Tech Soft 3D Blog

Beyond 3D Podcast: How Big Data, AI, Machine Learning and Other Tech is Driving the Future of Retail

Posted by Tyler Barnes on Jul 17, 2019 6:50:25 PM

This episode of Beyond 3D talks about an industry we’ve never touched on before – the retail space, and the kind of technology being used to drive everything from the construction of a space, the layout of products, which products are sold in the store and where they are placed, to the supply chain. We talk with Guy Moates, a Director with C A Design Services from the UK.

Did you know that the retail industry has historically been very early adopters of new technology and the use of big data?  What can other industries learn from retail? And after listening to this podcast, you will never enter a store with the same mindset again.

Listen to this episode:


For more information about C A Design Services, visit

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To read the full podcast transcript, see below. 


Welcome to the Beyond 3D podcast where we explore all things 3D and the important role that 3D data plays throughout the manufacturing process, driving decisions throughout a product's life cycle. Here we talk with industry analysts, business owners, developers, and industry influencers, and hear real stories that you can relate to and learn from and know which trends and technologies apply to your business. So join us as we go Beyond 3D.

Angela Simoes: Welcome everybody to another episode of Beyond 3D. My name is Angela Simoes and I am here with Dave Opsahl, who is Vice President of Corporate Development for Tech Soft 3D. Hi Dave. How are you? Welcome again.

Dave Opsahl: Hi Angela. Doing Great. Glad to be with you as always.

Angela Simoes: And today's guest is Guy Moates, who is a director with C A Design Services out of the U.K. Welcome Guy. How are you?

Guy Moates: Hi. Yeah, I'm really good. Thank you.

Angela Simoes: Good. We're really excited about this episode because it's a topic we've never talked about before and I think something that maybe people don't always think about when they think about 3D or manufacturing or things like that. And so that is the retail space. So why don't you give our listeners a little bit of background about yourself as well as C A Design Services and then we can go from there.

Guy Moates: Okay, Angela. Well, no pressure there if it's a first time topic for you. My company C A Design Services has been established for around about 35 years and we're very much involved in the planning of shops and stores using CAD, using 3D. So we've got teams of people who go out and survey stores, we plan the stores for the retailers and we've got a software platform that actually helps them plan the stores too.

Guy Moates: For me personally, I've worked here for 23 years, so quite a long time. I originally joined the company as an AutoCAD trainer and my role with the company today is very much... I'm responsible for the direction of our software platforms, our store space and store view software. And I'm still very much hands on with some key account management.

Angela Simoes: Excellent. So this is something that I think everybody can relate to, right? Because we all walk into some sort of store almost on a daily basis. Right? Whether it's the grocery store or a clothing store or a CVS, something, right? We're all walking into stores. So how has retail changed over the past few years since you've been in this space for so long?

Guy Moates: It's a really interesting point and as I talk about retail, everybody has an opinion because everybody shops of course. So the question about what's changed is huge really. I mean retail is going through some quite fundamental shifts at the moment in terms of the traditional sort of bricks and mortar retail, retailers are finding themselves with too much space on their hands with needing smaller stores, obviously competing with the Internet and trying to draw footfall into their stores. And those pressures are different in different market segments.

Guy Moates: So a FMCG, which is basically food retailing in the fast moving consumer goods sector is seeing different changes and different pressures to other sectors like DIY or pharmacy or fashion. But all in all, it's still a very exciting environment to operate in. The demise of the high street shop has certainly been sort of overstated and there's still some real success stories going on.

Angela Simoes: You mentioned briefly that your technology is about planning the store layout, right? So when you walk in the store, your software is going to say this fixture should be here and these products should be on that fixture and towards the back of the store is whereas that should be-

Guy Moates: Correct, yeah. The terms that are typically used in the industry are micro and macro space. So a micro space is effectively the products which are on the shelves. If you are standing square onto a fixture and looking at the front elevation of that fixture as it were, that's the micro space. And then the top down view of the store, the store plan itself, is called macro space. And that's where our products and my company sits in terms of helping customers, helping clients with their macro floor plans, which links strongly into floor plans and 3D and auto AutoCAD and those sorts of platforms.

Angela Simoes: Yeah. So I have a few questions sort of all tied into one. So that's technology being used in that capacity, but where else is technology being used throughout the retail process and where is it having the biggest impact? Is it really there on the floor or is it, I guess, earlier on... Is there-

Guy Moates: I mean technology is huge in the retail sector and I think a lot of retailers are very early adopters of big data, of cloud-based platforms and handheld technology. Obviously we've all seen the pinging of barcodes in stores has been around for many, many years and the linking of that to databases. And retail is usually a very early adopter of technology, not just on the shop floor but in the construction processes as well, where they're perhaps not constrained by government funding or anything like that. And if there's a clear return on investment for technology, retailers will generally jump in and make a success of it.

Guy Moates: The data involved typically is obviously multilevel in terms of there's the construction process of actually building and maintaining a store. So, facilities management software and platforms involved in the property process and procurement and construction, all the way through to big data, the information coming out of the sales information to the store, which is typically aggregated and moved into what's termed as a data lake. All the way down to the products, which I mentioned in terms of the shop floor, the points at which the product, which all the research and effort has gone into manufacturing and buying and putting on the shelf and ensuring that product meets the client in a very logical way in terms of customer journey around the store and in a sensible place in the store.

Angela Simoes: Right. So when you were talking about this, I can't help but think of artificial intelligence and if that plays a role in any way.

Guy Moates: Yeah, yeah, it definitely does. And we're seeing more of artificial intelligence and machine learning playing a role in choosing the products which are being put onto the shelves. So where it really comes into play, and this really isn't my personal area of expertise, but it comes in with companies such as Nielsen who who have these big data lakes where they've got aggregated shared data anonymized from lots of different retailers. And they're working with their retailers on their decisions around range and assortment to ensure the best possible use is being made a space and the right products are meeting the customer.

Guy Moates: Good examples would be where AI and machine learning comes in, is that understanding the cannibalization of product sales where one product is introduced alongside another, being it an owned brand product or perhaps a product from a competitor or even a different size product of the same product, if you're with me. Different sizes of maybe table sources or ketchup or something like that. And there's very complex algorithms and mathematics but running behind the scenes, looking at existing data and the effect of introducing those products and whether it's actually going to increase sales or just alter what is being purchased in terms of the product mix without any increase in sales at all.

Angela Simoes: And as part of that data lake, I imagine some of those predictions have to take into account geographical location and behaviors of... the demographics of wherever the store is. So how does the technology account for that?

Guy Moates: Again, the retailers are very advanced in these ways, particularly in the context of food retailing in particular. So, for instance, you mentioned geographic clustering, that's obviously a very obvious example, but they cluster in lots of different ways. So obviously the affluence of local population and these sorts of things are typically done in GIS software rather than in a CAD package or other systems. I think there's a system called Mosaic which helps. So, this clustering happens at lots of different levels in terms of the distance to the nearest competitor store. A lot of people will just drive to their nearest store and won't drive past a store to reach another store. And this is a compelling reason to do so. So the clustering is definitely multilayered. And again, the retailers have an excellent understanding generally of what that looks like.

Angela Simoes: It's interesting as you're talking, you're starting to mention so many different technologies in the areas of industry that, at least in my experience, there's not a whole lot of industries that have such overlap. You mentioned GIS technology and then you've got CAD, but then you have to have demographic data. I mean, there's so many things happening here.

Guy Moates: There is, yeah.

Angela Simoes: And Dave, I wonder if you have any thoughts on this because you work with lots of different industries or companies in different industries. What's your take on that and just the great overlap? Because, I mean, when we talk about the data lake, I'm thinking this is probably one of the biggest lakes that we've really encountered or talked about or maybe I'm wrong. But I just was curious on your thoughts around that.

Dave Opsahl: Yeah, it's a really interesting question and I hadn't considered it before. But you're right, the data sources for what it is that C A Design Services is doing is much more than what I would normally expect to see in a manufacturing company. I think the closest thing that comes to it is what's happening in the Internet of things. It's the amount and the volume of data that is probably similar. When you start having all of these manufactured products, sending information over the Internet, the volume of data is going to go up. But the dispersion of sources, the different places... I'm sitting there as I was listening to Guy talk, thinking about, "Yeah, there's a demographic database, there's an Esri or a GIS database. There's the database architectural plans for the store." I mean it's endless. It actually dwarfs what I would expect to see in a manufacturing company.

Guy Moates: And then there's a huge amount of consumer research comes into play as well. So for instance, there may be an increase at the moment in craft beers. And so understanding whether the local demographics of a store have got the kind of people locally who would be seeking to go into a store and buy craft beers. And so two stores that are identically sized would have perhaps different range and assortment depending on that local population. And there is a big move at the moment into what's called store specific planogramming, whereas instead of just having the same range in every store, that it's been heavily tailored to the local population.

Guy Moates: A store at the end of the day is a map. It's a map. And on the technology front, a lot of the retailers are looking at in-store navigation and putting beacons in now. And being able to download an app so that you can actually be guided to the right products, that potentially you could have augmented reality running on your phone with special offers flashing up as you walk down an aisle actually highlighting and pointing to a product on a shelf, which it knows that you would be likely to buy based upon your previous buying habits and patterns. All these things are coming on stream and will certainly in the next few years be on everybody's mobile phone.

Dave Opsahl: Guy, there's another question that came to mind as I was listening, which was I think most people have an understanding that there's some amount of analysis that goes into where do you put a product on a shelf. But what I'm not sure most people understand is the relationship between where things are, the fixtures in the store for certain things, and you mentioned something interesting when we were talking the other day about... Can you share with our audience the banana example?

Guy Moates: Yeah, sure. Well, I thought of another example after we talked as well around about how important the site is as well. Because again, if there's onsite parking for a mega store of some description, the retailers generally understand the importance, or even if it's in a shopping mall, the importance of actually parking your car. And a high percentage of your satisfaction with a shopping trip is actually, "Was my car safe and was my walk from my car to the shop actually enjoyable and safe," and the facilities. So the retailers at the very starting point of the customer journey understand that very well as well. So nobody ever parks next door to the places where the trolleys are pushed into for fear of having their cars banged by somebody with a trolley or something like that.

Guy Moates: So the example I gave you on the bananas were the clash between the store planning process, the layout process, that macro space planning, which I touched on right at the start and the replenishment. So bananas I gave as an example as being one of the most replenished categories in a store. And if the doors through to the back of house warehouse are put in the wrong place as the store is designed by the architect, it actually means the recruitment of an additional member of staff if that banana store in the back of house is a long distance away from where the bananas are being sold from.

Guy Moates: One of the things our software does for one of our clients is it actually calculates the distance between the back of house freezers and the freezers on the sales floor. They know they've got maybe a 15 minute window of opportunity from the moment that cage has pulled out from the back of store to when the products have to be reinserted on the sales floor into a freezer. So, that distance is crucial as well and our software will actually report on that for one of our clients. That's a critical metric to ensure that ice cream hasn't defrosted and been refrozen and then you're giving somebody food poisoning.

Guy Moates: So all these things have a distance that can be pulled back to a drawing, can be pulled back to a CAD file and could be potentially reported on from a website at some point.

Dave Opsahl: Considering the people that are involved in the workflow for any store chain, Guy, how critical is it that the experience that your software gives them is tailored specifically to their needs? I mean, these are not people that typically understand CAD very well, are they?

Guy Moates: No. So, we have a version of our software called Store Space Planner, which is an OEM AutoCAD version. And basically the complexity of AutoCAD and the ribbons and all of that is actually hidden from the user. And there's quite a simple toolbar and set of tools used to drag and drop planograms from a database directly onto the AutoCAD fixtures on the store. So other than understanding the concept of a paper space and how to create a block and to zoom in and out with your wheel, that's really all the AutoCAD functionality you need to be able to use our software and use it in a store planning environment.

Angela Simoes: Yeah, because I imagine going back to the knowing the nuances of a local store, someone on the floor that day,... I'm thinking of if it rains and they decide, "Oh, we need to put the umbrellas at the front of the house." Right? Because it's raining. How do you account for that kind of change that happens on the fly that way. Because according to the store plan, the umbrellas were either halfway through or at the back of the house, but you know, "Oh, it's raining. We got to move them to the front."

Angela Simoes: Is the person on the floor able to implement that kind of a change to make sure that that data is being fed because like, "Oh wow, we had a big uplift in umbrella sales today. I wonder why that was." "Well, it's because they were moved," right? How do you capture that kind of data?

Guy Moates: That kind of data is attached to the fixtures on a store plan. So just as long as the umbrella stand has been specified as a piece of fixture for that store. Obviously if it's on wheels or suitable as an item to be moved, it could be moved to the front of the store.

Guy Moates: Probably a better example is perhaps retailers looking at the weather forecast. So even though they don't change the share of space perhaps within the fixtures, if it's going to be sunny weather and they know they're going to be selling a lot of burgers and sausages and barbecue kind of stuff, what they do is they ensure there's a lot of stock at the back of house so that those shelves can be replenished very quickly. Because they know they're going to be rushed off their feet with barbecuing if the weather forecast is good. And look, the weather forecast can have a dramatic impact on the takings of a store and the ability and need to restock those shelves quite quickly.

Guy Moates: So the software and the algorithms which run on the store from a micro space perspective is doing some really clever things in terms of understanding the replenishment cycle, when the next truck is due in store, to ensure the right number of facings or the products are on the shelf based upon average sales rates, and ensure there's no out-of-stocks happening. It's a real science behind the... You can probably tell, I find it fascinating and it's a very exciting environment to work in.

Angela Simoes: No, it is. And with every new data set that you mentioned, it makes me go, "Oh my God. Yeah, that's right." Because you talked about the safety aspect, right? So there's got to be a database of crime statistics in a particular area, right?

Guy Moates: Yeah.

Angela Simoes: And how do you take that into account when designing, like you said, from the architect perspective, but then also is there a lighting? What are the store hours? All that kind of... So yet, there's another dataset. It's so amazing. It's just...

Guy Moates: I can give you a really good example of that, Angela. We've worked with a client here in the UK, an electrical hardware goods store, and in certain stores they will not put memory cards out on display. That you have to ask for them and they're pulled from a hook from behind the counter. And in other parts of the country, again more affluent, less likely to have theft, they're actually out on display and in blister packs on hooks. They change where they are in store and they change the accessibility to those products based upon local demographics. They probably wouldn't admit to it, but they do.

Dave Opsahl: So Guy, would that imply that there's yet another database of crime statistics and data such as that that's been looked at when some of the decisions are being made by the software?

Guy Moates: Absolutely. That's just another cluster-type, Dave, in terms of understanding and overlaying that information within that GIS dataset and ensuring that the store is recorded as being in a certain type of area, in a certain geographic area with a local demographic of X and so on. And here in the UK, and I know it's the same in the US for instance, there's different licensing laws in different parts of the country in terms of alcohol availability being sold. So again, that would change the layout. That would change the opening hours. Even in certain part of the UK, there's gates on the end of the alcohol aisle and under-eighteens aren't allowed in that aisle within the store.

Angela Simoes: Interesting. And it also makes me think of a grocery store in my parents' hometown in Northern California where they were having such a high rate of theft. People literally walking into the grocery store, grabbing things off the shelf and walking out. They've reconstructed the entrances to the stores and now I'm wondering, was that driven by data from a system like yours or was that just the managers of the store getting together with an architect and saying, "How are we going to fix this problem?"

Guy Moates: Isn't it fascinating though, because obviously it's on YouTube and you can take a look at it. Amazon obviously got their new Amazon Go brand, which haven't got any checkouts at all in. It's a fascinating technology and how you're able to walk into a store. I think it's incredibly exciting and just pop things straight into your shopping bag and then walk straight out again and have it booked to your Amazon account.

Guy Moates: I mean, there is the future right there. That's so exciting. It's obviously clearly very open to people trying to hide things from the cameras or trying to steal things perhaps. I don't know. I think it's incredible technology they've got running and very exciting as to how that's going to develop. And a great example, as I say, said that the outset of retailers being very early adopters of technology and trying these things out and then these technologies then typically feed into other industries.

Dave Opsahl: In the example you just gave, as you were describing it, I'm thinking, "That does sound really, really interesting." The Amazon Go thing. But wouldn't that also suggests that if I'm able to walk into a store, open up my bag, pull things from the shelf, drop them in the bag and turn around and walk out of the store, it had to know that I walked into the store to begin with.

Guy Moates: Yes. Yeah, there must be some kind of check-in so that it knows that it's you and then from that point it's tracking you personally around the store and understanding and filming you from different angles. Perhaps filming is the wrong word. Tracking probably would be more accurate from different angles. And if you watch the video on YouTube, which is fascinating, somebody takes a product off a shelf, you can effectively see it go onto their shopping checkout list, and then they change their mind and they put that cake back on the shelf and then it subtracts itself from the shopping list. So it understands that you've actually taken something off and pops it back. So it must have actually recognized the products as well and understood that. So that's, again, a great technology and I'm sure everybody's watching on with interest of all the other retailers.

Angela Simoes: Right. And I imagine too, they're actually tracking the patterns, like where people walk. Did they walk in the store and go to the right or did they go to the left and which aisle do they go down? Are there certain aisles that are heavily trafficked? Are there some that aren't trafficked much at all? Is that because of the products on the shelves? Is it because of location, all those sorts of things, right?

Guy Moates: The technology behind that is actually a mixture that there's just been a sort of laser beam that someone breaks as they walk through it, just in terms of canceling. But that doesn't give you the ability to check or count or see which way somebody was walking through that. That's the simplest form of counting people. The more complex way is to use passive infrared detectors or even cameras managed into the ceiling of a store to track people.

Guy Moates: And what the retailers are typically interested in is as much what you don't buy is what you buy. So we've looked at the technology before. Somebody walks up to a perfume counter perhaps in a shop and maybe the dwell time is measured in terms of them standing there for 30 seconds or 40 seconds, and then they turn away and don't buy anything.

Guy Moates: So the big question for the retailer is, "Why didn't they buy something?" They were clearly interested because they stood there for 40 seconds. Maybe there's a staffing issue in terms of they didn't actually get served because the shop assistant was already busy talking to somebody else, in which case that highlights a typical problem. Or maybe there's an opportunity to improve the signage or they didn't actually see what they wanted. So the technology raises a lot of questions for the retailer and it isn't a simple binary response as in they didn't want the product. There could be lots of other factors affecting that, including the environment they're in and the staffing dimension to the problem too.

Angela Simoes: I want to go back to something that you've mentioned a couple of times now and that's the fact that the retail industry has been early adopters of technology. And I want to know from your perspective why that is. Because it's something that we have talked about with manufacturing or AEC and how some industries are slower to adopt than others. And what is it about the retail industry that has made them such early adopters? Is it that they see the benefits right away? Is it because they're getting this data about their customers and so they can make decisions more quickly about things? What do you think has driven that early adoption?

Guy Moates: I think it's because they're profit-driven. I think pure and simply if you can put a return on investment case in front of a retailer that says if you do this you will make more money, or provide a better service or experience for your customers, which of course will result in more profit, then they will always put their hands in their pockets and find the money to do it. And I don't think that's necessarily the case in every industry.

Angela Simoes: Very true.

Guy Moates: So that's one of the reasons I think. We can get very quick instructions on things sometimes in terms of we can go from a phone call to an order very quickly in terms of data capture, in terms of projects and planning and big decisions being taken very quickly. I certainly would say that's unusual and quite unique to retail. Sometimes things have to be planned and budgeted for in other market places , and take maybe years to come to fruition. But retail is much more nimble. Retail tends to move much more quickly and be happy to take slightly higher risks, I would say.

Angela Simoes: No, it makes a ton of sense because in another industries the sales cycles are much longer. It can take years to complete a structure, or a machine, or something like that. So it does make a lot more sense that the [crosstalk 00:26:33].

Guy Moates: Yeah. But Dave, Angela, don't let me paint a picture that's too rosy because I can also go into a retailer, I can get a phone call to say, "Could you come in and help us?" And I look at their processes and I say, "Where are all your store plans?" "Oh, we haven't got any." "How do you currently plan your stores?" "Oh, we use Excel and PowerPoint." So there are some really, really big retailers out there who haven't got these things in place and who need to do the investment. And you don't realize the equity and the value that they've got in store plans and making a difference using these sort of software tools.

Guy Moates: And it's very much a cultural thing between retailers as well, I think, because sometimes we'll come across a retailer who have actively fostered and encouraged an atmosphere of entrepreneurialism within their store managers to give them the latitude and to say, "Move those umbrellas to the front of the store," and make some local decisions on things. Whereas other retailers are much more rigid to say, "Our headquarters knows best." You must follow this to the letter and not have that level of localism as it were. So that can vary enormously from retailer to retailer.

Guy Moates: The problem with the former one, which is where you've encouraged the store manager to be more entrepreneurial, is you'll get ones that will do it very well and perhaps even out-perform the headquarters' model. But then you'll get some who will be very bad at it and there'll be a whole pallet of expensive goods, clothes or whatever it may be sitting in the back of the store that they couldn't fit out on the sales floor because they've decided to focus on something else. And then those heavy, expensive winter coats suddenly remain unsold come the summer and there needs to be a fire sale to get rid of them.

Angela Simoes: Right.

Guy Moates: So yeah, as I say, there's good and bad examples all the way through. Although I'm obviously not mentioning any names.

Angela Simoes: For sure. I don't think there's ever a 100% adoption in any industry. Right? So there's always room for them to grow.

Guy Moates: Yeah. From a floor planning perspective, when I go in to see somebody and I say, "How do you order all of the shop fit equipment for your store?" And as soon as I see them with a hard copy plan and a highlighter pen, I know I've got a great opportunity. Because that still goes on. People counting things and manually entering them into Excel or trusting suppliers to do the same thing, and just linking that floor plan, that CAD data, to a database and being able to report.

Guy Moates: And more importantly, retailers are great at changing their minds quite a lot. Going through that iteration of revisions on drawings where it has to be done again and again and again. Not to use software and automated processes for that is crazy. So in effect, we were doing what is now termed as BIM. We were doing that from a takeoff perspective years ago, just using AutoCAD and our software and just didn't call it anything. But again, early adopters using technology to cool off drawings and pre-pack containers from China, which have exactly the right number of components to fit out that store, to avoid that waste going into store, and then being pulled away or even thrown into the skip a store because it's low value and just simply not worth taking away brand new equipment that was ordered in surplus. We've seen all of those things down the years, which is a real shame.

Angela Simoes: This is truly fascinating. And so we are at our time, but I do want to ask one last question because you did hint at it at the beginning of the conversation in terms of where retail is going and there's going to be augmented reality on our phones as we shop. And I immediately thought, "Oh, I'll be able to virtually try on clothes without actually getting undressed. So that'll be handy." So where do you think retail will be in the next five to 10 years? Some people say there won't even be retail shops, but I think that's more along the lines of what you were talking about.

Guy Moates: Yeah, the shopping experience is going to change. So, where stores are too big, we're seeing smaller franchise, local retailers sitting in alongside the big national retailer and they're giving up some space and renting that out and enjoying rental income from a sub contractor or... Sorry, from a sublet. We're seeing things like, I don't know, nail bars and barbers coming into a fashion environment so that people cannot just wear their new clothes, they can get their hair cut or have their beard trimmed and walk out of the store feeling a $1 million and just adding services into the retail environment.

Guy Moates: There's an expectation. I've got a 22-year-old daughter and if she can't flick and scroll on her iPhone as she walks into a store and check the price of something and so on, then she walks out again. So the retailers have to be nimble again and smart about understanding that people are going to do that by providing free Wifi and so on.

Guy Moates: I think the pace of change has been dramatic in the last five years certainly and will, if anything, slightly accelerate. You mentioned, Angela, about not having to get your clothes off, if that doesn't sound too rude. You can do that right now. There's magic mirrors available where you can actually drag a piece of clothing from a catalog onto the mirror that you're standing right in front of, and you can see yourself wearing that piece of clothing without even putting it on. And then you could even change your hair color and things like that.

Angela Simoes: Wow! really?

Guy Moates: Yeah, absolutely. That technology is available right now and I-

Angela Simoes: Not in any store I've been in.

Guy Moates: You need to get yourself to London.

Angela Simoes: Okay.

Guy Moates: I'll link you up after the podcast and send you a link to the technology. It's very cool.

Guy Moates: So those kinds of things are really kicking in and I think to be a successful retailer in today's market, you've got to be embracing all of these things and have a unique selling point of what you're doing. And differentiate yourself from the competition in some way via through range, assortment, experience, having great stores, great design, and having something in your shops that you can't get online. That pulls back to people as well.

Angela Simoes: Mm-hmm (affirmative). Can I put in a request for either an app or a feature or something, especially for grocery stores? That on an app or your phone, that as I'm buying tortillas, it shows me what the price of those same tortillas are at other stores and I can decide if I want to buy it at that store or save it and add it to the list for a different store because it's cheaper.

Guy Moates: You can actually do that. I don't know if it's available in the States, but in the UK, there's a website where you can actually enter your entire shopping list and it actually tells you which supermarket will be the cheapest to buy it at.

Angela Simoes: I didn't know that.

Guy Moates: Yeah.

Angela Simoes: So, you have to send me that link after the show as well.

Guy Moates: Yeah.

Angela Simoes: Yeah, that would be amazing. But where retail is going and some of the things that you've talked about is truly fascinating and I think anybody who's listened to this podcast, if they weren't aware of everything that went into the planning of a retail space and the products that go in it, never will look at a retail store the same again. At least I know I won't. It's really fascinating.

Angela Simoes: So I really thank you for your time, Guy. I really hope everybody that listened was entertained and enlightened by this podcast because I know I was. And Dave, thank you for your time as well as always.

Dave Opsahl: Well, thank you. This has been, I think, the most interesting podcast we've done and I wanted to say thanks Guy for sharing your knowledge and spending-

Guy Moates: That's okay. It's been an absolute pleasure. I'm always very happy to talk about retail. I'm very passionate about it as you could probably hear.

Angela Simoes: It's great and I think people usually think retail is the person behind the counter. So there's just so much more that goes into it. But thank you again and thank you everybody out there who spent half an hour or so with us listening to our conversation. We hope you enjoyed it and if you haven't hit subscribe yet, please do so and share the podcast with your friends and colleagues and anyone else you think would be interested in the topics that we've been talking about that all usually circle around 3D technology. So with that, thanks everybody and have a wonderful day.

Thank you for joining us on the Beyond 3D podcast, hosted by Tech Soft 3D. Be sure to subscribe on iTunes and leave us a review or subscribe on SoundCloud. To listen to past episodes or learn more about Tech Soft 3D, visit Send us comments and suggestions at

Thanks again for listening and we hope you'll join us again on the next episode of Beyond 3D.


Topics: Cloud, Big Data, 3D, BIM, AI

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