AI-Powered Marketing - Conversations about AI , and digital marketing
AI in Casino Marketing: Insights from Andrew Pearson Interview | #196
>> Hair one, welcome back to the AI-powered marketing show. Today, we've got an incredible guest whose career is as diverse as it is fascinating. Get ready to meet Andrew Pearson. >> Welcome to the digital marketing revolution. This is the AI-powered marketing show, where the future of marketing is not just imagined, it's already here. Are you an entrepreneur, a digital marketer, or a tech enthusiast? Then you're in the right place. Every day, we explore the cutting edge tools that help you manifest and monetize your expertise through the power of funnel hubs, supercharge with artificial intelligence. Unlock the secrets of turning your expertise into a digital power house. From actionable insights to transformative strategies, we've got you covered. Now, let's dive into the world where AI meets marketing, where ideas meet execution, and where you meet success. Your journey to marketing mastery starts here. Here's your host, Heath Bell, bringing the future of marketing to you today. >> Andrew's journey is truly global, born in Pakistan, raised in Singapore, and educated in England and the United States. He holds a psychology degree from UCLA, and is ventured into IT, marketing, mobile tech, social media, e-sports, and entertainment. Talk about a really varied career. In Hollywood, Andrew adapted several novels working with big name directors like Kevin Hooks and Diane Ladd. His screenwriting talents even earned him a spot in the Zotrop screenwriting composition and finalist position in the screenplay search competition. But that's not all. In 2017, Andrew published the predictive casino, which kicked off his series on using analytics in different industries. His writing has been on sports, retail, air, travel, and more. His AI books like the AI Sportsbook and the AI Marketer are must reads. I have a copy of the AI Marketer myself. Andrew is a prolific columnist, writing for top publications like the Journal of Mobile and Social Media Marketing and Computer World HK. He serves on editorial boards and is president of the Advanced Analytics Association of Macau. In 2023, his debut novel was published by brother Mockingbird Publishing and snagged an honorable mention at the Los Angeles Book Festival. His film adaptation of the Dead Ship Syndicate has won over 30 film festival awards. Andrew's not just about work. He's an avid traveler and sought after speaker, whether he's exploring Hong Kong's Lan Kwafong. Hope I said that right, Andrew. Enjoying street food in Singapore or trying his luck in Macau. He's always on the move, seeking the next great story. So let's get an engaging conversation going with the one and only Andrew Pearson. Welcome to the show, Andrew. Very good Keith, how are you? Thanks God. I'm so excited that you are here. I can't wait to pick your brain about everything AI and just a little bit about maybe we'll talk a little bit about some European football as well. But I'm just wondering if you could tell us a little bit about your backstory, like how you got involved with AI and how this became part of your life. Sure. So I was actually living in LA, working in the film business about 13 through about 20 years ago. And I have a twin brother who runs a software consulting company. And so I was doing some stuff for him on the director of marketing side of things, creating content for him, doing a lot of the content for the websites for the company website. And then he actually needed someone to come out to Macau, China, because he was doing a lot of business in the casino industry. And if you know anything about Macau and China or Macau, it's basically the biggest casino city in the world and country in the world. So I came here to oversee an implementation of, it was a product called major value optimization, which is basically a product that tapped into loyalty cards and tracked every single dime or Pataka Hong Kong dollar that a customer spends on the floor at the Venetian Macau. And then gave them rewards accordingly. So it's a very complicated system. So I basically moved here. I grew up partly in Singapore. So I'm very familiar with Asia. Love Asia saw this is the Asian century. I do believe there's an element of truth to that. And then basically, once I got here, I was working with the company and then working with a lot of software vendor partners to pitch to other casinos. We closed the deal with some interesting sports books down in Australia. We closed some deals with a cruise line in Asia, which was mostly uploading casino cruise line. And then a few other businesses as well. And the reality is about five years ago, maybe six years ago now, I wrote the book, The AI Marketer, that's thank you for purchasing that. And basically, there you go. Great work. What you talking about Saturday? Thanks. It's like generations out of date at this point. It's like generative AI was not even in the twinkle of open AI at that point. But it's a fascinating field. So I just kept writing, learning about it. And the beauty is when you work with these software vendors, they all have, based on that as kind of the future 10 years ago. So they're all doing some really cool stuff, which I'll get into a bit later on. But yeah, it's a fantastic field. And anyone who's in it should thank the lucky stars for being in it. And anyone who wants to have a good future needs to keep a close eye on this, because marketers know that companies may have problems, but they rarely will cut down on the marketing department unless they're really stupid. And it's a very challenging world out there, but a fascinating one too, in terms of marketing. So yeah, I thoroughly enjoy it. And last point, then I wrote a fiction book recently that took some of the AI stuff, some crypto stuff that was happening here in Macau, and basically wrote a thriller about that. So yeah, I will be happy that. Oh, you did. Okay, great. I'm going on a trip to Mexico, and I'm going to read it on the beach. I like it. Well, you know, when you read it, understand that a lot of those things that happen in the book are real things that happen in Macau. So I kind of, you know, because it's very funny. It's weird and funky stuff, you know, very Elmore Leonard-esque and and quirky characters. And it was just, I got here and it was just, oh man, this is this is so much great fodder for a story. I just couldn't ignore it. So for my audience, can you talk a little bit about that book real quick, the title on everything? Sure. Sure. So so basically, it's about an American expat who moves to Macau. And Macau's interesting because they have the casinos, but then they have these junket rooms within the casinos, which used to be run by mobsters. So it's like a high roller room that the mobsters kind of control. And then the Chinese players can deposit money inside China at the junket office in in Shanghai, let's say, and then they collect the money in Macau. And then what they do then is they play with the chips here in Macau, and then those are like specifically for that one junket room, but as they play it and they roll it, then they get it into regular chips, which then they can, you know, take to the cage and send to anywhere else in the world. So it's kind of a way where it's a good way to get money out of China. Wandering. Yeah, that would be one word for it. And then so there's so there's the main character is the American who comes to live here to run a casino company, a casino software consulting company, and like me, and he has a twin brother. And he's not sure what his twin brother's doing, but his twin brother is trying to sell the company. And there's a junket operator that they're doing business with some facial recognition technology so that the junket operator can keep track of all the people coming through his junket room, and then basically figure out who's doing the money laundering. And then basically the someone dies in the alone shark kills someone that was playing in the junket room. And the junket operator, whose name is Cash Chiang, he gets arrested. And at that point he realizes that if he doesn't get out on Macau, then he's probably going to go to jail for the rest of his life. So and the funny thing about Macau is we did have a junket operator probably about 20 years ago who ended up making a movie about his life. And he shut down one of the bridges here, he was seen where an informant gets killed. And you know, so and then he tried to he tried to blow up the undersecretary of security. And that's when they basically locked him away for 15 years. Though my character also has a desire to make a movie about himself. So he asks our main character to write the story about his life, which is really his documentation of all the people that he met. And so so anyway, at the end, I won't spoil it, but it's basically a very quirky story. A lot of humor, you know, a lot of basically fish out of water. So a character kind of coming into Macau to a culture he knows nothing about. The other thing we had in Macau, which is funny a few years ago, was a crypto coin was used to raise money for supposedly a floating casino. So the coin ended up, they were supposed to also be allied with the junket operators. The coin ended up actually going public in an ICO, but they weren't able to get it connected to the junket rooms and all that. So the valuation was not quite good. But you know, apparently the Norwegian government was about to invest in it because they understand a lot about oil rigs off the coast of Norway. So it's just a funky mix of all these crazy people. And then the reviews have been really good. You know, I found a publisher very quickly for it. It was one of the first publishers that I reached out to. And then another one was interested as well, but she wanted some changes. So I was just like having my last point, having worked in Hollywood for about 10 or 15 years, trying to get represented, trying to get movies close, but never made. You know, once someone said, let's do this, I was like, yeah, weird. So and it basically took a year to get it, you know, to get the cover done and all the editing done and out. So and I am writing, can you give us the title for the for mine? Yeah, the the dead chips syndicate. I like it. So so the so the dead chip is the is the kind of it's the kind of chip that you play in with inside the junket rooms. So they call it a dead chip because it only has value in that unit room. So you have to play it. And when you win, you get good ships, you get your dead ship back again. And then you keep playing until, you know, once you lose all those. And then, and it's, it's honestly, it's a very clever way to launder money out of China. Because the way they do it as well is you put a million Hong Kong in China, and you can get five times that in Macau. So, you know, it's it's a friend. Okay, you know, I don't know if I talk, I don't know if I, I used to be, I used to be in law enforcement. I did fraud investigation. Yeah, really? How, how long? I've been out, uh, eight years now. I was a, uh, that's yeah, local police detective. And the one of the things I thought about, when I started reading your book and when I got involved with AI was God, I wish this stuff was around, you know, back when I was doing, uh, you know, I did a lot of, uh, you know, financial crimes. And it would have been great to have to do data analytics and put together patterns. You know, imagine me sitting at my desk trying to do spreadsheets and, you know, telling a story with spreadsheets and that's hard to do. So, but anyway, nothing. Exceptionally, and the, the, the company that I came out here, um, that sold the product was SAS, and they have their big into any money laundering. And, you know, they work with all the, um, the banks. And, you know, even, even in, you know, the funny thing is, a few years ago, there was, uh, the, there was a, the bank of Brunei or the bank of Bangladesh, one of those, you know, it was like, I'm maybe a hundred million dollars from Tholan. A lot of it ended up in a jacket room in the Philippines. And they were able to trace it down. And then the junked operator was forced to pay a fine, which he ended up trying to pay in pesos, you know, physical marketing that he came in with counterfeit money. And they were like, come on, you know, you're trying to pay, uh, a fine money for money laundering with counterfeit. And you just kind of see, just helped the crazy depths that this gets to. Yeah. But anyway, crime, I'll leave it with, uh, crime in some cases pays. Unfortunately, that's the way our society is. Anyway, I want to switch gears and talk about your company. You tell me a little bit about your company, just a lot. Yeah. Sure. My last point on the book, I just want to, when I was, and this is kind of a funny thing too, like the reason when I was the first time I flew into Manila, I was intrigued because I remember the name of the, the, the airport was Nino, Nino Aikino Airport. And I had remembered that Nino Aikino had actually been killed on that tarmac, right? Because he was the one that was, um, uh, an antagonist of, uh, Marcos. So Marcos said, don't come, don't come. He flew in from Taiwan. They 60 minutes did a piece where he's wearing a pull approved best at a hotel in Taiwan. And unfortunately they shot him in the head and they killed him. So he died on that tarmac, right? And so the first thought of my character in the opening line of the book is he remembers that he's just about to land at one of the, uh, the only airport in the world named after someone who was murdered on a tarmac. And he was worried that something else was going to happen to hit, but that he might be murdered there too, because he had just been warned that, that, um, some hitman were arrested in Macau, um, basically looking to kill him. So, so, you know, I just can't wait to read the little quirk. I can't wait to read it. Well, I hope you enjoyed it. And do doubt or not, let me know what you think about it once you eat it. And I'll get you the, I'll get you a copy of the, the, the sequel once it's done as well. Awesome. Awesome. So, uh, let's talk a little bit about your company. Uh, once the tell buddy about, uh, what your company is and what you're doing and, you know, where you're going. Sure. So basically I have a company that's incorporated in both Macau and Hong Kong called intelligentsia, limited. And we, I, it's kind of evolved from the work that I was doing when I first came out here to work with the Venetian. So, um, you know, we do BI and tell, you know, is this intelligence work? We do, we do a lot of data integration. You know, if you know anything about modeling and analytics, you have to get the data right. And that's, you know, in some cases, 75% of the work. So we do a lot of that. We do quite a bit of digital marketing as well. Um, and then customer experience as well as another one of our, uh, one of our, uh, strengths. And we mostly work in the casino industry. We have clients like the Venetian Macau, Galaxy Macau, Resorts world. We do actually work with Resorts world New York. And then we also, and that's the whole ganting group. So they have, they have quite a few properties throughout the world. Uh, and then we do a little bit of work with retailers, a little bit of work with manufacturers of clothing and stuff like that. And then we did some work with, uh, an insurance provider in the US as well and a big, big, uh, food, fast food joint. And then we're doing a little bit of work with an interesting company in Australia, which is a, uh, liquor, high-end liquor distributor. So, um, and then we've done a lot of work with sports books as well. So, um, you know, casinos are interesting because they have, uh, you know, the ones in Macau, they have enormous amounts of customers, um, but they're limited in how they can market to, because they can market inside China. So, you know, they can market the hotel rooms. They can market the spas, but they can market the casinos. So that limits a lot of what they can do. Um, and you know, because the reality about the casino is the odds are pretty much set. I think back around is 1.5%. You know, so we, you know, so they tend, they're making quite a bit of money, but they tend to be quite conservative. Whereas the sports books are, um, they have to be very strict on their odds, because if not, there'll be a lot of clever players who will come in and hammer those odds. And they will also, um, you know, we had a client down in Australia and these people are sending out a hundred thousand emails a day during, you know, they have, they don't have the Kentucky Derby down there. Obviously, but they have the Melbourne Cup and they, you know, they're a big or three nation and huge gamblers. So we did quite a bit of work with them. And then we also do some work with a sports book here. And actually, I kind of really enjoy the sports book stuff. I do bet a little on sports myself, um, and enjoy the horse track in Hong Kong. Um, but it's, it moves a lot faster, you know, so we, we created some interesting products. And then a lot of, a lot of what we do is just implementing stuff as well. So, and then, um, in terms of gen AI, which we can talk about in a minute, you know, we're trying to get our customers to look at it and forward on it, because there's a lot of opportunity to hear. Um, and we see, you know, when you've got a casino property like Galaxy Macau, which is literally bigger than the Pentagon, the footprint of that building is larger than the Pentagon officially. So, and I think they have 15 or 20,000 people working there. So it's a whole, you know, it's a smart city in itself, almost. And just a massive amount of people that they need to figure out what on earth to do with, you know, them alone. I did see, I saw a documentary a few years ago about Marina Bay Sands. And I think they bring in a ton of ooh, just to feed the people of work there every day. So you're like, you know, these are, this is an enormous amount of, uh, supply chain issues, enormous amount of, you know, uh, labor issues. So, you know, and we've worked on some interesting things, you know, and I can delve into what I can. Um, but you know, the, you know, the funny thing about Macau is you have casinos that in some ways are interested in testing out products, you know, because they're very interested in finding out who the best, um, and the most profitable patrons are. And then you kind of have the overseer, which is the D I C J, which is kind of like a gaming commission. And I'll go, I'll just explain one story, which was kind of funny a couple of years ago. So, well, what they wanted to do in Macau is basically, um, a lot of these players don't like to, they don't use cards, you know, because they don't want people to know who they are, right? I mean, it's, as, as in my book, right? Um, so what they were doing was they implemented facial recognition technology to get in base, but they also had, um, I don't know what they called it, but it was basically technology to keep an eye on how the bets were, how these people were betting. So in Baccarat, there's a very simple, a very easy way to bet, which is banker or player. And it's the house makes 1.5%, not a lot. Um, then there's a, there's another bet, which is basically tie. So I think the two hands are going to come up both with AIDS. So that's a tie. It pays a lot more, but it's a lot less likely to come up. And just in any kind of betting, uh, the riskier, the more the payoff is, the bigger the cut the house takes. So the house was looking at, you know, people playing those risky bets and saying, these are the ones I want to market to, because I want them to come back. So they were associating the face, which would play, which was quite clever. Very clever. Right. And that won't. Yeah. And it was, I don't know how long they got away with it, poor, but once the DCIJ found out about it, they were like, you can't do that. And you can only use facial recognition technology for security purposes. And, but, you know, I don't know what casino it was. And if even if I did, I probably shouldn't say it. Um, but that's technology that did, then they can use in a lot of other places, you know, if it was, if it was Venetian, they could use it in Singapore, maybe, although the Singapore government is pretty tight down there too. But, you know, the Philippines, which we do some business with, um, or some companies there, they don't have those kind of restrictions. So, man, you know, I'm sure probably in, in, in Vegas, they could get away with that as well. You know, and there's nothing really wrong with it. Um, you know, talk about, I don't really think there's much morally wrong with it. Talk about hyper personalization. I mean, that's, if you get up from a marketing perspective, um, AI going forward is all about, you know, the total customer experience. And that is, I mean, that's an I never heard of that before. That's an incredible use case for, uh, explaining personalization to the, to the 10th degree. Yeah. Yep. And, you know, like a lot of people in, in the U S and in, in the cow, there are quite a fair of people who do use the cards, you know, so they do want to track the amount that you're spending, you know, and these cards track every single spin of the, of the slot machine, you know, the hat when you're dealing with table games, it's a little trickier because you don't have camera, you know, you don't have a pair of eyes on it, digital or human all the time. So obviously a lot easier with a slot machine because the machine is actually keeping track of all of that. But, you know, it's, it's just understanding a player on such a deep intimate kind of level, then allows you to provide them with, um, you know, the, the, uh, the gifts and the rewards that a lot of them are motivated by. So it kind of works for both parties involved. So, um, at the very, but it was quite clever. Yeah, it was quite clever. One of the things that you mentioned is that you're trying your, your company is trying to get, um, your clients to like integrate. If I understand correctly, AI or these tools that you have into their business, what's, what's been the biggest like resistance points with your clients? Like, what's holding them back from going forward? So the biggest resistance point out here is education. So, uh, I, I had a meeting in Cambodia. There's an interesting casino down there called Naga land, Naga world, owned by a Hong Kong company. And I think the owner just died like about a year ago. But what was interesting, because you go there and, you know, they'll be Americans, they'll be Australian, some Europeans, basically in the executive level and they, um, they'll tell you to your base that, you know, we, we, we're dealing with people who don't even have a high school education, right? We're dealing with people who, you know, came from the villages, you know, so we can't, you know, you can send a PA someone with a PhD and do the modeling and that's fine, but we'd much rather have drop down things where, you know, the modeling is all done and, you know, we have, you know, we have tools now where they'll do four different models, you know, and then it'll tell you, oh, this one's the most, this one's coming closest to what you need, you know, so, so in the past, when I first moved out here, you know, we had some very expensive modders from Australia or the US who would come in, meet the clients and you would just have, it wouldn't be a vacuous look in their eyes, but you would, you know, you would have to tell them what was going on, you know, many, many, many times, you know, and some of the stuff wasn't that complicated, at least to us, you know, so, so a lot of these casinos are dealing with a level, but it's not intelligence, it's just not, it's just education, you know, I mean, these people can be intelligent in other ways, but, you know, they don't have a very, they don't have a basic understanding that, that European or American, you know, someone who starts at a casino would have, and then let's see, what are the other ones, you know, there's a lot of, you know, as with any industry and kind of any job, when you come in and you tell people, you need to do something new, you know, they'll be, they'll be a lot of, there's a lot of just time. Yes, and we found, once again, I won't say what casino this far is that said to me, but you said basically, you know, I have five people doing what one person in the US was doing, so we had five people in Macau for everyone in the US, and I've actually heard that that's kind of a number, the 20%, I think productivity is about 20%, what it is in the US in China, and if you think about just the, it's not the people as much as the technology, and Macau is very unique in that, you know, it's got, it's got an unemployment rate that's lower than the US, which is hard to believe, but we, you have as many people looking for jobs as there are job offerings, they get to the point where they bring in Chinese people to do a lot of the jobs they bring in, they have to bring in Filipinos to do a lot of the jobs here, and it's just, so, you know, so getting someone who all their job is is building this one model that will give the hosts on the floor an understanding of who their best customers are and how much they've spent this month and how much they should be giving in marketing, you know, offers, and then saying, well, we have a system that can do this, and then, you know, we're going to give you another job, there's, we've found quite a bit of, and then the other one I'll point out to is like, it's kind of difficult doing business in China sometimes because you do have, you do have it, and obviously there's a, you know, the, the, the, the iG that is very, you know, everyone understands and everyone knows about that, but you do, you will go through several meetings with a client and they'll, you know, it'll look like everything's smooth sailing, and then, you know, after the fifth or sixth meeting, you know, it's, it goes dead, you know, and so that's a bit discouraging in many ways, but, you know, I had one, actually in the Philippines, it's owned by a Chinese company where that recently happened with, and it was just, you know, it was a bit of, you know, a bit annoying, a bit discouraging because, you know, you always feel like that unwanted, you know, where did, where did that woman go? I was like, what, not returning like that churn. Hey digital marketers, entrepreneurs, and tech enthusiasts. Ready to elevate your AI game? Check out the AI-powered marketer newsletter from Keith Bell, host of the AI-powered marketing show. The AI-powered marketer newsletter is your go-to resource packed with actionable insights, cutting-edge tools, and the latest news in AI and digital marketing, whether you're optimizing sales funnels, exploring new AI strategies, or staying ahead of industry trends. This newsletter has you covered. Don't miss out on the chance to supercharge your marketing efforts. Subscribe now. Just click the link in the show notes to sign up today, and remember the future of marketing is here and it's powered by AI. See you in the newsletter. One of the things that you talk about in the AI marketer is CXM and how the customer experience, and now it was a buzzword four years ago. Now it's pretty much common, please. Talk about how what you do improves that customer experience. Sure. In the book, there's a really interesting graph. I can't remember who the guy was that created it. Maybe I'll send you later the name. Actually, Hughes Ray was the name of the guy, and what he did was he broke it down into the race model. Reach, act, convert, and engage, and I think, and then he had three different types of AI, which was machine learning, propensity modeling, and AI applications. Once again, this is like five years ago, so it's changed quite a bit, but I think what's interesting about it was the utilizing the demand generation. Once again, this is personalization. You're basically trying to get to a goal of the one-to-one dynamic content emails, and now it's not just emails, but applications, mobile apps and social media. You're basically trying to get to the point where Adobe uses the term. I think it's the marketing to the customer of one, something like that. Basically, we've got these, in many cases, systems that cost maybe hundreds of thousands of dollars, just so that we can market to the very particular individual. The marketing that we did for sports books was very interesting, because you're breaking it down to not just the preferred team that someone might like to bet on, but also the team that he might hate. If Arsenal's playing, and he's a Tottenham fan, maybe you market, maybe they're Arsenal's playing wolves, so you might want to tweet someone, or in the US, in the US, UCLA's playing. Maybe they're not playing that weekend, but USC's playing. As a UCLA fan and a former student, I might just throw a little money down on the team playing UCLA. I think the odds are good. On the demand generation and purchase intent was the smart content creation, and the AI generated content, which I think is some of the most interesting stuff going on in marketing right now. I actually do a little bit of, and this is just virtual, but it's kind of a hitting. It's a sports book. Here in Macau, we used to be able to do some training, some betting on some sports books. There was an English one that I did quite well with, and then all of a sudden, China got, you know, they considered gaming the opium of the 21st century was one of the things that they said, and basically, I kind of remember it was battery six. There was a well-known brand, a very trustable brand, and they just were like, we're out. We don't want to bother. We don't want to deal with the government of China anymore, and we're like, we're not China, but they're like, no, you're close enough. Here at SAR, so there's a company called, I think it's manifold, and what they do is, what's really interesting is you can go in and create your own markets. So if I want to, like I put up earlier today, it was a zero bank or the best young player of the tournament, and what's interesting is, there's no one looking at, so they wanted to put up an image with my market, right? And what the image does is it goes out, basically binds a football player, you know, and then creates a, he's in a stadium. So it's a very simple picture, but it would have been created through some AI generated, you know, program, I don't know which one it is, like I couldn't really tell, but it was like, it's much better than just putting up a blank screen with text all over the place, you know, people want images, and I was just like, oh, that's kind of clever, you know, and it was just a brilliant use of Gen AI, and they're probably not paying much for it, because, you know, it's quite simple. I put up a couple of other markets, and they get a bit more sophisticated, and it was just like, okay, there's content that, you know, it's very much, it fits my market, and it kind of looks, you know, quite professional. So I thought that was really cool. And then obviously, the content aspect of text, you know, the ability to create, you know, once again, you know, if you wanted to create some, you know, latest information about a player or a team, you know, you can do all of that through, through, through Generation of AI. Another interesting one that I recently wrote about in my, I write papers for general, digital and social media marketing, and apparently Mercedes is now using, or will be using Generation of AI, probably, I don't know if it was mid-journey, or probably Dally 2, or Dally 3 or 4, whatever it's on now, but basically, they would, in the past, spend hundreds of thousands of dollars to bring all of the latest models down to the Lakebed in Utah, Salt Lake, Salt Lake, Lakebed, the famous one, or Death Valley, I think it was Death Valley. So they spent hundreds of thousands of dollars to get all of the latest models driving across that famous landscape. And now they want to take an image, you know, because if you own a Mercedes, a lot of, you know, it's high-end, you know, it's a high network person, usually. And they, and a lot of these, you know, they know these people, so they've seen it, pictures of these people. So they wanted to actually create a image of their customer, potential customer, and put them in those latest models. So the model pictures would be inside, you know, Dally 2 or Dally 4, whatever it was, and then they would have that person and put in sitting behind the wheel of their latest Mercedes model. And, you know, up down that, I did that, you know, I whipped up something and, you know, two out of the four images weren't for useless, you know, we're in very new technology. You know, so you're getting personalization to the point where it's actually the image of you inside a car that is just rolling up the production line, you know, so, and then they're also talking about utilizing a lot of the text-based stuff. They said, "Americans, they don't read the manuals that they get." The Germans, however, read every word. So, you know, they will customize the manuals according to who you are, whether you're a male or you're a female, whether you're German or American or whatever. And it was just like, you know, the book that you got, you know, that basically gets printed, it's on Amazon, it gets printed when you order it, right? So, it's all the stuff printed on demand this reel these days. You know, so a 30-page, 50-page book, you know, to have your face on it in an image that looks really nice, you know, it's easy to do now. And I think the beauty of kind of what what my last point, the beauty of where we are with General Debei and AI and all this technology is it's so, so available and so cheap, you know, it's really quite amazing. So, you know, those are some examples, but interesting stuff too. How much does predictive analytics play a role in this improved customer experience? Quite, quite a lot. You know, as I said, the, you know, when we started, it was, it was breaking down a customer according to what he, what games he played in the casino, let's say, you know, you know, in sports books, it was more about, you know, you know, what, what, not just what games, what, what teams, what leagues. And then one of the things that I was pitching to the casinos, which they don't, I don't know if they cry a grasp, but if they don't, they don't, they don't, they could, it's a workable idea. But basically, we have, in Macau, we have these giant, it's called stadium seating. So, you're about 100 people playing. It surrounds an area of, there's like dealers, and they'll deal about seven hands of back rat and they'll be used to roulette, to roulette wheels. And so, people are sitting in these hundred seats, basically playing hands, you know, within seconds of each other. And it was a ways where, you know, once you get the money into the machine, you know, then there's a psychological element of it's not money anymore. It's just numbers, right? So, people are a lot faster to spend money that is on a digital board rather than a physical piece of paper. But my idea was, why don't we create a situation where you go in and like I was, like I was telling you earlier about, you would know who was the more profitable customer. Why don't we go in and we look at who's a banker player and who likes to play banker and who likes to play player, like there's two sides in back rat, banker and player. So, the thing about back rat is, if you can get a 50/50 split on that table, then you're just taking money, basically, you're, you know, you're just taking that 1.5% on every hand. So, my argument was like, let's have a, basically, a back rat tournament where we'll take these three, these three stadium seedings or maybe just this one and put 100 people that we know, half of them are the propensity to play one side and half of them have the propensity to play the other side and then just break in the monies, supposedly. And then when people go, then you start tracking basically the level of the, you know, are we higher on the players? Do we need to bring more? You know, and then because we have the ability now with our phones and apps in which we can market to people this very second, you know, once you see the level going way too high on the player side, you just start marketing to the, you know, to the, to the banker side and bring them back and bring it to equity. You know, but once again, sometimes, you know, that's quite a lot of work. I do think it's, I do think it would be, it would be, you know, would be a way to, to, to increase revenue quite considerably, but I just haven't been able to convince someone to do it. I think it might work actually better with online casino companies, you know, because I think then, then you have a lot more than 100 playing at one time, you can have, you know, thousands of players. And then, sorry, what was your, um, I lost track. I lost time. My question. I was listening to you, but yeah, just how, how predictive analytics plays a role in it. Okay, so, so, you know, once again, we, we like to use analytics to break down the, or we call segmentation. So you're looking at, you know, you can segment customers in a multitude of ways, not just demographics, not just where they live. You know, marketing can be, that can help marketing enormously, because once you understand, um, who the customer is, let's again, we have background tournaments, we have, you know, um, background tournaments, blackjack tournaments, roulette tournaments. Um, and it's funny because these are by country as well. You know, you go down to Malaysia, they love roulette down there. They don't like roulette so much. So much here that its background is, is the big deal here. Um, and then blackjack Singapore, they don't mind. They like, they like a little bit of blackjack there. So, you know, so you're, you're using segmentation to kind of define who you, who your customers are. And then you can also use it to, if you know, the casino is going to be full on a particular weekend with just background players, let's say you don't, you want to keep the blackjack players away. And you also want to invite the people who will be filling up the rooms and filling up the restaurants. And you know that they're, they're not big gamblers, but hey, you know, let's, let's get them into the club clubs become enormously profitable for these casinos as well. So then, you know, then we'll work on, um, recency frequency, monetary stuff, where you're getting a very good idea of the value of your customers. And also you, basically you're looking at how much they're spending, how, how often they're coming, how much they spend when they're here. So you can break it down to about kind of different 10 or 15 different here, uh, groups. And the bottom of which could be like the customer churn, um, group, the people that you, if you go on market to right away, you're going to lose. Um, and then you can also break it down, you know, and then you can also look at them and basically look at what is going to motivate them to come in and spend more money, you know, or what is going to motivate, you know, there's ways where they're looking at households instead of individuals. So you're looking at, oh, if I give these people a free room, I know it's a husband and wife. So I got double, double, double marketing bucks for that one room, kind of, um, and then, you know, with, with the beauty of what a lot of the tools you have now, you know, we work with Altrics, we work with SaaS, we work with a lot of, um, a lot of BI tools that have now become really sophisticated on the analytics front. You know, a lot of them, a click is another one of our orders, which has a nice auto ML, um, cloud based tool that you can, you know, start using AI. And you know, the beauty is it'll give you what's, as I said before, it'll give you four different models that it'll, you know, run through a bunch of variations of a, um, you know, a logistic regression or a, uh, decision tree or random forest and then say, oh, this is the one that is probably going to work best. And then, um, yeah, and then use that to market to them to try to get them to come back. And then what's underpinning everything is the loyalty aspect. And you're trying to figure out what is going to turn this person from, you know, a new customer to a loyal customer to ultimately a customer who's going to do your marketing for you. So, you know, I don't know the, with acolyte is in the term, but basically someone that is, is going to advocate, tell everyone else, your advocate. Yeah. So, so now that, you know, I mean, you get all this data, you get all this, this segmentation and personalization, what kind of marketing offers are you like putting out to, like say, bring in more players in the, you know, when the player to banker ratio is lower, like, you know, because I got to imagine it's got to be, you know, fairly quick turnaround in terms of like, are you sending out SMS, marketing messages or, you know, um, when I first got here, they were using SMS quite a bit, but not so much anymore. But back to the, back to the, um, the modeling as well, there's, there's the other big thing here, Macau is dynamic pricing. So, it's basically, you know, figuring out how your tables are, um, and what, what minimum price you should be using, and what, what time you should be changing, uh, these prices, um, and there are, you know, there, there are systems like, TANGEM that will do that. And there are, you know, they, they do it for the hotel rooms as well. Um, but the, the, in terms of the dynamic pricing for the casino tables, it's very interesting because, um, you know, someone like the Venetian has, I think 1500 tables. So that's an enormous amount of tables. And there are times when you, if you've got one very rich guy, you don't mind having only him on the table and using one dealer, because they're going to be dealing that a lot faster to just the single guy, right? Instead of dealing with, uh, all the other people putting chips on the table and the, um, you know, the, the dealer having to pay everyone off. So, so there are times when it's better to have one person on the table. And there are other times when, you know, you want that seven or here we have, I think 13 seats at that point. And then the other element is, you know, once again, there's a labor, labor aspect to it as well. Because, you know, these, those are coveted jobs here in Macau dealers. Only Macau people can do that. They're very easy jobs to do and they pay very good. So that's, that's why, but you have a, you know, it is a bit of a limitation because you only have so many. So there are times when the model would include, do I, um, ask the dealer to stay for a few hours extra or do I bring in the other dealer and open up two tables? So it's, it's all, it's not just looking at pricing for the floor and what you expect the demand is going to be, but it's also what your labor needs and what you project your label, labor, um, will utilize. You know, these models are quite sophisticated because they are taking into account what your, um, you know, forecasting what you're, your past, um, you know, floor has been and what you were, you know, what you expect your hotel occupancy to be. And you know, there was, there's an element there where we were arguing, you know, one of the problems with dynamic pricing is once you're filled, you don't really know what the demand would be. So we were arguing, you know, why don't you, why don't you look at the floor in terms of, you know, use cameras to see, to kind of understand how busy it is and how that might be an aspect that you're missing. Um, and obviously that got a little bit better because now now they do have a lot more cameras on the floor, but you know, you know, because it is, the bottom line is this huge amount of money, you know, if you're doubling, if you're doubling your, uh, minimum bet, then you are going to make it considerably, you bring your profit. So, so there was that one. And then, um, there was, oh, yeah. So, so there's also the lead scoring aspect as well. So you do want to kind of figure out the value of the customer. Um, you know, there, we, when we were doing some modeling more in more in the U S, they were finding that they did have some people who were just basically take the opera, because then it was making and then we're going across the street and playing at, you know, the Bellagio instead of Treasure Island or whatever, you know, so you do have that aspect. So there is, you do need to worry about customers who are taking advantage of you. Um, here in McGowan, in the Philippines, you do have a, uh, do you have hosts who can be very generous? You know, so they'll be on the floor and they'll, they'll be giving free packets of cigarettes out to people. Um, you know, they're known gamblers. And then, you know, the host will then go away and change shifts. And then gambler will, you know, hide the cigarettes and then get up the neck and host for the same thing. So our argument was like, you know, why don't you track all of that stuff? Because, you know, you're giving away more stuff than you didn't want it. Um, yeah. Yeah. So yeah, one, one question that popped into my mind is, um, we talked a little bit and we'll get into this next about psychographics and the lizard brain. And, you know, anglers are, um, at least from my observations are, um, how I put this, they, they have like superstitions built in superstitions. And like, if they like a... Especially the Chinese. Yeah, especially the Chinese. Um, if they, I played Texas Hold 'em for a lot, a lot of, a lot of years. And, um, you know, I would see them in the tournaments, but, um, how much of that, like, you know, did they have, like, will the model look at, okay, they really like this particular dealer. So we're going to put that person on when they're on the table that it, does it look at things like that or? It does. It's, well, we... We're like a... They do look at it. Yeah. And like, well, they do, I actually do look at, they use, they use bottles, um, just look at the hand speed, because if you have a dealer that's a little slow, that's costing the house money, right? So, they were, you know, we did some, we did an interesting, um, flick, um, floor plan. So they were able to actually drill down to each table and look at how fast the dealer was dealing. And then he could also, we could also look at all the people who were playing at that table. And you were getting, the thing about the casino, it did, it, it, it understands your actual win, but it's going to look at your Theo win as well. So it looks at how long you're sitting on that table, what the minimum hand is, um, how long you were playing for, how much you bought in for, and then it'll figure out, okay, this guy was there for four hours, 200 Hong Kong dollars per hand. It was blackjack. So that adds to a thousand Hong Kong dollars in, you know, which means maybe a free hotel room. So they're tracking it to that level, right? So, they understand, and then the flip side is, you know, a lot of these players know how you're tracking them. So they'll make it look like they're a big player when they sit down, but then they'll kind of lower their bets. And once the, you know, once the pit boss walks away. So, you know, so it's a very interesting, uh, an interesting game of, uh, whack-a-mole. You gotta, you gotta love the human experience. Indeed, indeed. Um, yeah, and you know, they love to wear the red underwear here. Um, one of the superstitions is they don't want to see a monk or a, you know, a Buddhist monk. If you see any monk, apparently it's bad luck. So it's bad. Well, yes. So, and one of those delicious. And they don't drink here in Macales, like in Hong Kong, I mean, in, in Higgis, obviously, they love to push the alcohol because it makes you, you know, much more free with your money. But here they don't do that. They save it for the, they have K.D. me rooms. They love their singer after the after. They learn. But they're actually now they, they have their rooms on the floor. They can't smoke in the casinos. Oh, which is kind of nice. So they're going through nicotine after you're outside. Well, they, and they have little spots on the floor where they can walk in, close the door like they had, like they have at the airport, you know, so the other, the other model that I forgot to mention was, I mean, this is something we did for sports books and for casinos is looking at problem gamblers, you know, so, especially with sports books, there's a lot of government regulation there where you have to cash these people. And it's a lot easier with looking at someone's play when you can access it. And you can, you can, you can spot the particular behavior of doubling down, you know, doubling up a lot. And there's a lot of, I did some, I, I wrote a lot about this a little bit and was kind of wanted to, to see if I could find a partner for it too. Because there's a lot of, not just human traits, but also, you know, like if your parents were a gambler, obviously, you know, if they were problem gamers, that, but if you, you went to jail, apparently there was a, that's works against you, addictions to, you know, alcohol, that's also, so there were a lot of traits that basically, you could put into a model and then understand if someone, you know, in places like Singapore, where they do, where they have, you know, you can, the family can opt out of a person from gambling. So you, you have a nice track record of, of whether the family had issues. And then, you know, if you're in debt, there's a certain level of debt that, you know, if you're, you know, so there was, there was an interesting, and, and, you know, these, these, these governments have become very worried about that. I think in England recently, I read every other commercial on TV is basically an anti or, you know, problem gambling. If you, if you have an addiction, you should seek help commercials. So, and obviously America kind of embraced, finally embraced sports betting a few years ago. And have a weird patchwork quilt of, of legality, legalities throughout the country, you know, but, but we're also, we did some work with a casino group down in Mexico, which does also have a sports book. And I'm talking to them about some potential AI work as well. So, and just one last point too, on that, when we, we created something Bedwatch, I think, is what we called it. And it did have an element where it allowed the sports board to look at individual games and then put a certain level of risk on there. And then it was also looking at the people who were consistently beating you and looking at the people who you don't want to give any marketing dollars to or bonus money to. And then we did create a very interesting model that a lot of sports books down in Australia actually have a, have a nice ability to cut off players. So, anyone who looks like they're, anyone who consistently beats the sports book, they can come in and say, you're not allowed to bet with us anymore. The Australian government allows them. So, we went to a couple of the sports books there. And we said, look, it normally takes you 10, 20 bets to figure out whether someone's a very good gambler or not. We have a system where we're going to look at their first few bets and then watch the line, like if the line goes in their favor consistently, then they're probably pretty slick better. Good betters normally will, once the line opens up, they'll jump on it because that's the time when they think there's the most potential for moving. But if you have one who three or four times, the line is going in their favor. Say it goes from, say they got it at seven and it goes down to five, then they could, in one sense, maybe take the other side of the bet and ensure that they're going to break even at the worst and win on both sides. So, our argument was, yeah, why don't you do that? Why don't you, why don't you, when you get a new better, because it's a very simple model to do. We ended up not getting the deal with them, and I won't name them, but they ended up getting their analytics partner to develop it. And we found out later on, because our modeler ended up working with one of their modelers and he was rating about it. One of the problems with his business is you, you know, you're giving away your ideas with your clients and it's not, you know, it's a clever idea that my modeler down in Australia came out with, but once you know it, it's like, oh, yeah, it's not that hard to do, you know? So, unfortunate. But anyway, yeah, it is. So, but, you know, it's an example of how you can use, you know, because the thing about sports betting for the providers is it's a very little margin business. So, you have to be very tight on your bonus, the bonus money. And a lot of these, you know, very few sports betters are loyal to their sports book, you know, they'll go wherever the best bonus money is, you know? I think the only business that's got a tighter margin or supermarkets. Yeah. And you know, I see all of these companies that come out and think, oh, you know what, we'll digitize the supermarket experience and we'll have deliveries. And it's just how many of them have to go under that he's people. Yeah, it's not going to work. So, well, man, I, an hour is blown by here so fast. I, you know, I have thoroughly joined this conversation. I just want to kind of have you give like, you know, some final thoughts here on the future of AI, the future of your company. I would love to have you back on again sometime in the future. Maybe after you write your book, we'll get you back. Would love to. So, yeah, I, and I'm, I need to work on the AI marketer second edition as well, because it's, it has, you know, changed exponentially, you know? And when I read the book initially, you know, as a writer, you're always trying to catch buzzwords, you know, because, you know, marketing these days is so much about buzzwords, you know, in an unfortunate way, you know, but, you know, when you start marketing a book as well, you just see that. It's like, it's, it's quite overwhelming. But marketing is a fascinating, you know, it's a fascinating field. And, you know, there is an element where you're convincing people to buy something that maybe they shouldn't have, especially in America, and especially in China, I mean, it's just, what's your brain? That lives your brain. And it's just, it's a lizard brain, but on steroids, you know, it's just like, you have in China, you have this crazy thing where these people are basically doing live streaming, you know, it's like live streaming. This is my bag, but you'll walk down the street in China and places like Shanghai, and there'll be 30 people sitting on the sidewalk, all live streaming stuff. And you're just like, oh, yeah, I know one of those people maybe making money, you know, but not, it's, it's a harsh, I get bombarded on TikTok. But there's people building. Yeah, that's, that's where about most of them are, or towel power or whatever, you know, and it's, it's, it's human nature. We need things, but, you know, a lot of things we don't need, but we still want to buy, but, you know, an AI, you know, I think, I think one, one of the things that I was hoping when social media and internet and the internet came around was like, you had that instant connection to kind of find all the information that you wanted, you know, and you had the ability to really, you know, sign books that, you know, I, you would have had to go to the library previous to them. I remember when Gutenberg popped up and I think there was, there was even MP3.com or something, which was like, this whole interesting web website that just had all these bands, you know, putting up music and it was fantastic. And then, of course, Universal came in and bought it and killed it because, you know, they, they were threatened by it. And, you know, but, but I think the best thing about AI, my last part will be it does give you the ability for this personalization, you know, a level of personalization that is really unattainable 10 years ago. And then the last quote, I have a quote in the book, actually, which you might remember, it was someone talking about the differences between marketing in the 90s and marketing today. And he was comparing it to a first person shooter, you know, and how all this stuff incoming, you're shooting, you know, whether it's emails, you know, messages, SMS or, or direct messages through your social channels or your apps. And it's like, we've got to a point where it's just enormously complex. And then you've had the element of all the different channels and all the different phones and all of this, you know, it is. But it's kind of extraordinary that you can connect with people on such a cheap, you know, in such cheap ways. So, so yeah, and I don't think it's ever it's just gonna be, I think we're probably in the renaissance of AI as well. I think there's a lot of companies spending a lot of money to give you tools that are almost free to use. You know, I played around with some of these, some of these, uh, text to video and that's quite interesting. And I just, there's one, the one last thing on that front, um, the actor, the African American. Perry Perry was a Tyler Perry. Did you reset? Did you see what he recently did? No. So he, so he saw the AI videos from Sora, which is the, the tool coming from Open AI. And he canceled an 800 million dollar. Um, he was basically going to read, you know, build a bunch of new state stages at is Atlanta, a movie studio. And he said he saw what they did with a high. And he was just like, there's no way we can compete against that. You know, and it's like, you know, in some ways, you know, you're losing all that state space. He was using all those jobs. But in other ways, that might have been sitting around doing very little, you know, so I, I think he probably is, is smart to do that. I wonder if that'll translate to cheaper ticket prices. You know, probably not, you know, probably not. Probably not. Um, yeah. I took my wife to the U S last year. Uh, she wanted to do two things. She wanted to fire a gun. How come to America to shoot a gun? Actually, exactly. Uh, and she also wanted to walk on the red carpet, which is because I was there for a screen play. I actually wrote a, the, a script based on, um, the debt ship city. And it was, it got into the Beverly Hills film, that little, um, it was one of 140 that were, that were chosen. So it wasn't really a lot. I mean, you know, there's a lot, a lot of competition. Um, and yeah, so we did a little, you know, did a little red carpet thing at the Beverly Hills, uh, Roosevelt Hotel, which is where bound the first, um, the first Academy Award once. So we got a little picture. It was very nice. Very nice. Yeah. And then she wanted a nice. Thank you for tuning into the AI powered marketing show. Remember, the future of marketing is not just about innovation. It's about how you harness the power of AI to create extraordinary results. Keep exploring, keep innovating, keep iterating, and join us next time as we continue to push the boundaries of digital marketing. Until then, stay ahead of the curve. Take care. [inaudible] (gentle music)