[Emerging Tech] Turning Online Reviews Into Growth With George Swetlitz
- Quik! News Team
- 13 minutes ago
- 24 min read
George Swetlitz is the Co-Founder and CEO of RightResponse AI, a reputation management platform that helps location-based businesses win more customers by improving their visibility and credibility through strategic responses to online reviews. He previously served as CEO of Alpaca Audiology, a private equity-backed healthcare business that grew to over 200 locations nationwide. Earlier in his career, George worked at McKinsey & Company and held leadership roles at Sara Lee before advising CEOs and private equity firms on operational strategy and profitability improvement. He currently focuses on helping businesses turn customer feedback into actionable insights that drive growth and better customer experiences.
Here’s a glimpse of what you’ll learn:
[2:09] George Swetlitz discusses how RightResponse AI helps location-based businesses grow through reputation management
[3:16] Why weak reputations can hurt ad performance and send leads to competitors
[5:07] George’s definition of reputation through reviews and business responses
[7:20] Common reasons some locations develop worse reputations than others
[11:50] How RightResponse AI uses business differentiators in review responses
[14:24] Restaurant examples that turn review replies into marketing messages
[16:59] Auto-responding to positive reviews while routing negative ones to humans
[18:29] Balancing deterministic systems and probabilistic AI outputs
[21:29] Multistep QA checks to keep AI-generated responses accurate and on-brand
[27:42] George’s learning curve as a non-technical founder building an AI-first company
In this episode…
Online reviews can quietly undermine marketing spend, customer acquisition, and local search visibility, especially for businesses with multiple locations. When responses are generic or missing, strong operations may still lose prospects to competitors with better reputations. How can businesses turn reviews from a reactive chore into a real growth strategy?
George Swetlitz, an expert in AI-driven reputation management for location-based businesses, discusses practical ways to fix the problem. He emphasizes treating reviews as public marketing assets — encouraging positive feedback, responding in ways that highlight differentiators, learning from negative reviews, and using AI with guardrails to generate varied, accurate responses. George also highlights the value of combining response automation with human review for lower ratings, leveraging voice-of-customer analysis to spot patterns, and making review generation easier through text, email, and QR codes.
In this episode of The Customer Wins, Richard Walker interviews George Swetlitz, Co-Founder and CEO of RightResponse AI, about using AI and customer reviews to drive growth. George also discusses why reputation affects conversion rates, how to keep AI responses accurate without sounding robotic, and what he learned as a non-technical founder building an AI-first business.
Resources Mentioned in this episode
"[Emerging Tech] Compounding Institutional Knowledge for Growth With Ian Karnell" on The Customer Wins
"[Emerging Tech Series] Transforming Financial Advisors’ Workflows With AI Agents With Chirag Gandhi" on The Customer Wins
"[Emerging Tech] Eliminating Data Complexity for Growth With Mark Ovaska" on The Customer Wins
Quotable Moments:
“Sometimes what you write in the response doesn't have to even be relevant to the review.”
“If you're not asking for reviews, you're going to get more negative reviews as a percentage.”
“In many businesses, when you advertise, you might just be advertising for your competitors.”
“People are more motivated to write when they're angry than when they're happy.”
“More people read reviews than visit websites.”
Action Steps:
Treat online reviews as a marketing opportunity: Reviews are public conversations between customers and potential customers that help communicate your brand’s strengths and influence future buying decisions.
Respond to reviews in a personalized and authentic way: Generic responses can make a business seem indifferent or automated while tailored replies show customers you care and reinforce what makes your business stand out.
Encourage more customers to leave reviews: Many satisfied customers simply need to be asked, and actively requesting reviews helps balance feedback and ensure positive experiences are represented online.
Use customer feedback to improve operations: Reviews often reveal patterns about service quality, staff interactions, or product experiences that businesses can analyze to fix problems and strengthen customer satisfaction.
Combine AI automation with human oversight: AI can handle routine responses quickly and consistently while human review ensures sensitive or negative feedback receives thoughtful attention and protects the brand’s reputation.
Sponsor for this episode...
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Episode Transcript:
Intro: 00:02
Welcome to The Customer Wins podcast, where business leaders discuss their secrets and techniques for helping their customers succeed and, in turn, grow their business.
Richard Walker: 00:16
Hi, I'm Rich Walker, the host of The Customer Wins, where I talk to business leaders about how they help their customers win and how their focus on customer experience leads to growth. Today is a special episode of my series on new and emerging solutions, and today's guest is George Swetlitz, co-founder of RightResponse AI. Some of my past guests in this series have included Ian Karnell, a VastAdvisor, Chirag Gandhi of Mili, and Mark Ovaska of Precept. And today's episode is brought to you by Quik!, the leader in enterprise forms processing. When your business relies upon processing forms, don't waste your team's valuable time manually reviewing the forms.
Instead, get Quik!. Using Quik!, you'll be able to generate completed forms and get back clean, context-rich data that reduces manual reviews to only one out of a thousand submissions. Visit quickforms.com to get started. All right. Today's guest, George Swetlitz, is the co-founder of RightResponse AI, a reputation management platform designed to help location-based businesses drive customer growth.
Before launching RightResponse AI, George led Alpaca Audiology, scaling the retail healthcare company to over 220 locations nationwide. He began his career in consumer goods at Sara Lee Corporation, later advising businesses on earnings improvements and operations strategy. George, welcome to The Customer Wins.
George Swetlitz: 01:46
It's great to be here and speak with you today, Rich. Thank you.
Richard Walker: 01:49
Oh, I'm excited to have you here. So for those who haven't heard my podcast before, I love to talk to business leaders about what they're doing to help their customers win, how they built and deliver a great customer experience, and the challenges to growing their own company. So, George, I want to understand your business a little bit better. How does your company help people?
George Swetlitz: 02:09
Well, you mentioned during the intro the last thing that I did, which was being CEO of this 220 location business. And in that role, we struggled with reputation management and how to do that for our 220 locations. And so that's what RightResponse is all about. It's about helping companies, whether they're small single-location businesses or large multi 100 location businesses, get more customers organically through optimizing the reputation management ecosystem.
Richard Walker: 02:48
You know, you know, what's funny about what you're saying is I'm an entrepreneur. I have started over ten businesses since age 12. And before I started Quik!, I was struggling with what's the great idea? And my mentor said, just get involved in some kind of content expertise, and you'll discover the idea. So here's your current business, which is an outgrowth of the other business.
Like, what better way to find a problem and solve it, right? So why was this problem plaguing you when there are, I would think, lots of services around this already?
George Swetlitz: 03:16
Right? Well, it all started with an observation. And the observation was that we had clinics where we would run advertising, right pay-per-click, things like that social. And we would have very disparate returns on that advertising. So clinics that were doing very well that had great reputations would convert a bigger percentage of those leads than other clinics whose operations were exactly the same, but they weren't as well regarded.
And it was this connection between reputation and conversion that really focused our attention. And so it was this idea that in many businesses, when you advertise, you might just be advertising for your competitors, right, because.
Richard Walker: 04:12
Your reputation is so bad.
George Swetlitz: 04:13
Right? So, you know, they Google you or they look for you on the map, and you show up in a list, and if you're not in the right place on that list or people aren't saying the right things about you, they might gravitate to one of the people either above or below you on that list and end up calling them. And so and that's what would happen to us if we had poor performing locations. It was often because their reputation was not good. And so when we would bring them to that list, they would say, oh, they're not very good.
I'm going to call this other person. And that was the kernel of the.
Richard Walker: 04:55
I feel like I'm gonna ask a really dumb question, but I love asking dumb questions because I always learn too. So what is reputation then? How are you defining this idea of reputation in this context?
George Swetlitz: 05:07
Well, reputation for many location-based businesses manifests itself primarily in your reviews, because your reviews are what your customers are telling the world about you. There's a conversation that's taking place between your customers and the rest of the world, your potential customers. And the question is, what are you doing as a business to participate in that conversation? So people have to reorient their thinking. They have to stop thinking about reviews as a task, something that I have to do, something that I have to respond to, to realize that that's a tremendous marketing opportunity, not just getting reviews, but how you respond to them, what you say, how you communicate, what you communicate.
All of those things are part of your reputation. So think about this whether or not you respond, whether or not you respond with a template or something that sounds more natural all affect your reputation.
Richard Walker: 06:28
Okay.
George Swetlitz: 06:29
What are you saying? If you don't respond, you're saying I don't care?
Richard Walker: 06:32
Ignoring them, I don't care, right?
George Swetlitz: 06:34
I don't care, I don't care or if you just have the same template over and over again, that's what you're telling me.
Richard Walker: 06:41
I don't. Thank you for your response. Thank you for your response.
George Swetlitz: 06:44
I don't care enough about your feedback to actually respond in a thoughtful way.
Richard Walker: 06:50
Yeah.
George Swetlitz: 06:52
So all of these things. Yeah. Go ahead.
Richard Walker: 06:54
I know this is where your product is going, so I want to get there, but I also want to go back. So you have 220 locations, presumably all operating in the same playbook and therefore following under the same brand umbrella, I would presume. How is it that one location gets a bad reputation from another? Is it somebody on the team? Is it a bad service model?
Is it what was going on that created the bad reputation in the first place?
George Swetlitz: 07:20
You know, it's an interesting question because sometimes you do have a staff member that's not performing well and they can drag down your reputation. You can have a front desk person who is in kind, comes across as short or abrupt, and they can affect your reputation. But other times it's just that you're not getting enough reviews. And so if you think about it, if you're not asking for reviews, you're going to get more negative reviews as a percentage of your total because people are more motivated to write when they're angry than when they're happy. And so and so a lot of our customers, when we first start working with them, that's their problem.
They have a nice business, but they're just getting negative reviews. Yeah. And so that's all that people see. So sometimes just getting more reviews from the people who are legitimately fans of yours is enough to change your reputation. And so when, when, when I was kind of when I was running alpaca.
There there were platforms, those platforms, those reputation management platforms are still out there. One of the problems that you have when you have scale is that a $20 or $30 a month per location fee times 200 locations becomes a lot of money. Yeah. So as a big company, you have a problem that a smaller company doesn't have. It's one thing to spend $30 a month.
It's another thing to spend 6000. I mean, you might have bigger budgets and you have, but you start looking at these things. You say, I'm going to spend 70,000. I'll spend $100,000 a year on this. So you're right, you start to have those kinds of issues.
But when you run, when you run a chain, you're competing against people who are owners, right? In audiology, a lot of your competitors are audiologists who run their own clinic. And so they naturally. Yeah.
Richard Walker: 09:45
That makes a lot of sense, right? Because you guys built the bigger brand, it's really, really hard to achieve 220 locations. You had to have a lot of maturity and structure and skill. And so most people are out there, they've got 1 or 2 locations. And so that you're right, in every geography you've got different competitors all the way around.
Yeah, that makes it very interesting. And they have community appeal because they're part of the community in some way typically. That's right.
George Swetlitz: 10:10
Yeah. And they'll go home at night and they'll respond to reviews manually. Writing is very nice. I'm sorry. They're writing very nice responses.
Richard Walker: 10:19
Yeah.
George Swetlitz: 10:20
When someone who's a staff member isn't going to do that. So we have to have people that we pay. They might be in our contact center. They might be managers who are doing this. And it's we who explain why this is important.
But at the end of the day, it's a task for them. They have to do it. So there's you know when you're and every market is different, you might have you might we might be in a market where you have a local competitor that responds wonderfully to the reviews. You might be in another market where you have an equally formidable competitor who doesn't respond. And that's a very different competitive environment.
And so you really have to understand what is the competitive environment that I'm in in this location and how do I win? Given that, and that's the challenge that every local business has.
Richard Walker: 11:19
Yeah. And that just goes across the board really, whether you have a single office, single place or a bunch of offices, even if they have different brands like in financial services, you might have a lot of advisors with their own different brands that represent you as your ultimate company. So let's get back to response. RightResponse AI.
I mean, look, I think there's a lot of value in how AI can work, but also a lot of backlash and what it's producing. And is it sincere? Is it real? So what are you guys actually doing with your product?
George Swetlitz: 11:50
Yeah. So it's a great question. And we talk to a lot of our customers about that because there's this view, there's this reality. The reality is you go on social media. Look what happened over last weekend.
You go on social media and you can't tell what's real and what's not real, and that's all AI. So there's a view because of the reality that we live in today, that AI is fake and creates fakeness. It's not genuine. And what I try to explain to our customers is that you can use AI in lots of different ways, and the way that we use AI at RightResponse is to help them take their genuine differentiators, what makes them special and use AI not to be fake, but to do the work of infusing that into their responses.
Richard Walker: 12:49
So what's an example of that?
George Swetlitz: 12:51
So let's say you're a restaurant and you are just so proud of the fact that you buy all your steak from a farm in Colorado that you've had this relationship with for ten years. Well, if somebody writes a review about how they just loved the steak and it was the tastiest steak that they've ever eaten, wouldn't it be nice if the review said, we're glad you loved the steak? We love them, too, because we've had this relationship with this farm in Colorado and they do X, Y, and Z. That's a nice, real, robust, interesting and informative response, not only to the person who ate there and maybe didn't know that, but to every other person who's looking for a steak house. They read that and say, wow, I want to go there.
Richard Walker: 13:50
So you're doing a couple of things. Then one is you're helping craft a message that infuses the value. The underlying value the business provides so that you can restate it, which then becomes a marketing tool for everybody else to see while simultaneously giving a more, I guess, full response. It might be the right way to look at it, because you're right, the owner would be proud of this, this relationship they've had and how they sourced it and what they put the care they put into it, and therefore it is a good result. Okay.
I can see how that can snowball.
George Swetlitz: 14:24
Right. So we have a restaurant that we work with in San Francisco, and they go down to the pier every day and they buy oysters and they sell them for a dollar. So there's a deal, a dollar. But you might think, oh, a deal, that's a dollar. Maybe they're terrible oysters.
So telling somebody in the response. Glad you love the dollar oysters. We go down to the pier every day and get them fresh. Wow. Well, now I want to go.
Richard Walker: 14:55
Yeah.
George Swetlitz: 14:55
So it's also on their website. But the reality is that more people read reviews than visit websites. Yeah.
Richard Walker: 15:06
This is perfect. You're giving me a perfect example of a restaurant back in the 90s that I love to go to in Los Angeles. It's a sushi restaurant. And if you saw it driving by, you would never stop. It is one of those hole in the wall type places.
You would never think that's good sushi. But the reputation and the word on the street was that the sushi chef who's from Japan would go down to the docks every morning and hand select the fish he was going to serve that day. And therefore the selection was always fresh, sometimes different, but hand-picked by a sushi artist. And so then when you're spending $70, which might have only cost $30 anywhere else, and you're getting the best experience, you know why this is all before social media? So I can just imagine now how this plays out in online reviews and the social presence that they're building.
George Swetlitz: 15:57
Right? So sometimes what you write in the response doesn't have to even be relevant to the review. It can just be your key marketing messages like that, right? Or it could be somebody says, man, the fish just tasted so fresh. And you're right.
Yeah. That's because we go down to the dock every day and we pick fresh fish. You know, we have one where the same guy is in, you know, when people talk about it, if the review says something authentic, it tasted authentic. So we look for that. The AI looks for that.
What is it saying? And so when somebody talks about authentic Mexican cuisine, the response is yes. Our chef comes from a remote village in Yucatan and he brings that style to the restaurant.
Richard Walker: 16:45
Nice, nice.
George Swetlitz: 16:47
Then you say, I want to go there.
Richard Walker: 16:49
If your system is reading these reviews and creating these responses, who's responsible to post the response? Does the AI just do it, or do you have a human in the loop?
George Swetlitz: 16:59
So it's up to the business. So we do have an auto responder that will publish the responses. But generally what people do is they auto respond to positive reviews. Four and five star reviews. And they put eyes on the one, two and three stars because they want to try to understand what's going on and tweak the response in some way based on what's on there that the AI wouldn't know to do.
And for most people, that might be 5% of their reviews. So if they're getting 100 a month, they really only have to work on five of them. So it changes the game in terms of where they have to spend their time.
Richard Walker: 17:47
Oh that's nice. Okay, look, I have a new set of words that I have been really thinking a lot about when it comes to AI, and it's the difference between deterministic and probabilistic meaning. Traditional software is deterministic. You tell it what to do. It does it every single time.
AI, large language models are probabilistic. They're trying to guess at what the next thing is to do, and they guess really, really well. How do you manage your product to make sure that you're getting high quality responses and not just regurgitating the same story about the chef, or the same story about the steak every single time the word steak appears. How deterministic versus probabilistic are you? Is your system?
George Swetlitz: 18:29
No, it's a great question. And so there's a lot of different levels that take place. So let's start at the level of what's a relevant fact or message that I want to incorporate. So the way we do it is we we we when you build your messages you say if somebody mentions something about the authentic, about the authenticity of the steak or whatever is food, then they build options, right? So there might be ten possible responses that will say different things.
And so what happens is when somebody on boards with us, we do this work for them. We read all their reviews. We read all their responses. We read their website, and we use the reviews to determine what people talk about. And then we use their historical responses in our website to craft answers.
And we want to get as wide a variety of possible answers as you can get. And then the AI engine selects one of those answers randomly. So did you get variation because you're I mean, while normal software is deterministic, the problem with AI is that there is a most likely answer. And so AI will repeat itself unless you do something about that repetition. There are ways to do that.
One way is what I just talked about, where you create lots of different ways to say things and you choose those. Another way to do it is to say when you're generating an answer, generate four answers, each with a 10% probability. It forces the AI to be creative and then it selects one of those randomly. So there's a lot of mechanisms that you can use to get creativity within. Structure that you create so that you don't go out of bounds.
You don't want it making stuff up.
Richard Walker: 20:46
Yeah.
George Swetlitz: 20:47
Those things. So you have to have it's a multi-step process, but there are a number of different ways to solve that problem.
Richard Walker: 20:54
Yeah, it's a fascinating challenge because of how different AI can be. I mean, you give it the same prompt twice and give you two different answers, just simply because you didn't have a clear prompt. But that's making it simplistic. I want to ask you questions, but I'm afraid I'll be asking you to reveal trade secrets, so I'll.
George Swetlitz: 21:13
That's fine.
Richard Walker: 21:14
Well, look, so here's one of my things. I think AI needs to be checked. So do you have gates and checks to make sure that you've got maybe different LM models reviewing what's coming out before things get posted.
George Swetlitz: 21:29
So we do something we call it. We do like a final QA check. So after that our process is an agentic process. It's a multi-step process. And there's about 12 different steps that take place before the outputs of that go into our response writer, which writes the response, and then after we get the answer, this is the response.
We do a QA check, and the QA check is not checking everything, but it's checking the most important things. Did it stay true to the facts? Did it stay true to some of the core elements that we specify? And then. You want to tweak the grammar, the order, whatever it is.
And then that's the final output. So 100% if you have a problem with AI. So I want to go back to what you just said. If you have a complicated question, it's making a series of decisions along the way. And even if it's using the 90th percentile right answer if each step is 90th percentile nine times, nine times, nine times.
Before you know it, you have a lot of variety.
Richard Walker: 22:56
Yeah.
George Swetlitz: 22:57
Right. With the same prompt. And so you really have to be very cognizant of that mathematical, you know, problem. And that's why we break it. When we first started we had one very long prompt.
And now we've broken it in. You know it's about 20 individual things so that we can manage them much more tightly.
Richard Walker: 23:21
Yeah. No, that's smart. You have to break it down. And that's what I've found as well. AI responds better when you give it small, small tasks to stay consistent in how it works, at least.
Right? George, let's turn this around. So obviously, if somebody wants to build their reputation, this is great. What if they want to turn their reputation from a true negative to a super positive. How does the right response actually elevate them?
How long does it take to repair a bad reputation, etc.?
George Swetlitz: 23:51
Yeah, so there's two elements to that. One is understanding what's what. Why am I getting the ratings I'm getting? So I can solve a problem if I have it. So we have the voice of the customer built into RightResponse where we analyze.
We analyze every review against a set of topics that we create for the business. So the business and it will be different for every business. The restaurant will be different from a doctor's office. The topics will be very, very different. We generate a set and then the customer can change them.
But in any case, what they're doing is they're getting a very consistent view of what customers are saying. And it will highlight exactly where the negative issues are. So the first step is trying to better your business, trying to use knowledge, right? Customer feedback in a structured way. The second step is then just getting more reviews.
And so that gathering process, review gathering is another element of our software. You can get reviews by, you know, texting people by emailing people. QR codes for some businesses are a really great way because the conversion rate on QR codes is so high, so many people will write a review and you ask them face to face and give them a QR code to scan, like 60% really, really high. And so we have a business that we work with and. And it's actually the same one that we were talking about this Mexican restaurant, San Francisco. One month ago and maybe a month and a half ago, one month ago, they ranked it for the search term Mexican restaurant in San Francisco.
You can imagine it's a very difficult market.
Richard Walker: 25:51
Yeah.
George Swetlitz: 25:53
Mexican restaurant. They ranked 58th. So if you. I want the technical way of coming up with that ranking. But if you rank all the Mexican restaurants, they were number 58.
We then talked to them about using QR codes to get more reviews. And so they went. It's a three restaurant group. They went from getting about 30 a month across their three restaurants to about 400 a month.
Richard Walker: 26:25
Wow.
George Swetlitz: 26:26
Huge change.
Richard Walker: 26:28
Yeah.
George Swetlitz: 26:28
Just by asking their customers, will you do this? If you enjoyed tonight, will you leave us a review? Here's the code. And what we do is we will tie those codes to employees. So every employee gets their own code, and we track that.
And there's a leaderboard so we can see any incense people and gamify it and do all of that stuff to create some enthusiasm around it. And we just ran a report the other day. And now in that area of San Francisco, he's number five. Wow. From 58 to 5 in about a month and a half.
Richard Walker: 27:07
Wow. No, that's impressive. I mean, that really does speak to the power of what reviews are doing for people. I mean, we know it because Amazon gives us the five star review capability in Amazon. That was a game changer, you know, 15, 20 years ago.
So look I have a totally different interest question I want to ask you. I don't know if you are a technical co-founder. Did you have this AI background when you started this?
George Swetlitz: 27:35
Well, we started this about a month after they launched ChatGPT.
Richard Walker: 27:41
Okay.
George Swetlitz: 27:42
So I'm not a technical guy, but I've become I know a lot about AI because we built this from the ground up around AI. It's AI first.
Richard Walker: 27:55
Yeah. So you've learned on your way then. How has that journey been? Did you face a lot of fear challenges like how do I make this work, not having that background and learning as you go?
George Swetlitz: 28:10
Yeah. So there's, you know, there's this understanding element which shapes the way you do things. And I participate a lot in that. We have a technical side, you know, development team that understands the APIs and how to do things and how to make it all work. And that side.
So I don't understand any of that, but I'll, I'll advise around how I think we should structure things. So, you know, we work with all the different companies. You know, we decided a long time ago that we weren't going to use a lot of people to cut costs. We'll use open source models. and we don't do that because things are changing too quickly and there's too much benefit associated with each turn of those models.
And so if you train a model with your own open source and you train it and all that, then you're kind of, you know, you're there. It's a tremendous amount of work to then go and do it again. So we didn't make a decision early on that it was too early in the life cycle of all of this, especially with the complexity of what we're trying to do to do that. So we work with all the models. We have a whole way of testing them.
And different models are good at different things. And so we identify, you know, where we get the best cost benefit for each type of thing that we're trying to do and leverage those models. We've learned things like this for example. We wanted to develop a monthly evaluation around the voice of the customer. And we, you know, we started by feeding all of this data into the LM, and it just failed.
And the reason it failed is because a lot of the work that needed to be done was math. Yeah, there's a thousand reviews, 1500 reviews. There's all of these topics. There's percent positive, percent negative. And we were asking the LM to do math and LMS didn't do math.
Richard Walker: 30:28
It's right. People don't realize that.
George Swetlitz: 30:30
They don't.
Richard Walker: 30:31
Realize. Yeah.
George Swetlitz: 30:33
So what we did is that we went and we took that data and we processed it, and we injected our table into the LM and said, never do any math. You're forbidden from doing math. Any information you need, any numerical information. Pull from this table and trust that it's right. So then you could focus on what it does best, which was analyzing the sentiment, understanding what people were saying.
And then when it wanted to say 22%, it would just pull that from the table and not have to think about it. So it was faster and better and repeatable. And so to answer your question earlier, you just learned that by trying you do.
Richard Walker: 31:25
Right. You just there's no other way. Nobody could have told you these things. There was no manual that we could all read that says, this is how it all works. It's been a fascinating journey.
So look, I have a bunch of other questions. I'm only going to ask one more before I get to my end here. I'm thinking a lot about how responses are being generated with AI, and even a lot of documents are being generated by AI, and we all see it and notice it. And now there's even detection systems for it. So as simple as the Em dash, the long dash that's out there.
So how are you guys protecting against reading reviews that may not have been posted by real people and counting them or using them, and outputting your responses that aren't necessarily being seen as AI or detected by written AI type of things.
George Swetlitz: 32:13
Right. So, you know, in terms of. Not, you know, generating responses that are not AI, that don't feel like AI. And you mentioned the Em dash. We have a list of prohibited words and phrases that we tell the model not to use.
And right now we've generated that list, you know. Oh, we appreciate your kind words. You know the em dash. We tell them not to do these things, but in the future we're actually going to let people make their own decisions. Because what I don't like, I don't like when the response says, oh, thank you for your kind words, I hate that.
To me that screams AI. But then I've had people email support and say things like, it never says this. I want it to say I like kind words. And so we've realized that that's something that even though to me it's an AI trigger, other people like that. So we're actually going to suggest a set of phrases, but then let people decide what they want to do.
Richard Walker: 33:18
That's a great idea, George. I love this conversation and I don't want to quit, but I do have to wrap it up. So before I get to my last question, what is the best way for people to find and connect with you?
George Swetlitz: 33:29
So the best way is to go to rightresponseai.com. That's our website. People can schedule meetings with me right from the site, and so it's really the best place to find me and connect with me. We also have a place on our site for guests of this show where we have some information and some special offers. And so that would be right.
Richard Walker: 33:59
Nice. That's awesome. Thank you for doing that. All right. This is one of my favorite questions to ask people.
Who has had the biggest impact on your leadership style and how you approach your role today?
George Swetlitz: 34:12
That's an interesting question. So I'll say I worked at McKinsey early in my career, and one of the gentlemen that I worked for, a guy named John Schuck. Super, super smart guy, super structured guy. And he really, more than anyone else, taught me how to be structured, how to think in a very structured way to get from point A to point B and the things I learned from him, I carried with me my entire career.
Richard Walker: 34:44
A nice man must have given you a better sense of organization and leadership and communication style, I love that. Yeah, yeah. Thank you for sharing that. All right. I want to give a big thank you to George Swetlitz, co-founder of RightResponse AI, for being on this episode of The Customer Wins.
Go check out George's website at RightResponse. And don't forget to check out Quik! at quickforms.com, we make processing forms easy. I hope you enjoyed this discussion. We'll click the like button, share this with someone, and subscribe to our channels for future episodes of The Customer Wins. George, thank you so much for joining me today.
George Swetlitz: 35:24
Thanks for having me, Rich. I really appreciate it.
Outro: 35:28
Thanks for listening to The Customer Wins podcast. We'll see you again next time, and be sure to click subscribe to get future episodes.
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