Conversational Loyalty: The Impact of Interactive Rewards

In this episode of Travel Buddy, Rachel Satow and Ian Andersen unpack the rise of conversational loyalty and its impact on customer experience. The conversation explores how AI-powered chatbots are reshaping loyalty programs, making them more intuitive and engaging, while raising important questions about data, privacy, and the need for seamless integration across business channels. With real-world examples, strong perspectives, and practical guidance on technology and user experience, this episode offers business leaders, marketers, and technologists timely insights on where travel loyalty is headed next. Tune in to discover how genuine conversation and smart technology can transform the future of customer relationships.

[00:00:00] Welcome to Travel Buddy, presented by Switchfly. In this podcast, we talk about all things travel, rewards, and loyalty. Let's get to it. 

Brandon Giella: today we're talking about conversational loyalty. Yes, it's about AI, but there's a lot of practical use cases here to think about the customer journey from, say, a chatbot into a customer loyalty bot and the conversions between all of these different departments and how they use AI. I think what would be really helpful, Rachel, I'll start with you, is talk to me, what is conversational loyalty? I know this is a growing trend. A lot of people are talking about this. There's a lot of use cases out there, I think. But define this for us, and then we'll go from there

Rachel Satow: Yeah. So conversational loyalty is essentially the next phase of what we see today in terms of someone coming to your site, your program, your app, etc., having a conversation with a chatbot. When you think about it from a loyalty perspective, traditional programs often feel like a [00:01:00] catalog. Someone is needing to, browse through, really dig into some of the redemption options that they have.

The idea of conversational loyalty essentially turns that into a conversation, one, but a two-way street. So someone who is looking to redeem, say, 60,000 points can come to that chatbot, come to that tool within your program and say, "I would like to redeem 60,000 points for a beach vacation in March." And the conversation agent will allow them to surface ideas and options in a more streamlined manner.

So ... And then ask more about it. So for example, if ... Let's use the example I just, just used. A beach vacation in March. I want to redeem 60,000 points. What can I get for it? It may be able to surface that I could fly on specific, airlines, go through specific hotels, have this room versus that room, and help me make decisions faster while [00:02:00] also inquiring more details, all without having to necessarily leave and go to a different browser to do that research.

So the idea of conversational loyalty is that you, you essentially have a companion to help you in the decision-making process so that you can move through the funnel faster.

Brandon Giella: I love that. I love the aspiration. I'm feeling a headache growing in legal teams and engineering teams everywhere, which is totally fine. This is obviously the direction in which we are headed with AI. We can clearly see that case happening. so it's kind of like a get ready for this. This is for sure happening. And Claude, everybody's familiar with using AI tools today. We're chatting with these things all the time. a lot of hallucinations in there. You gotta be really careful, especially if you're in certain industries. Totally get that. And yet, you can see this could be super helpful. We've talked about in the past using AI to do like trip planning and itineraries, potentially booking tickets for you and car rentals and so on, of course. [00:03:00] you guys have a lot of great technology at Switchfly. but there's a lot of technical things to, uh, get in place. So before we get there and talk about more, more of the practical side of things, talk to us a little bit about how you see the traditional loyalty landscape and how people are using booking redeeming points now, and then kinda shifting on where we're going and how to get there.

Rachel Satow: Yeah, I mean, even if you have the strongest rewards catalog in the world, they can feel less valuable if there's friction points in that process, in the redemption experience. So when your program becomes difficult to use from a, in today's, you know, quote unquote traditional program structure, if those reward, rewards and redemptions are difficult to use, that's when you start to feel some loyalty fatigue.

Like, people are getting inundated with offers from a bajillion different channels. You're essentially pushing all of these different things to someone, and it is that [00:04:00] one-way street. So this is the natural next step in being able to reduce some of that friction within your program and help move past, you know, like confusing redemption charts or hidden restrictions that people don't know.

It's allowing you, it will be eventually a two-way street to a- allow further conversation, deeper conversation. But as it exists and can exist today, it helps to surface answers a lot faster. So it can talk through some of those program rules that might not be readily available unless you're digging through it.

It may help with comparing options. and all of that is something that is totally available today and to tap into, to your point, with, LLMs as they exist. but yeah, I think from a member experience, they will be able to find more value in your program if your ex- your overall process is just easier to navigate because you're implementing tools that may [00:05:00] be trained on your own documentation, etc.,

but you're implementing tools that help expedite things for them

Brandon Giella: That's right. That's right. I'll, I'll turn this next question to you. what's the worst chatbot experience you've ever had? No, I'm just kidding. no, so no, I'm kinda joking there, because obviously like some of these tools, it's like it sounds great in theory, and then you start working with it, and you're like, "This is-- Just let me talk to a human," you

Ian Andersen: Yeah

Brandon Giella: and you see a lot of like AI assistants in like call centers, for example, and being able to surface, you know, it's like reading the transcript and surface relevant articles. I actually had a wonderful chatbot experience a couple of weeks ago. It was very, very well-trained on a knowledge base, and it actually did answer my question really well, and I had kind of a particular question. but I wanna talk to you, Ian, a little bit about like, tell us like some of the, you know, guardrails or risks or ways to like, yes, we can understand how this could be more personalized and help the decision-making, but [00:06:00] there's definitely some things to think about, of course, from an engineering perspective, but also from like a policy or a program perspective that might help build some of these.

Ian Andersen: when we're thinking about AI models in general, to include chatbots, clearly there are still mistakes being made, right? And still, gaps to where it really does-- There is a point in which a human on at least one end of that interaction needs to be, involved to, to make some sort of determination, or at least, you know, spot if something's off or not. I think we're seeing it get better and better all the time. I know in training AI agents, you can be, pretty draconian in instructions given about, you know, not leaping to conclusions, not, filling in gaps with extraneous info. I think as these companies are building, building [00:07:00] their, their AI models and training them, especially when it comes to things like handling money, there's going to be some very severe, restrictions and limitations put on it. That said, the, the industry is advancing rapidly. there's, there's-- In virtually every situation you can, you can foresee way in which, AI will at least, if not replace, at least expediate a lot of the process, and this is, is clearly one of those areas. I think when we're talking loyalty, it's, it's understandable we get bogged down a little in like the, redemption, conversation.

But I think even before that, what we're seeing now is companies building, buying and purchasing sort of if you will. you know, you can go on the Amazon app and say-- and, and talk to Alexa on there and say, [00:08:00] "Hey, you know, I kinda want this thing and, but I'm not really sure," whatever, and, and the AI will help lead you down the direction of to looking what you're buying.

I think the loyalty part of that's just a natural extension, right? You're, helping a user, whether they're a member or not, come to a buying, decision, helping them make the purchase, right? And then, on top of that, if you can add in that loyalty aspect of like, "Hey, if you become a member and you wanna buy this again, you get you get discounts, you get whatever."

Or if they are a member, you know, during that buying process, if I'm looking for shoes and, you know, they can-- the, the AI can kinda say, "Hey- You can pay cash for this, or there's these other shoes or this brand you're not even aware of that we have a agreement with, you know, that you get double the [00:09:00] points for or what, you know, whatever the case may be. there's just, there's, there's infinite room for expansion in that sort of area. So it becomes not-- you're not having your, your customer support AI chatbot, and your buying your support AI chatbot, and your loyalty support AI chatbot. It really is a whole organization that, that really takes the, the prosp- you know, the person from prospect through customer and then repeat buyer, right?

Through, engagement and loyalty. And it, it, obviously the word conversational, we tend to think, know, immediate direct conversation when you're interacting. But I mean, on top of that, there's so many, additional marketing and growth opportunities that, that tie in, right? If, if the AI's looking at your, your, chat history and your purchasing history, they're gonna be able to recommend certain things for you.

They're gonna [00:10:00] be able to email you or send you notifications or, you know, whatever, even after the conversation that, that brings you back into, into it, you know? as Rachel mentioned, you know, if you're-- if, if I say I want a beach vacation, you know, in this timeframe, what can you do for me? maybe it can't do anything good right now and, but a month later it says, "Hey, because of X, Y, and Z, these hotels are now on sale.

You wanna come back and revisit it?" You know? So I think it's better to look at conversation not as just that immediate chatbot interaction, but that ongoing total conversation you're having with a buyer, right?

Brandon Giella: The, yeah, gosh, I, I have, I have, I'm gonna go on a diatribe. Rachel, you go ahead. Yeah, yeah, you go

Rachel Satow: Yeah. I mean, as I have two, I have two things there. I think the first that I want to address is that there is such an opportunity to [00:11:00] streamline channels, to Ian's point. Like, yes, all of the information that those conversations will be giving to you and that the reference points of your data that is training the AI can pr- surface to the user, that is

That's amazing. The biggest thing that I see in the future is that all of those different aspects, the, you know, the buyer's agent, the customer service agent, the, the, loyalty agent, they'll all eventually converge into one just simple, straightforward agent that becomes your conversation companion, someone that you can ask all of those different things to.

And while Ian's absolutely right in that all that information you're getting from that can be dispersed across your marketing channels, can go into your platform to be able to serve better options if they're, you know, looking manually, etc., the other aspect of it is you'll be able to have a conversation

more [00:12:00] proactive conversations. So if you think about it from somebody booking a trip, yes, eventually I think that conversation can be, "I want to redeem for a beach vacation in March," surface later like, "Hey, if you wait a month, things may be a little bit cheaper. Let's revisit back then." And then they can come in and say, "Hey, like remember we talked about this?"

So you're able to, to kind of circle back. But then it ... once they actually book, you're able to have an ongoing conversation leading up to that trip, throughout that trip, after that trip, all in one place, rather than it coming from, like if somebody's booking with one agent now, then your emails are eventually going to drip to them come time for them to actually travel.

You'll have a, a net new, a, a net new channel to be able to have those conversations to prepare your travelers. The caveat to all of that, going back to your question, Brandon, about risk I think that [00:13:00] programs today will find a challenge with their data being complete and connected enough to be able to get there.

You know, conversational loyalty and a- an AI bot, the way we're discussing it aspirationally, needs the right context and the right training, and it needs to be holistic in order to get to that point. So many lo- mo- loyalty programs are going to run into the challenge the, of fragmented data across a CRM and their booking platform, and the loyalty platform that they're using, the customer service tools that they're using.

They're all... They all carry their own specific data, and all of that data is in those platforms, and it's hard to, for loyalty programs to find a way to get all of that data in one source of truth. and if the conversation agent only sees one aspect of the member relationship because that's the only part of the data that it has [00:14:00] access to, the recommendations are going to feel incomplete or not personalized enough.

And when you think about creating loyalty, accuracy is going to matter more than a casual AI engagement or use the way we're doing it to Acclaim Trips now.

Brandon Giella: Mm-hmm.

Rachel Satow: Them being able to serve, the most accurate piece because they have complete profiles on individual members is going to be more important in cultivating loyalty than just having the ability to have a conversation

Ian Andersen: Yeah, I don't, I don't know. I, I don't know if I wholeheartedly agree with that. The-- I think directionally you're right, for, th-there's-- every part of the organization has their own data silo and hoard, right? And, and yes, the, the out-of-the-box, like, solution to turn on the chatbot [00:15:00] isn't necessarily gonna work across the board right out the gate. Which why-- is why I think it sort of has to grow internally, from a single starting point to start incorporating the, the other areas, right? As, as it gets better and better and more, more and more trained, more and more knowledgeable. I don't think we're gonna come out tomorrow and say, like, "Here's your loyalty chatbot. it in, you know, integrate with your CRM and off to the races," right? It has to be that of growing holistic thing. And I think... Brandon, to your point earlier, you ha- you, you mentioned having a really great conversation with AI chatbot, earlier. I've had, I think, some relatively decent ones recently, at least like ultimately helpful. I've had a few, you know, recently that probably weren't as helpful, but a few that you could almost not know you're talking to an AI chatbot, right? If you t- sort of take it out of it. and I think [00:16:00] people are willing to forgive a little bit of and, and headache if they're seeing the ultimate reward, right?

If, if you're showing we're trying to develop this thing, it may not be perfect, it may not get you to the one hundred percent end state, but it'll get you eighty-five, ninety percent of the way there, and then we'll give you a link or whatever to, to get the extra five, ten percent. I think people might be willing to give it a little grace. I mean, we, we all know l- this conversation two years ago, we'd be some theoretical day in the future AI might be able to do a couple of these things, and now we're talking about it being here, right? It's just it being hard to, to implement. But it is here, and, I think people understand with how rapid the pace of technology is changing in this, in this, that yes, we're gonna have some growing pains, [00:17:00] but I know a little bit of investment now is gonna really pay off for me, you know, six months, eight months down the road.

Rachel Satow: I would, I, I would argue back, that I think the three of us and many of our listen- listeners probably have a slight bias because we are on the more tech savvy, cutting edge... Like, we're, we're working with this, this type of tool all the time, and the typical user might not. The, the end user might not. So I think we would be more forgiving in those instances than, say, m- my parents or grandparents or anything like that.

Ian Andersen: Yeah.

Brandon Giella: I, I actually did just read a report, that, that if the, if the chatbot apologized for getting something wrong, that it was actually a better... Like, folks rated it a better experience when it was like,

Rachel Satow: My chatbot is constantly apologizing. It's always apologizing to me. "You're right. I'm sorry."

Brandon Giella: a, yeah. [00:18:00] And not attorneys. So I, like

Rachel Satow: not attorney

Ian Andersen: but like we are getting more and more tech-savvy as a society as a whole just by sheer need, right? Like it, you know, how many people... When I joined the military, basically it did 21 years ago, we don't need to worry about exact numbers.

the-- I remember having guys, guy, who checked their email, right? Who literally wouldn't turn their computer on, and the only reason it was in their office is 'cause they had to, they, they were forced to have it in their office. now th-th-those, those people cannot survive in an organization, in virtually any organization, whatever your industry, right?

Without being able to check an email. AI, I [00:19:00] think it's just gonna become so much more ubiquitous that, that, that sort of tech illiteracy isn't gonna be as sharp of a ramp-up as maybe some other forms in the past.

Brandon Giella: I, and I think it is the... It, it is a classic debate between, of course, privacy and convenience. That's been a debate in tech for 30 years, probably longer. And there's also a debate now between a chat interface the proper UI to create a good experience for, like, a customer? Maybe there's other ways to do it.

We just haven't figured out exactly how to use AI with, in, in some other kind of interfaces, unless it just builds things for you, like you're building a website or whatever. And so, but, but what I love about that, the, some of these trade-offs, it's convenience, personalization, privacy, you know, ease of, of using this thing, is that it flattens [00:20:00] all of these different, that people have had into, like, a unifying layer. Like what you're talking about, Rachel, and, and Ian, both of you, where it's sort of, collapsing a lot of different data silos or departments within a company. Because everybody hates, like, you know, I call a, a credit card or, you know, a travel firm or whatever, and it's like, "Oh, well, that's... We're on the booking department.

You have to call the rescheduling department over there, and this is... Oh, you're talking about membership? Oh, you gotta... I'll transfer you over to this department. Oh, this is about your credit card-specific billing details? Well, let me call these folks over here about your, you know, details." And it's like, gosh, I've spent two hours on the phone with something that a chatbot could've figured out in literally one thread But at the same time, I think it's also not only just the different departments, but like the journey, like what Rachel, what you're talking about, like, a-and, and Ian, you mentioned like prospect to customer and beyond. All of these debates, [00:21:00] conversations, the technicalities, the different departments, sales and marketing, customer support, whatever, all of that is collapsing. I find it like a fascinating that I be willing to trade everything Claude knows about me, including maybe some conversations I've had with my therapist, and I'm like really digging into something, and I'm, I was just like talking to it, talking to it late at night. Do-- will I trade all of that to get way more personalized information into offers, loyalty, my membership status, getting more points, more savings, helping me plan a trip, helping me book a car, knowing things about my family and things I should consider that I hadn't even thought of? Would I be willing to trade all that and interact in a chat interface to grow from, you know, a middling, know, once a year user to like, I'm talking to this thing week?

'Cause I'm thinking about so many different [00:22:00] things that a company can do for me. You know, I'm thinking of like a larger, you know, travel company. There's lots of things that I'm-- I gotta plan and think about and do, and, could it help me with that? Like it's a, it's like a fascinating... then thinking like in two years, this technology is gonna be literally ten X better.

Like every four months, there is a step change in the model and how efficient it is and how much context it can... And, and how, you know, cheap it gets, and the compute obviously needs to keep up, and the electrical grid needs to keep up, and so on. But if the trajectory remains the same, at least in the midterm, these things are gonna be crazy good at booking and me as a customer on all kinds of things.

And that's fascinating, and I'm willing to trade a little bit of my privacy maybe for that

Ian Andersen: Yeah, I think it's gonna not be an option, right? Like,

Brandon Giella: Yeah, right. Yeah

Ian Andersen: if you're wanting to buy in the market, you know, using your credit card or whatever, at some point some of the stuff is gonna be non, [00:23:00] non-negotiable

Rachel Satow: I would agree with that. And then to play devil's advocate, I think we will see iterations of things like GDPR come through, and say, actually, AI needs to provide the user the ability to control what brands are able to see and utilize within their own platforms. Because at the ... Like, Brandon, to your standpoint, like I'd be willing to, to trade certain information.

Like, how much of that information am I willing to trade? I think we, we will find ... And again, not a lawyer, not an attorney, not in policy. But like, I think we will find that it becomes so prevalent, that question becomes so prevalent of, are people willing to trade their data for more personalized experiences, and if so, what data and how much of it are they willing to trade?

It, that question I think is going to surface at an entirely separate [00:24:00] level than just conversational loyalty, and how loyalty programs can utilize that information they're collecting. Because at the end of the day, personalization is supposed to feel helpful. It is supposed to feel like we are providing you with something that we think you will like based on your past behavior, and the other indicators that you have provided to us, and given us consent to use.

Not like the program is Big Brother, and watching every move, and per- using every single piece of detail that I could have on you in order to provide you with the most unique experience possible. I think from a policy standpoint, we will likely see some sort of, of,legislature come through requiring the ability for people to dictate how much information is being taken, what kind of information.

Brandon Giella: If it's collecting information that you'd say you don't want it to use, what it does with it. I think obviously that is, that is well in the [00:25:00] future, because it's not quite yet there. But I do think that that's going to come into fruition here, for sure. Yeah.

Rachel Satow: yeah

Brandon Giella: I was listening to, Lenny's podcast recently, and, the guest was talking about how she uses, several OpenClaw agents to manage her family. And so she had like her own Mac Mini servers in her, in her home kinda that were disconnected from her personal life and all that kind of stuff. But, but that they would help manage some things.

And she was saying, you know, what a great kind of opening UX could be is instead of filling out a form, the chatbot would just like introduce itself to you. Like, "Hi, I'm Claire," you know. "Tell me about yourself." And then you give the information you want to give to the chatbot to help it plan for you, and you only give it so much.

Whatever you tell it, it can use, you know. That could be like a-- I, I imagine a fairly simple policy. Again, I'm not an expert here. But I imagine

Ian Andersen: I think I'm

Brandon Giella: here's some stuff about me." Like I imagine like five questions could probably get a good agent [00:26:00] tuned into what you need

Ian Andersen: Sure. I, I am less optimistic than you two, I think, about,

Brandon Giella: come on, Ian

Ian Andersen: regulation being introduced. I mean, been, it was 2003 that CAN-SPAM Act came out. It's been

Brandon Giella: don't know. I'm not that old. Sorry

Ian Andersen: the FCC, Privacy Protection Act, right? Like I th- Especially in seeing recent developments with, with some of these AI companies going public and just having unimaginable levels of resources, they are not going to want to be regulated.

No

definitely not to any, particular degree. So I'm, I'm for now gonna operate under the assumption that it's gonna go on essentially like the wild, right? And,to the individual company's policies, and sorry, I don't necessarily trust that they're gonna be super, [00:27:00] user-forward when it comes to, comes to data and information,

Brandon Giella: Yeah, of course. Yeah. Yeah, of course

Ian Andersen: so I, there is a bit of fatalism in that, that I think we've kind of crossed the Rubicon on a lot of this stuff, and th- it's just a fact of life you have to live accept to some degree that your data is out there and accessible, and it, you know, a-accessible by a lot of different organizations you never necessarily gave it specific access to. so why not make it work for you a little bit and

Rachel Satow: Yeah.

Brandon Giella: Either,

Rachel Satow: Brandon

Brandon Giella: entirely or get off of it. It's kinda

Rachel Satow: yeah

Brandon Giella: yeah.

Ian Andersen: Yeah

Rachel Satow: Brandon, you, you made a comment before we went down the data rabbit hole about whether or not chat and chatbots are the channel that this should be utilized for. And I think in, in my opinion, the answer is yes, it's the only one that truly [00:28:00] makes sense. if you look at some research, you know, two-thirds of Americans spend more than four hours a day on their phone, and around 90% of consumers have said they want to use texts to communicate with businesses, but when they send a text, they never get a response.

So we're using our pocket computers constantly, and that, it... That's just, that's not gonna change, in my opinion. But, like, your s- your marketing and your service, like, it has to evolve to remain effective, and that includes recognizing when there is a shift in the dynamic of preferred channels and communication, both from a tech standpoint of how you're going to implement conversation, conversational loyalty, conversation bots, and just, like, a generational standpoint.

I mean, we, we all have family members who just, like, don't want to use their cell phone. They prefer to have a landline. Like, that still [00:29:00] absolutely exists. But on the other hand, you have a generation who is perpetually online.

Brandon Giella: And

Rachel Satow: And I...

Brandon Giella: to be, to counter

Rachel Satow: And exactly

Brandon Giella: There's like folks that are 25 and under, they're probably not on email, but they will text you or Instagram DM you. Are you

Rachel Satow: Yeah.

Ian Andersen: I, I

Rachel Satow: so many businesses that have s- sorry, Ian. Many businesses that have started implementing some of this technology are using a WhatsApp, a Messenger, something that is, is inherently baked in the way that we as humans are communicating with each other, and I think that, I think that's the only avenue for it, honestly

Brandon Giella: Yeah

Ian Andersen: I think the only problem with that, i- is so is the chatbot the right, channel or, or platform for this? And the answer is yes. And is phone and voice? Yes. And is email? Yes. Like, it, it can't be one thing, right? And with AI, with the capabilities that it's developing, it [00:30:00] doesn't have to be, right? You can have your AI chatbot, be, be voice if somebody wants to actually dial a phone number and talk.

It can be a chatbot, text message, email. It can be multiple avenues, and I think it has to be all of them, right? If, if you wanna be successful

Rachel Satow: Yeah, I would, I would agree. The, the biggest tip for anybody who is starting to develop this that I would say is just ensure there's a way out of the co- AI conversation. Ensure that there is a way for the user to actually get ahold of a person on the other end. Because, 'cause, I mean, let's, talk about this theoretically.

If you're, if you implement something and it doesn't have all the data, from all of the different silos within your company, and someone is truly trying to utilize this to get a very specific answer and you're, you're just not quite there yet, the friction of someone needing to get to an actual human [00:31:00] to solve that answer is o- going to completely eradicate any benefit you're getting from, from this conversation from an AI bot.

And in reality, there's about, like, there's over, I think it's, like, over 70% of people still prefer to communicate and get the help of an actual human rather than solely interacting with the chatbot. It's not that they don't want to use a chatbot, it's that going back to how it exists today versus the aspirational side of things, a- as it exists today, most chat isn't, doesn't have the documentation, doesn't have the mo- the most robust training on all aspects that someone may be trying to utilize it for.

And so that's just my very long-winded way of saying, if you are going to experiment with this technology and implement it, please make sure there is an easy way out for users to funnel to an actual human con- conversation instead of solely relying on a [00:32:00] may or may not well-documented, well do- well-documented database from an AI, AI bo- AI bot

Brandon Giella: I could not agree more strongly. Like I, i-it's, it's hard to separate like what chatbots are today my frustrating experience with so many of them so often where it gives me a list of five options because that's what the, the team has defined as my only options to respond to this thing. And it's like none of those, none of those address my question. 

Rachel Satow: Where's the other?

Brandon Giella: God, I just wanna throw my computer through a screen or through a window. so I totally agree with that. But I think like, and I, and I don't know if this has ever been true in, in, in history, but the pace at the advancement of this is like, I mean, if you saw Google I/O three weeks ago, or if you see Meta or Apple's WWDC a couple of weeks ago, like if you see where things are going, like [00:33:00] much now, like these things are happening.

They're, they're at the very, very early stages, but like talking to somebody in a chat, somebo-somebody, I use that anthropological term very loosely, but you, you are talking to a, an entity that can sound just like a human being and, and be as helpful as that. That technology is like a year from now, months from now, that is happening. So, I mean, even ChatGPT and Claude, their voice bot sounds incredible. So it's here, but you know, on an enterprise scale, maybe a year or two from now. So all that to say, like I totally agree with you and it's, it like you have to prepare for that now. So how do you set the data? How do you set the policies?

How do you set everything you need to, to like collapse that conversation to go from prospect to very loyal customer and let somebody talk through all the stages of their journey? I think it's a tremendous, tremendous advice. Yeah.[00:34:00] 

Ian Andersen: Absolutely

Brandon Giella: Well, I guess that's the end of the episode. I don't know. I don't have anything else. That's great. No, I just totally agree. I love where your, where your head's at, and I, I, I couldn't agree more. I love it. Yeah.

Rachel Satow: I think the only other piece that I would say is if you are implementing this or you're, you're working with it, focus on natural conversation flows, rather than just, like repeat prompting because, I mean, you go on LinkedIn and there's someone ranting about all of the ways that they can tell that your content is written by AI, and it's

it like it ... I would say just be conscientious of, like how natural conversations flow. There are a lot of tangents. This podcast is a great example of all of the tangents that can happen within a natural conversation.

Brandon Giella: not. We stick to one topic.

Ian Andersen: Yeah

Rachel Satow: all the time, yeah. We're very straightforward. but like just be, be [00:35:00] cognizant that when you're developing something, it should not be so

What else can I do for you today? W-

Brandon Giella: yeah

Rachel Satow: would you like this? Would you like that? You're right, I'm sorry. It should not be so polished that the conversation feels inauthentic. it should understand when the conversation naturally ends and take that opportunity to kind of like close out and then revisit with all of the data it gathered and go from there

Brandon Giella: Yes. And while I like niceties, it shouldn't be sycophantic to say like, "Oh, that is a great suggestion, Rachel. suggestion." You know? Like

Ian Andersen: and that's just one of those things that it's, that's gonna develop naturally,

Brandon Giella: Of course, yeah.

Ian Andersen: gonna,

Brandon Giella: Yeah. But no, it's, it's definitely ... It's, it's really thinking about the, the experience. Like, at what point is AI [00:36:00] helpful and an incredible benefit to the user experience, the customer journey? And at what point is it like, "You should talk to a person. Let me get you in touch with so and so."

You know? yeah, I think that's a really great mark. Well, guys, as always, thank you for this topic. I love the topic. I love the direction, the way y'all are thinking about it, and I think it's, it's so, so important to be thinking about now because this is dramatically changing. I mean, just two days ago we were seeing these product launches on some stuff that I was like, "This is mind-blowing what is happening right now."

Like, mind-blowing. I've been doing this for 12, 13 years, and it's like, gosh, that's so cool. so yeah, it's just happening so fast. And, the time is now. thank you.

Rachel Satow: is now.

Brandon Giella: And if you

Rachel Satow: Thanks, Bryn

Brandon Giella: your chatbot or your agent on wonderful resources, please go to switchfly.com. They have amazing resources to talk to you all about travel and loyalty.

So as always, thank you, and we'll see you on the next episode

Rachel Satow: Thanks, Brandon 

[00:37:00]