Episode 189: The Great Shopping Shift: How AI is Rewriting the Rules of Commerce

Speaker A: Foreign. I'm Dan Correll with DCA Card Links and this is Commerce Code, a bi weekly digital commerce podcast for leaders in card linking, loyalty and digital marketing, mobile wallets and payments, and financial data. Thanks for joining this running conversation with leaders in the industry and if this podcast is helpful to you, come join us at a DCA Card Links event. You can learn more at www.digco. This week on Commerce Code, I'm talking with Tim DeSoto, the founder of Good Life. Good Life is an intelligent personal shopping companion that helps people save time, money and effort while shopping. In today's conversation, Tim and I are talking about what the brand new Good Life product does, of course, why he built it, and just as importantly, the AI tools he used to build it and the AI capabilities that Good Life incorporates to dramatically improve the shopping experience for consumers. It's a great conversation on a cutting edge development in digital commerce. So stay tuned for the great shopping shift. How AI is rewriting the Rules of Commerce A conversation with Tim DeSoto from Good Life Commerce Code is brought to you in part by VantageScore. Eight of the top 10 banks and over 3,400 leading banks and fintechs use VantageScore to predict and manage repayment risk. Learn more about the latest advances in credit scoring and how to grow your lending business by leveraging financial inclusion@vantagescore.com. Tim, welcome. It is great to have you back on Commerce Code. I looked it up. The last time you were on was April of 2022, which seems like a second ago, but it was actually like three years. Wow, you're back, you're ready, you're rested. The listeners to Commerce Code are going to have a treat because, uh, you and I have talked about this a lot in advance and let me set it up this way. A couple years ago you descended into your secret laboratory and I will get to that story in a minute because it's a good story. Um, but when you were there, you built something and you have now just emerged blinking into the sun with this thing. And so I just want to start by kind of telling our listeners what is the thing basically, um, and what it basically does. So it's a product for consumers, Good Life. And what did you build for them?

Speaker B: Dan, as you mentioned, it's been a long time since I've been on the show. It's always great to see you. I've been a big fan of your podcast. You've been doing A lot of great insights have come from it and I'm really glad to be Here today to your question about what I've been cooking in the secret laboratory has been something that I think is much needed in the industry and for consumers, especially at a time where there's concerns about rising prices, where there's lot happening. And what we've done is at Good Life, we are introducing the intelligent Shopping companion for consumers that helps them streamline their shopping experiences while saving the most money they can around their relationships with retailers, with credit cards that they have, with loyalty programs, et cetera. And so we find a way to help them optimize their personal purchasing power based off of those relationships. And we enable those companies to be able to have a high signal to low noise ratio channel to deliver those messages of value.

Speaker A: All right, we're going to unpack all that. And that's. And uh, to me the distinctive thing there is because I've learned in all of this work, it makes so much difference where you sit in the ecosystem and how it plays kind of with everybody. Right. And so you're serving consumers, it's an exciting product for consumers. We'll talk about all that. But it plays with the other stuff in the ecosystem, it sounds like. And so we'll get to all that too. I said at the beginning, you disappeared into your secret laboratory. And I just, I need to know, know like, is it inside a mountain? Or do you have your own island? Or like, what is. How is this.

Speaker B: I wish I had my own island for this, but we're really operating in uh, Silicon Valley, in near San Francisco, really taking the best insights of what's happening in the world of AI, building that out in our native AI company where we can create the most leverage possible for the people working on this product and delivering it to consumers, while also allowing our consumers to leverage the power of AI to help them do more in their life. So, you know, we see it as an opportunity for us to leverage AI for good for people, uh, in a time when there's a lot of fear that AI might do things that aren't

Speaker A: so good, you know, that that answer is so conventional and reassuring that I'm going to just take that as a yes. I own an island with a mountain on it and I have a team of AI people inside it. That's fine. And so you were at Sam's club, you did a little through uh, like Walmart also and that gave you like the visibility and I think some inspiration and kind of a vision for what you were going to do. And so I'd love to just kind of get that story like, how did you. What did you see? What did you learn? And how did you decide to take, you know, a big jump and do this?

Speaker B: Yeah, that's a great question, Dan. I've been working in retail and e Commerce since 2010 with Barnes and Noble, Nook, Walmart and Sam's Club, all. All companies with paid memberships. And when I reflect on this, I think there are three parts to it. The first came from a sense of frustration, seeing a disconnect between the value a company was creating for its members and how aware those members were of that value. In some of those roles, I built programs designed to help people save more and get more out of their memberships. But awareness was always the toughest challenge. What stood out to me was that we were spending significant marketing dollars just to help existing members discover benefits they already had access to. Realization really struck me how inefficient it was to connect people with the value that's already there for them. But, uh, as we all know, there's so much noise in the market. We're in this oversaturated attention economy where it's really hard to get your message across to consumers. And so with that, there's just this continuously rising noise that, uh, we all compete with as companies and that just increase our costs and there's a lot of diminishing returns we have to then try and get back. And that only comes back through increasing price or, uh, lower lowering quality of product are lowering profits. And all those are bad scenarios. And so I thought, how can we create something that actually allows for all that value to get to the person that wants to use that value and it ends up creating deeper relationships. It really reshapes loyalty. It really does. All these things that we're missing in the space and they have to be done in context. And that's where my background in content licensing and distribution at the Wall Street Journal really came in handy. My experience displaying the right content in the right context at the right time helped me realize, wow, now's the perfect time to think about that new model. Moving from a promotional push of content to this contextual pool based off intent. And when I thought about that and the technology that was becoming available and the ability for us to do this, it was never possible before AI, but now it is. And so I saw that moment and I thought, I need to be able to do something about that. And so when we think about, one, the frustration I had, two, the insight I had around content, and three, kind of my passion for being able to empower People leveraging information and technology to be able to help them live a better life. I thought, there's no better way than for me to do this right now and to create good life.

Speaker A: Mhm. So, you know, AI is an important part of the story, obviously, as you've just said, literally is only possible because of AI. And so you decide to go build some software because you're basically an IT guy with a ton of coding experience and you know all about AI, right? Is that the story?

Speaker B: Oh, Dan, I only wish it was true. I was always an early adopter of technology from the consumer side, but I was never a developer, I was never technical that way. I studied finance in undergrad and in business school because I came from an extremely modest economic background in my family. And I was trying to figure out how to empower my family and myself to be able to have money work for us, rather than us work for money in that same way. And so I always looked back and thought, I wish I would have done software engineering and other elements. And I've even up till a couple years ago, thought I should maybe take a course or learn this. But what's beautiful about AI now is that as a consumer of AI tools, as somebody that's using the tools you can actually build now. And so last year, before Vibe coding actually became a thing last September, I actually built the AlphaV version of this in the cloud, you know, using GitHub and all the pipelines and being able to set things up, uh, and test this with consumers as an actual product. Vibe coding using cursor. And it took me a long time. It took me, you know, about a thousand hours, about ten weeks for me to create this whole thing from scratch. But I got it, it was working. I got good feedback and good signals from the, from the early testers and thought this is something we really need to build using the right method, with real developers leveraging AI. But it taught me a lot. Around this I became much more technical and I learned something. But more importantly, I found that there is an insight to how I think this market is going to change and how there's going to be opportunity for people like me that want to solve problems that, uh, want to help build, but just didn't have that technical background. And I like to joke because if you say, man, you spent a thousand hours building this on cursor, if you look at cursor today, it would never take me a thousand hours. It'd probably take me less than 100, maybe 50 to do what I did. But back Then it was like, you know, like your grandparents would say. I was, I was walking five miles in the snow on cursor to be able to do all the development work that now with linting and agentic solutions that are built into cursor, just allow that to happen. So, um, so yeah, I believe that ultimately this is a signal or a story around the empowerment of people that care about problems to be able to solve those problems as builders in this new builder economy that's coming.

Speaker A: It's amazing how the rate of improvement in these labor saving devices and just the time frame you're talking about to go from a thousand hours to 100 is nothing. But it's no different than you go into a genuinely old home, which in the Americas would have to be on the east coast almost always. And they don't really have much of a basement because they had to dig it by hand. Then when you go to it and our homes 100 years old and the basement is much deeper, but it's not as big and wide as a contemporary home because now like the, you know, right, the hydraulic earth moving equipment's like, boom, done, there's your basement. Right. And that took like a couple hundred years for that evolution to all happen that I've just described. And against what's ultimately some pretty straightforward technology. And like the rate at which these things have gone from, you know, massive technical expertise required to, you know, finance guy with a proclivity towards computers can get it done almost. Did you ever feel like, uh, you're going to pass out, have a heart attack, anything? I mean, your description of it sounded like it was not like a pleasant thousand hours. It was round the clock. I slept a little bit.

Speaker B: Oh, Dan, you're hitting the nail on the head. What was interesting is I had a lot of engineering friends that told me, don't do this, Tim, don't do this. Because they said, you know, it's great for a quick prototype, it's great for a demo, but you'll never be able to build because as the context window needs to get bigger and bigger to be able to solve this, you're going to get more hallucinations in the code. And they were absolutely right. Um, but then what I did and because, I don't know, coding the code was coming out at the time, this is pre typescript world of everything else. This was still producing JavaScript for me. And as I was looking at that, at that code, I didn't know about 60, 70% of it was right. The other part was wrong. But Because I'm not a developer, I know which part that was. So I ended up having to um, pull up other instances with other models of AI to interrogate the code and find out how to improve that code to 90, 95% and be able to test it and then be able to find errors, be able to review it and be able to build. And that took a lot of the extra time that is now being done agentically through these services, which makes it so much easier. And so yes, I really did brute force my way through it and I wouldn't recommend it on, on my worst enemy in terms of going through that process at the time. But ultimately uh, it served as a real education for me. I learned um, how to really think about microservices and linting and being somebody that's more of a full stack developer and how to have a true appreciation for the work and the context switching problems that developers have created. A whole other level of empathy and insight which I think is always just helpful in life to be able to have that and to be able to share it with others so that they can learn, they can grow and do more.

Speaker A: Well, uh, it sounds like you had a great deal of fun doing it and I bet your family loved you during this time. I bet you were a delight, a joy and a delight to be with. Um, but that's all speculation. No need to respond to that. That's kind of fifth amendment stuff. You can just go ahead and let that slide by. But um, uh, it does give me a sense I guess of the intensity and the kind of the passion that you were bringing to it because you had locked onto a problem that you felt like was solvable. And so I want to come Mac, you gave us just the kind of like the essentials up top of what is good life. So I want to come back to now that uh, we've got hopefully a basic understanding of this. You described it as an intelligent shopping companion. Um, it kind of to me sort of puts the consumer, gives the consumer their own list or their own place, an intelligent source, a companion, as you've said, that will help them shop. And this I think is a key thing, not just sort of at one place but like you can shop at Amazon and Sam's Club and Johnson and, and Gap and whatever, all you know, using that tool. And it will, because it's intelligent, will do a lot of things to help that person make decisions, see where the prices are different and so on. That's my very rough. Is that right? Like tell us a little Bit more about what the thing kind of does.

Speaker B: That's a great summarization, Dan. And ultimately what we did is we built really a tool that has several, um, touch points with the consumer to meet them where they're at and help them in the ways they need it. So there is this browser plugin that helps consumers shop, like always save, but save like never before as they're kind of going through these different sites. Can imagine it like having your own LLM or chat, um, AI Chat Assistant that just kind of helps you solve different things, but also immediately see ways to be able to kind of maximize your savings on what you're doing and also see and compare other stores that have that same product and being able to make sure that you have as much confidence as possible about what you're buying in the moment, ah, real time. And we think that that's super important for the consumer to be able to understand that and be able to shop with confidence, to be able to save more, use that money to buy the other things they need or do the other things they want. And at the same time, this is really great for businesses because if you're a credit card company and the wallet of credit cards that that consumer has, if your credit card's providing the most rewards, we're going to show them in that moment which credit cards providing the most rewards around what, they can still select which one they want. But those credit card companies are going to have their brand front and center at different moments of intent for the consumer, starting at the top of the funnel, when they're looking at a product in the consideration phase and at the moment of transaction. And today they're not any part of that transaction, but they really are because they're making an impact and they're providing value. But that value is invisible to the consumer. Today we like to surface that and bring that to life. And not just for financial institutions, but anybody that's playing a role in the transaction, anyone that's thinking about how they can provide more value to that consumer. And that's really about strengthening those relationships. And that's happening on the fly as that consumer is going throughout these different sites. But we also know that consumers are really missing out on the opportunity to have their own lean back experience, their own thoughtful experience about what it is they need to buy, what it is they need to accomplish. At the end of the day, people build more happiness and excitement when they're able to do the things they need to do in life to be able to accomplish things. And so instead of Being distracted to do what somebody else has on their agenda for you, or uh, to go look at other things that you weren't really focused on. Being able to accomplish those mini tasks in your day just make you feel better. So we create a completely noise free scenario. No advertisements, nothing else, just the products and the things you viewed. We provide the, this instant visual memory of all the things you've browsed and looked at. So you can see it immediately. You can ask the assistant on your own kind of shopping dashboard, your own private space on the Internet that you have, you can ask it questions like, hey, I saw some jewelry last week on Saturday, can you show me what I looked at? Because you don't remember the brand, you don't know the store, um, you know that you had it. Maybe it's in the hundred tabs you have open somewhere on your computer, but you'll never find it again. And so we help you save all that time to be able to see that immediately, right? You can then say, oh great, you know, I want to buy this for my wife, or I want to put this into a list or do other things. And we can remember that. And we can also remember preferences related to the people you shop for are for yourself. So it saves you massive amounts of time to find the shoes you wanted in your shoe size that are actually in stock right now, rather than you going through this entire journey only to find out at the end that there is no pot of gold at the end of that rainbow. Right? And so how do we think about that and how do we bring that to life for consumers in their own private space to do that? These shopping lists, these smart shopping lists that we create for them allows them to put things in there and then they can just ask, help me save more money. And it will let them know immediately what items can be bought. You can buy these three other items somewhere else and save an additional $62, would you like to do that? And it breaks it out for them. And then we have these other lists that, um, you can just create that are really around the shopping missions in your life life to be able to say, great, I've got a birthday party coming up, or we have this trip to Hawaii we're planning for, or we've got this home renovation we're doing and you can drop all the things in there, maybe you're not buying them all at one time, but you want to know how much it's going to cost you. And we immediately show you how many items that are inside that list. What is the actual kind of cost on the store and how much more can we save you? And then you can look at all that and immediately know, yeah, that fits kind of in my budget. It or that's what's there. And so bringing these things to a consumer in the moment that matters to them and be able to have them be empowered, we think that that is really important. One of the big things we thought about when we built this was all these companies have a lot of data scientists that help them understand the consumer, that help them create graphs, their own CRMs, all these things that are really helpful to be able to create great value for consumers. But where's that on the consumer side? Where's the consumer's CRM? M. Right. And so we created this new category that we call the shopping Relationship management platform that we power through AI and our proprietary system to be able to do that for consumers and allow them to build off those relationships they have on the business side to be able to create more value than, uh, they've ever been able to see real time. How many times have you have consumers gone and bought something and only to find out there was an offer in their credit card somewhere where they could have saved an extra 20%? Or they opened an email later to only find out that they missed out on savings or something else that was there for them because it didn't happen in the moment they needed it. And so it was just lost. It was like, if the offer falls in the forest, does it make a sound? Right? Like, if it goes unopened, does it make a sound? And so all that is happening within kind of this experience we've created through the dashboard. And then, of course, we have, uh, a messaging channel that helps really serve as this confidant to the shopper as they're going through on their mobile phone or looking at different items and making sure they're getting the item that's best for them at the best deal for them. Uh, we're able to help them there as well as they share with them the same way they'd share with a friend.

Speaker A: And surely it learns over time. I mean, I think about how much time. And this is not in the shopping context, but this morning I spent an enormous, well, no, too much time, whatever it was, looking for a document that I know for sure that I had and I wrote and whatever, eventually I found it. But it is amazing how you can know what it is. And then there are enough different platforms, places where you could have communicated this these days that it's hard to Find. Well, I mean in shopping you can multiply that a fair bit, right? It's just like, well, so to the point about timing, we consume all kinds of information. I mean card linked offers, you see them, you know, like, yeah, I've seen that, I think somewhere. But it's the chances of retrieving that knowledge and being able to find it again in the course of like at the moment when I'm actually going to buy something, there's a huge opportunity there, right. It's still, it's still just, and I think everybody in the sector knows, like, it's still just missing the consumer in a ton of different ways. And you could describe a lot of that as timing problems, which is that, well, at the, you know, when my head is in the, the space of consideration and awareness, that's one thing, but when my head's in the space of transacting, that's another. And it's really only for products that I'm super focused on that I would stitch it all together and be able to say, oh no, no, this is the right time and place to buy this for this reason, whatever, whether it's from a price standpoint or a quality or delivery or you name it. The other thing is, uh, you think about how primitive things are now compared to what they surely will be with the development of AI. I mean, I still find my, like your orders list on Amazon to be hugely helpful because it'll, you know, you can just go and be like, I bought that one thing once, like, what was that? It's the, it takes a fair bit of time to use. It's in no way automated, it's just there, it just happens to be the things that you bought before. But it is quite helpful to be like, oh yeah, that's that one thing. Actually, you know, I wanted the coffee to be lighter than that. So let me go one click. Right. But it gives you, well, I mean all of that intelligence is the stuff.

Speaker C: Stuff.

Speaker A: Not reactively, not like I need to go looking for it. But I think if I understand the uh, the shopping companion idea, it's like there, right? It's just, it's, it's learning and knowing over time, it's gaining that intelligence about you as you're in a, in that back and forth with it, you know. And I think the idea of that shopping relationship management thing, I mean it's um, building that ah, and using it on your behalf. This is the difference to CRM. I'm a little nervous about the CRM comparison because everybody wants to to murder their CRM. It's not possible because it's actually just a piece of software, but it's because the CRMs don't do any. They just sit there, right? They don't. At least as of today or maybe as of a few months ago, they didn't do anything. I think we're going to get to where they're wildly more effective than they used to be. And the shopping relationship management thing, to your point, has, like, never been tried, except for there's a little piece of paper on the side of my refrigerator, Tim. And I am repeatedly told by the one I love the most that if I want something, I have to write it on the thing. That's our shop relationship management system right now. And I generally fail at that. I wanted some macaroni and cheese the other day and it wasn't in the pantry. And I was told, well, did you write it on? And, oh, no, I didn't write it on the thing. Uh, it's just things that don't happen. Hey, you have this image, though, and when you and I talked before that I loved and have still been thinking about, which is from the retailer, let's say, perspective. There's so much message and so much noise out there. And you described it as, uh, a New York bar. And I'll just. I'm going to steal your idea and describe it this way and then you could elaborate. But, you know, the 1970s, the 1980s were, you know, I'm the retailer, you're the consumer. You and I are sitting in a New York bar and it's 4pm and so, you know, we can hear each other, we're sitting next to each other. But if you fast forward to, you know, today, it's 7:30pm it's hot, it's a din. And the effect, and this is the point you made when we chatted before, that I think is so right. It's like the effect is the louder everybody talks about, the louder everyone talks. And pretty soon I'm trying to scream in your ear, but so is every other retailer in the bar. Uh, and you're basically. And this is exactly what happens, right? You're in a combination of. I'm trying to figure out what to pay attention to and I actually don't want to pay attention to any of you anymore. Right? Like, that's where the consumer ends up. But it's a huge problem for retailers, um, advertisers and everything. And so with that image, I like, you've had a way of kind of describing the vision, uh, the intent, um, of what you're doing with Good Life. And so because you had a vision for like, or you had a way of describing how you're solving that.

Speaker B: Yeah, there's a lot to unpack there. I'll start with the analogy you just gave about being in the noisy bar in New York. And let's make it a, uh, noisy New York restaurant with let's say a buffets around the restaurant in different places. And this analogy will make a lot more sense in a second. So yes, it's getting louder, the voices are getting louder, but they're all speaking to one person, to you, the customer. And you're trying to hear from all of them at once. Meanwhile, a few of those voices are telling you where to go to which buffet around the restaurant to get the food you want, and the rest are shouting other things to you that have nothing to do with food. Right? And so, so you're trying to listen to all of that and imagine that that's what a consumer does all day long. And then we wonder why the consumer's fatigued. We wonder why there's this law of diminishing returns around the marketing and the messaging and the fact that we're inundating them with notifications, emails, advertisements while they're out trying to do all these other things. It's just impossible. And so Good Life is that companion that is basically the noise canceling headphones that go into their ears that enable them to hear the one conversation they need to hear at that moment. And instead of them having to go around the buffet everywhere, they can sit at a table and it's brought to them. And I think that that's the power of this analogy, of how that works. And I'll take it another step further. I know earlier you mentioned my family and how they, how I don't. I can plead the fifth on that experience. But what's been great is that in wherever I'm located, in a mountain, in a cave, my family is there with me. And what's really interesting is that my children get a front row seat to how these things are working. And my children created custom GPTs when OpenAI announced them two years ago in ways that blew my mind, right? And they're young and so these are not children in high school, barely, maybe junior high at this point, but back then, elementary school, and they built out things that I just, just couldn't believe. And I remember telling them, I said, you guys don't understand the old world, right? Like we used to have Phones that were wired to the wall that we would talk through all the time. And one of my, my older child says, oh, I remember that used to have to plug it in to charge it because now you just put it on a, on a magnet, right? And I thought, oh my goodness, this, this is a very interesting way, an analogy to look at it because it's like websites, right? Like I told them, websites won't be a thing you go to in the future, right. Instead you're going to have these assistants and you're going to have these dynamic interfaces of information that's provided to you with progressive disclosure to show you only what you need in the moment that's going to help you around whatever mission or thing you're trying to accomplish. And you won't need to go to all these other places for that. It will be brought, brought to you, right? And so, you know, the days websites won't be dead for a long time, but they are going to be walking zombies soon. And so how do we think about that experience? And more to the point about phones, remember when we did have landlines to your point earlier about asynchronous and synchronous information? And when you receive it, you had to be home to receive a message and you had to get it live real time for a long, uh, forever until we created answering machines and then answering machines enabled you to receive it asynchronously when you returned to the right spot. Now with mobile phones you can get that anytime, real time, asynchronously, whatever that is. And that was a big shift. So I wanted to share that because I think there's a lot of insight into how that is changing and how we can understand what that trend looks like in this space.

Speaker A: There's a, uh, way to have had great conversations recently on commerce code about um, agentic kind of an AI commerce. And it does make you kind of think like, what's the path? Because I think there's a sense in which our kids, my children are out of college now, but that they grew up in a world that was awfully similar to the one I grew up in and fully granted, totally. I think social media, that kind of stuff, very different. The smartphone, very different. But in many other respects I'd say like a linear evolution in a lot of ways and in some ways identical. So the point is that the change happens not really incrementally. Uh, it's usually very, very small or no changes and then huge changes that take place in short periods of time and then you're on a new path. And so uh, we're all figuring out, I think we, everybody knows we're on a new path now. Um, with the LLM, um based AI, it's just, we don't know what it looks like totally. But it is an interesting point point about, you know, what's the, when the, does the locus shift, um, the locus of action, the locus of intelligence, that kind of stuff shift in a highly decentralized way to each consumer? Does it, you know, is it what, what's the new equilibrium? How does it work? And so I think there's a lot of interesting questions there. I um, will say for the record that I'm still trying to convince uh, at least our daughter to use AI at all. And so um, uh, God bless her, she's going to be a middle school Latin teacher. So I mean I think she's going to be holding down the um, I don't know what to say, like the paleo conservative corner with a bunch of poor, I guess 11 year olds or whatever you are when you're in middle school. But it'll be good for them, it'll be a good growth experience and they'll learn how to conjugate things. Okay, so what is just like right into the, from your heart as the, as the one who created this particular thing, what's your favorite thing about it? Like what's your favorite feature or thing that you, you know that as far as you can disclose, I know that maybe there's things that are still to come or whatever, but like what's your favorite thing about it?

Speaker B: Right now, uh, I'm smiling ear to ear because one, there is a favorite feature I have today and there's some ones that are coming up soon that are going to be really mind blowing in what we're doing. But I would say the one that made my jaw drop when I first saw it, it was our smart shopping list. The ability for you to just, you know, click on items you want to buy right now, uh, immediately just tell the assistant that you want to save more money and it being able to identify one, what does that look like in terms of savings across coupons, across rewards, across which credit card you should use for all these items and then immediately be able to tell you which stores to buy them at based off of the availability across different stores and what that deal looks like for you across those stores for the, these items. It's highly complex in how we designed it and how we built it, but when I, when I click that button and within a few seconds I see that I can save $120 across four items by just shifting them to a couple of stores in places where I thought I was already getting the best deal. That's a pretty incredible experience and it's extremely rewarding. And so when I saw that and saw that we can do that for millions of Americans that don't have the time to spend on these things and would love to have that money back in their pocket, that was the moment I got goosebumps when I said this is how we help people. And ultimately the reason we created Good Life was to help people. And so we think that not only can we do that, but we're also opening up a much more efficient channel for all these companies that are serving these people that are shopping to be able to save their cost, to not have to spend as much on what I consider a tax inefficient market is additional advertising beyond what you need to do. Yes, you'll always need it for awareness, you're always going to need it for certain areas. But there's a lot of savings opportunity there that can be reallocated into lowering the price for the consumer, increasing the quality of the brand, or maybe even taking a little more profits off the table. But ultimately this empowers people to, on both the supply side and the demand side, to be able to save at the point of checkout. And I think that that's what's really exciting.

Speaker A: I have, I can't resist just sharing some slightly more, uh, abstract thoughts on this one, which is one of the most expensive things and one of the insights of 20th century economics is just that information is costly. And it's like, duh, of course we know that now, but that was the non obvious thing in the mid 20th century to have this observation of like, look, information is very costly and if you think about it, maybe one of the more costly things in the world. And so one of the things that I have thought from when I sort of got to know the Kardlink document space, for example, in digital commerce more broadly, is look, these offers are for everyone because from the retailer and the advertiser perspective, they want the issuer perspective, they want a broad audience to see these offers in practice. I've always suspected, and I think some people have enough data to know that the people that are most engaged with them, um, are one of two flavors. One, they're deeply involved in a particular product segment that they're really into. And so they just know it in and out and they know how to whatever, but they're not engaging with a broad set of offers. And then the other is like, if you will, the sort of professional coupon clipper, like the person who is just an enthusiast for this kind of thing, heck, that goes back decades to people who had three ring binders of coupons and they could come out of the grocery store with, you know, having paid, uh, you know, $4 for a week's groceries or whatever it was. But that's not a big audience either, right? And when you're doing offers, you actually want to hit a large audience of people. And the reason that the vast majority of people aren't enthusiasts and professional coupon clippers is because it takes an incredible amount of time. It has to be fun for you to do that. And that describes a small percentage of people. So the other thing I guess I'm thinking is that what you've built here is essentially the shopping companion that is, if you will, the professional coupon clipper, the professional deal getter at the level of know, an AI tool that can get all of that stuff costlessly and without any time spend for the consumer. But it's also the case that, you know, you put the offer out there because you're trying to build the audience or build the market for something new, for something different, for a new, you know, product, shoe product or whatever it is, and you can't break through the noise. And so I think it does, you know, it helps the market clear by allowing that information costs to come down and get the stuff in the right place at the right time. Anyway, that's my rant on the thing because it seems to me like it solves some pretty essential problems. Tim.

Speaker B: Yeah, I really appreciate that summary, Dan. And to go a little more academically, right, at the end of the day, the marketing wars are in game theory perspective really this prisoner's dilemma, right? And no party can unilaterally disarm in this scenario. And so how do we create efficiencies in the market? We create tools, our ability, abilities to be able to break free from that. And really good life is this delivery mechanism, this new model for content delivery that enables us to break through that noise and that end that entire way of uh, that paradigm of how it's operating by this kind of promotional push content and advertising and all these other things. And yes, we'll still need that for awareness. We're still going to need all those elements, but not to the same degree. We can take that and reallocate that in an efficient manner and enable Companies to get those value messages to either new customers they're trying to reach or existing customers that they have to be able to let them know, here's where we're at and here's what we can do for you. And every customer can look at that and see it and say, wonderful. Look at this and look at these companies that are helping me through this process. Right? There's real value, there's real relationships that being built. At the end of the day, commerce started with relationships, it started with people. We do, we see that at the center of this and we don't see that leaving. We see how do we strengthen that amongst everyone and at the same time allow for a more efficient market where everyone wins. And right now we just have this level of inefficiency. And so our goal is to be able to help solve this, to be able to usher in a new world to do that. Any company that is interested in being able to get their message across again, this is kind of this really high signal, low noise channel to be able to deliver their content, whether it's their products, whether it's their offers, their marketing, their, uh, loyalty programs, they can reach out to us and be able to do that. Right? And we just set them up very quickly. We make that as, as painless as possible to be able to streamline those effects on the supply side while really at the end of the day just creating this improved, better experience for consumers to be able to really save time, money and effort around shopping and live a good life.

Speaker A: Terrific. Tim. This is, uh, super exciting stuff and super fun and I'm looking forward to playing with it. And I signed up yesterday on the webpage. Where can people find Good Life? Where can they find you? If they want to find you, they

Speaker B: can find good life@heygoodlife.com and if they're interested in this shopping relationship management proprietary carry system I mentioned, they can go to heygoodlife.com SRM that's uh, shopping relationship management SRM M and if they'd like to connect, I'd love to over LinkedIn so they can reach me. I'm basically DeSoto on LinkedIn. I was an early adopter, as I said, uh, so you can find me there.

Speaker A: Terrific. And then is there anything up your sleeve that you can hint at? Like there's more to come, right?

Speaker B: Yeah, there's definitely more to come. So to be clear, we will be launching, um, this holiday season and we have some additional features that are there. If you go to heygoodlife.com now, you can sign up for the wait list and uh, be one of the early Access members to Good Life. We're excited about that. We have some things that will, um, help people save even more time for those that don't even plan and that find ways to save in the moment and some new ways to engage and create better experiences for consumers.

Speaker A: Terrific. Tim, thank you so much for your time. Your thoughts today and I'm on the waitlist already. I'm looking forward to, uh, getting the product and playing with us it and uh, yeah, we look forward to having you again on Commerce Code.

Speaker B: Thanks so much. It's been a pleasure, Dan.

Speaker C: Commerce Code is sponsored by Pentadata, the all in one financial data API. Whether it is bank account data, credit card transaction data, or credit reports and credit scores, Pentadata has it all in one simple and easy to use API. With coverage of over 6,000 banks, over 200 million credit files and 60 million merchants, you can get all the data you need for your apps@, uh, pentadatainc.com commerce code is a bi weekly podcast bringing you conversations with executives who are leading the way in digital commerce. If you like Commerce Code, your company should join the Digital Commerce alliance and become part of our mission of advancing trade for good through standard setting, industry networking, conferences and best practice sharing. Check out our website at www.digcommall.org. on behalf of DCA, have a great weekend.

Speaker B: M.