lot of texts hanging off of a product. At that point. It was a couple of sentences that most guessed what, like statistical keyword, you know, occurrence, relevance that just was not going to give you, you know, anything that was meaningful in terms of ordering meanwhile, you know, like what was on sale and like, what were the most popular items? These factors that we know are super obvious for search relevance in commerce, like, you know, that those were going to be ignored. Um, yeah, so, so it was just a great opportunity. And because of that, um, we landed and we gave a better way to search and that got us entree into, you know, working with that sort of, you know, second generation replatforming of e-commerce through the two thousands, which was really exciting. I mean that point, the shopping experience wasn't even really well understood. It was being sorted out in real time as we evolved the product.
Rob:
Yeah. So fundamentally the way that I always understood the core Endeca technology was if you had an information space that has a lot of different types of data in them and the data, the data is only semi-structured and can be tagged in a lot of different volatile ways. There wasn't a good way to navigate that space. At that era, you had BI tools that you could maybe put a couple dozen dimensions into to slice and dice through the data. But if you, if you were a Walmart, if you were a home Depot, if you had thousands of product categories and those thousands of product categories had tens of thousands of ways to navigate within the categories, the depth of the bathtub, the finish of the faucet, the weather, the house plan is indoor outdoor stuff like that. But things that you want to click on in order to filter through the space, like no system could actually scale and produce search results in real time that, you know, that that a consumer would expect, I mean, your truck, you're talking about a hundred millisecond, 200 millisecond returns. And so that, that alone was new. Um, and then in DECA started doing things that were unique to merchandising, which I think, you know, there are things that actually, I think most brand manufacturers don't think of today. So for example, um, they had a relevance ranking module on the search results that a merchandiser within a category could go in and say like, look, if somebody searches for, um, uh, energy star refrigerators boost this one to the top, because I'm trying to sell more of them and it's high margin and they could like manipulate the search results from a merchandiser perspective as well.
Adam:
Yeah, it's funny. Actually, I think one of the key insights we had, I mean, you're, you're spot on with technology. Basically. We started with what the user experience wanted to look like. And we started with, with the data, the reality of what the data e-commerce data had, you know, tons and tons of attributes, sparsely populated, right? Like there are category specific attributes that would only be populated in that part of the taxonomy. Um, you know, it was, it was messy, fast changing data. You get the, you know, the owner of a category realizing that maybe an additional attribute was useful based on the keywords they were seeing in the search. And so that now they pull that out. And so it was volatile. It was sparse, it was tough stuff, but we wanted the experience to be this like almost a concierge of like, here's all the options that you could select and have that be very obviously it's shopping so it needed to be super fast and kind of work backwards from that reality of the data and desires of the experience and got to really a pleasant underlying technology insight, which was the structure of a traditional search index could be ever so slightly morphed to also capture structured data and deliver a really, really high speed way of aggregating that into those facets. So it was, it was kind of cool, I'm one of these nice stories of user experience leading the technology, but then driving down to some really basic, you know, this is like database indexing type stuff. I think we came up with a very unique take on that, that hadn't been done before and then enable this super high speed aggregation that you need for facets. But I think one of the things like that's the technology part of the story to me, the cool part of the insight at a higher level was search is the site, right?
Adam:
Like searching the PDP is the site. If you go back to the, the, those days, like we'd land in these things. And like, what we had been procured for was to be the search box, right? Like if you're building an eComm site in 2005, you probably were like, okay, like important stuff are going to get my econ platform. I'm going to really work on my information architecture. Like what are the categories I'm going to really like, think about the structure of my site because people were in a car they're going to browse all over that site and shop, Oh, by the way, also going to procure a search box. I can stick it on there. It turns out like this is what happens. Shoppers come to the site, they've got their own goals, they've got their own process. They want to, they don't care how you organize the site. It was all a waste. They immediately would come and be like, this is what I want and just jam them in the search box. At that point, you're often searching for land. And I think one of the insights we had was facets were a way that you could carry the information architecture. You could take your categorization the way you'd organize your products into groups that were meaningful and carry that into the search experience. So in a way, what we did was we both preserved the investment that people had in thinking about the organization of their catalog, but also then made it more interactive and dynamic and responsive to your search. So it was, it was a really key insight. And I think, um, you know, sheds a light to where things are today, where there's so much focus on the data and the search experience and having an excellent experience. Once you do get to that product detail page and less on the like, you know, information architecture.
Rob:
Yeah. Like even, even today in 2020, you look at websites that compete effectively with Amazon, they're doing it primarily on the facets. So Wayfair considers their faceted structure to be their fundamental, competitive advantage, as it, as it compares to Amazon, you could into rugs and you can find nautical themes, drugs, or forest esteem, drugs. And, and so they do this really extensive tagging on every single product that allows people to not just spear fish, but also discover and really kind of work their way through a space to understand what the options are. Um, and it's funny today that, you know, 20 years after Endeca more than 20 years after Endeca was founded, most sites don't really do a good job at this. It's the, there's very few of them that do. Um, but yeah, so to get back to that era, one of the hardest things about standing up those types of experiences with all the tagging that's across thousands of different categories is actually getting the damn tags. Right. And so how did the retailers, if you're Walmart in 2005 of your target in 2005, how do you even begin to attribute all of the products and your entire catalog for the search experience once you, once you bought them in DECA?
Adam:
So it turned out, I mean, this is amazing. It was a real problem. We, you know, this is like, we're, we're pretty early in our careers and starting that company. And we certainly didn't know the, you know, the ins and outs of the retail ecosystem behind the scenes. And I think we really were focused on building the tech, building this awesome search tech and, you know, we would have these sample datasets, like early on in the, in the, in the company, we crawl a bunch of wind data and we build this super beautiful, like wine database. It was actually kind of a funny thing. We would go out whenever we'd be pitching the product. People would be able to be like, love the product, but also could I keep access to that wine navigator so that I can know how to pick wines? You know, it was like, it was, but in a way, right, we were fooling ourselves. Like we put this lavish, like, you know, curation into buildings, beautiful wine dataset, and then you would land like, you know, tier one retailer you'd be deploying Home Depot. And we were so excited about Home Depot because we felt the technology would shine with complexity of the catalog, which was a hundred percent true. Right. And home Depot, like every, all these different, crazy product categories and you know, what meaningful, um, you know, challenging shopping experience. It's like, which one of these snowblowers am I going to buy? It's actually kind of a hard question. It's expensive and they've got lots of different features and stuff like that. So we were fired up, but meanwhile, and so, you know, you Pollyannaish walk in and you're like, surely home Depot is going to have the most brilliant catalog of, you know, power drills in the universe. And it's like, you're, you're, you're immediately sorely disappointed.
Adam:
You'd get in. And you'd find the catalog is quite a mess. The core structure of it, the basics of the catalog, you know, fundamental, you know, but the basic attributes that would come out of an ERP, that's good. Why, because that's essential for them running their stores. And so that stuff already had to be buttoned down, anything having to do with, you know, digital merchandising and all that. Like the ways people would actually want to search, um, and experience, you know, that product and a product detail page that was kind of a crazy mess. You'd get like some attributes simply not pop populated by some vendors. Um, you know, you know, you get attributes or like all caps and, you know, just very messy data that like didn't well, um, you know, the gaps in it made search hard, the inconsistencies of, of, of representing stuff made it hard, um, for facets like facets, you want to kind of one idea represented one way so that like you're like after that feature, you click that one feature and you get all the relevant results. So we find that like in deploying these big sites, a big part of what we would have to do is help them operationalize data cleanup. And I think like the view at that time was that a lot of the data cleanup would happen centrally at the retailer. Um, you know, this is still in the transition period to larger catalogs that now is, you know, driven by Amazon, right? You've got to have crazy selection. Um, you can't have just a small selection. So like, you know, we invested tons in those days like helping, helping the deployments, you know, cleaning up the data just doesn't scale. The reality was that like, you know, I think the lesson being learned through those years was that the retailers were gonna need to source the data better from, from the vendors, right? Like it's, it's just too complicated and messy for them to do it centrally,
Rob:
But they, I mean, they, they burned a good decade trying to do it centrally though, using Informatica and data cleansing and text analytics and all kinds of, they were throwing every tool in the toolbox at the create attributes problem. And at some point they couldn't. So I want to fast forward to around 2010, 2012, you know, in that range, the tech, the commerce tech stack sort of fork in the road, in my view, it's um, in 2005, you cobbled together an eCommerce site using best of breed pieces of technology. So the commerce platform was one piece, but also the search box was another piece and in person, and if you did any type of, um, personalization, that was the third piece, and you'd have a bunch of different pieces of tech that you'd buy in cobble together to throw the website by about 2012, we started getting things like Demandware, which had everything in the box. So you could go off the shelf. And then on the other hand, you had the tier one retailers just going full custom. And, and so I think let's talk, let's spend a second talking about exactly that moment in time, because I think it's a really, really interesting moment in e-commerce technology.
Adam:
Yeah. W we, we observed this, um, you know, we spent the two thousands, um, doing, doing all these tier one retailer deployments. Um, but at the time we liked that we were paying more than half of the top 100, um, econ sites on the internet. It was crazy. Right. Um, and you know, you could see it evolve. I mean, the early days of the tech stack were changing very quickly. Replatforming was, you know, the constant thing, um, just by necessity web technologies. I mean, when we started at Endeca, like, it was really important that we have Perl support in our API. Like we were experts in like the mod Pearl extension to Apache. Like this is kind of so primitive through those years, it's like churning so quickly. That might be the end of that decade. Um, the maturation was incredible. I remember we were part of the replatforming of target com I'm in the late two thousands. And this is while by that point, we were one of, probably about a dozen technology vendors into that, into that replatform. It was crazy. And there were like multiple big systems integrators involved with that. I remember going, I was in Minneapolis at the headquarters and they had the Gantt chart for the whole project. And the thing was, I mean, we're talking about like, you know, tens of yards of, of, of paper on the wall. And it was like these tiny little fonts and boxes. It was like the, you know, it was like the build plan for the death star. It was incredible. So just like, you know, the recognition of that moment was for these tier one sites, the level of maturation was a lot, like it came light years. And I mean, I think, you know, the transition there was a, it was partly, yeah, the, you know, the user experience, what shopping was online was maturing and stabilizing to some extent such they could kind of pour that kind of cement.
Adam:
Um, and that's where you saw those tier one retailers really recognizing that it's ineffective. They were tech companies. I remember in those years we had been powering walmart.com, um, from 2004 on. And so right about that time, right, 2011, that they acquire cosmetics and, you know, decide to build Walmart labs. I mean, one of the drivers being, they weren't going to buy a search anymore. It was too mission critical, right. They were going to actually own it and own every cause they were pushing us hard, always through those years for new features and specific stuff that they wanted. And they just, they just take it off the table and just to be completely custom. But exactly, it's the funny irony, right? Like the, the maturation, the fact that like what the shopping experience is and the capabilities and user experience was stabilizing meant that there was a moment where democratization was what's possible. Like you, you start to get some of these, you know, more mature econ platforms like the man where, um, you know the out of the box and you start to get, you know, the technology going towards the API economy, like these things being delivered as services with easy to use, you know, API APIs. Like if you looked at a 2005 build, it was highly bestow, bespoke, custom code. It was a gigantic software development project. You know, you know, these days, I think you're getting to a world where it's a lot more composition and API APIs, right. Things are a lot more nimble and you don't have to actually do code integration for every last bit of your site. So you're in a, in a way, or we're in a moment in time where tier one are these completely custom gigantic, like, you know, worlds of their own, but the broader ecosystem and the ability for like, for instance, a brand to have a really compelling, like in talk about talking about like facets and relevant, you know, attribution that gives you a great shopping experience, who knows that better than the maker of the product.
Adam:
And suddenly the technology is there and it's nimble enough that they can deliver a really beautiful shopping experience. Um, you know, which it's, it's cool. I mean, I know personally I've benefited, I like to fish off the shore. And like recently I wanted to buy a new fishing rod. It's like trying to do it on Amazon. She's not back right now to experience, but you know, what, if you go to like a st cry.com, like they've got all the details and they make it a lot easier, pick out the specific attributes it's like, you know, you could see that happening over and over in every category. It's just like, there's a great democratization of the shopping center.
Rob:
Yeah. There's, like, um, a version, especially for brands that tend to have smaller catalogs. So if you're standing up snacks.com as Pepsi in 2020 during the pandemic, it's pretty easy. Like you can stand up a pretty good looking site. And, and the, you know, the search is super basic and the nav is super basic, but it's all reached this point of, um, good enough. And actually for small catalogs can be good. Enough can be a much better experience than Amazon, or then Walmart can be. Um, it's really interesting. So, so like, if you look at that particular, the trends that you're talking about from 2010, the tier one, the tier one retailers have determined that search and experience are so mission critical. And so differentiating that it's no longer acceptable to use out of the box technology. You've got to go your own. So Walmart targets, they, they, they, through at, through acquihires and through other, other staffing up, they now have huge tech armies that are DIY, right? If your Instacart and you're, and you're just born natively in this world, you're just doing your own search. You're not, but you're not buying something out of the box. And then the tier two folks, and I would include brands going direct to consumer as the tier, as kind of a tier two retailer, just, they have less traffic, their catalogs are less complicated and so on and so forth. They're buying this off the shelf technology for the most part, um, underlying this all there's some tech trends that I'm not exactly sure how seriously to take them. So for example, if you're a tier two merchant, it's pretty clear, you just buy it off the shelf commerce stack, and it's fine. Um, and then if you're tier one merchant, you go on your own. So where do the things like headless commerce stacks line up here? Is there, is there actually a big market for them? Is there a replatforming, like why were, why were we platforms and e-commerce stacks so common for so long? And is that going to continue to be a thing that happens?
Adam:
Well, I think if you look at some of the drivers for headless, I mean, one of the biggest drivers for headless is pretty obvious. It's mobile, right? We shop on mobile now, it's, it's the primary shopping, um, location. And, you know, that you want to be able to deliver consistent, but customized experiences across channels. And I think, um, you know, that's, that's where the idea of headless commerce emerges from is being able to decouple the glass from the core, you know, um, merchandising and catalog, and, you know, the, the, the, the underlying back backend concerns of commerce. Um, I, it isn't, I think actually it plays into what I was saying before about, you know, the evolution of the API economy and things becoming more service oriented versus, you know, you, you own and integrate the code oriented. I think headless commerce is a trend where, and, and you see this in, in, in, depending on the commerce, some car commerce platforms are better suited in their core domain model to, to like be API oriented, but you see all the commerce platforms being influenced by the headless trend and providing better API capabilities, because there's just, you know, a greater desire to deliver, um, you know, innovative shopping experiences and, and stand up new, new faces on the, on your catalog and, you know, and how people shop on it.
Adam:
Um, so I think it's having that, that influence. Um, it's not clear to me whether there is a, you know, a replatforming round that comes out of that versus just it like changing the way things are built in a way that's, it's already happening organically. It's it's, you know, and, and again, I always come back to, um, you know, we often look at the vendors and these big, like, you know, buzzword things like, um, like headless commerce, it comes, it comes back to the core ways that the basic technologies are evolving. It's like, you've got, you know, much nicer UI technology, everything from, you know, frameworks like react and, you know, a site generator like a Gatsby, it's like, you've got these really nimble, nice tech, you know, um, components that are evolving on the landscape. They fit in with the larger ecosystem of just easier, nicer ways to work with API APIs. Um, you look at like, we've been in the rest era for a while, and there's just even nicer tech coming with, uh, um, with an idea like craft QL that brings a little bit more, you know, structured a querying and an ability to test for, um, you know, whether or not a contract is going to be observed. So you're getting this stuff is evolving. It's retaining its agility, but becoming more powerful. Um, it's those underpinnings that I think are enabling, um, this democratization of capabilities and easier composition in assembly, um, that that is the headless trend. So I think there's something there, but I think it's actually, it was, it was organically falling out of the environment, um, and influencing the commerce capabilities. Um, as we went along,
Rob:
I'm going to mix metaphors for a second here. But if you, if you, if you forgive me, um, there there's an old African proverb, which is, you know, if you want to go far, go alone, if you want to go fast to go together. And I feel like there's, there's an element there. If you look at commerce platforms, if you want to go fast, like a bundled commerce platform that has it all in one place, like Shopify, big commerce, one of those guys like you can, you can, you can move fast, getting stuff site standing up. That's good. But if you really want to go far, if you want to do something unique, you have to go alone. You got to do things like Walmart or Instacart is doing, which is DIY. And it's in those experiences where I think maybe the, the decoupled capabilities that some of these headless surfaces can offer might have, might have a place.
Rob:
And so, just as an example, like Jim Barksdale, CEO of Netscape famously said, you know, 25 years ago, there's only two strategies in business bundling or unbundling. And so the Shopify is a bundle of commerce capabilities. And headless in broad strokes is an unbundling of commerce capabilities. And some of those capabilities may be much better delivered separately. So you can imagine a personalization engine that is aggregating insight across a whole bunch of site experiences. And using that to train a model, which is more effective than any single individual site could get training their model with just their own data. Um, so we haven't seen anything like that. I mean, there's companies like five mines that are out there that are starting to do some more predictive AI based, um, navigation that I think are really, really interesting to pay attention to. But, uh, you know, if there's a bull case in headless, that's kind of where I see it. It's these new types of services that do something incrementally different than what the core commerce bundle looks like it's doing. Um, have you, have you seen any AI out there, any, any AI services or prediction, predictive algorithms or anything like that that look potentially promising to keep an eye on?
Adam:
So it's an interesting question about AI. It's like, there's so much discussion of AI these days and, and, and ML. And I think, I mean, by the way, the core tech of AI and ML has come so far, just in terms of, you know, how powerful models you can build, how easily, um, it's been interesting like AI in things like personalization. Um, it's been discussed for ages. I mean, they were personalization engines back through the two thousands and, you know, you'd see them deployed at some success. And I think it's, it's been interesting that we haven't seen one really get massive momentum and, and, and get a dominant position. So I think your point about headless completely well-taken, it's like the unbundling of these capabilities and the presentation of them through API APIs makes it easier to compose, um, capabilities like that in. And, um, and I think my, my point is I think that composition is democratizing, like in a way that, you know, even the, the, the, the, not the, not the tier, the tier ones, I think there are a bit of, there's, there's a bit of a dinosaur, you know, the notion there, like you're gonna be able to compose really powerful stuff as a tier two, and it's getting a lot more affordable just from a development perspective because it's being based on services and APIs. And so I think we're going to continue to see innovation in that area. There's, again, the fundamentals to do that kind of stuff has gotten so powerful. Um, it's less clear to me. I haven't seen, like, you know, Hey, here's the one, here's the one winner in that space. We, I mean, we've seen a lot of really interesting, um, you know, uh, offerings there, but again, I think, I think it's going to still be a lot of different variety in that space.
Rob:
Yeah. That makes a lot of sense. I mean, so then if you want it to take a big, big prediction here, and you want to look over the next five, 10 years of commerce, what do you think the big moves are going to be on the, on the tech stack basis? Like what, what do you see coming that that's going to be new to the space? That's going to shake things up.
Adam:
I mean, maybe I guess I tend to be a conservative and I tend to think of these things evolutionarily versus revolutionarily. Um, I think that, you know, we're going, gonna continue to see this trend towards, um, service orientation, ergonomic composition of, of capabilities. Um, you'll see API tech, like graph QL, um, you know, make it a lot easier and more powerful to cause to compose things. Um, you're going to see that, that means that the types of experiences that can be delivered, you know, we were working on just an, uh, uh, a really pretty incredible trend of, um, how good experiences are, for example, on, on mobile. And, you know, like you're going to see that. And, you know, I feel like we're less in the revolutionary phase that I felt like we were in the two thousands. And we're more in an evolutionary phase. The fun part there is that's the tech stack part of it. I think you're seeing, um, you know, we're in kind of the model of the plateau of productivity where it's like, there's really nice trends in play. The, the, where are you seeing the revolution where that's playing out and rapid change. Isn't just all the different ways of shopping. It's like everything from now, like you're shopping on Instagram. It's like, now there's like, you know, ads are shoppable. It's, you're going to see this, like, just, and you mentioned like snacks.com. It's like all these different varieties of really quality, like actually really quite nice shopping experiences, marketplaces. Um, you know, it's, it's, that's the innovation now happening much more in the plane of the consumer experience, which is exciting. And I think it's like, it means great things for us as shoppers. I mean, you know, if I look back on the conversation, it's like, boy in the nineties e-commerce was pretty pretty, you know, you had to, you don't really want to do that for some specific reason.
Adam:
And then it kinda got adequate. And I feel like we're getting into a zone now where it's becoming delightful and I have more experiences. I mean, you know, if I look back 10 years, we're still like, it was, you have so many experiences where you'd be landing on a product detail page. It was probably hard to get there. You're like, wait, what is this thing? Is this the right thing for me? And you are confused. And then I always remember this experience. Like you get to a product detail page and then you'd go search NAB elsewhere and you couldn't get back there. I remember how frustrated, I don't know if you ever had that experience. It's just like, you know, like you're talking. I mean, I just, it's just not a great experience. I feel like we've gotten to a place, um, where that's less the case. Right. I just feel like it's, shopping's better than it was. That means that you can really get into this gear where the innovation is around. Like, you know, what's, what's, what's great for the consumer versus making the basics work. You know what I mean? Yeah. It's, I mean said another way. It's like,
Rob:
Right now, the onus is on the business to find creative ways to apply the technology. The technology itself has gotten to a point where it's no longer blocking you from accomplishing things you think in the nineties that the biggest.com a waste of money was web then famously in retail. Right. But you know, like a webbed, like there were GPS that existed, but that was like the only core technology that existed at that point. You didn't have a wireless network that could support people that were doing delivery. You didn't even sell cell phones. Penetration was still low. You didn't have smartphones and so on and so forth. And so, you know, between web van imploding and destroying $700 million of investment or whatever it was, and Instacart, you had a bunch of fundamental technologies and ultimately Instacart isn't a new technology so much as an application of the technologies that have really come to fruition between those two businesses.
Adam:
Yeah. And you know, it isn't to say that I think there's exciting stuff. That's that we're on the precipice. I mean, real, real adoption of AR and VR, um, in 3d, I think that's going to be really wonderful for certain categories, right? Like, I mean, I, I still, like I'm, I'm old school. I still love to go to the store. I mean, you know, these days you never go to the store before researching online, but I still like experiencing products, but I do wonder how many of those are going to be like the kind of thing where I'm going to be psyched to see it in a 3d VR setting. I just need to get to that tipping point of adoption and having the right hardware out there. But it's actually something where, you know, it's, it's made meaningful progress in the past, you know, five to 10 years. And I think it's just, it's just waiting to kind of have that impact. So there's stuff. I mean, it's not to say there aren't, these step changes that are going to happen. Um, but, um, it's, it's definitely come a long way.
Rob:
Yeah. That's a good place. Good place to end call to action business, learn what the technology can do so that you can apply it creatively on a go forward basis. Um, Adam, thank you so much for the time and expertise.
Adam:
It's been really fun. Thanks for having me on.
