Creating A Trustworthy Business in the Age of AI

Punit 00:00 

Creating a trustworthy business. Yes. How do you create a trustworthy business? Does digital trust matter for all businesses? How is AI playing the role? What is the role of privacy? What role does compliance play in life of an entrepreneur? How do you manage compliance if you're an entrepreneur? And more importantly, how do you set up. And grow a sustainable, profitable, and trustworthy business. Now these are interesting questions and not easy ones. Indeed. So for this, we are going to go and talk to Neil Twa, who is a professional who helps entrepreneurs set up and grow businesses, and he has developed his own methodology and he's also going to distribute 10 of his books for free. If you use the code FIT4PRIVACY all in caps, then you have a chance to get those books and let's ask these questions, how to set, grow, and expand a trustworthy business with Neil Twa. 

FIT4Privacy Introduction 01:11 Hello and welcome to the FIT4Privacy Podcast with Punit Bhatia. This is the podcast for those who care about their privacy. Here, your host, Punit Bhatia has conversations with industry leaders about their perspectives, ideas, and opinions relating to privacy, data protection, and related matters. Be aware that the views and opinions expressed in this podcast are not legal advice. Let us get started. 

Punit 01:40 Hello, and welcome to another episode of the Fit4Privacy podcast. And today we have Neil Twa with us. Neil, welcome to FIT4Privacy podcast. 

Neil  01:49 Punit, thanks for having me on. I appreciate it. I'm glad to be here and honored to talk about some things in privacy and business and growth and everything else we wanna unpack today. 

Punit 01:56 Looking forward to it. So maybe let's start with the simple question. The businesses are becoming digital or digital footprint of a business is very critical these days. 

Neil  02:04 Yeah. 

Punit 02:05 And when we talk about a digital footprint, there's this challenge of trust. Cause can we trust this business? Like I get a lot of emails, you get a lot of emails, we visit a lot of websites, and the question is, can we trust? Can we trust this product? 

Neil  02:17 Yeah.

Punit 02:17 And direct concept of digital trust is coming up. How do you define this concept of digital trust? 

Neil  02:24 Well, in my experience, there's three components of this that build into any kind of relationship business, personal business, you know, otherwise whether you're the person having dealings with the business owner or whether or not you have a relationship with a business or a company. 

Punit 02:37 Mm-hmm. 

Neil  02:37 It's the know, like, and trust relationship structure. It has to do with whether or not you know and understand what they're doing. You know, what they're about, you know what the value benefit of that is. You like it, you like the people that are involved. You like the concept, you like the idea, you know, not just know it, but like it. And then by a proxy, you're willing to leverage some trust. Trust. But verify is an important component of this. No one should implicitly trust anything yet until they have a chance to verify it. Every you know, everybody's level of verification is different ofcourse. But if you remember back not too long ago, we had our verification of trust in the business world through the Yellow Pages, right? 

Punit 03:14 
 Yes. 

Neil 03:14 It was published companies in the Yellow Pages. They were just sort of implicitly trusted, right? If they're in the book, they must be legit. That quickly moved to the internet world where it was brochure websites. A company must have a brochure website or they're not a legitimate company. And then we moved into the, you know, fast forward the digital age of course, which has moved extremely quick. And you know, it's been a little harder with so much information, so many people and so many new things coming online. And now it seems like literally every day, every week there's a new AI system we hear about or some new thing going on, and the question becomes, well, what can you trust in all of that information? Since we move so quickly into the world for me and being in the physical product world and the branding world of those physical products in both a virtual real estate of the online world, Amazon, TikTok, Shopify websites, et cetera. And then the physical aspect of that actual product that you can, you know, touch. This is the one that I leveraged to be able to create a virtual real estate. You know, no like relationship with the customer and the trust comes from when they get the product. So, with the actual physical product, I'm able to create a trust relationship with my customers, which is an. Like a purely digital model. I had done digital models a lot. I had done digital marketing, I'd done affiliate marketing. I'd done those other things and, and learned and experienced and had success and failures in those. But when it came down to com, you know, putting a component of a physical product behind it in my world, that made the whole relationship real, it made it tangible, you know? And so, at this stage now, the no like and trust component of that comes out of them believing that they're gonna get the product, you know, and having a no and like with it, and the trust comes when the product actually lands in their lap. And this is one of the things I think that, you know, has been more difficult in the world of pure digital marketing and your AI driven systems and stuff to establish trust above other systems that are in the marketplace. And that's a little harder sometimes for customers to try to, you know, navigate that jungle, if you will. 

Punit 05:05 That's always challenging to navigate, but it's also challenging for entrepreneurs or people setting up businesses to navigate the building up of the business. How do you build up the business? How do you make it sustainable? How do you make it profitable? And of course, the trustworthy, so? 

Neil  05:21  Absolutely. 

Punit 05:21 You when we talked earlier, you were talking about that four-step approach, which you have. 

Neil  05:26  mm-hmm. 

Punit 05:27 Building a successful, trustworthy, sustainable, and profitable business. 

Neil  05:31  Yeah. 

Punit 05:31Would you elaborate on that one? 

Neil  05:33  Yeah. When I when I first got involved in business a while ago after like 18 years ago, I left my job at IBM. Which was, you know, a trustworthy organization many people understood it and knew what its value was and understood the cost basis of it. And of course, when I jumped out of that and I burned the boats, which meant I was never gonna go back, I didn't burn the bridges. I was at least smart enough to not burn bridges when I left but the boats I burned because I was never gonna go back. And with that, I set out on my own. And, and one of the things I had trouble with in the first three, four years was establishing trust. It was establishing a network, establishing credibility through a sales cycle. Eventually I kind of figured that out. I got a mentor. And he really hammered into my brain. You know, sales fixes everything, but here are the ethics of selling. And, and as I continue to learn how to do that in business, eventually, you know, in the physical product world, I discovered, you know, products are a little easier to gain that trust, as I mentioned earlier. And one of the major components of gaining the trust is understanding where the market is and then providing the market what it wants, right? there's something called demand creation, and then there's demand capture. With a new business, a new service, new software, new product. You know, demand creation is where you get out and you make videos and you explain things, and you go on podcasts and you make people aware of your value, what you are, who you are, what your narrative is, what are you about, what's your principles or can I relate to them? Can I like them? Do they fall in line with my belief structure as a person or my worldview? And then demand, you know, capture. Is your ability to grab that person or situation and turn it into a sale. It's our number one thing. And I remember our first conversation I had with somebody at the consulting level when I had finally broken past my seven figures in my physical product brand as an operator. I had a lot of people who were like, Hey, how did you do that? I want to do that. I'm trying to do that. I'm not getting it right. And I took a lot of free consulting calls from people when I was explaining and trying to help people and, and not charging them, but just doing it and helping them realizing I was spending so much time doing it. But in one particular call we get through the, you know, the first stage of product research, the first step. And I remember we get to the end and I explained, and I thought I did a really great job of articulate. I thought he understood. And then we get to the end of the conversation, he goes, but Neil, what the hell do I sell? And I'm like, wait, why did you not get that? Like we just went over this. So I realized there had to be more. Behind the answer to the question in step one, what the heck do I sell and who do I sell it to? And it became a fundamental component of the process because it forced me to think, well, how did I get the seven figures? What did I actually sell and why did I sell it? And where did I go? And I wanna make sure I repeat that process and I really wanna understand how to standardize it so I can chart it into a repeatable business model, not just a one hit wonder. Right? And that led me to understanding the second step after conditionally looking into the market. And asking, what the heck can I sell? I learned that places like Amazon at that point through their fulfilled by Amazon mechanism called FBA, was a demand capture platform. As other things were growing and this was growing more in the marketplace, many people were coming to it because they trusted the delivery of the products they trusted that when they ordered a product, it would show up. They trusted the review system because they believed in the integrity of the review system. It was relatively new then, and many companies have replicated it over the last 12 years into their systems. But it was new and it was a process by which many people felt that it was trustworthy and with that process, they were willing to take a risk and order a product they'd never seen, believing that in two days it was gonna show up and meet their requirements. Okay? And as long as I did that, I captured that demand. What I had to do was make sure that it went by the numbers, and that's step two. Knowing the numbers of the business was a critical component to not just identifying what product I should sell. But can I make it profitable? Like the most important aspect of the business model? Can I make it profitable when I sell a unit? Do I get to keep anything from it? obviously running a business at breakeven is not cool, right? running a business at a loss, of course not cool. Running business on vanity metrics like revenue, not cool. We say revenue is vanity. Cash flow is king and profit is sanity. Okay? So we need the sanity of profit for ourselves, our family, our business, whatever. We can't grow without it. We have to know the numbers. In a physical product world, knowing your numbers are extreme, I importance in the movement of product just in time delivery, ordering and manufacturing product from different locations from the United States all to the rest of the world. Having them delivered in such a way and making sure the product has an integrity to it, a quality product, right? But the other component of that I realized was step three was not to marry the products. Don't fall in love with the products. There are millions of them. It's a mistake. Many amateur or aspiring entrepreneurs make. When they think about getting into a physical product business or they start down the road of a physical product business, they get married to their products, blood, sweat, tears, love, Hey, all this stuff gets thrown in all the hopes and dreams, what we call the hopium mentality of the online world, right? like a little dime bag of Hopium you know, my selling my product or selling this business or selling all these things is going to, you know, create all my Lambo hopes and dreams, right? and it typically is not one product. It is usually a portfolio of products. So we need to understand. The portfolio, and as we did, we called it our five by five methodology. That was making sure that we had launched at least a minimum of five products in a market test to determine that what the market wanted we were able to provide. In other words, the market drove what we create and did and still does, and we work our best to understand what the customer needs are of that market. And a lot of that has now become AI driven, which is cool. We'll dig into that, I'm sure. But it's to understand that we don't marry our products. There's plenty of girlfriends to steal. In other words, I can build a brand and put a bunch of products in that brand and then determine what the market wants to buy from me. I'm not smart enough to tell the market what it wants. Most people are not. They think they are. They think they need to be Elon Musk. They think they need to go on Shark Tank. They think they need to, you know, if the old Iowa thing, if you build it, they will come kind of stuff. And that's not actually how it works, okay? The market is already in demand for 99% of the available products out there, so it'll become part of the 99%, provide a product that they want, but keep asking the market what it wants from you until they find, until it finds a product and you find a product that dials in profitably. Then just replicate that. Do it Jim. Good Jim, good. Excuse me. Jim Collins says, and good to great you, hedgehog. So as we don't marry our products, we discover which ones are great and then we hedgehog into those products. We borrow things from retail like apple. Okay? If you have an iWatch, you got an iPad, you got an IMac in your house, and then you have one for your kid or your wife or your significant other, and pretty soon you got 20 Apple products in your house. You go vertical and then you go horizontal across your brand. Once you find what the market wants to give you, just keep Hedge hogging down into that brand and just keep going. Then the phrase success is boring, sort of kicks in later on because, well, you're giving the market everything they want from you, and you've built this brand, and it kind of becomes more of an almost automated income at that point because you're just continuing to follow the same pipeline of products and innovations. And innovation is an important word there. We don't invent, we innovate. That's the 99%, not the 1%, and then we have to get traffic. Okay? The fourth step is making sure that you have eyeballs on your offer. Who is buying your product? Once you understand what's out there and what you can provide, how do you get to that? Well, we leverage an asset that was already created, okay. And it is built by a guy named Jim Bezos called Amazon, and they already have 200 million customers in there. And guess what? They're only there to buy stuff. So we take products to the demand that is already there, and we ask the market, do you want this product from us? And it responds by giving us sales. The one that gets the most sales at the most profit is the one that we continue to work on. It's the one that gets marketed. It's the one that grows, and I'm oversimplifying this a little bit in my explanation on it, but that's, it's really find a product, manufacture a product, and sell a product. It really is, at the end of the day, what we do is we pivot through enough products and to discover that demand. Because it's flowing like a river. We say Amazon is like a river, but it's also a decision tree of information ran by a large AI system. So when we're looking at this AI system, it is continuously a generating petabytes and zetabytes of information that are being consumed by large language models and have been for a long time. Originally, it was a semantic search engine. Keyword based, which has driven into so much information that now AI is driving it with large language models, and one of them is called Cosmo, which is the ranking engine that runs below amazon.com. When you search for products, it's a customer intent or customer needs based engine. And the other one's called Rufuss, which is your kind of helper, a AI helper that kind of helps you go through and discover what kind of products you want. And that engine is moving extremely fast. They launched it last year and it's being used more and more literally every day into the hundreds of millions of searches that are helping to. Condition data towards a customer need. And so what ended up happening and what has happened over the years we've done this, is we moved from placing product in front of that demand, that river of traffic, in such a way that it was keyword driven, and now we're doing it on a need space. What do they need? What's the intent of that need? Because now the AI system. It's driving all the information that turns that customer into a just in time buyer in 30 seconds or less based on a product they didn't even know they needed, but now they're gonna, they're gonna buy it because they just realized, well, I need it because the engine was smart enough to have figured that out. So we actually sell data to an AI engine, okay? 

Punit 14:32  Hmm. 

Neil 14:33 It sells products to customers, right? So, I'm not a product development person. I'm a product alignment person. Who sells data and information to an AI engine that sells the product to the customer. When you know that role, you invert the relationship in fear of the original question, what the hell do I sell? Why? Because the engine will tell you, the engine will tell you what it wants, what is it needs, and what is already in demand. And you simply need to provide a brand and then you unique selling position, a slight bit of in, in innovation and put that product in the market because the need is already flowing. And on Amazon it's 8,600 units a minute. The system turns 8,600 units a minute. If you can't figure out how to get a product to turn past six figures on Amazon, you're missing something. If you don't understand how to do it profitable, you probably chose the wrong business metrics to make sure that it's profitable, but that is the four steps to determining a product through growth and taking advantage and then moving into multiple channels. Beyond Amazon. Amazon is not an only business model. It's a sales channel. It is one sales channel in multiple channels that you should expand into a holistic e-commerce company. And with that we have something called the Platinum Principle. It's a bonus step here in this process, and that is that these businesses are worth more in the end than at any time during the business building phase. We are building for three- and five-year momentum and growth to an executable state where that brand is worth potentially millions of dollars. 

Punit 15:52 You mentioned the use of AI by Amazon, and you also mentioned something called cell data to AI engine or cell data. 

Neil 16:01 Yeah. Selling data to an AI. 

Punit 16:02 You really mean selling data or feeding data? 

Neil 16:04 So, when I sell data to an engine, I have to do that with a physical product behind it. So technically I have to buy the product, I have to sell the engine on my product being the best product so that I can turn through that inventory. So, there is a cost associated with that, and my goal is to get that engine to believe that I'm the better product. Okay. Out of the current stream of data moving there 247365. There's a particular area in this big giant technical filing cabinet where that product lives and where that product lives has only so many competitors that are selling that product. Okay? It could be seven, could be 23, could be 12. We can identify how many people are there, and then identify which ones have the top 80% of profit for that stream. Could be, they say air fryers, okay, that are searched 35 million times a year. Okay, and there are like 36 competitors, and those 36 competitors have divided up market share for the 35 million searches a year that are coming through that platform. So, it's very specific. I came there, I'm looking for an air fryer, I wanna buy an air fryer. Here are my 36 choices, basically from 36 vendors. If I wanna be the 37th vendor, I have to understand where to place my product in that system correctly. I have to understand what the AI wants from me with that particular product, and then I have to give it the data that says, Hey, I'm one of the top people. You just haven't recognized it yet, and in time you're going to see that I'm the better product. I'm the better product data. Okay? So, it looks at everything about the conversions, the metrics, the copy and the engine data that powers it to the customer, and it meets the customer's demand, and then it delivers a product through that infrastructure, right? It does it for me automatically from its warehouse. It picks and packs and ships the product, and as long as I get a sale. Then that sale is just another data point that validates my demand. If I get a positive review, it's another data point that validates my integrity of data in the system. We all start with 100 on an IDQ score, it's called, and then that goes down. As long as I keep my data very relevant and keep it high on the score list, I will start to overtake competitors in the marketplace. Why my data okay for my product is better than the other ones. And when it becomes better, the demand for my product becomes greater, and I get closer to what we call Amazon's slipstream, which is where that product might be moving a thousand units a day of air fryers. and I just am not there yet. I'm moving closer and closer to that slipstream as I take over more market share. Pretty soon I'm overtaking other competitors' market share. I'm going from a hundred to 200 to 500 to 600 units a day. As I get closer to that with my data becoming more relevant. Punit 18:38  And when you say data, that means the data relating the product and the company.  The brand perception and the product perception. Neil 18:46 Fran is the image, the graphics, the copy, the listing itself, which is like a webpage. Okay. Punit 18:51  Mm-hmm. 

Neil 18:52 And it's that data and conversion data. Along with how many sales I'm converting out of how many people viewed my listing CRO customer relationship data. And it's down to the conversion metrics, right? How many people am I converting per, per every 1000 people that view my product. And as long as my data is going higher and greater, which means it's more in demand by the customers who are viewing it, my data will overtake the other data from the customers that are already there. Who are buying somebody else's product, and instead they're buying mine. So as that data gets better and the reviews get better, then my entire data set matures, and the longer it matures in the market, the more units I can move. 

Punit 19:29 So, it's nothing to do with personal data. Privacy is still protected. 

Neil 19:33 It's protected through Amazon's terms of service. Right. So, through the customer base that I'm leveraging, Amazon has a term of service with each of us, and I don't know if you do, but we do, we order three, four times a week from Amazon. The customer integrity of that platform is done by their terms of service and as a customer, we have, you know, reciprocal things we can do through rating the feedback of the seller to rating the product itself in a, in an actual review to complaining to Amazon as a customer for the product we got that had a problem, a broken. A, a defect, a return policy. You know, we're protected through that data in that system by leveraging their platform. 

Punit 20:07  Good. And you also talked, so I'm glad Privacy is insured or assure 

Neil 20:13 Yeah. 

Punit 20:13The other aspect you talked about was use usage of AI, artificial intelligence. 

Neil  20:18
 Yes 

Punit 20:18So is it the usage by Amazon or even the e-commerce builders or providers of products using AI in one or the other way? 

Neil  20:26 
So the simple answer is both. I'll explain both. You know, Amazon obviously is built large language models and investing a lot of money in AI driven customer intent models and through acquisitions of certain platforms. Even putting a bid in this week to get TikTok possibly to add that data set and demand creation to their platform and then Twitch and Free V and Amazon Prime, that's pulling data and viewership data for certain businesses. And so, they can start putting, you know, direct response commercials inside those platforms for specific products using the AI data. You know, they've developed a whole strategy of AI and ranking that's behind them and using Cosmo and Rufuss and other systems. To use AI to get just in front of that customer right before they realize what they need and give them the product that it, it predicts that they need based on their intent and showing and being like, oh wait, I actually do need that product. And it shows up during a freebie video. You were watching for, you know, outdoor guides and you love outdoor products and it's like, well here's the best outdoor product for you. And you're like, oh yeah, I actually need that. So, you click over, and you buy it that customer needs an intent is based in the, in their engine. They now give us some of that data. We have compiled data and product data in our own system over time and have developed AI systems on our own platforms. One's called Cayman Data, where we have our own systems, AI information you know, massaging data, looking for trends, looking at the customer needs. Producing what we call a green light process in that to give us the green, yellow, or red based on that data as to whether or not it's a product that we should sell. So ours became a very methodical, data driven and using AI systems and massaging the data for presentation back to the user. In this instance, it's us right now. We're able to see exactly what's in demand, how much that demand is actually being met and not met, and where to position products. In the top 2, 3, 4 positions of a of a specific data set. Okay or a product, let's say an air fryer. We know exactly where to place which air fryer, which variation and which type into the market to meet a customer demand segment that exists. So, we're not guessing. We're using AI and we're using data. We're using data analytics, and the engines are turning that over for us, and now we're just going out with agents and pulling that data together, compiling it, and then presenting it to us and showing us here. This is the product you should go after. This is the one that has great customer needs, has profitability has upside potential. Tells us competitor data. And it all presents a very good decision-making process that's data driven. And most of that is driven by AI based systems. Now. 

Punit Bhatia is one of the leading privacy experts who works independently and has worked with professionals in over 30 countries. Punit works with business and privacy leaders to create an organization culture with high AI & privacy awareness and compliance as a business priority by creating and implementing a AI & privacy strategy and policy.

Punit is the author of books “Be Ready for GDPR” which was rated as the best GDPR Book, “AI & Privacy – How to Find Balance”, “Intro To GDPR”, and “Be an Effective DPO”. Punit is a global speaker who has spoken at over 50 global events. Punit is the creator and host of the FIT4PRIVACY Podcast. This podcast has been featured amongst top GDPR and privacy podcasts.

As a person, Punit is an avid thinker and believes in thinking, believing, and acting in line with one’s value to have joy in life. He has developed the philosophy named ‘ABC for joy of life’ which passionately shares. Punit is based out of Belgium, the heart of Europe.

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