Who Built Viizable and Why

Test Delete · created Jun 19, 2026 · 0% posted (0/11) · Active

Brief

Okay you're going to need to flesh out or put in some information about me and my history and I'm going to throw it out here I'm going to try and tell you the parts that we probably should include and maybe minimize some of the others but basically you know I started in business working with my dad in the insurance business and I moved to Houston and started my own company and was written up within 2 years as being the fastest growing insurance agency and all of Houston Texas and I was only 21 or 2 at the time 23 I guess and so I had this knack for figuring out processes business processes okay fast forward a few year I went to work I sold my agency and I went to work for a friend of mine in Dallas near Dallas it owned an insurance company and they wanted me to be the vice president of Business Development and what ended up happening is I developed a system that was so effective that the State Board of insurance came in and warned my friend and his father-in-law that if they didn't get more Capital the State Board of insurance was going to shut them down well they told me to keep going and their deal fell through with the last minutes so State Board of insurance literally shut the business down because I was too effective at recruiting agencies to sell this insurance companies policies well after that I got very interested in computers and went to work for a local bank and about that time I heard about an agency that was being started under the FDIC Federal Deposit Insurance Corporation that would literally liquidate the assets of about 900 Banks and so I went there and within 2 years I had jumped from a single One Bank location to where I was given a new title and had responsibility for the systems over five banks in Houston and then I was moved to Dallas where I had responsibility for 150 Banks a joint responsibility with other peers and then I was moved out to Dallas where I had another $150 Banks and then through that process I decided to move to near the Washington DC area and worked for contractors and also you know contractors as a consultant as a as a consultant and my employers literally paid several hundred thousand dollars for my education as a business processing engineering consultant and also a computer-aided system engineer home which basically would allow us to draw up the things that the business tells us that it does and translate that into data and process models and then literally generate all the screens and functions within the within the tool We can meet within the tool we could create a new system for a large division that would take a couple months that used to take an army of developers two or three years and so I got to where I was literally expert level at discussing with the users what they needed and then identifying the right way to architect the system and the business process is so that they could minimize cost and increase in efficiency usually they would drop about 60% of the Staffing costs and about 50% of the system cost and the cost of system development this way was about half of what traditional waterfall development processes work okay from there I went a friend asked me to come help him at a startup called ecampus.com that was at the beginning of the com praise and these investors Dave Thomas of Wendy's so and so of Long John Silver's several Sports celebrities the ex governor of Kentucky put together and raised a little over 100 million dollars to build the world's largest College bookstore and I was the chief technology officer at the time and we were building data centers because they didn't exist back then for.com businesses we were literally writing the code to create a website and today you can get a website for free we were having to architect all of the payment processing and the communications with the warehouse and whatever and all of this was literally built from scratch including our customer service systems and everything else. so when the CEO came to me and says look we need you to help do the marketing you're more familiar with all of the things that we can possibly do technically you know so I set up the outbound email Outreach to the different colleges we developed you know I literally put a hand a dozen college students in a room and had them literally start barely reaching out to other college students we built a system that allowed college students to post their photos to communicate with each other hand And we built out the system so that students could sell back their books and we were approached by Amazon I can't verify this because I wasn't on the other side of the phone call but Amazon took our 2.6 million book catalog and we were the first bookstore in there what's currently there Amazon product pages you know I'll have to get the exact title of what what it's called today but we were like the first Amazon store and we also seeded eBay's half.com and these were all innovations that don't want to ever done before and so we had to literally build out the infrastructure the interfaces there were no apis back then and this was you know Brute Force but I was lucky enough to know how to communicate with very intelligent developers and system engineers and networking experts to basically get all of these things done for the company and we started growing growing hockey stick growth but as we started getting more attraction the CEO recognized that he would have to pull in someone that had a better resume than I did and so they pulled in a guy from Harvard and he immediately started posting ads in Rolling Stone and buying video spots in front of Cinema you know popular movies Etc and while this got us mentioned it didn't really Drive pure Revenue and so the company went bankrupt. well on the other side of bankruptcy it was very critical that the new owners had someone that understood the marketing and marketing literally without the resources of 100 million dollar Company the company that bought he campus only spent a couple million dollars and so they came to me I pulled out the original marketing plan that I had and we started and I started implementing it and within a few months we were doing hockey stick growth again and in the first 21 months we went from $4 million dollars in Revenue to over 21 million in Revenue so let's talk about those early days of marketing this was back when there was no Google Yahoo was the leader and there was lycos and there was Alta Vista and we figured out or you know and I figured out along with my team how to get into the search rankings and we were so good at it that a lot of our keywords like discount textbooks we were in all 10 spots at times we would use doorway Pages we would use backlinks we would you know build new websites we created a couple new bookstores strictly to make sure that we were there but we knew how to get in front of the customer and deal with the technical challenges that were there at the time the key thing to remember here is when Google first came up And started you know getting traction there was no class you could take there was no there were no gurus I mean everybody says their Guru but I mean people who really knew what was going on inside of Google they didn't exist and so the only method we had of figuring out how to rank was to take the top ranked businesses and reverse engineer them and like I said my entire you know 10-15 year career working with large businesses in the Washington DC area Denver Dallas Etc was basically reverse engineering a business or a process and then figuring out how to make that work more efficiently so in fact when I left video Professor I'm sorry when I left the campus and went to video professor they were Denver's number one the largest direct marketing company and they had had four directors of e-commerce or directors of internet marketing before I got there one every 6 months and I literally had to beg them to let me work for them but when I saw how poorly organized the marketing department was compared in and the technology how distant it was from the marketing I knew if they would give me free reign there that I could literally blow their sales up so back to search engine optimization the we we instantly started improving their sales from SEO that that was a gift but I had a new problem there because video professor used what's called a negative option meaning it's a free trial and everywhere on television and on the internet we would use the word free free well many customers that got billed for two or three months without looking at their bank statement after they got the free CDs didn't realize that it was a free trial and it would Bill them every month so the company had a lot of negative posts negative comments and so video Professor we managed to get in the top three or four spots for most of their products like learn Excel or learn word or learn PowerPoint but there was always one or two websites where someone had complained that was right there below us and it was a royal pain in the ass. so we figured out that we would go out to all of our Affiliates and we had hundreds of Affiliates thousands of affiliates that we're sending traffic to us and many of them had built websites and they were actually doing relatively well in the Google listings and so what I did is bring them in and help them become expert at getting ranked for our keywords our major keywords ahead of the negative websites I think Ripoff Report was one of them but this is essentially why I feel or why why I feel qualified literally to give to the industry the key factors That we got from our research and I spent a ton of money and time on this but we literally pulled in over 30,000 local businesses that AI recommended as the best in their local area and And we're continuing our research and right now we have over 100 different business types that are going to lose Google traffic and recommendations and Word of Mouth recommendations to AI and so it's an ongoing process to continually evaluate these businesses and pull in the factors that are common to all of them or common to or factors that showed up when a business was evaluated not all businesses have these 150 criteria that need to be looked at obviously if your a plumber it's a good idea to have your business license linked back to the state where it exists it's a good idea to have your insurance perhaps your insurance company listed maybe not the amounts or whatever the type of insurance but at least say you know that you have insurance that maybe your employees are bonded because this is this is important to AI but if you're a restaurant it's not going to care AI is not going to be looking at you know whether you're a contractor's license is valid so you know the factors are there because we went across so many different Industries but the point is these are the factors that we found that in many cases if you align them carefully with list then you automatically are getting closer to getting into the AI recommendations list shortly okay so Okay so I'll get into what my engineers and I did to to get the data and will also go into what what the average business scored and we'll go into the definitions about you know the different criteria and we'll also go into what we believe should be done to fix that particular criteria so we also have the waiting that AI itself has come back and said look of all these criteria I would wait this one highest and this one the next highest in this one the next Heist and we do this across all of the AIS that are you know the cover about 85% of all the the requests for local business services and products okay all right so that's that's that chapter maybe I need to say Okay the reason yeah let me put this in there as the fact that after video professor I basically started my own companies worked with partners and have launched over a dozen different companies most of which I sold about 10 or 12 years ago and since that time I have spent my time traveling from the tip of Alaska almost to the tip of South America and I visited over 200 different cities I was looking for something specific which was I wanted to live somewhere where the water was absolutely pure you could drink it out of the ground where there was no glyphosphate or pesticides or fungicides being used on the vegetables and fruit that I ate where the the cows and other animals were raised on grass that was as tall as her stomach and there was no commercial feedlots to get into the mix and introduce antibiotics or you know other additives into the meat and so I want it I realized that making money was great but living was better and I wanted to live as long as I could and enjoy every day and where I lived the days drug out and there were no there's no stress there's nobody trying to steal your nobody trying to run in you know slamming on their brakes hoping you run into the back of them so they can sue you there's nobody that you know is is literally trying to break into your house or rape your your daughter so this is just a a better place to be but in paragraph new line new line the reason why I left South America and came back and started working in the United States started worrying about the United States is because over the span of my career I had helped probably a thousand different small businesses either through one of our marketing companies or personally or one of the you know or personally and I just knew that most of them were going to get caught off guard and when I looked there was nothing out there to help a small business deal with the decline of traffic from Google and Word of Mouth and get them positioned for the future in the future is If you're not positioned in the AR recommendations you have a pretty strong chance of not surviving over the next four or five years. But what I forgot was how hard-headed and difficult to convince other marketing experts are about A New Concept it's been a tough road because I believe that we've built probably the best tool it's ever been built to help these local businesses get into AI all the other tools that I've seen were basically here's where you are and here's where you're not but there was no work bench built in did a loud businesses to excuse me that allowed the SEO to dive in and start work it seems that all of the the discussions these days are not you know well is this a good source of a backlink or is this and that is what a mature process that's the conversations of a mature process but today AI is just like it was like Google was when it first showed up and like Yahoo was when it first started becoming a traffic Source in lycos and I could name four or five others so here's the issue that the industry is going to have to get over you're going to have to pick a A strategy and a source of Truth to line up with this is not a long game this is not something that can be discussed over a year to come up with a ideal strategy. this is a a race and like so many mentors have told me it's it's ultimately better to vigorously work on a path that you think will get you to success that's 80% correct then it is to sit around and draw until you figure out what the other 20% is so I hope this guide gives you some insight into why I believe it is absolutely the best thing that the industry can do to get started the the world is waiting The world is waiting on the marketing agencies and the seos to stop doing research about you know why a brand made it over here and why this business got recommended over here and this one didn't and what about citations and what about these mentions and you know what are the on-site factors the onsite factors do backlinks matter what about you know what does SEO even factor in anymore and so all those questions are getting in the way of us as a group making progress for the individual client and I'm publishing this guy which is proprietary information that we spent 10 months getting because I would rather see these small businesses helped Dan to hoard a few hundred and not help the rest so anyway if you got good clients I highly recommend that you take these factors and review their sites and see and also review their competition that's ahead of them and see what what the checklist is that you need to work on to get your client more aligned with its competitors that are ahead of it okay I'm just going to use this document because I got started on it for something else but basically I want to add in you know that I'm a father I have three wonderful children and a handful of grandchildren and like I say I live normally in the coffee triangle of Columbia where they have arguably the best coffee in the world and in the past I would sit in a coffee shop in New York or San Francisco or Seattle and think to myself man this coffee is great I just wonder what it's like to actually drink it sitting at a coffee Farm and that was part of what drove me to come down here I also need to add in a section about you know I owned my own marketing agency called ad Leverage and I was also the co-founder of a company called convertis with some other industry leaders and we took that business from zero to like 18 million run rate in just one year and is the primary internet marketing executive at Colorado's largest direct marketing company at the time I took their sales from 11 million to 66 million in just 13 months and I think I've already described what happened at eCampus and then I also owned a company called National gift and we helped thousands of small businesses with marketing and products for their websites and basically I after my trip to Nome Alaska I semi retired and no actually I I opened a an Outsourcing company down in Peru and we had 150 employees from Peru Ecuador Nicaragua Mexico Columbia and Venezuela and I spent you know many many or several years you know going from office to office getting to know the employees Etc and literally having one of the best times of my life and you know that's when I knew that I probably would live down here for the rest of my life because you know I found places that were water was so pristine you could drink it right out of the mountain there was some you know all of the beef is grass-fed and they stand in these fields where the grass is literally touching their their shoulders and you know the fruits and vegetables are so pure there's no toxins or glyphosphate and so it's it's just such a healthy wonderful place to live the Roman Catholic ethnic ethic is everywhere and you know the families are they care for each other and most of you know if there's any crime down here there's a little bit of you know juvenile delinquency but in general people are just concerned about working and raising their kids properly and so it's a wonderful place to live you know I recently invested in a company called Colombian visas.com and also I have invested in a company that buys and sells and helps people buy Caribbean facing Real estate and I hope property in the middle of the country and then again on the coast so the reason I returned to the United States was to help the small businesses that I had worked with deal with the fact that an intermediary has stepped between their normal source of new prospects and their business and if they don't have the the tools to immediately identify what they need to change in order to get in that stream of new prospects then many of them over the next few years could literally lose their businesses and that was my my purpose so that's my current project and that's what I'm excited to be doing and I plan to be doing for the next year or two helping as many people as I can and then we need to say the research that we did while we're trying to figure out what these businesses needed to do lend me to reverse engineer about $35,000 top ranked local businesses and we found approximately 150 different factors that we could measure that these businesses included or had that one or more of the five or six primary AIDS required and it was this index that we built another tools specifically for SEO AEO Geo marketing agencies that were at the at the moment still struggling with what factors to fix for their clients and so we created visible and it's not a tool that Nordstrom or Victoria's Secret or Best Buy would use because it's focused on the local businesses you know restaurants Florist plumbers Bakery auto mechanics dentist Etc and these local businesses can see very clearly who their competitors are near them and our tool actually will reverse engineer their competitors factors and so they can compare Head to Head and see what it is they need to adjust to be in the top four five six businesses in their competitive market and so this this is how they get ranked is by clearing these factors in aligning to what AI needs so anyway that's that's how this all started and I'm real proud of you know those AI business score and which we may bring Rebrand to AI best friend because it's more of a what we doing is more ranking than scoring and then you know also we have visible which is spelled v i i z a b l e okay so that's that's the current projects we're working on we're really excited to be going back and forth I get a chance to see my family part of the time and one of my sons is was involved in the founding of these companies as well
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The engineer who got a company shut down for being too effective built the AI ranking framework.
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Brent Tuttle spent 30 years reverse-engineering how businesses get found — from Yahoo's earliest rankings to Google's rise. Now he's doing it again, this time for the AI assistants replacing both.
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Brent Tuttle spent 30 years reverse-engineering how businesses get found — from Yahoo's earliest search results to Google's first algorithm shifts. Now he's applying that same method to AI assistants. Viizable exists because local businesses need a workbench, not just a warning, before AI replaces their last reliable source of new customers.
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Brent Tuttle has reverse-engineered how businesses get found since before Google existed. At eCampus.com he owned all ten top search results for key terms. At Colorado's largest direct-marketing company he took revenue from $11 million to $66 million in 13 months. At a second venture he hit an $18 million run rate in one year. That same discipline — study what's winning, identify the exact factors, build the system — is what produced the AI Ranking Factors framework: 150 measurable criteria pulled from analyzing more than 35,000 local businesses AI actually recommends. Viizable exists because Brent has done this before, and the window to act is now.
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At 23, I was named the fastest-growing insurance agency in Houston. By my early thirties, I'd grown an e-commerce startup from $4 million to $21 million in revenue in 21 months. At Colorado's largest direct marketing company, I took sales from $11 million to $66 million in 13 months. I'm not listing these to impress you — I'm listing them because every one of those results came from the same discipline: reverse-engineering what was already working and building a repeatable process around it. That's exactly what I did with AI recommendations. When Google first appeared, there were no courses, no gurus, no playbooks. The only way to figure out how it ranked businesses was to study the businesses it ranked. I did that then. I'm doing it again now — this time with the AI assistants that are quietly replacing Google as the first stop for local business recommendations. My team and I pulled in more than 30,000 local businesses that AI assistants were actively recommending across more than 100 business categories. We reverse-engineered approximately 150 measurable factors those businesses had in common. We weighted those factors against the responses of the AI systems that cover roughly 85 percent of all local business queries. That research became the AI Ranking Factors framework — and the tool we built around it, Viizable, is the workbench that lets marketing professionals act on those findings for their clients, starting today. I built this because small businesses don't have two years to wait while the industry debates strategy. The shift is already happening. — J. Brent Tuttle
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The question most people ask about an AI ranking tool is whether it works. The better question is whether the person behind it has ever actually been in the fight — building something from scratch, watching it succeed or fail in real time, and doing it again. That is the only credential that matters here. J. Brent Tuttle started in business at 21, running the fastest-growing insurance agency in Houston. By 23 he had built a recruiting system so effective the Texas State Board of Insurance shut the company down — not for fraud, but because he was growing faster than the capital structure could support. That early lesson — that a well-built process can outrun the infrastructure around it — has defined everything since. He spent the better part of a decade as a business process engineering consultant in Washington, D.C., working with some of the largest institutions in the country, including the FDIC's asset liquidation of nearly 900 failed banks. His employers paid several hundred thousand dollars for his training. The core skill he developed was the same one he uses today: sit with the people who do the work, reverse engineer what they actually do, then build a model that cuts cost and complexity in half. When the dot-com era arrived, Brent was Chief Technology Officer at eCampus.com, a $100-million-backed venture to build the world's largest college bookstore. There were no APIs, no off-the-shelf infrastructure, no playbook. He and his team built the payment processing, the warehouse communications, the customer service systems, and one of the first third-party storefronts on what would become Amazon's marketplace. After the company changed leadership and went bankrupt, the buyers came back to him — and in 21 months he took the business from $4 million to over $21 million in revenue. That growth came from search. This was before Google dominated, before any certification programs existed, before anyone called themselves an SEO. The only method available was the same one Brent had always used: take the businesses ranking at the top, reverse engineer every factor in common, and systematically align to what the algorithm required. He did it again at Colorado's largest direct marketing company at the time, taking their online sales from $11 million to $66 million in 13 months. That experience is exactly what Viizable is built on. When AI assistants began recommending local businesses to consumers, Brent recognized the pattern immediately: a new intermediary, no established playbook, and a narrow window to figure out what the algorithm actually rewards before the market consolidates. His team reverse-engineered more than 35,000 local businesses that AI recommended as best-in-area and identified approximately 150 measurable factors across more than 100 business categories. The result is the AI Ranking Factors framework — and Viizable, the workbench built specifically so marketing agencies and local businesses can act on those factors, not just read about them. He did not build this from theory. He built it the same way he has built everything else: by doing the work first.
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The single most important thing I can tell you about AI Ranking Factors is that the framework wasn't built in a conference room by people theorizing about search. It was built by reverse-engineering more than 35,000 local businesses that AI assistants already recommend — and measuring exactly what those businesses have in common that their competitors don't. That process took ten months, produced approximately 150 measurable factors, and cost more than most small businesses spend on marketing in a year. I'm publishing the findings anyway, because I've spent the better part of my career helping small businesses compete, and I'm not willing to watch a thousand of them lose their customer pipeline to a technology shift they never saw coming. Here's the short version of why I'm qualified to say any of this. I started in business at twenty-one, building an insurance agency in Houston that was recognized within two years as the fastest-growing in the city. I learned early that growth is mostly a systems problem — if you can identify the right process and execute it relentlessly, the numbers follow. That instinct took me to a vice president role at a Dallas-area insurance company, where I built a recruiting system so effective that the State Board of Insurance shut the company down because it couldn't keep pace with the capital requirements my growth was triggering. That was my first lesson in what happens when a system outperforms the structure around it. From there I moved into technology, joined the FDIC's Resolution Trust Corporation during the savings and loan crisis, and went from managing systems for one bank to carrying joint responsibility for a portfolio of 150 banks inside of a few years. My employers then spent several hundred thousand dollars training me as a business process engineering consultant and computer-aided systems engineer. The discipline of that work — sitting with end users, mapping what a business actually does, translating that into clean data and process models, and building systems that cut staffing costs by sixty percent and development costs in half — became the foundation for everything I've done since. I got very good at reverse-engineering how something works, stripping out what's unnecessary, and rebuilding it to perform. That skill is what brought me to eCampus.com at the beginning of the dot-com era, where I served as Chief Technology Officer. The investors had raised over a hundred million dollars to build the world's largest college bookstore. There were no APIs, no cloud infrastructure, no off-the-shelf e-commerce platforms. We built payment processing, warehouse communication systems, customer service tools, and data center infrastructure from scratch. When the CEO needed someone to lead marketing, he came to me because I understood everything that sat underneath it. We built peer-to-peer networks for college students, a book buyback system, and we seeded what became Amazon's third-party marketplace and eBay's Half.com with our 2.6-million-title catalog. Those weren't strategic partnerships with polished contract terms — they were brute-force technical integrations that nobody had done before. After eCampus, I joined Video Professor, then Colorado's largest direct-marketing company. I had to beg them to hire me. I could see from the outside that their marketing operation and their technology were two separate worlds, and I knew what would happen if someone connected them. I took their internet sales from eleven million to sixty-six million in thirteen months. The harder problem there wasn't getting ranked — we hit the top four positions for most of our major keywords quickly — it was that the company's free-trial billing model had generated complaint sites that sat just below us in the results. We solved it by bringing our affiliate network in, teaching them how to rank for our target keywords, and systematically displaced the negative listings with content that we could influence. That was my first deliberate, systematic exercise in managing what appears when someone searches for a brand. I went on to co-found Convertis with other industry leaders, taking that business from zero to an eighteen-million-dollar run rate in one year, and later built Ad Leverage, my own marketing agency, along with National Gift, which helped thousands of small businesses with marketing and product infrastructure for their websites. Then I stopped. I'd helped launch and sell more than a dozen companies, and I wanted to actually live. I spent years traveling from Nome, Alaska to the southern tip of South America — more than two hundred cities — looking for a place where the water came clean out of the mountain, the beef was grass-fed in fields where the grass reached the animals' shoulders, and the vegetables carried no pesticide residue. I found it in Colombia's coffee triangle, where I eventually opened an outsourcing operation with a hundred and fifty employees across six countries. I still own property there. I plan to spend most of my life there. It is, without exaggeration, one of the best decisions I've ever made. What brought me back was watching a technology shift accelerate toward small businesses that have no framework to respond to it. When Google first gained traction, there were no gurus who actually knew how it worked. The only method that produced real results was to take the businesses that were ranking and reverse-engineer what they had. That's what my whole career had trained me to do. I did it then, and I'm doing it now. AI assistants are replacing a meaningful share of how consumers find and choose local businesses. The businesses that get recommended share measurable characteristics. We pulled in more than 35,000 of them across more than 100 business types, identified approximately 150 factors that matter, and weighted those factors by what the AI systems themselves report as priorities — covering roughly 85 percent of all local business queries across the major platforms. We built Viizable — spelled V-I-I-Z-A-B-L-E — specifically for SEO professionals, AEO practitioners, and marketing agencies who need a workbench, not just a score. The tool reverse-engineers a client's local competitors so you can see, head to head, exactly what needs to change. This is not a long game. The businesses that adapt now will take positions that are very hard to displace later. The ones that wait for the industry to reach consensus on methodology will lose ground they may not recover. I've watched this movie before. I know how it ends for the people who move first.
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Title: Who Built Viizable — and Why It Exists
Excerpt: J. Brent Tuttle has spent 30 years reverse-engineering how businesses get found — from Yahoo's early days to the AI assistants reshaping local search right now. Here's the story behind the AI Ranking Factors framework and the tool built to act on it.
Tags: AI ranking factors,local SEO,AEO,Viizable,J. Brent Tuttle,AI recommendations,local business,GEO,search history
Image: A weathered but sharp-eyed entrepreneur sitting at a worn wooden table in a sun-drenched Colombian coffee-region farmhouse, laptop open, a steaming cup of fresh-brewed coffee beside him, shelves of business books and framed technical diagrams visible on the adobe wall behind him, warm morning light streaming through an open window — the feeling of hard-earned expertise meeting a new frontier

Who Built Viizable — and Why It Exists

Every tool worth using was built by someone who got burned by not having it. That's the short version of this story.

The longer version starts in Houston, Texas, in the early 1980s — and it explains exactly why I believe local businesses have somewhere between 12 and 36 months to get positioned in front of AI assistants before the window closes on a lot of them for good.

A Career Built on Reverse Engineering

I started in business at 21 working in insurance — sold my own agency before I was 23, and was written up as the fastest-growing agency in Houston at the time. What I learned early wasn't insurance. It was process. How to look at something that works, strip it down to its parts, and rebuild it better.

That skill took me into banking systems, then to a federal agency that was liquidating the assets of roughly 900 failed banks. Within two years I'd gone from managing systems at a single bank to carrying joint responsibility for 150 banks at a time. From there I moved into Washington D.C. and spent more than a decade as a business process engineering consultant — the kind of work where large organizations paid serious money to have someone map exactly what they did, cut what didn't need to exist, and redesign everything else. Typical result: 60% reduction in staffing costs, 50% reduction in systems cost, development timelines that shrank from years to months.

Pattern recognition under pressure. That's what the work was.

The eCampus Years — and What They Taught Me About Search

In the late 1990s a group of investors — including Dave Thomas of Wendy's and a former Kentucky governor — raised over $100 million to build the world's largest college bookstore online. I joined as Chief Technology Officer. We built everything from scratch: data centers, payment processing, warehouse communication, customer service systems, a social platform for college students to connect and trade books. There were no APIs, no plug-and-play infrastructure. Every piece was engineered by hand.

When the CEO needed someone to drive marketing, he turned to me because I understood both sides of the equation. We built outbound outreach systems, seeded what became Amazon's marketplace with our 2.6 million book catalog, and helped launch eBay's Half.com. Hockey-stick growth followed — until it didn't. The company eventually filed for bankruptcy after the incoming Harvard-pedigreed marketing executive redirected the budget toward Rolling Stone ads and cinema spots.

The buyers kept me on. I pulled out the original marketing plan, started executing it with a fraction of the original budget, and took the company from $4 million to $21 million in revenue over 21 months.

Here is what made that possible: we knew how to rank. This was the era of Yahoo, Lycos, and AltaVista — before Google had established dominance. There was no course to take, no authority to consult. The only method we had was to take the top-ranked businesses and reverse engineer them. It's the same approach I'd used on business processes for fifteen years. It translated perfectly.

The Problem No One Talks About Honestly

Later, as the primary internet marketing executive at Colorado's largest direct marketing company, I took sales from $11 million to $66 million in 13 months. I co-founded a performance marketing company called Convertis that hit an $18 million run rate in its first year. I ran my own agency, Ad Leverage, and worked with thousands of small businesses through a company called National Gift.

After all of that, I semi-retired. I opened an outsourcing operation in Peru that grew to 150 employees across six Latin American countries. I spent years traveling — Nome, Alaska to the southern tip of South America — looking for a place where the water was clean enough to drink from the ground, the beef was genuinely grass-fed, and the pace of life didn't grind people down. I found it in Colombia's coffee region, and I've lived there most of the time since. I'm a father and grandfather, and I'll tell you honestly: the coffee here, sitting a few miles from where it was grown, is worth the trip alone.

But I kept watching what was happening to the small businesses I'd worked with over the years. And what I saw concerned me enough to come back.

Why the Next Two Years Are the Window

AI assistants — ChatGPT, Gemini, Perplexity, and the others that now handle roughly 85% of local business queries — are not Google. They don't return ten blue links and let the user decide. They return a short list of businesses they trust, drawn from a very specific set of signals. Most local business owners don't know what those signals are. Most marketing agencies are still debating them.

I wasn't willing to debate. I wanted data.

My team and I pulled in over 35,000 local businesses that AI assistants had already recommended as best-in-area across more than 100 business types. We ran every one of them through our analysis and identified approximately 150 measurable factors that these recommended businesses had in common — factors that one or more of the major AI systems consistently used to validate trust, relevance, and authority.

A few things we confirmed quickly:

  • The factors are not identical across industries. A plumber needs verifiable licensing tied to a state database. A restaurant doesn't — but the restaurant has other signals that matter just as much.
  • The AI assistants themselves, when asked directly, will weight these factors and tell you which ones they consider most important. We collected that weighting across every major platform.
  • Most local businesses scored poorly — not because they're bad businesses, but because no one ever told them these factors existed.

That research became the AI Ranking Factors framework. And the framework needed a workbench — a tool that didn't just show a business where it stood, but let an SEO or AEO professional actually dig in and fix what needed fixing, with competitive context built in.

That tool is Viizable.

Built for the People Doing the Work

Viizable is not built for national retailers. It's built for the local plumber, the independent restaurant, the family dentist, the bakery that's been on the same corner for twenty years — and for the agencies and SEO professionals who serve them.

Pull up any local business. See exactly how it scores against the AI Ranking Factors. Then pull up the competitors that are already getting recommended ahead of it and compare them side by side. The gap between where a business is and where it needs to be becomes concrete and actionable — not a theory, not a debate topic.

I've published the framework openly because I'd rather see thousands of small businesses helped than protect a methodology. These businesses are running out of time to adapt, and the marketing industry is still arguing about whether AI recommendations are real yet.

They're real. The race has started. The businesses that move now — with clear data and a workbench to act on it — are the ones that will still have a pipeline of new customers five years from now.

That's why I built this. That's why I came back.

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Blog — aibusinessscore.com error 0 words
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Generation failed: Could not parse blog JSON — click Regenerate.
Social 4/4
X / Twitter generated 169 words
Tags: AIRankingFactors, LocalSEO, AEO
I got too good at my job once. The state insurance board shut down my employer because I recruited agencies too fast. That was my first lesson: systems work — sometimes better than anyone expects. --- I've reverse-engineered businesses my whole career. Insurance. Banking. eCampus.com ($4M → $21M in 21 months). Video Professor ($11M → $66M in 13 months). The method never changed: find what the top performers do, model it, outwork the gap. --- When Google launched, there were no gurus. We figured out rankings by reverse engineering whoever was winning. AI recommendations today are exactly where Google was then — wide open, no playbook, first movers win. --- So I pulled 35,000 local businesses that AI actually recommends. We found ~150 measurable factors those businesses share. That index became Viizable — built for the agencies and SEOs trying to get their clients into AI results before the window closes. --- I'm publishing the research because helping small businesses survive the AI shift matters more than hoarding the data. The race is on. #AIRankingFactors #LocalSEO #AEO
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Open X - @brenttuttle ↗
Facebook generated 127 words
Tags: AIRankingFactors,LocalBusiness,Viizable
People ask why I built Viizable. Honest answer: I've helped close to a thousand small businesses over my career, and I could see what was coming before most people were talking about it. AI assistants are now stepping between local businesses and their next customer. If a plumber, dentist, or bakery isn't showing up in those recommendations, they're invisible — and most of them have no idea it's happening. I spent months reverse-engineering over 30,000 businesses that AI actually recommends. Not guessing. Measuring. The tool we built came directly from that research. Small businesses built this country. They deserve a fighting chance in this new landscape. If you run a local business or work with them — are you paying attention to how AI is finding (or missing) you yet?
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Open Facebook AI Business Score ↗
LinkedIn generated 182 words
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Tags: AIRankingFactors,LocalBusiness,AISearch,GEO,DigitalMarketing
I spent 15 years reverse-engineering how large enterprises worked — then spent another decade doing the same thing to Google, Yahoo, and every search engine that followed. That pattern recognition is what led me to build Viizable. When I watched AI assistants quietly replace the search bar as the way people find local businesses, I recognized the moment immediately. Same disruption. Same urgency. Same window before it closes. So I did what I've always done: reverse-engineered the winners. We pulled in over 30,000 local businesses that AI was already recommending. We identified roughly 150 measurable factors across more than 100 business types. We weighted those factors against the AI engines that handle about 85% of local business queries. The result is the AI Ranking Factors framework — and Viizable, the workbench built specifically so marketers and business owners can actually act on it. This isn't a scoring report you read and file away. It's a tool that shows you exactly where your business stands, who's ahead of you, and what to fix first. Small businesses don't need another audit. They need a clear path forward — before the window closes.
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Open LinkedIn — Brent Tuttle ↗
Reddit (no promo) generated 514 words
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Tags: SEO,AEO,GEO,local SEO,AI search,generative search,LLM recommendations,AI assistants,local business marketing,search marketing,ChatGPT recommendations,Perplexity,AI visibility,digital marketing,small business
Title: I spent 10 months reverse-engineering 35,000 locally recommended businesses to figure out why AI assistants pick them — here's what I found Background so you know where this is coming from: I've been doing search marketing since before Google was the answer. Back when Yahoo, Lycos, and AltaVista were the battleground, I was the guy reverse-engineering the top-ranked pages to figure out what the algorithm actually rewarded. No courses existed. No gurus. You just pulled apart what was winning and built a model. That same approach is what I applied here — except instead of search rankings, the question was: why does an AI assistant recommend THIS plumber, THIS dentist, THIS restaurant when someone asks for the best one nearby? Here's what the research actually showed: **The volume of factors is bigger than most people realize.** We identified roughly 150 measurable signals across the businesses that consistently showed up in AI recommendations. Not all of them matter for every business type — a restaurant has a completely different relevant factor set than a contractor — but the breadth surprised even me. **The factors aren't mysterious. The gap is in execution.** Things like: whether your business license is verifiable and linked to a state database (huge for contractors, irrelevant for restaurants), whether your hours are consistent across every surface AI might read, whether the language on your site matches the way people actually describe the problem they're trying to solve, whether third-party review platforms corroborate what your own site claims about you. None of this is magic. It's alignment. AI synthesizes sources. If your sources contradict each other or leave gaps, the model loses confidence in you as an answer. **Most local businesses scored poorly — not because they're bad businesses, but because nobody told them these signals exist.** The average score across the businesses we analyzed was genuinely low. These weren't neglected businesses. Many had been doing SEO for years. But the criteria AI uses to build trust in a local recommendation is different from what got you ranked on page one in 2019. **The competitive intelligence angle is underused.** The most actionable thing any marketer can do right now is pull the top AI-recommended businesses in a client's category and geography, map their signals, and do a direct comparison. Where your client has gaps that competitors have filled — that's your work order. It's the same reverse-engineering logic that worked in 1999 and it works now. **My honest take on where the industry is stuck:** There are a lot of smart people having very sophisticated conversations about whether backlinks still matter for AI, what "GEO" means vs "AEO" vs "SEO", whether citations are dead, etc. Those are real questions. But while we're debating the finer points, local businesses are losing recommendation share right now. An 80% correct strategy executed today beats a perfect strategy delivered in Q3. The pattern I keep seeing: businesses that are winning AI recommendations aren't doing anything exotic. They've just closed more of the basic gaps than their competitors have. Happy to go deep on any specific factor category if that's useful. What are you seeing in your own testing?
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Open Reddit - choose community ↗
Long Video 1/1
YouTube — Long Script generated 994 words
Title: Who Built Viizable and Why: The Man Behind the AI Ranking Factors Framework
Description: Before there were SEO gurus, before Google was even the default, Brent Tuttle was reverse-engineering search rankings from scratch — and winning. In this video, Brent shares the career that built the AI Ranking Factors framework: from running Houston's fastest-growing insurance agency at 23, to serving as CTO of a $100M e-commerce startup, to taking a Colorado company from $11M to $66M in 13 months. And why, after years living in South America, he came back to build Viizable — a tool designed to keep local businesses from being left behind by AI. If your customers are starting to find businesses through ChatGPT, Gemini, or Perplexity instead of Google, this video is for you.
Tags: AI ranking factors, local business AI, AI recommendations local business, Viizable, J Brent Tuttle, AEO agency tool, AI search optimization, GEO local business, local SEO vs AI, AI business visibility, answer engine optimization, local business marketing 2025, AI local search, how AI recommends businesses, ChatGPT local business, Perplexity local business, AI SEO tool, small business AI strategy
[COLD OPEN — avatar on screen, direct eye contact, calm but urgent tone] Right now, an AI assistant is recommending a local business to someone in your market. And there's a very good chance it isn't yours. That's not a scare tactic. It's what the data shows — across more than 35,000 businesses we analyzed, in over 100 different business categories. My name is J. Brent Tuttle, and I want to tell you how I got here, and why I built Viizable to solve this problem. [B-ROLL: slow aerial of Houston skyline, then cut to vintage-style montage of early business imagery — insurance offices, handshakes, filing cabinets] --- **SECTION 1 — EARLY CAREER: BUILT TO FIND WHAT WORKS** I started in business working with my dad in insurance. By 23, I'd started my own agency in Houston and was written up as the fastest-growing in the city. I didn't have a playbook. I had a knack for spotting how processes worked — and where they broke down. That same skill took me to a VP of Business Development role at a regional insurance company near Dallas. I built a recruiting system so effective that the State Board of Insurance walked in and told my employer to either raise capital immediately — or they'd shut the company down. They shut it down. Because I was too good at growing it. [B-ROLL: motion graphic of organizational charts, data flows, system architecture diagrams] From there, I moved into banking technology — eventually managing systems across 150 financial institutions for a federal agency liquidating the assets of nearly 900 failed banks. Then into the Washington D.C. consulting world, where my employers invested hundreds of thousands of dollars training me as a business process engineering consultant. We could design and generate a system in two months that would've taken a traditional development team two to three years. Clients typically cut staffing costs by 60% and system development costs in half. The pattern across all of it: take something complex, reverse engineer it, rebuild it smarter. --- **SECTION 2 — THE ECOMMERCE YEARS: LEARNING TO RANK BEFORE RANKING HAD A NAME** [B-ROLL: retro 2000s-era internet aesthetics — early web browsers, spinning loading icons, dot-com energy] In the late 1990s, I joined eCampus.com as Chief Technology Officer. We raised just over $100 million to build the world's largest college textbook store. We built the data centers from scratch, wrote the code, architected the payment systems, the warehouse integrations, the customer service tools — everything. There were no templates. No APIs. No playbook. We seeded eBay's Half.com with our catalog. We're believed to be one of the first third-party sellers on what eventually became Amazon's marketplace. Hockey-stick growth — until leadership pivoted to brand advertising over direct response and burned through the capital. When the company was acquired for a fraction of its value, the new owners came to me. I pulled out the original marketing plan. We implemented it. In 21 months, revenue went from $4 million to over $21 million. [B-ROLL: upward trending graph animation, clean and minimal] That growth came from search. And at the time, there were no courses. No gurus who actually knew what was happening inside the algorithm. The only method that worked was to take the top-ranked sites and reverse engineer them. Same skill. Different arena. --- **SECTION 3 — THE PATTERN THAT LED TO AI RANKING FACTORS** [B-ROLL: split-screen — one side Google search results, other side a ChatGPT or AI assistant interface] I went on to take Colorado's largest direct marketing company from $11 million to $66 million in 13 months. I co-founded Convertis — zero to an $18 million run rate in one year. I ran my own agency, ad Leverage, and helped thousands of small businesses with digital marketing. Then I stepped back. I spent years traveling — over 200 cities from Alaska to the tip of South America — looking for somewhere to actually live well. I found it in Colombia's coffee triangle. Clean water, grass-fed beef, food grown without the chemical load that follows everything in the U.S. I built an outsourcing company in Peru with 150 employees. I invested in real estate. I had every reason to stay put. [B-ROLL: aerial footage of Colombian mountain landscape, coffee farms, green valleys] But I kept thinking about the small business owners I'd worked with over 30 years. Restaurants. Plumbers. Dentists. Florists. And I could see what was coming — an intermediary stepping directly between those businesses and the customers who used to find them through Google search and word of mouth. That intermediary is AI. --- **SECTION 4 — WHY VIIZABLE EXISTS** [B-ROLL: clean UI animation of Viizable dashboard — competitor comparison, factor checklist, scoring interface] So I came back. And my team and I spent ten months analyzing over 35,000 local businesses that AI systems were already recommending. We identified approximately 150 measurable factors that those top-recommended businesses had in common — factors that one or more of the major AI platforms actively use when deciding who to recommend. We built that into an index. And then we built Viizable — a workbench specifically for SEO professionals, AEO practitioners, and local marketing agencies who need to know not just where a client stands, but exactly what to fix, and how their client's factors stack up against the competitors already ahead of them. This isn't a scoring report you print and file. It's a working tool. [B-ROLL: avatar returns to center frame, confident, measured] --- **OUTRO** [Direct to camera, unhurried] The conversation in the industry right now — about whether backlinks matter to AI, whether citations count, whether on-site SEO still applies — that conversation is natural. It's also happening at exactly the wrong speed. When Google first arrived, the businesses that waited for a consensus strategy lost ground they never recovered. The ones who started moving — even imperfectly — won. The AI Ranking Factors framework gives you a place to start. Viizable gives you the tools to act. If you work with local businesses, or you are one, subscribe. We're publishing what we found — because the businesses that need this can't afford to wait. [END CARD: Viizable logo, website URL, subscribe prompt]
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Video-gen prompt
Produce a 16:9 YouTube video featuring a professional AI-generated male presenter, mid-50s in appearance, confident and authoritative but approachable — business casual attire, no tie, calm steady delivery. The presenter speaks directly to camera throughout, with natural head movement and occasional hand gestures to emphasize key points. Background: fluid AI-generated motion background that shifts organically across the video — opening in deep navy and charcoal tones suggesting depth and technology, transitioning to warmer amber and green tones during the South America/Colombia segment, returning to clean blue-grey with subtle data-visualization particle effects during the Viizable product section. The background should feel alive but never distracting — always keeping the presenter as the visual anchor. B-roll sequences are intercut at the moments marked in the script: — Houston skyline aerial and vintage business imagery (soft sepia color grade) — Animated organizational charts and data flow diagrams (clean, modern, white-on-dark) — Retro dot-com era aesthetic montage (early browser interfaces, pixelated web elements, nostalgic warmth) — Upward trending revenue graph, minimalist animated style — Split-screen: Google search interface left / AI assistant chat interface right (contemporary, clean) — Colombian mountain and coffee farm aerial footage (lush green, natural light, serene) — Viizable dashboard UI animation showing competitor comparison and factor checklist (clean SaaS UI, light mode) Lighting on presenter: soft key light from screen-left, subtle fill from right, no harsh shadows. Color grading throughout: desaturated slightly, slightly cool, professional. Lower-third text animations in clean sans-serif should appear for key claims (company names, revenue figures, timeframes). Pacing: measured and deliberate — not rushed. Total runtime: 5 to 6 minutes. Tone: authoritative, trustworthy, urgent without being alarmist.
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Open YouTube Studio ↗
Shorts 4/4
YouTube Short generated 135 words
Title: Who Built Viizable — And Why a 30-Year Career Led to This One Tool for Local Businesses
Description: J. Brent Tuttle didn't start as an SEO. He started by building systems that made businesses work — from running Houston's fastest-growing insurance agency at 22, to serving as CTO of a $100M e-commerce startup, to cracking Google's early algorithm before anyone was teaching it. Now he's reversed-engineered over 35,000 local businesses to find the exact factors AI assistants use when recommending a business to a customer. That research became Viizable. This is the short version of why. Learn more about the AI Ranking Factors framework and how Viizable helps local businesses get recommended by AI at viizable.com
Tags: Viizable, AI Ranking Factors, J Brent Tuttle, local business AI, AI recommendations for local business, AEO, answer engine optimization, GEO, generative engine optimization, local SEO 2025, AI search ranking, ChatGPT local business, how AI recommends businesses, local business marketing, AI visibility tool, SEO for local business, small business AI strategy
[Open on presenter, direct eye contact, tight frame] Thirty years ago I reverse-engineered Google before anyone knew what that meant. [Cut to motion graphic — data points converging into a location pin] I've been CTO of a hundred-million-dollar startup. Took a company from four million to twenty-one million in under two years. Figured out search when there were no rules — just results. [Presenter back on screen, leaning slightly forward] Now AI is doing exactly what Google did in 1999 — quietly deciding which local businesses get recommended and which ones disappear. [Subtle data-stream visual behind presenter] So I spent ten months reverse-engineering thirty-five thousand businesses AI already trusts. That research became Viizable. [Hard cut to logo mark] Because the race started. And most local businesses don't even know they're in it. [Presenter — calm, direct close] Now you do.
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Video-gen prompt
Vertical 9:16 format, cinematic quality. AI-generated male presenter, mid-50s, authoritative yet approachable, business-casual — open collar, no tie. Lit with soft directional key light; slight studio shadow behind him for depth. He speaks directly to camera with calm confidence — no hand-waving, deliberate pauses, steady gaze. Background is a fluid AI-generated motion environment: deep navy and slate gradients with slow-moving abstract data streams — glowing threads of light, subtle map-pin icons, faint network nodes drifting. The motion is elegant, never distracting. Think Bloomberg terminal meets ambient generative art. At the line "That research became Viizable" — the background briefly brightens, a clean logo mark pulses once into frame then fades. Final frame holds presenter in a composed, confident close-up as the background dims to near black behind him. Mood throughout: serious, credible, quietly urgent. No music drop, no hype energy — this is the tone of someone who has already won several of these races and is about to explain the next one.
🎞 Video clips live in this topic's Grok Video plan — one reusable video for every short.
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Open YouTube Studio ↗
LinkedIn Short generated 124 words
Preview ↗
Title: Why I Built Viizable: The AI Ranking Wake-Up Call Every Local Business Needs to Hear
Description: J. Brent Tuttle didn't build Viizable because it was a good idea. He built it because he watched AI quietly step between local businesses and their next customer — and nobody was doing anything about it. With a career spanning the early days of Google, a $100M e-commerce startup, and taking a company from $11M to $66M in 13 months, Brent has spent decades reverse-engineering what actually drives business growth. Now he's doing it for the AI era. This is why.
Tags: AI ranking factors, local business marketing, AEO, generative engine optimization, AI recommendations, Viizable, J Brent Tuttle, local SEO, AI search, small business growth, GEO marketing, AI visibility, ChatGPT local search, AI business score
[Open on avatar, direct eye contact, no intro music — straight to the point] AI has already picked your competitors over you. Not maybe. Not soon. Right now. [Cut: bold text on screen — "AI Ranking Factors"] I spent 30 years figuring out how businesses get found — through Yahoo, through Google, through every shift in between. I reverse-engineered over 35,000 local businesses that AI actually recommends. We found 150 measurable factors. We built a tool around them. [Cut: Viizable logo appears — clean, minimal] It's called Viizable. And it exists for one reason: Because the businesses I've spent my career helping don't have four years to wait this out. [Hold on avatar, steady, no smile — serious close] The window is open. Right now. Are you in the ranking — or invisible?
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Video-gen prompt
Vertical 9:16 format. AI-generated professional male avatar presenter, mid-40s to late-50s appearance, calm and authoritative presence, dressed in a clean dark business-casual shirt, speaking directly into camera with confident, unhurried delivery — no gestures, no theatrics, just credibility. Background is a fluid AI-generated motion field: slow-moving deep navy and slate blue abstract gradients with subtle data-point particles drifting upward like digital signals, evoking intelligence and movement without distraction. Lighting on the avatar is soft front-lit studio quality. At the moment "AI Ranking Factors" is spoken, a clean white bold text overlay appears centered on screen for 1.5 seconds then fades. At the Viizable mention, the Viizable wordmark appears in the lower third, white on transparent, fading in smoothly. Pacing is deliberate — each sentence lands with a half-beat pause. Tone is urgent but controlled: this is a warning delivered by someone who has seen this pattern before. Closing shot holds on avatar in silence for 1 full second before fade to black.
🎞 Video clips live in this topic's Grok Video plan — one reusable video for every short.
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Open LinkedIn — Brent Tuttle ↗
X Short generated 129 words
Title: The Man Who Reverse-Engineered Google Before Anyone Knew It Existed — Now Doing the Same for AI
Description: J. Brent Tuttle built one of Houston's fastest-growing insurance agencies at 22, helped take eCampus from $4M to $21M in 21 months, and grew a direct marketing company from $11M to $66M in 13 months — by reverse-engineering how search engines ranked businesses before anyone else knew the rules. Now he's doing it again. AI assistants are replacing Google as how people find local businesses, and Brent spent 10 months reverse-engineering 35,000 top-ranked local businesses to find the ~150 factors AI uses to make recommendations. That research became the AI Ranking Factors framework — and Viizable, the workbench built to help agencies and local businesses act on it. The race has already started.
Tags: AI ranking factors, local business AI, Viizable, J Brent Tuttle, AI search optimization, AEO, generative engine optimization, local SEO 2025, AI recommendations, small business marketing, ChatGPT local search, AI visibility, GEO marketing, local business visibility, AI business score
[Open on avatar — direct eye contact, confident stillness] The first time Google started ranking businesses, there were no gurus. No courses. No playbook. [Cut: text pulse — "1990s. No rules. No roadmap."] The only move was to take whoever ranked first — and reverse-engineer them. That's exactly what I did then. [Pause — slight lean forward] And that's exactly what I did with AI. I pulled 35,000 local businesses that AI actually recommends — and mapped every factor they had in common. [Cut: text pulse — "~150 factors. 100+ business types. Real data."] That research became the AI Ranking Factors framework — and the tool we built around it is called Viizable. [Avatar — steady, measured close] AI is already deciding which local businesses get found. The question is whether yours is one of them. [End card: Viizable wordmark]
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Video-gen prompt
Vertical 9:16 aspect ratio. AI-generated presenter avatar: a composed, credible man in his 50s, business-casual — open-collar dark shirt, no jacket. Confident posture, direct gaze into camera, measured and unhurried delivery. Slight forward lean at the key pause. Background: fluid AI-generated motion — deep navy and dark slate base with slow-moving abstract data-light particles and soft geometric lines suggesting a network or index map; no hard edges, no stock-photo feel. Color temperature cool-to-warm shift mid-clip to signal the pivot from "then" to "now." Text overlays appear as clean white sans-serif kinetic type, pulsing in for 1.5 seconds then fading — not flashy, authoritative. Overall mood: intelligent, grounded, urgent without panic. No music bed during speech; subtle low ambient texture underneath. End card: plain dark background, "Viizable" wordmark centered in white, URL beneath it.
🎞 Video clips live in this topic's Grok Video plan — one reusable video for every short.
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Open X - @brenttuttle ↗
Facebook Short generated 128 words
Title: Who Built Viizable — and Why Every Local Business Should Care
Description: J. Brent Tuttle didn't stumble into AI rankings research. He spent decades reverse-engineering what works — from Yahoo's early days to Google's rise — and now he's applied that same discipline to the AI assistants reshaping how customers find local businesses. This is who built Viizable, why it exists, and what it means for your business.
Tags: AI rankings, local business marketing, AI recommendations, Viizable, J Brent Tuttle, AEO, AI ranking factors, local SEO, ChatGPT recommendations, AI search, small business visibility, generative AI marketing, AI business score, local business AI
[Cut to presenter, direct eye contact, confident energy] I've reverse-engineered businesses my entire career — insurance agencies, dot-com startups, direct marketing companies. [Beat — slight pause] When Google showed up, there were no gurus. So I did what I always do: I studied what was already winning and figured out why. [Visual pulse on screen — data flowing] AI assistants are doing the same thing to local search that Google did in 2001. [Presenter leans slightly forward] So I spent ten months, analyzed over thirty thousand businesses AI actually recommended — and mapped exactly what they had in common. [Strong finish — steady gaze] That became Viizable. And those factors? That's what separates the businesses AI recommends… from the ones it ignores. [Pause — subtle nod] The race already started. Let's get you in it.
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Video-gen prompt
Vertical 9:16 format. AI-generated male presenter, late 50s, confident and credible bearing, business-casual attire in deep navy — no tie. He speaks directly into camera with measured authority, occasional slight forward lean for emphasis. Lighting is clean and modern: soft key light from the left, subtle rim light separating him from the background. Background is a fluid, dark AI-generated motion environment — think deep indigo and slate gradients with slow-moving abstract data streams, faint circuit-like geometries drifting in and out of focus, never distracting. When the line "thirty thousand businesses" is spoken, a brief visual pulse of soft glowing nodes and connection lines blooms behind him and fades. Text lower-thirds appear at two moments: "30,000+ Businesses Analyzed" and "Viizable — AI Ranking Factors" — clean sans-serif white typography, no drop shadow. Overall mood: serious, credible, forward-looking. No stock-footage feel. Cinematic but grounded.
🎞 Video clips live in this topic's Grok Video plan — one reusable video for every short.
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Open Facebook AI Business Score ↗
Adjust & regenerate
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