Podcast appearance
How to Turn Customer Reviews into Revenue with George Swetlitz
Why review readers are already deciding, and every public response is part of the conversion moment.
Why review readers are already deciding, and every public response is part of the conversion moment.
Alec Cheung and Barb VanSomeren frame reviews as a marketing and conversion channel, then test the idea against trust, revenue, multi-location competition, and the early warning signals hidden in customer feedback.
“Well, I got to tell you, this has opened my eyes to reputation management and what you can do now. I was kind of thinking that we're at the mercy of Google. But really, we do have it within our control to change this dynamic a bit, right?”
Terminology note: this conversation uses the earlier word “facts.” RightResponse now calls the verified business knowledge used in a response “messages.” The transcript preserves the language used in the original recording.
Review management sits closer to revenue than many organizations assume. People reading reviews are often comparing a short list of businesses, so the public response becomes part of the evidence they use to decide. The conversation also shows how patterns across locations can reveal deeper operational problems before they become larger reputation problems.
Reviews influence which businesses prospective customers consider, while substantive responses can add useful reasons to choose the business at the moment of decision.
They typically restate the review or use interchangeable language, so they do little to inform the next customer or reinforce the business's differentiators.
Each location operates in a different competitive market and can have different review cadence, sentiment, service issues, and conversion performance.
Yes. Trends in review topics and sentiment can act as early warning signals for service, staffing, product, or location-level problems.
The original episode is available from The Marketing Share and through the listening link on this page.
Explore the Review Management Platform
This transcript was generated from the original episode audio and lightly formatted for readability. Minor speaker or wording errors may remain.
[00:00:00] One of the things that was a real challenge for us at this company Alpaca was reputation management because essentially, as you know, you know, we had 220 locations, each exists in its own local competitive environment, and we're trying to win in every market. And so reputation, how you're seen in each market is critical to your success. Hi, I'm Barb. And I'm Alec, and this is the marketing share where we cover what leaders need to know to run marketing. The marketing share is your go-to for the latest thinking from experts all across the marketing field. Let's get started. Hey folks, welcome back to the marketing share podcast. Glad to have you here with us. I'm Alec Cheung and I'm here with my co-host, Barb. How's it going, Barb today? Hello, Alec. How's it going? I'm good. You're a little bit under the weather I know. I was too recently, so I think we still sound good enough.
[00:01:04] I think so. Hopefully I'm not coughing the whole time. Yeah, but it's also season also. Maybe it's analogies. Hopefully it's just that. But let's tell some listeners about our guests today. I think topic is kind of interesting. This is one that I personally don't know a whole lot about. So I think I'm very curious to talk to our guests today. Who do we at? Yeah, so today is George Sweatletz and George actually is the co-founder of a company called Right Response AI. And he's actually been a former CEO in the B2C world of practices. Okay, care practices and I know that space as well. And so he actually found this issue. You know, when you're getting reviews for your practice, it's really like a really big deal.
[00:01:50] Right. It's like if you have a good review, if you don't, I've managed like multiple locations where, you know, if you have a bad review, can really hurt your reputation. So the notion of reputation management is really at the forefront of many of these high trust products and practices, right? Yep, yep. And look, reviews are really critical, especially in consumer driven business B2C. It's also important on the B2B side. Yeah. You know, reviews are also your reputation is also critical, but it's a different game when you're B2C. Like reviews form a key part of it. And I think that at least from what I've understand for what George has got to talk about. I think it's really interesting because he's looking at reviews not just as a like a way to respond to customers, but as a way to actually carry your marketing message forward.
[00:02:41] And I think that's going to be interesting to cover that angle. Yeah. I mean, the fact that we're moving more toward conversations, you know, as authenticity, even in an AI world is really important to this discussion. So let's take a look. Talk to George. Yeah, let's go talk to George. Welcome George to the marketing share podcast. How are you? Great. Great. Good to be here. Thanks for joining us. Hey, tell us a little bit about your amazing career journey and how you came to start right response AI. Sure. So I've had a long career. I started in consulting. So I was at McKinsey for a number of years.
[00:03:27] And then went from McKinsey into an operating role. It's fairly corporation. And so I ended up right after the fall of the Berlin Wall was kind of helping build a business in central Europe. And then I came back to the States and got back involved in consulting and did that for a number of years engaged with the number of private equity firms. And then in 2019, I was invited to be on the board of a audiology roll up called Alpaca audiology, which you happen to be familiar with. And so I started there and got more involved operationally. And then when COVID happened was asked to step in a CEO. And so was there at CEO until until the sale and a few years later. Congratulations. It's not often that you find somebody who's come from your particular area of the business world, right. You know, like the hearing industry is so specialized little group. Right. Right. Absolutely. Yeah. And so, you know, to kind of bridge that one of the things that was a real challenge for us at this company Alpaca was reputation management. Because essentially, as you know, you know, we had 220 locations, each exists in its own local competitive environment.
[00:04:52] And we're trying to win in every market. And so reputation, how you were seen in each market is critical to your success. And so we became real studies, you know, study years of reputation management. And all the tools and resources that were available, which were not that great in my opinion. And so after the sale, chat GPT came out. And when chat GPT came out, I thought, wow, this could really have an impact on all the different elements of the review ecosystem and how they all fit together. And so I talked to some members of my team and said, hey, you want to take a go at this. You know, you want to take a run at it and see whether we can build something to influence and change the space. And so that was the the genesis of right response. Yeah. That's really great. Let me ask a question to help our listeners. Reputation management could mean a broad scope of things or it could be a more focused and a tighter scope of things. So how are you defining when we're talking here, reputation management, what's included in that? Right. That's a great question. So what the way I think about at least the element of reputation or reputation that we participated is kind of the review ecosystem. Yeah. Plus the competitive environment. So how do you fit? What are your goals? It's easy to think about reputation management on its own.
[00:06:28] But it's helpful to think about it in the context of the competitive environment that you're in because you can have two businesses that you think internally perform equally well. But they might in fact perform very differently because of the competitive environment that they're both in. And so you have to your goal for one of them, even though they're the same, they operate the same. Your goal for one of them may be much, maybe by just by the way the notion of reality might be much harder to be successful in one market than another. I face the same thing, right, with 1,500 locations right across the country. And reputation management was huge, right, because there's a million touch points, especially in a in a B2C business like that, right? I mean, think of any franchise, a multi site business has the same challenges. And each touch point is a chance to either build or detract from that brand experience or that experience. How folks are looking at it. So how do you think AI is accelerating this ecosystem of reviews that we're always chasing? Right. Well, it's impacting or can impact and is impacting in various ways all the elements of that ecosystem.
[00:07:52] I break it down into four components. There's review gathering, getting more reviews. There's a review understanding, right, sentiment analysis, voice of the customer. What are these reviews telling us so that we can do better. There's responding to the reviews because that's essential to trust to building trust with the perspective customer. And then there's understanding what's happening in the local environment. And AI is impacting every one of those in at different pace of different speed and in different ways, but it's it's impacting all of us. So let's drill down a little bit more on that like like all four of those equally. Is it a progression? Like how would you coach another marketer who is faced with this challenge, kind of similar to what you've gone through, right? And having now been doing what you're doing and also now trying to apply AI, what's your advice to marketing leaders right now who have to are facing this challenge? Right. So I mean, we could I think maybe it would be helpful to walk through each of those stuff and talk about what are the dynamics and how does AI impact you so maybe maybe that's a way to do it. So if we start on review gathering clearly review gathering is essential because the number of reviews you get is a proxy for popular.
[00:09:17] You know, if you get a lot of reviews, you're popular. And if you don't get a lot of reviews, you're not popular. So you have to get a lot of reviews. Yeah. And the key, the key to getting more reviews is personalization, right? Because if you think about the options in review gathering, the less personal it is, the lower the conversion of the request of the review. So on one end is emails. Emails are if people don't check their emails every minute, right? So the conversion rate on an email might be one percent, two percent. Okay. Then you get to text messages. Now those are more personal because that that text is more immediate to the customer. Yeah. Fewer people have that phone number. And so it's more immediate. And the conversion rate on, on text messages is just higher.
[00:10:18] Okay. Six, seven percent, something like that. We also do QR codes. So we have features where people can issue QR codes to their employees. So think about home services. That kind of thing where somebody's in front of a customer. For us, QR codes, the conversion rate is 50, 60, 70 percent. Why? Because you're in front of the customer. You're right there. How much more personal can you get when you're right in front of them? And you say, hey, would you give me a review? Yeah. If you enjoy it. That's so personal that the conversion range high. So the question is, how do you take something like a text message or an email and make it more personal? And AI can help with that. So how can AI help? AI can help with it because it can rather than having a template, you can personalize the request. We know a lot of things about our customers. We know how long they've been a customer. We know which person they work with.
[00:11:20] We know what services they buy for. We know a lot of things. So it's one thing to do what we all do today. Which is thank you for visiting this business. Would you be kind enough to leave us a review versus saying something like Marcy was so pleased to see you on the fourth. We, you know, we value so much the fact that you've been a customer for six years. It would mean so much to Marcy and the rest of the team if you would leave a review. So now we personalize that review and we see that that can double or triple the conversion rate. So we take an email that might be a two percent. It jumps to six to seven percent. It takes text messages. Yeah. At six percent, it can go to 12 or 18 percent. Okay. So that's a way to use AI to drive to do more for your for your business. Yeah.
[00:12:17] Yeah. You know, I'm sitting here listening to you. And even on the B to B side, which Alec and I have worked on as well as the B to C side, you know, one or two percent email is quite high. Right. So and if you're asking in the B to B world, which is also important for high trust products and, you know, very involved product categories, I can't even imagine what's that's like to get an actual review from somebody. So I guess you're cracking a code in an area that it's tough, you know, paying the review, right? Right. Right. So that's the first step. You can't do anything until you actually have a review. Right. So you have to get them and AI, AI will increasingly be able to get you more reviews. That's one piece of it. The second piece then is the analysis of the reviews themselves, voice of the customer sentiment analysis. Clearly, AI is just leaps and bounds in terms of what you can learn, not only in terms of classification, but then in terms of analysis, analyzing the vast amounts of data. I spent a ton of time at right response, thinking about what are the best ways of analyzing, presenting, thinking about if you think about the old days, it was word clouds. Right. If it was a burger joint, like burger would be in the center of the word cloud, you know, who cares? Of course, burger is going to be in the center of the word cloud.
[00:13:46] So, so what we, what our approach has been to say, especially for our larger clients, they have KPIs, they know how they think about the business, they know what the values are and the ways that they want to measure things. And so we allow our larger clients to, to shape the categories and topics that we then evaluate the reviews again, so that it fits with their existing KPIs. It's going to be very meaningful to them. And then we use AI to help analyze trends and things like. Okay. So then that's the, I don't, I remember the first two. I forgot the last two. What are the third? The third is review response. Okay. All right. Right. And again, let's maybe think about that from an historical perspective. So review response started out where people would actually type responses. Right. And of course, that's very difficult to scale, especially in large organizations. Yeah. And so when, when I was doing this, it was mostly templates. You know, you would have template responses.
[00:14:53] And you would tick which template you were going to use. And you would try to develop as many templates as you could. But that was, it was very, you know, I mean, it didn't really contribute to the conversation anyway. It was just a response. And it had to be, and you had, you'd had to have people doing that, right? Obviously, before, yeah, it had to be someone doing that using pulling, finding the right template, crafting up some response. Right. Because, you know, especially with a negative review, you'd want to find the template that was relevant to that particular negative review. You'd have to choose that. Yeah. And, and, and, and, and execute on that. And by the way, is it your opinion or your stance that, like, all reviews should be responded to 100, probably especially negative ones, but even positive ones?
[00:15:42] 100%. And I'll tell you why in a minute. Okay. So the next step then was, you know, AI comes out. Yeah. And what everybody does now, every platform now, it's a generic AI response. And when you, so when you, and you, you know, this, you read them all the time, it's essentially just parroting back what's in the review. Right. So the review said, oh, you know, the burgers were great, but I didn't like the fries. And the response is, oh, we're glad you love the burgers. Oh, we're so sad you didn't like the fries. It was, it's that kind of, because it doesn't know anything other than what's in the review. So it's essentially just, in my view, templated responses and generic AI are essentially the same. They're a waste of space. They don't contribute to the conversation. They don't do anything. People seeing that they're a, they view a whole review system that's kind of up. It's a check the box kind of thing. We need reviews. We have to respond to reviews. I can check the box. It's operations that does this. And I did it. And so I'm done KPIs high. I responded to all the reviews. That's great.
[00:16:55] Right local in their 2026 survey, one of the questions that they asked had to do with how do you feel when you see a generic or templated response? And the statement, of course, I don't know exactly how they phrased it, whatever it was, but it was 50% of consumers would are unlikely to buy from someone who provides templated or generic response. That seems like a very high number. And I don't know how people act on that because they're all generic and templated. So I don't know what that all means. But what it does reflect is that when somebody gets asked a question about that, it's a negative feeling that they have. Yeah, which makes a lot of sense. And so the question is, well, okay, is there an opportunity there? And so to differentiate yourself. So if you're in a list of competitors and people are trying to decide which roofer they're going to hire and they're reading through reviews and responses. And you have responses that are very real and helpful. Is that going to be positively received? So that's the question.
[00:18:15] If the answer that is yes, then how do you do it? And so AI is the way that you do it. And so what we've done. So what we do is when we on board one of our clients, we read all of their historical reviews. All of their historical responses and their website. We read it all. We use the reviews to understand what people ask, what people talk about, what are the things that they talk about. And then we use the historical responses and the website to come up with messages, marketing messages. What do you say on your website about various things? How do you differentiate your business? And we create what we call a message database filled with these messages. And then what happens is when a review comes in, we compare that review to all of these messages. We determine which ones are relevant to the review. And we then incorporate those messages into the response.
[00:19:24] So let's say you have a restaurant and people love the steak. So a generic responder would say, oh, we're glad you love the steak. Our responder would say it's terrific that you enjoyed the steak. We work with a farm in Colorado that we've been working with for six years. That just is phenomenal. Whatever that kind of message telling, we would build that into the response automatically. To make that a helpful, useful, informative response that somebody reading that would look at that and say, wow, I want to go there and try that steak. That's the conversion opportunity. Because no one's closer to the bottom of the funnel than someone who's reading reviews. They're deciding.
[00:20:19] So however you got them to your Google business profile, you could be doing social, you could be doing Google, whatever ads, whatever report, whatever it is, they get there. And now they're trying to make a decision. And that decision is based on what people say. But what most people miss is that it can be creatively influenced by what you as the company say. And that can have a big impact or conversion. I think you have a term that you believe reviews are your conversation engine. It's conversion engine. It's the conversion engine.
[00:21:06] That is the central notion for us. If you can contribute to the building of trust through your responses, you're more likely to be the one that somebody picks. George, having been on the other side of a not so great review for whatever reason, you know, on some kind of businesses in the past, always it was, what do we do about this? What can we counter something? I mean, that was always the big question. But what do you do nowadays when AI is part of the conversation and they are actually steering people to your location? I guess it would be the same in that if you provide great responses like that, AI is going to pick up those responses and direct the conversation that way. Would that be accurate?
[00:21:56] Yeah, no, I 100%. So the AI answer engines are in bias to the review. They're biased to content. Right, they want content. So when you say interesting things in your responses, that's just as important. As a customer saying interesting things. So what we find with our clients is that if you go and of course Google ranks the reviews not on recency but on relevance. So one of the things we look at is how many of our responses does Google deem to be relevant?
[00:22:38] And so we'll see in the relevant for our customers reviews that don't necessarily say a lot but the response has a lot. And Google looks at that as relevant. It's kind of content relevant and we see that when we look at that list of relevant reviews. So you're saying that even a very short review, even if it's just a short very, it doesn't say much but it's positive. But if you respond well to that, it can still be a net plus for you. You can still capitalize on that opportunity. Yeah, so think about that. The restaurant example.
[00:23:21] When you start talking about your vendor and this relationship with the farm and grain fed cattle and all of this stuff that you're talking about, that's great content. Yeah. So, you know, the AIS engine is going to say, hey, this is, you know, we know this about this business now. And we can say that they have a vendor that's, you know, that says, it doesn't matter where the content comes from. It's just looking for content. Okay. So I'm tracking with you. And now I'm going to the next level, which is your customizing a response. But you're using AI doing that. So how are you sounding authentic and not like a generic AI response so that you come back with this interesting response that's going to give you a robust kind of relevancy. Yeah. It's an interesting, it's an interesting point because, you know, in our, our customers talk to us a lot about this.
[00:24:19] Especially our prospective customers when we're in conversations because in our world today, AI is often associated with inauthenticity. You go on to social media. You don't know what's true and what's not true. So there's this kind of feeling that AI means inauthentic. What I try to explain to people is AI means what you make it me. So if you, if you build this database with your messages, this is what you would say to a customer if they were in front of you. That's what our AI engine is incorporating into the response. Then that is authentic. Things are only inauthentic when they're inauthentic. But if you, but if you're the one crafting the database, if you're the one crafting the messages, it is authentic by definition.
[00:25:15] You've crafted it. You don't have to write it to be authentic. I use AI all the time to help you write. But that doesn't make my writing an authentic. It's my ideas. AI helps me write it in a smoother way, for example. I had a thought about a question here. You, you started in the beginning by saying one of the things that you wanted is you want to get more reviews. That's the number one thing, right? Just get more reviews. What if, though, you're in a situation where you're trying to get reviews or maybe you already get reviews, but a lot of your reviews are bad reviews. Can the process of responding to reviews in a more effective and personalized manner, like you're saying, can that even still turn a bad situation and maybe not turn it around? But can that still have a positive impact on what maybe is a bad situation? Because bad reviews probably mean that there is something underlying that's wrong, usually, right? So how, like how do you coach or or guide clients that maybe in that situation?
[00:26:23] Yeah, so it's really the nature of the review itself. So sometimes reviews get to some systemic problem. Yeah, right. The front desk at a doctor's office is just me. You know, you can't really see other than apologizing and saying we're going to work on this. There's communication. There are things that you can say, but you really have to go solve the problem. And that's where sentiment analysis voice of the customer really matters. Okay, yeah. But other times, in fact, we just had this with one of our, we have a done for you service and we just had this situation the other day where someone left a one star review because they came in and everything was out of stock. And so the guy called and we talked about it, but the answer was, you know, there was a convention in town and there was more demand and they thought, so you could actually answer that. You can say, you can tell the truth. You can say, this is what happened. This is not AI saying this right? AI doesn't know this, but as a person, you can say, hey, apologize. You know, we, there was a, there was a convention in town and just we got slammed and we were out. You were right. We were out when you came in.
[00:27:38] We apologize. It doesn't happen very often. But, you know, give us, you know, email us at this address and we'll make it right for you. And hopefully you'll enjoy the experience work. And that can be a net positive for you when somebody reads that back and say, wow, these people care and they're honest and they're, you know, they're trying to do things with nobody's perfect. So that unanswered is bad, but that answered can be in that positive. Yeah, that's a great answer. Okay. So, you know, I'm thinking about this. We keep talking about, you know, reputation or retention as the new acquisition in the world, right? So I see an example that you just mentioned about how you can change something that's operationally broken or something in your, in your organization. But can this be a force kind of multiplier for retention advantage or I mean, that's, that's a revenue generator right there.
[00:28:41] Well, right. And so when you think about one of my frustrations, Alpaca, was the inability to, to get out in front of problems. And when you have 200 or 50 locations or 1500 locations, there's always a location going wrong. Always. And it was always frustrating to me that we couldn't see that in advance. And really, that's what we try to do with our sentiment analysis. The sentiment analysis of reviews is an early warning messaging system. In most businesses, you know the kinds of things that people will say if you're beginning to have a problem. And so those are the things that you can train your version of the sentiment analysis to find and report.
[00:29:36] So we have a thing we call percent positive. And so if you have a, if you have a topic and let's say the topic, you know, for example, in an audiology clinic, one topic might be the quality of the fit. Right. The quality, you know, do people are they happy with the result? You know over time that certain people are going to write in and say positive things and you're going to get some negatives. And over time, you might know that a 95% positive ratio is a good ratio for fit. So you can track that. And so when you start to see a location where for a couple of months, that ratio turns to 85%. Well, there's a problem developing there that you can get in front of.
[00:30:32] And that's how you can use sentiment analysis as the early warning system for the key KPIs for a business. Okay. Now I'm going to flip over to what happens if you have a new practice, right? It's a brand new green field area. And you don't have a lot of reviews. How does that apply? And what can you do if you don't have a lot of the key learnings of that particular area that can populate, you know, your AI? I mean, what do you do to kind of ramp this up? Do you just provide lots of answers and lots of content for that new practice? Well, let me kind of break that into two pieces. So, and I'll tell a little bit of the story. So I remember we opened a green field location in Harrisburg, Pennsylvania. Everyone told me Harrisburg is the greatest town and we're going to make so much noise. It's perfect area. And we opened that location and we were just crushed, just got crushed.
[00:31:37] So I go in and I pull up Google Maps and I'm looking around and there's this amazing clinic group that six locations. We were like literally in the center of this six location, amazing group. We never should have gone there. It was the wrong location, wrong town, wrong location. If we wanted to be in Harrisburg, we should have bought somebody. We should not have tried to open a green field location. So that gets to competitive analysis. It's really trying to understand what's going on in the town, who's great, who's not great. And importantly, you're going to have to climb the map pack in that town. What is it going to take to do that?
[00:32:27] You go to Google and Google says there's 750 reviews and you sit and you don't let go. How are we ever going to get 750 reviews? We'll never catch up. But if you drill down, they might only be getting 15 reviews a month now. They might have been around for 20 years. Google doesn't care that they got a five star review 12 years ago. Right. Google cares about what's happening now. Longevity matters, all those things matter, but there's a big way that's placed on a recency. How many reviews are you getting now? What's the rating now? So you might actually see that they have a 4.5 rating on not so many reviews now.
[00:33:11] Well, now you actually have a target. You can say to your team, look, we need to be getting 15, 20 reviews a month. We need to be above 4.5. Now, if we're able to do that, we have a shot of climbing the rankings. Right. Of achieving that. Now, if there are 10 competitors who were all getting 15, you see what I'm saying? It all depends on the local environment. You have to understand what you up against before you start so that you can set goals and have targets in order to have a shot at obtaining them. You might go into a town where all the providers or all the competitors are crappy. Well, now your job's a lot easier, but it wouldn't be a good thing to know that before you start. So that's the idea of the competitor analysis. And then to your point, Barb, once you know that, then you can say to your team, okay, we have to get reviews.
[00:34:10] This one who is really, really isn't responding or they're responding with template reviews. So we can need to make sure that our response, they're responding with template of responses. So we have to make sure that we're on point. We have great responses so that we can beat them on numbers on rating and on quality. And I say all this thinking, man, if I'd only had this five years ago, we would have been much more effective as a company. We'd have two locations that were pretty similar, but when we would do, you know, paperclip or social, we would have much higher conversion at one clinic than another. And that always used to blow my mind like, why? But it was all about, you know, the competitive environment. If our reputation was a 4.2, but everybody else was at 4.5, we were just advertising for their benefit. Right? We were bringing them to the map back and then they would go to somebody else.
[00:35:19] In the other town, we were a 4.5 than everybody else with a 4.2. So we were on top and we were winning them all. And so, again, you really have to understand, you have to part of the model for, you know, for spend analysis. I think if I was building an analytics model today, I would be looking at competitor, you know, competitor review, quality, all of those indicators as part of my body. George, you at one time said that relevance of the review was more important for Google, but then you also pointed out that recency does matter too. Is it equally important or does one take, have a heavier waiting? So I don't know that Google, from Google's perspective, it's going to be ratings and recency. So the way that the phrase that I use for people, as I say, reviews are for ranking.
[00:36:29] Responses are for conversion. Okay, okay. The responses don't necessarily get you higher in the rankings. Recency and your actual average rating, recent actual rating, so the number of reviews. Okay. And your average rating near term is a huge weight on your, right, along with your website, a lot of other things. Yeah, yeah.
[00:36:52] Okay. The response quality is increasingly important for AI answer engines. Yeah. But it's absolutely important for the human. That's actually reading that review and the response, trying to decide what decision they're going to make. Google made a decision where are we going to put this person in this business. The human decides who am I going to call?
[00:37:17] And the quality of that response is really important to the human. That's a good way to remember it, assisting that like that. So what do you say? I could see some naysayers coming in and saying, you know what, George? At this point, you know, 60% of those searches now end without a click anywhere and much more in-depth look, right, at the reviews. How does, how do you respond to that? And how does it still make sense to have these responses that will be picked up by LLMs in some of those areas?
[00:37:50] I think it depends on search intent. What are you trying to learn? So I think, you know, the 60% really is a lot when people are trying to understand and learn, you know, those kinds of things. I think when people are actively trying to find a business, you know, the map still gets displayed. They're still looking at the Google business profile. You know, that's, that's a much more kind of tangible, you know, I'm, I'm in buying mode. I'm not going to necessarily buy based off of, you know, chat CPT's, right?
[00:38:25] Yeah. Chat CPT can't read Google's reviews and responses anyway, right? Google blocks that. So, you know, chat CPT's just is looking at TripAdvisor and you know, you know, they're looking at all these places that they can look because they can't read Google's. Really? That surprises me especially for Google's. Sorry, sorry, you said it can't read Google reviews. Yeah.
[00:38:49] Oh, yeah. What about just do a search after this? Like go search, like for a local restaurant and say, what can you tell me about this restaurant? And when you look at it and you say, and in particular, I'm interested in customer sentiment or what people are saying. Yeah. You won't see Google reviews showing up in that. Huh, really?
[00:39:07] What even even if you do that using, um, Gemini, Gemini, Google's Gemini, yeah, that's their secret, right? Yeah. So they they can look at that. Okay. Yeah. Yeah. Yeah.
[00:39:20] So it's behind kind of a little bit of a wall. Yeah. Yeah. Yeah. And I would assume that this is super appropriate for businesses that are high trust, high involvement, personal involvement. Would that be accurate? Is that your big customer base?
[00:39:34] I mean, we're B2C for the most part. Right. So, yeah. You know, when when people are trying to make a decision. Right. Right. Yeah.
[00:39:44] We're less so B2B because we're primarily, you know, our fundamental building block is Google reviews. Yeah. That being said, we have customers that are trust pilot. You know, they get all the reviews on trust pilot or consumer affairs. You know, most of our customers are location based businesses, but we do have a lot of customers that, you know, they're big national companies and they're B2C, but they're not Google B2C. They're trust pilot B2C, consumer affairs B2C, BBB, B2C.
[00:40:20] And that's just as important for them too. George, if you do this right and use some of your techniques, how quickly can you expect to start seeing some results? Starting with, like, just number one, getting more reviews to begin with. You know, like, what's the timeframe on these types of things? Yeah. It's a couple of months. Okay.
[00:40:44] It's a couple of months. You know, getting more reviews has always been something that people try to do. And you see that if you can get more reviews, if you can get people to... So we have a thing in our review requester that allows you to ask questions, so you can... You can seed. It doesn't really work for... For texts, because texts have to be short.
[00:41:11] But if you have an email, then you can ask people to write about certain things. You can say, hey, you know, here are some questions that you might want to think about, including in your response. And then you can get SEO keywords in the responses, which matters a lot. Especially if you're a business where, you know, you're trying to expand your geographic area and getting a town name or, you know, a region name in that... In that review itself tells Google, oh, yeah, they serve this area. Those are things that can happen very, very quickly. So we see a number of things happen quickly.
[00:41:51] One, you know, you can ramp up your reviews quickly. Two, it's amazing how quickly Google will populate the relevant results. Okay. The relevant reviews with these reviews that have your content in them. Okay. It's really fascinating how quickly that happens. Quickly like a matter of a few days or even a couple months.
[00:42:18] A couple months. Okay. So you've shown this a couple of months. Okay. So then that means, though, that you do have to try a tactic for a couple of months to give it a good enough time to see if it's right. Because you mentioned some things in the beginning too about trying different ways to engage and get more reviews, like personalizing them. Right. Yeah.
[00:42:40] All right. Well, I got to tell you, this has opened my eyes to reputation management and what you can do now. I was kind of thinking that we're at the mercy of, you know, at Google. But really, we do have it within our control to change this dynamic a bit, right? Especially if we... You know, this is kind of like the topic that Alec and I have gone through on AI, right? AI is about putting more of the sales conversation into your website or, you know, to become more relevant on these OLMs.
[00:43:08] It's really kind of the same dynamic that we're talking about, right? If you have a more robust conversation on the review side in picking it up or in responding, you're probably going to be more at advantage as well. Yeah. 100% agree. It's about bringing the website to the review system, right? You spend all this time developing all this great content for your website. Just pick it up and use it in your review responses.
[00:43:37] Yeah. Yeah. That's a great advice to wrap with. If our listeners want to work with you, tell us, tell them me on what's the name of your company and how can they get in touch with you? Sure. So it's right to response AI.com, right?
[00:43:51] Response AI.com. And you can go right to the site. You can book a call with me. It's the easiest thing in the world to do. We do strategy sessions and things like that for our customers. Okay. And is it right as in right wrong or is it right as in right or review?
[00:44:08] Right. It's a good question. It's right as in right and wrong. Okay. All right. The whole idea is that, you know, it's the right response. Correct response.
[00:44:19] Yes. How do you engage in the right way? Yes. But it's a clever double 100 because then you need to write the correct response when you, you know, respond. You're right. I like that of that. You're under pressure.
[00:44:34] Alex got ideas for you. Here we go. And I think you should develop that competitive advantage service line. Yeah. I think that would be a big idea, right? Yeah. All right, George.
[00:44:43] Thank you so much for being part of the marketing share. Yeah. Thanks for joining us today. Great to be here. Thank you for having me. Thank you for listening to the marketing share. We hope you'll join us again next time.
[00:44:54] And if you like what you heard, please also remember to follow or subscribe to our show.