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The Best SEO Podcast: Defining the Future of Search with LLM Visibility™
How To Turn Google Reviews Into Profit With George Swetlitz
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This is the Unknown Secrets of Internet Marketing, your insider guide to the strategies top marketers use to crush the competition. Ready to unlock your business full potential?
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Let's get started. Howdy. Welcome back to another fun filled episode of the Unknown Secrets of Internet Marketing or the Best SEO Podcast. We're focused on LLM visibility. I'm really going to try to get that switched up after 12 years. We also, we'll have a new intro coming in. We are on YouTube at best SEO podcast, so we would ask you to go check that out. Leave a review a, like a comment, let us know. It's, it's kind of quiet over there, but thank you so much. Wherever you're listening, I have a exciting guest for you today. As I've been going down the rabbit hole of AI and LLM visibility, it is expanding into every area of digital marketing and beyond. And one of the things that I'm doing selfishly is I brought somebody on. I'm working on a strategy for a major law firm to spin up, you know, 100 something locations across the United States. And generating reviews for each one of those locations has been quite difficult. And so I have an expert that also I just finished my Harvard, you know, business executive course, but I have someone here that has actually MBA from Harvard also I've been taking a lot of AI courses from Wharton and I have somebody here that has actually graduated from Ben. So, so, so I've done the certifications, but I have somebody that, that, that's done the actual work and is focused on AI. I've taken a bunch of certifications from IBM. He was a managing director at IBM, so there's some associations but he's the real deal. So I wanted to bring on George Sweatlets with Right response. AI. That's a AI review management course. So George, welcome to the show.
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A
Yeah, no, that was very interesting and unique introduction. So thank you Matt. Happy to be here.
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B
Yeah, no, I, I, I'm, I'm excited to talk to you because there's, there's a lot of kind of points that cross over. I would first say I'm in a Oxford program right now for, for AI, which, what is it called Sarcastic algebra and gradient descent. And all this stuff with AI is really having to dust off what I learned in school. So it's really challenging me. Enjoyed the Harvard program. Got a better understanding of kind of the Harvard associations to the different companies out there and how papers are structured and who writes the different books for the Harvard Business Review. So it was very insightful. I can also Tell you that out of all the courses I've taken, the Wharton classes for AI were just my favorite. I don't know. And I did have a buddy that went to Wharton and I was like man, I should have gone to Wharton, I love all this stuff. So I thought that that was interesting. And you know what you're doing right now makes a ton of sense. There was actually a number of tools that people are launching even like you know like a LinkedIn kind of assessing how people write on LinkedIn in their profile to understand maybe what disc category they go in of how you should speak to them. And like sentiment analysis we were talking in the pre interview is huge. And also if there's kind of like if it's not on your roadmap right now and you're not currently doing it, I know you will. Where you have agentic agents that are like figuring out oh hey we need this kind of review, go get this kind of review. You upload your list like there's just so much you can do with workflows today. But I would love to hear you kind of set the table for why you decided to launch Right Response AI and kind of what is the core problem that it's solving.
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A
Yeah, no, great. So you know prior to doing Right Response I was the CEO of a 220 location roll up of hearing aid clinics. And so you know when you're running a lot of locations you can do paid search and you can do paid social to bring in customers. But ideally what you want people to do is just come to you, you just want them to call you because that's the most cost effective route. And so we spent a lot of time trying to figure out how do we get more people to just call us. And that led us to obviously the Google business profile and your presence there. And so as we dug into that it was a really dynamic space. You know you have, you have leakage coming from the profile in the sense because you don't get, you don't get enough people leaving you reviews. Anyone who doesn't leave you a review that could is leakage and it's reducing the power of your profile on Google. Because a review to Google is a proxy for popularity. The more more reviews you get, the more Google says man this is a really popular place. So review leakage is an element of that. Then you get a review and sometimes they're negative. And so what can you learn from that to do better so that your average rating is higher. And then the reality is that regardless of Whether you're advertising or not advertising, people read reviews. They read reviews today more than they visit websites, which is fascinating. So when they come to your review, you know, we talk about terms like bottom of the funnel. They are the most bottom of the funnel people around not reading your review for fun. They're reading your review because they're making a decision. And so if they read your reviews and go somewhere else, that's leakage. So we noticed in my old company that locations that we had that had great reputations had higher response rates from paid social, paid search, advertising. Why? We didn't quite get it then, but the reason is because of the reputation. They come to your profile, they read your reviews, they're great reviews and, and so they buy from you. So, so after we exited from this company and ChatGPT came out 2022, I sat back and said, you know, I think, I think I could really help us kind of deal with this problem at scale. And so I got a team together and we built Right Response AI not as a review management system, but, but as a revenue enhancement system to cut out the leakage. So back to you. I love that.
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B
And there's a couple points that I need to be taking better notes as you're talking, so I might miss some of these. But the first is I love the idea of leakage, right. Like you should try to be mapping one to one. That's kind of what digital is like your digital profile versus your public, who you are, you're trying to map those. And that's what Google's trying to do is create kind of a twin, a digital twin across the Internet. And so every patient should leave you a review. And typically the bad reviews people leave are. There's a higher likelihood that the data says to leave a bad review and then good reviews. So you got to kind of pull out the good reviews from the people. But I like that idea of mapping it. Like it gives you a pulse on how you're doing. Also reviews, besides the name of the profile in G and B is the, the number one kind of decision factor. And why is that going back to what you're saying? Well, it's people trying to decide what they're going to do. I'm even seeing this in the data right now. I'm doing a couple different studies and people are going to chat GBT or, or whatever. They're using the perplexity, you know, search engine. A lot of people are starting to use that as well. I think that that's why chat GPT just came out with theirs. But essentially people are asking AI what they think of your business. Okay. And so people are doing that bot of the funnel. Let me try to make a decision. And then you said something else is the ads that you're running are converting better than if you have good reviews. Well why is that? Like we can't track attribution very well. I mean Google gets, gets a lot of last click attribution. Like Google's working great, but in reality it's all the other things that people are doing in that customer journey to make that decision. But the most influential thing you can do is leave a review. And then the last thing that I would say, and I forget exactly what this term is called, but people are busy today and they don't have time to do all this deep research which I think a lot of people are starting to lean on know the large language models to do that deep research forum which makes a lot of sense. But people are using reviews as a proxy and I forget the exact term but the data was like something like that. You have to see at least 7 reviews to 12 reviews to it be a snapshot and enough that someone's going to take action on it or believe it like if you only have one or two reviews. And so people are just taking reviews as a proxy for is this product good or not. And then you even see the summaries that are happening on Amazon or wherever where they're summarizing the sentiment and the reviews and they're giving people even short hand form of even looking at the reviews themselves. And so that's also what the AIs are doing, like is this a good company or not? So I, I think reviews are absolutely critical. Finding a way to, to pull out those reviews to get those reviews and to get people to relieve those reviews is a full time job. And it used to be on the different locations. And also, you know, I've talked to a lot of the different review tools which they try to wrap reviews into other tools and it kind of bloats the product. And we've danced around on a couple of different services from a review standpoint and, and in this even project for this law firm that I'm working on, it's the number one issue. Like if we're going to spin these up like you can't just have a blank review, like that's not going to convert anybody. That's not going to be helpful. That might even hurt us if we have like zero reviews across, you know, all these different businesses. So I Think reviews are absolutely critical. I would love to hear more about the logic or the thought process of how you injected AI into your review service.
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A
Yeah, no, absolutely. So let's, let's break it down. Let's go step by step and talk about each element. So let's start with the review request. So what, what's the, what's the big. I won't ask you the question. I'll just, you know, put. The biggest problem with review requests is getting people to actually write the review. So we talk about the request to review conversion rate, right? Because, you know, you know, every. Especially if you're a law firm, like, we work with a number of personal injury law firms and you don't have that many customers. It's not like McDonald's. You, you know, you. Every customer you have is important, right. In terms of getting a review.
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Yeah.
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So one of the things that we found that's really useful to drive that conversion is personalization. So if you can make that review request more personalized, more emotional, then that person has a higher likelihood of writing a review. Right. So, hey, so, you know, how do you, how do you react to that?
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Well, I, I know that digital marketing agencies, unless you're like high volume, high churn, we, we have a lot of great clients that have never left, never left us a review. Right. And, and I put it on the account managers to like, hey, you need to get a review. Like, you've done something that should, like, that's review worthy this month. Like, what is one thing that you've done? They're a client that you can show a success factor for and ask for a review. And not only that, there's, there's kind of starting to be a proliferation of all these different review sites, and people are checking out different stuff. And so reviews in general are just becoming a big issue. And I think you just have to have a process. But typically it's like an email, right. And it's not like I'm even thinking, oh my gosh, like, what if you could like, ask a form of, like, you ask a question. They put a word in, they put a word in, they put a word in and then it generates the review for them. Or like a couple of different options and then they can select one. Because you got to hold people's hands sometimes because they don't want to use the cognitive load to write the review. Like, they might want to give you a review, but it's, it's too much friction. That's, that's what I've found Like that?
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Yeah, yeah, no, that's great. That's actually in our development path. But what we're doing now is, is providing our clients with the ability to pull in from their CRM any information that would be useful to making that request more emotional. So think about a law firm, the type of case it was a motorcycle accident, Was it a negotiated settlement or a trial, Kind of a win at a trial. What's the name of the paralegal that helped the lawyer? You can pull all that information in and AI can write this really nice request that incorporates all those elements.
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B
Yeah, I can see that. That, that's fantastic. And it is unstructured data. Because I think the, the, the sticking point previously that I've found with salespeople or CRMs is if you don't have somebody constantly focused on keeping that, the data hygiene clean. You know, if you were just grabbing fields, a lot of times they wouldn't be filled out or whatever. But LMS can grab it in unstructured data to pull it all together.
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Yeah, that's right. So it doesn't have to be perfect. Yeah, but the, but the LLM will do a good job of understanding the context. So that's the first point. The second point is in some, in some industries, maybe not law firms, but for example, real estate agents, you can include a photo.
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Yeah.
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Include the photo of the couple in front of the house that you took. Anyway, so include that into the request. The third kind of very different point is. And you talked about that before a little bit. Sometimes people don't know what to write about. So if you can put at the bottom of the request, hey, if you're looking for some inspiration, here are some things that people reading reviews like to know about. And then you can put at the bottom and it can switch up. You can have 10 questions, they rotate. What type of case did we handle for you? What did you, what was the thing that you like the most about Joe the attorney? What, what part of town do you live in? Because it's really great for Google if, if the review says, oh, I'm in south Houston or I'm over here, wherever you are. So it knows that you are in that area.
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B
And I, and I can see that for different industries or even different areas, you can, you can build like templates that they can load in that gives them suggestions. Right. Or even a gentic in the background knowing some of this stuff with the background information on the company. No, I think this is a great use case. I was actually talking to this VP of Innovation on this other project I was working on and there was like a big article that came out now, now, I saw the article of like, you know, now, now layoffs are happening and AIs take like laying off 10,000 people, something. I think I saw that yesterday. But previous to that there was an article out there going, the AI hype's over. And there, you know, whatever. And I felt like this VP of Innovation read that same article as me because I felt like he was kind of speaking the talking points and he was like, yeah, there's really no use cases for AI. And I was just like, everywhere I look, if I put on my AI glasses, there are use cases. And so I think we need to get into the language of speaking AI. And we went through like four or five points almost immediately. And this is a publicly traded company. And he's like, yeah, that's a good idea, that's a good idea, that's a good idea. And I would say that this is firmly in that category of, you know, all the friction. I just call it friction of putting a review together. I can help you solve that, can help you reach out, can help you get it. And, and reviews are probably for, for digital marketing, I would say. Yeah. And we need to highlight this more. I wish I had a data point on it, but it's probably one of the most, if not the most important thing that you should be focused on generating for your business is making sure the leakage that every single review that's possible to get, you should get it like you should. Like, I have customers that have been customers for a long time that honestly, like, I have it on my list, like, we need to get a review from them, but we haven't done it yet. Or we, you know, there's not a proper way to ask for it or like it just hasn't been a focus. And sometimes clients end in their contract, like, we finished whatever project, we built that website for them. And I was like, hey, get a review? Yeah, we're going to get a review. My team, like, we're going to get a review and then they don't get a review. And so I can think of, I would say probably more than half of our clients and past clients haven't left a review and the number is actually probably even higher than that. So I. And we don't have that many clients. Like, we need more reviews, right? Like, you know, we're not doing the high volume, like bring them in and you got, you know, 10 to 40 patients a day that you get Reviews off of like, we get like, you know, one to two clients new a month, you know, and I mean so yeah, so I, I think they're critical.
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A
Yeah, they're critical, everyone's critical. And, and so what we're planning in the future on the development path is, is that, you know, if we follow up the second and the third time, maybe the third time what we do is we say, look, we understand you're busy, just type a couple of words, like type some phrases. Don't worry about perfect grammar, perfect language, just tell us simple things and we'll draft a review that you can edit.
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Yeah.
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And then they can go and they can take that. And so you know, if you give them things, if you give them, if you give them an emotional reason, if you, if you suggest things to talk about and then later even help them draft it, the conversion of request to review is going to go up and that's the first leakage point.
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B
So. Yeah, so, so I love the emotional trigger standpoint and the sentiment and then pulling in all the relevant data from the CRM, hooking into that. I feel like when I talk to most businesses, even medium sized businesses, I work with a lot of medium sized businesses, they are not effective with their CRMs like, and the CRM system is like so critical for whether it be sales or client management, depending on how they're using it, what it's for. You need to bolt everything into that. That's your like hub and spoke. Right. And I haven't talked to, I don't think one review company and maybe they do it, but I don't, I haven't heard it like that's critical. Plug into that data, pull that data out there and help that in crafting the reviews. I love that.
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Yeah, yeah, no, the integration part is complicated. And you know, I make the point to the, to companies that like you mentioned that are, you know, low to medium volume, that this is so important it's worth someone spending. Even if you do it in a Google sheet, it's not that hard to do. And if you can double or triple the number of reviews you're getting by by spending an extra 30 minutes a month putting these important variables into a Google sheet, it's worth it.
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Yeah, yeah.
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And so you know, some of our larger clients, they spend the time to add fields in their CRMs that can then integrate into our systems. But that's tougher for kind of small and medium.
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So, so I would love to geek out for a second and go into kind of what's going on, under the hood of where AI plugs in to this process, like in, in the workflow. I, I would love it if you would share whatever you're willing to share about that.
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A
Yeah, I mean, I think, you know, the, the, the, the more interesting side of the actual workings is on the response side, the response to the review. So let's, let's, let's fast forward to that and we can talk about kind of what's going on under the covers. So when a review comes in, we, we bring the review in and then we have an agentic flow. So we look at a lot of things. Is this a legit review? Right. So a lot of, a lot of elements to the term legit. But is this a, does this seem like it's a review of this business first step? Because a lot of times people will just type stupid stuff and it's not really a review.
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I see that on Facebook right now. Like Facebook reviews are like not even helpful anymore. It's just a bunch of spam.
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A
Right? Yeah. Right. And so that comes up sometimes in Google or other platforms. And so if that happens, we filter it out, we look for the name. Like we have an agent that looks at the name and, and decides what the name, what name should be used in the response. Right. Because sometimes, you know, it's a company name, sometimes it's just a list. You know, it's, it's initials, it might be all upper caps. You know, it looks at it and says, I'm, I'm confident we should use this name. Or I don't think we should use the name at all. Let's just skip the name.
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B
Okay.
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A
We look to see whether the review was updated. Is this an updated review? And if so, do we have a record of the earlier review? Yeah, because in Google you don't get that. You just get the new review. So if we've been working with a client, we actually know what the update is and we can then look at, well, what's the change? Should we be happy? Should we be sad? Right. So we do this whole series of things and then the part that's really the most interesting, I think, and what makes our responses kind of, I think the best there are is that we, we create a fact library for the, for the client. So before, when the client onboards, we go back and reread the last thousand reviews and we look at the kinds of things that people talk about.
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B
I like.
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A
Then we look at the responses and we say, is there anything in the responses to those reviews that has a marketing element to it. And most of the time the answer to that is no because most people use templates or they use generic AI. And so the responses don't add anything to the review. Right, the responses don't add, they just parrot back the review.
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B
Wow. So, yeah, so you're, you're helping tweak the reviews to increase the conversion rate where the reviews. Actually, yeah, I mean, we, we try to mention those things to the clients like these are the keywords or mention the service or whatever. But to help tweak the review where, where it speaks to different emotional elements or even marketing elements of that. And then I like that idea, which I actually haven't even done that. That's a brand new idea. So thank you. Is to go look at all the reviews. Like we, we build brand guides for clients or we look at all the information and we're building, you know, questions and you know, what people would ask. But understanding the, the, the, the review architecture of, of what they have I think is absolutely critical. I like that.
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A
Yeah. So I mean, this point that we're talking about is, is, is why we have the customers we have, because we do a better job of responding to reviews than anybody. For example, I was just doing a demo the other day and I used a natural food store. I just scraped their website, put it into our system. We developed a whole set of facts. If somebody writes in and says, I just love the selection of natural milk products, we had a fact that said if somebody talks about the natural milk products, because that's something that a lot of people talk about, talk about the fact that we carry goat milk and raw cheeses and all of these products that the store carries. And we pulled that off of the website. And so a generic AI responder would just say, oh, we're glad you loved our selection of natural milks. Our responder says, we're glad you loved our product selection of milk. But next time you come in, make sure you look for our goat chi, our natural goat cheese, our, you know, all of these products that they have.
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B
So George, you're, you're, you're putting that together, you're scraping that on the sales side of it, right? And so then you're saying, hey, here's what's information about you that you didn't even know. Right. And then you're saying, also our review tool will help enhance that so more clients will talk about it and we'll increase your conversion rates by doing it. So we have the, we have the answer to this. And through this software if you sign up, that's a very strong sales pitch.
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A
Yeah, I know. It's really cool. And so. And why is that important? It's important for a lot of reasons. Right. It's important because for that customer, they're going to get a notification of your review. They're going to read it, and they're going to look and say, wow, like, they're actually sharing something with me that I didn't know. Okay. Now a prospective customer is reading these reviews and they're noticing. They actually, like, in their brain, they're noticing that these responses are good. They're actually helpful. I'm learning something from reading these responses. And so if I'm trying to decide where I'm going to go, and I look at one company and it says, thanks for review. Thanks for review. Thanks. And this one says, hey, thanks, that's great. But we have this and we have that. You think these guys care? They're more engaged in their business. They care about the reviews and how they engage with that. And to your point earlier, LLMs are reading these things.
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B
Yeah. Oh, yeah.
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Reading the reviews, and they're reading the responses. If you go in to Perplexity and you ask about. And you ask about the reviews and then you say, well, what about the responses? Yeah, it'll say, well, there's really nothing useful in the response. It'll actually say that, yeah, they don't really engage. It's not really useful.
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B
Yeah.
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And so the whole world's changing. And so what we're trying to do or what we're doing is we're. We're trying to reduce the leakage at that point of engagement.
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B
Yeah.
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A
We want someone to come and start and look at those reviews and then decide to buy. That's the goal.
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B
So. So, George, like, one of the things that's starting to happen on this podcast, because I. I mean, I. We started using AI a lot. Okay. And then I was like, I can't speak about AI because I don't know it enough yet. Right. So then I, like, went on this flurry of let me learn everything I can about it. I'm constantly, you know, doing certifications and going to conferences and learning. Learning everything wasn't the most insightful things and a lot of why. So anybody that's listening, if you have an interesting AI First Company, reach out to me because I. I interviewed a. A driver's ed company. Okay? AI First Driver's ed Company. That was a. AI First Legit AI First Company. They're going to be the largest company in North America in the next three years based on their projections. And why is this? Right? And so I'm kind of removing from, from this to kind of talk to everybody on the side and say it's something like 71 or 72% of businesses still operate like they're in the industrial age. They're just now moving into the digital, the digital transformation age. And now we're moving into the AI age. And businesses that are using agentic flows, which are like employees, and they're building it in not just basic automation, but decision making and helping you enhance what you're doing. That's why, what is it in the stock market? You got these companies that are just taking off because they are, they're moving into AI first companies. And companies need to be either building themselves to become AI first, or they need to be using tools and companies that are AI first to get that kind of leverage. And I just want to say, George, some of the interviews that I've had, when I'm talking to business owners from AI first companies, like, when you wear the glasses of AI, it just like makes so much sense. And so, so this is, this is really exciting to see, see what you're doing. And I already know that you're, you're doing great things. But everybody, this was off of a inbound pitch, so I didn't know. Jane. George. He's not part of my network, but I love everything you're doing, George. So I just wanted to kind of insert that. What, what else do when, you know, when you talk about this or you're talking to customers that, that you think would be useful to add to this conversation or are there any case studies that, that you think are really impactful that you would like to share?
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A
Yeah, so. So, you know, when we started talking about the response stuff, we, you know, that was a little bit of a digression from the agentic flow.
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B
Yeah.
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A
And so let me go back to that for a minute. And so when that review comes in, we look at that review, we look at all those facts that the business has, and then we determine which ones are relevant. And then when we write the response, we incorporate all that. So it's exactly what you're saying. It's, you know, what we, One of the things we've learned, and this is kind of like an AI pro tip, is the narrower we make that AI.
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B
Yes.
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A
The better it is. Right. So to kind of make that real. So if somebody has 30 facts and we have a single prompt that says, evaluate this review for all 30 facts. It always gets the first one right and always gets the last one wrong. It's just the quality goes down the more you ask it to do in a single go.
- [32:35]
B
So, so to, to make this tangible for people that are not deep in AI, right now I'm building some magentic flows for content creation, for example. And previously our workflow and our prompting was larger chunks of information where it's processing that. And then I got on like an enterprise style tool and you know, they have their, their workbooks of how they're building it. And I was like, oh my gosh, like almost every data point has, it has its own agent. So it's, it's, you know, ones and zeros, asking the question. It's very narrow. And I was like, okay, I would do a prompt for all five of those outputs and then the enterprise agentic flow was like, no, we have five different agents, one for each one of those. And all they're evaluating and what they're focused on is making that, that one field or that, that, that one a data point or whatever it is, like a meta description or a title. Like it's all focused on that. And, and you're right, the longer you go, sometimes they'll get confused, they'll mix up stuff and, and so yeah, breaking it down, making it very narrow. I think that's a fantastic pro tip.
- [33:48]
A
Right? Yeah, yeah. So, you know, so if it's a medical business, for example, we have a separate agent that looks for phi. Right. You know, and, and all Phi.
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B
Sorry, what's phi?
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A
Personal health information.
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B
Okay, okay, right.
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A
So you know, you don't want to include anything in there that would be a violation of. Oh yeah, you know, hipaa, stuff like that. So we identify those things in a separate agent and it just sits on the side and then later on it goes in and makes sure that none of that stuff makes it into the response.
- [34:19]
B
George, what's that called? What is that called? What? Like, what is the like, like scientific term for narrowing the flow? Like, what would you call that?
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A
You know, I don't really know.
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B
Okay. I was just curious.
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A
I don't know if there's a technical term.
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B
Uhhuh.
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A
Yeah, don't know.
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B
Okay.
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A
Anyways, yeah, so, so I would say, you know, I, I think what, what everyone needs to think about is, you know, regardless of what business you're in, what are the micro steps that you can take to leverage AI?
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B
Yeah, right.
- [34:57]
A
And, and we do kind of one piece of what companies have. We just, we're just focused on this one little element, but there's lots of elements. And my advice to, you know, business managers, leaders, owners is don't start with the big things. Start with the small things that have a higher likelihood of being able to run and run effectively and, you know, and, and, and start that way and build your way forward as you get more expertise with those systems.
- [35:33]
B
Awesome. Give us a case study before we go.
- [35:36]
A
Yeah, yeah, absolutely. So we have a client that, this is a great example because they have like around 100 locations with regional managers. And so they were looking for a tool that was, that was going to do a better job helping their regional managers respond to reviews, because that's how they've done it. And of course, they all responded to varying degrees of, you know, sophistication and all of that. There was a lot of variability across the regions. And so they came to us and we, we generated these facts and we gave them a trial and we got done and we put it into practice. Right. We, they signed up and I realized when I was looking at the account that they hadn't invited the regional managers into this, into their. So I called up the guy I was working with and I said, you know, I thought you were going to include the regional managers. And he said, well, you've made it so simple, right? And the responses are so good that we just decided that I'm just going to do it. I'm just. Because there are so few negative reviews. And for the good reviews, we generate them and send them out. You know, we generate reply automatically. So it's just the entire process is automated. And for the negative ones, I need to go reach out to the customer anyway. So I'm just doing it all myself. So when you think about that, the quality went up, the amount of resources went down pretty dramatically, right? Those, those regional managers can now focus on improving the business, running the business and not worry about this stuff. And this guy who's kind of does marketing related stuff is just so happy because he can now do that job in a fraction of the time at a much higher level of quality. So that was a very recent, you know, proof point to us that we're on the right track.
- [37:42]
B
I love it. All right, and you've already shared with some great tips, but one of the tips that we're asking, and we're trying to make some shorts and, you know, get into the YouTube game, even though we're a podcast, the definition of podcast has changed. Everything's changing. What are some unknown secrets or underlying underutilized secrets of Internet Marketing, they're probably things related to reviews that people haven't thought about or should consider.
- [38:10]
A
So I think there are a couple of things that people, you know, that people don't think about. And I said it a little bit before, but no one is closer to the bottom of the funnel than someone reading your reviews. That to me is just something that everyone needs to think about all the time. Where are my prospective customers? They are reading your reviews. So I would say that's one secret. And another unknown secret is more people read your reviews than read your website.
- [38:51]
B
I didn't know that.
- [38:51]
A
And so people spend a tremendous amount of time on their websites, but the secret is you got to bring the website to the review because that's where people are engaging. You can sit there and try to ignore the fact that everyone's reading your reviews, or you can bring your website to the review. And I would say that's the second secret.
- [39:18]
B
I love it. I love it. So, George, how do people follow you, hear your thoughts, get in touch with you, find out more about Right response AI.
- [39:28]
A
So we have well wrote. And if you go to right response AI.com Best SEO. Right? That's your podcast. Best SEO. If you go to writeresponsei.com Best SEO. We have in there two things. One is the ability to set up a call with me directly and the other is a coupon code that you can use to get 3000 free credits if you upgrade to a paid account with us. Just a couple of things for all of your listeners.
- [40:06]
B
Awesome. Well, thank you everyone that's listening. Go check it out. I think George made a very strong case on how you need to focus on reviews. And thanks so much for coming on the Soar show, George and everyone, if you need help with these strategies, if you need help crafting, you have a problem, you're looking for an outcome, reach out to us at EWR Digital. They're the sponsor for our show that keep the podcast going. I've recently launched Matthew bertram.com also from an entity standpoint, we're talking about AI George. You'll appreciate this. I published books. I've been doing this for a long time. I used to go by Matt Bertram. My name is actually Matthew bertram. I have matthewbertrom.com. the LLMs and the search engines thought I was two different people. And so I'm trying to unify and merge those two profiles on mine. So check it out, guys. Let me know until the next time. My name is Matt Bertram. This is the Best SEO podcast. Bye bye for.