Paula: Welcome to Let’s Talk Loyalty, an industry podcast for loyalty marketing professionals. I’m Paula Thomas, the founder and CEO of Let’s Talk Loyalty and also Loyalty TV. If you work in loyalty marketing, you can watch our video interviews every Thursday on www. loyalty. tv. And of course, you can listen to our podcasts, every Tuesday, every Wednesday, and every Thursday to learn the latest ideas from loyalty experts around the world. Today’s episode is part of The Wiser Loyalty series, which is hosted by our partners, The Wise Marketer Group. The Wise Marketer Group is a media, education and advisory services company providing resources for loyalty marketers through The Wise marketer digital publication and The Loyalty Academy program that offers the certified loyalty marketing professional or CLMP designation. I hope you enjoy this weekly podcast, The Wiser Loyalty Series brought to you by Let’s Talk Loyalty and The Wise marketer Group.
This show is brought to you by Comarch, a multi country leader in customer engagement tools that help you forge meaningful connections and boost profits, leveraging over 10 years of experience in utilizing AI technology. From immersive loyalty programs to captivating marketing campaigns, Comarch helps you deliver personalized experiences across every touchpoint. Gather valuable insights. understand customer behavior, and watch your brand recognition soar. Comarch, where innovation meets customer satisfaction. To learn more, visit Comarch. com.
Bill: Welcome, everyone. It’s Bill Hanifin from The Wise Marketer, and I’m here with Aaron Dauphinee. We’re here for another episode of The Wiser Marketer, where executive faculty members from The Loyalty Academy talk about different topics that are based on our curriculum from The Loyalty Academy. So, Aaron, how are you?
Aaron: I’m well, Bill. How are you doing this week?
Bill: Good. I didn’t I just didn’t want to blast over and not say hello. So welcome.
Aaron: Nice to see you again. It’s good.
Bill: Thanks for being here. So, these are really great. So, we, we try to bring subject matter expertise with a tie into the curriculum in our Loyalty Academy and cover a different topic each month. So, here we are moving into September. And the topic that we’ve chosen for this month is loyalty member communications, which is our course number 110 in the core curriculum that leads to a certified loyalty marketing professional designation. So this is one of our core courses. Uh, this one in particular, right?
Aaron has been refreshed with new insights and points of view about how to contact members how to communicate with members, how to provide the support that they’re seeking that they frankly demand these days and all the initiatives around that. And it’s got to be one of the most interesting areas, maybe taking it from back room what you would call a call center type of things to, right in the middle of the importance of building a relationship, so this should be fun. And in this. Weeks episode in particular, we’re going to talk about artificial intelligence. So it’s seemingly everybody’s favorite topic, but it has extreme relevance to the topic of member communications. We’re going to talk about the rising integration of AI into loyalty program, member communications with three use cases, essentially search segmentation and service and support. So we’re on track Aaron so far.
Aaron: Yeah, absolutely. That’s a great setup.
Bill: Good, good. So. Listen, I know last week you went solo and you introduced this topic of loyalty member communications by talking with everyone about the importance of communication and building strong and tenured relationships.
Yeah, there’s no doubt in anyone’s mind that without forms for engaging in dialogue.
For the sharing of information, and where there’s the ability to listen and gathering details back and forth between two entities. That could be person to person, or a person to brand or otherwise. Then, you know, without all that, there really isn’t much hope of developing a true relationship, a trusted relationship.
And I was listening to your podcast last week, and I, one of the things that popped into my mind right away was how quickly the world is changing in terms of trusted dialogue with the, this exponential rise of AI. Uh, it’s changing rapidly. So in today’s conversation, I thought perhaps that we could tackle a bit on the impact of AI on some of the key communication channels within loyalty programs.
So I’m going to let you kick it off.
Aaron: Yeah, no, no, thanks, Bill. I, um, I really like this topic for today, and I don’t think we’ll have enough time, obviously, to go into every channel and discuss the impact of AI on how it’s changing the game for for all of the different components of communication. Um, but, uh, you know, in the way that marketers can interact with their customers, and our loyalty program members specifically, we do have some thoughts on a couple top level, uh, areas that we’ll talk about today. Um, I think, uh, I think we can shine, as I said, uh, some, some light, I guess, in terms of these obvious channels that are incorporating AI and machine learning for that matter, ML, uh, and where we have market cases that we can help actually support and show that AI is being utilized by brands and we have some observance, right? It’s one thing to talk about it in terms of conceptual, but there are some real actual live market examples for AI being utilized, both good and bad. And as we always say, perhaps get into some ugly, I don’t know, but maybe we’ll try to focus on just a few of the good.
Um, but to level set quickly, I think, uh, because we never really like to assume that. I think it’s important to define AI so that everyone’s on the same page. And for me, the real industry standard for how to define AI from a number of years ago when I was at a machine learning shop, um, came, comes from a trusted technology source, which is IBM.
And so if you go to IBM’s website, they define AI as, you know, quote, a technology that enables computers and machines to stimulate human learning, comprehension, problem solving, decision making, creativity, and autonomy, end quote. And, uh, you know, if we think about it on an AI timescale, which, uh, IBM does a great job of outlining for us, um, they envision us in a series of quite nested or like derivative concepts, essentially, uh, that have emerged over the past 70 years.
And that’s right. I said 70 years. So in the 50s, it was the starting point for AI, where it came into existence, where we had human intelligence that was exhibited by machines. Uh, then we, uh. passed forward 30 years and brought us to the 80s, where we use machine learning, ML, and that’s AI systems that can learn from historical data.
By the 2010s, we talked about deep learning, which is machine learning models that mimic human behavior functions. And now in the 2020s, we have a focus, uh, which is probably on the tip of most people’s tongues around generative AI or gen AI, which is really deep learning models or, uh, that create original condo or foundational models in place.
So that’s kind of the set the stage. I just wanted to start there.
Bill: Yeah, well, I think you chose the right source for a definition being IBM, um, because it’s, it’s helpful for context for people. And I’m guessing that a lot of people are still thinking about AI as being a really new concept. I mean, we’ve been talking about it intensely for about the last 18 months, and people have been focused on it for maybe, I don’t know, what do you think the last 3 years?
Suddenly it’s coming to our consciousness and it’s just everywhere.
Aaron: Yeah, maybe a bit longer 5 and I mean, for some even longer 8 or 10, but for the general populace, probably the last 5 or shorter for sure.
Bill: Yeah, there you go. That’s fair. That’s fair. So just like you mentioned, 70, when you think about the 50s, 70 years ago. Oh, my gosh. Long time. So. Um, I bet what a lot of people overlook, and you think about IBM, because they’ve been right in the center of AI development over the decades. But do you remember in 1997, IBM had something called Deep Blue? It defeated the world chess champion Garry Kasparov in a six game match.
So that was this big, stunning achievement, and people really freaked out over the fact that a machine could beat a human, especially in a game like chess, and so that was a big kind of awareness step forward in artificial intelligence, but then you know what, do you remember, too, 14 years later, 2011? Another IBM computer. It’s about 100 times faster, apparently the Deep Blue. Yeah, what’s in went, ahead and you remember they beat the Jeopardy champion, right? So, I mean, if you want to bring something into the public consciousness, just put it, put it in terms of either sport or, or pop culture or, you know, you know, entertainment that we like in the, and that’s what IBM has been doing.
So you’re right. It’s been around a lot longer than we think, and it’s not a new phenomenon, but. It is one that probably only in the last, as you said, five, maybe 10 years, we’ve seen an adoption of the tools in marketing communications and now in loyalty programs, which everybody’s talking about. So, um, what’s interesting is that consumers, we’ve been running a lot of research about this lately.
Consumers are increasingly using AI tools to purchase products. Um, there’s, there’s some facts. You, you shared a research report with me the other day from Storyblock that has some pretty interesting that’s in it. Like 40 percent of consumers report regularly using AI services like chat GPT when researching products.
So, okay. A little bit less than half, but, but just about half that we’re almost at the tipping point. And, but 17 percent of that group said their top source of information was chat GPT. So that, that sort of thing. And that’s so sure it trails Google and Amazon, um, but it leads a brand’s website. So people are going out there using generative. Type tools to gather information and help them make purchase decisions. And, um, you know, on the brand side, if you say, okay, flip it over 63 percent of brands say that is already impacting their marketing strategies. So I think there’s huge awareness. Um, probably you’ll see also in some of these research reports that the executives are saying. We know it’s important, but we haven’t adopted it nearly as much as we should, or certainly will in the future. Um, and we saw one number here that 47 percent of brands indicated that AI will significantly redefine their SEO strategies. 20 percent saying that it will result in a complete overhaul. So we see massive investment in AI.
No doubt about that. Um, we saw one more, I’ll give you one more stat that. 78 percent of companies surveyed in this one that we, uh, the Storyblock report, they’re using AI and marketing content creation. 70 percent are already using it to research 67 percent in content, content editing. So, this, this is becoming the centerpiece of brand strategy, brand execution in in the marketing area and brands really need to take into consideration.
How both customers and program and from program members are also using the same set of tools. So it’s kind of an interesting comparison to see at which pace, you know, brands and consumers are adopting it, so I know you have some examples you want to touch on another channel.
Aaron: Yeah, yeah, no, I think it’s really good that we talk about content because that’s a common area where, you know, the general populace is thinking about using AI and, and the ability of search coming into it, like, that really changes your communication strategy when it’s starting to rise up, you know, above your own website and, you know, getting nearer and nearer to Amazon, even themselves, of the behemoths, of course, so that was really intriguing. I think we don’t have time, obviously, and interest to go into a whole bunch of these channels like we talked about, but I do want to kind of isolate, you know, two other areas that we think are very important, particularly for loyalty marketers as a whole, in terms of how AI is affecting communications and and the impact it’s having on your communications.
And so. Uh, I mean, you noted some AI impacts, uh, sorry, some AI stats on, uh, search, obviously. So that is one area. Um, the other two use cases in loyalty industry for me are near time customer scoring and segmentation. Uh, it’s called kind of a back office calculation to get to how you’ll provide relevance in terms of your overall, um, end results of communications and offer strategy and content strategy.
But then also the number two is customer experience, service, and support. And so. You know, when I refer to scoring and segmentation, what I’m talking about really is the machine learning based algorithms that can be applied to generate strategies, you know, including after optimization is an example to maximize your revenue from respective customer segments in the moments of interaction and and scoring models can now be dynamically adjusted based on the computation of these large volumes of purchase history and zero party data.
And then determining the propensity for lookalike behaviors that kind of emulate behaviors of preferred segment groups and your best customers. Like this is, this is a now thing that you can do. It’s just a matter of making the application. And so, um, so that’s what the second area, the third area that I just want to identify. And again, we’ll go into too much detail, but I just want to make sure that this is identified for folks is, is, uh, when we’re talking about service and support. And so I’m, I’m really referring to what I’ve seen. And this is my personal opinion. I hope you agree. Is it really a step change that we’ve witnessed amongst some brands and how they’ve integrated uh, AI and chatbots, uh, or AI powered communication strategies, uh, into their customer or into addressing their customer inquiries. And so. You know, a recent stat to give some stats back to you that I came across was that the new generation of AI enabled chat solutions and virtual assistants, they have up to 80 percent first interaction resolution, which is amazing. Like that. That’s come so significantly far and and natural language processing, uh, NLP or generated by and generated by they really combined, I think to be able to comprehend questions now much more effectively. And then provide suitable answers back to those questions that are at a brand level. And so when we say brand level product details, return policies, FAQ type things, et cetera, but also now at a program level.
So getting to account balances, tier status requirements, reward statuses, et cetera, so forth. So, so it’s come a long way and it’s not quite there, but I know you probably have, uh, maybe an example on that that you can share in terms of your experience.
Bill: I do. I do. And it’s just, I’m listening to you talking and a light went on a little bit because think about the fact that you.
Think about how much brands invest in their website, trying to explain their product, explain their brand, provide some kind of helpful information, maybe some education about products that they’re selling. And then if now people are turning to Chat GPT, or even just writing a, you know, the, the appropriately worded question in the search bar to get information that that’s becoming a preferred way for them to find out.
And so I just, you know, as you were talking, I thought, Hmm, lately I was looking for an ultra lightweight camping tent, and I thought, you know, You know what I probably would have done in the past is I would have known one or two brands. I would have gone and search there. Now you can just type in and say, help me find the best lightweight camping tent.
And you know what it immediately you get a definition of what that is. You get a bunch of suggestions. I think who this could really hurt are some of these aggregator sites that are trying to rank and and survey and say, let us tell you who the best ones are. And they have an advertising model, you know, the eyeball model.
Well, you know, it’s going to be a little bit less useful for you to go there, but that’s that’s one element of it. But the other one, I guess that the example that I can give you is conversational commerce that. Really it’s the, you know, the, the chat, uh, assistance that you get online, the AI enabled chat solutions.
Um, the 80 percent number intrigues me because as a consumer, I feel like it’s about 20%. Like I think that, and I’m sure the capability could be nearly a hundred percent, I think properly configured. And maybe this, the investment is behind the curve. So I think your 80 percent might be the potential, like, the indicative potential, the way it stands today, I somewhat feel like I do notice a difference.
So let me not be too critical. I noticed a huge difference between maybe a chat assistant even a year ago, even 6 months ago, now, um, depends on the brand. It’s not always consistent, but when you’re asking certain questions, can you not tell immediately? When the answer comes back with context, and it’s actually somebody talking to you that seems to know, um, what you want, you know, it’s not trying to funnel you into 1 or 6 options that had already had programmed in is, you know, effectively a call tree, but it was automated.
So, you know, you can tell the difference and you can see the improvement, but I still think in some ways, we have a long way to go.
Aaron: Yeah, I would agree with that. I mean, I think we’ve come a long way indeed. And I wasn’t really adopter of this particular channels to chat and virtual assistants to have solution because I like talking to a person on the phone, but the trees were always a challenge to navigate.
And they gave me frustration. So I was always a bit perturbed by the time I got to an actual person. So I had to always check myself. And, you know, a number of times I’ve apologized for it’s not you. It’s, The brand and the protocols in the process. And then I know you’re just the messenger, not the, the, the one who designed this and how many times I’ve had to apologize, it gets frustrating.
So, so going to chat, I started to get for basic examples. And those ones that I listed, I think it is resolving at an 80 percent level, but for anything with some element of sophistication, it starts to fail quickly. If the brand hasn’t invested in, this is a function of AI needs examples, and these use cases that are a bit, abnormal or different or unique to learn to be able to then get improved upon. And I think we’re still in the learning phase. And so I released an example quickly, I ordered, and this is like literally last week type of thing, ordered Uber Eats, which is a staple for me for COVID. I can still admit it. Um, ordered some food.
I always pay for the premium service because I want it to come directly to me. Cause I like my food as hot as it can relatively be when you’re ordering it. Um, and I don’t want it to take forever because I’m using a moment of hanger and hangriness to some degree, but it was clear that the because I watched the map on that type of person that the driver stopped along the way.
And so I took a look at the profile and you only had 86 trips. So I recognize easy. Okay, new driver doesn’t maybe don’t understand it. I send a message. No response went to Uber Eats to the chat function to say help and went through there and I got a automated system is very clear that it was a I generated, I answered, but it was triggered off of well they haven’t picked up your order, but they had picked up my order and they were in the answer was they picked up your order and they’re on your way so we’ll resolve it then.
that they had picked up my order, but the problem issue was that they had stopped along the way. So it was a unique situation that they weren’t able to look at. That chatbot then cut me off though. And so I complained and then in the same chat stream, a second AI with the exact same opening line came in.
So I got a second AI bot. So not one, but two. reiterated the issue, same, same resolution, exactly like verbatim, and cut me off again. So now it’s two times. You can imagine my frustration. I’m, I’m, I’m, I’m quick to the draw to begin with when it comes to customer experience versus being poor. And so I put that into the chat that I was very frustrated and disappointed.
And that’s only when did I get sent to let me set you and I put the words representative. That’s when I got sent to an actual human being. Now, the good side of the story is once I got to the human, they said, Hey, let me take a look at the chat because I had explained it now twice. And it’s going, I didn’t want to explain it the third time.
So that’s a win. They resolved it. They came back. They said, Yep. It looks like the person’s new. Not a problem. We, we’ve refunded you your priority fee so that that’s taken care of. Um, we know that it’s on the way we’ve messaged the driver. We’ll tell them about this educational experience. Thank you for being, you know, an Uber Eats, um, um, user customer.
And so, uh, the human element still comes into this. And so I think there’s a , you know, a long story for a short way of saying that, you know, AI as a, as a first response is great when the questions are really basic. But brands need to educate their models and systems to be able to identify when the actions, uh, uh, of the individual or the customer have some rising temperatures for them, right?
And so, uh, or the AI has an inability to, to comprehend what’s, what really the, uh, issue is, uh, that the customer has. So, you know, uh, a quick example of how to resolve that is at the end of your chat, did I understand your inquiry correctly? And if the answer is yes, then great, move on. If it’s a no, okay, well then maybe we just transfer you to a human.
Bill: Mm hmm. I think that’s what’s required, at least at this early stage of implementation. You know, the recommendation would be that there has to be a way for you to get to human a human being. If you really need to. Okay. Make you play the game. Um, you know, use the capabilities of what’s there. But, um, at the same time, you know, I think probably as consumers, we have to think about this is a time for us not to be shy whatsoever about sharing our experience, experiences, you know, where we get irritated, some of our disappointments, you know, we, we need to be able to speak up and then we need to hopefully the brands don’t make it too hard for us. If we type representative, we actually get one, or if you press 0, you get through, or there’s got to be some way before the top blows off the tea kettle where you can get to somebody and do that.
But I think that’s how they learn. And maybe that’s the. The smartest way to apply AI is let it be truly a learning process, right? So if you get feedback in real time, you know, take that natural language. Um, verbatim sort of response or however mean it might’ve been. I’m sure it was, wasn’t particularly mean, but maybe just frustrated, but, you know, take that and do something with it. Like understand what it is because that’s how the whole system gets better. So it’s fascinating. And we’re, we’re, uh, in Camino, as they would say, you know, in process. So that’s a good place to wrap up though. I think, don’t you think?
Yeah, I think so. Yeah, so, um, thank you for listening.
Thanks for being here for The Wiser Marketer. Aaron and I are here each week with a different aspect of a topic this this month, of course, on loyalty program communications for anyone interested in joining our community of loyalty marketing professionals. You can learn more at loyaltyacademy. org, but how are you going to earn your designation, the CLMP and join the thousand people across 54 countries around the world that are carrying that designation and are participating in this pretty vibrant community.
So if you want to dig into previous podcasts, you can access the Wiser Loyalty podcast series at thewisemarketer.com or you can certainly go to letstalkloyalty.com. Uh, with that, we wish you all a fantastic week. Look forward to talking to you again soon. Thanks, Aaron.
Aaron: Stay loyal, everyone.
Paula: This show is sponsored by Wise Marketer Group, publisher of the Wise Marketer, the premier digital customer loyalty marketing resource for industry relevant news, insights, and research. Wise Marketer Group also offers loyalty education and training globally through its Loyalty Academy, which has certified nearly 900 marketers and executives in 49 countries as certified loyalty marketing professionals.
For global coverage of customer engagement and loyalty, check out thewisemarketer.com and become a wiser marketer or subscriber. Learn more about global loyalty education for individuals or corporate training programs at loyaltyacademy.org.
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