AI: The CX Power Tool

So tell me, have you heard this lately: “Hey, we should be using AI in our program.” Yeah, I thought so. So, should we?

Every time you see a new tool comes out, my engineer mind says, I got to go try it out. Play with it. The first question is, what problem are you trying to solve? And it’s like, if you don’t know what the problem is. I mean, one thing I tell people again, new tool, experiment and part of experimentation is a way to brainstorm new and better ways to do things. And the tools with AI give you that.

How can we approach artificial intelligence as an effective tool for customer experience? On this episode of The CX Leader Podcast.

The CX Leader Podcast is produced by Walker, an experience management firm that helps our clients accelerate their XM success. You can find out more at walkerinfo.com.

Hello everyone, I’m Pat Gibbons, I’m the host of this episode of The CX Leader Podcast and as always, thanks for listening. We believe it’s a great time to be a CX leader, and on this podcast we explore topics and themes to help leaders like you develop great programs and deliver amazing experiences for your customers. Have you ever seen the old classic Alfred Hitchcock movie The Birds? You know, there’s a famous scene when a flock of crows attack a group of fleeing schoolchildren, swarming without mercy, terrifying everyone in their path. Well, I don’t know about you, but sometimes I feel like those school children when it comes to the topic of AI. It’s like everybody’s picking at us, “You got to use AI!” Okay, maybe that’s a little overdramatic, but how can we approach this technology in a way to have it meaningfully contribute to our efforts? My guest today is going to give us some guidance on how to navigate this question. Mike Miserendino is the founder and president of GravityDrive, an experience design consultancy group, and this is his second appearance on the show. Mike, welcome back to The CX Leader Podcast.

Thanks, Pat. Definitely. Thanks for having me back I enjoyed it.

Well, you know, you always have some great insights and everything. You know, we now have over 300 episodes of the podcast. But Mike you were on episode 46, November 27th, uh, 2018, and you shared thoughts on the intersection of CX and UX. And I actually went back to your take home value piece at the end of the episode. And your tip was to avoid egocentric design of experiences or, you know, designing for yourself. Seems like it’s still good advice. Do you think that still stands?

Absolutely. We got, you know, like everybody has a great idea for a product, but not everybody wants to take the time to understand that they are not necessarily the consumer of their product. They want to make sure that the audience is fully vetted to buy into whatever they’re making. And a lot of times we don’t do enough of that.

Yeah, yeah. So true, so true. Well, Mike, let’s let’s start off, uh, tell our listeners a little bit about your background in CX/UX. There’s, you know, you definitely have kind of an interesting approach and perspective on this.

Uh, sure. Uh, my background, uh, I studied computer science in college, but I was fascinated always with about the human experience. And I started reading about human factors, which is, uh, the origins of the discipline of user experience itself. Uh, back when I was a child, because I wanted to be a fighter pilot, joined the Navy, be the first, uh, you know, astronaut to Mars and, you know, studying anything and everything to do with aerospace engineering. And a big part of that was understanding the human factor, the person behind, you know, the controls in a cockpit. And it just evolved from there. And when I was in college, learned about, you know, writing software, creating algorithms and all kinds of great stuff to make products. But they didn’t teach us about understanding people. Ultimately, the product is going to be made for. So I took it on my own to learn about it and started implementing, uh, basically user experience practices within companies I work for. Before UX was a term, and it just became a, you know, pretty much the core of what I do. And I decided to, uh, form Gravity Drive back in 2015 was a 2000, 2008. I’m sorry. We’re. Yeah, 15 years old now. And, uh, essentially, uh, help people across the globe make better products by understanding their, uh, audience. And, uh, CX I think is a great partner in the sense how we there’s a lot of crossover. What we do in UX and CX and UX combined can be very powerful.

Yeah, yeah. I’ve met, uh, Mike, as we’ve attended some, uh, networking events associated with the CXPA or the Customer Experience Professionals Association. He always has, you know, a great, uh, great insights to share, kind of from a unique perspective. So. Well, Mike, you know, that, uh, you know, AI is kind of this hot topic that is brand new for most CX professionals, but you have a unique background and an interesting perspective, you know, is it really that new or what’s, uh, what’s been when did you start into AI?

Uh, yeah. It’s like that’s the thing is, like, I think a lot of people have the, you know, understand that it just came out recently because a lot of the products that are providing an AI means of, uh, either giving people initial access to it or are using it, uh, only became really more marketed in the last, you know, two, three years, I would say, you know, heavily and everybody’s hearing about it. But the stuff I learned about goes back to, uh, the early 90s. I belonged to a, uh, special interest group when I was in college about artificial intelligence and how we could use it to help design things. And the early disciplines were looking at ways to, uh, basically automate vehicles. And they had a vehicle that could drive about, I think it was max, it was like 35 miles an hour, but it had trouble navigating parking lots so that, you know, it was about the cusp of what we knew back then. And most of that was pattern matching and fuzzy logic that were all new things. But how do we employ that to make it feel and think like the human brain? And it was really fascinating. But I actually had an interest in what AI is. Uh, when I was a kid, uh, I read a story called Bolo by Keith Laumer, and, uh, the guy served in the, uh, both, I think the Air Force and US Army, uh, Korean War vet.

And he started writing this series of, uh, sci fi novels after he got out. But he had these visions of the future, and a lot of the stuff he thought about came up today, and a lot of it with AI and that’s where I first heard about it. And I was, you know, primarily pre-teens. And it just kind of inspired me to want to learn, especially, uh, my other ancillary interest is games, game design. And AI is a huge part of that when you’re doing computer games I always wanted to dream up, how do we make a better computer opponent?

It’s really interesting. You know, it. It is like a lot of things. You you think it’s brand new, but it’s really just gotten to a point where it’s become more mainstream and all of a sudden people are following it pretty closely.

Well, it’s more I would say it’s more available because because back in the day, like when I was doing in college, unless you had a mainframe, you know, Super Mini or some, you know, powerful machine to use it, you couldn’t do it. And a lot of technology today has become more democratized so that the, the average individual, somebody at home with her, you know, like a desktop computer to a mobile phone, you have now the power to access and play with it.

Yeah. Well, in regard to its newness and being a hot topic, everybody seems to want to jump in and see how it can work for them. Is is that the right approach? What what do you think? How do people learn about this?

Well, the it’s a good and bad, uh, one, uh, first and foremost, when every, every time you see a new tool comes out, I mean, I’m, I’m like my engineer mind says, I got to go try it out, play with it. And the main goal is I want to learn what that tool can do. I mean, even when I was a kid, I used to build stuff like I was taught by my grandpa how to use, like, you know, saw hammer nails, you know, whatever to make something, you know, like, because he was a really, really awesome carpenter and builder and I learned how to use my hands. Then I got introduced to power tools. I thought, wow, I can do more, faster and more efficiently and not get exhausted in the process of doing it. So tools like AI promise to provide efficiencies and ways of doing things that would take either a larger workforce or complexities that, you know, an individual or small organization may not be able to fathom. So I think it breaks those barriers down.

But the risk of using it is that simply, is it right for you? And some of the questions I would say I’d pose to somebody is like, for one, what is the problem it’s trying to solve? Because we have this thing going back to like in UX is that everybody wants to come up with something really cool and shiny, but they wait till after they developed it way down the road to actually, you know, find out is there an answer to a problem that this is building and AI is like that. So if you want to embrace it, is there truly a problem that you have in the way your customer experience is working to the product itself or even internal operations, how that might be looking. But the first question is what problem are you trying to solve? And it’s like, if you don’t know what the problem is. I mean, one thing I tell people again, going back to number one new tool experiment, and part of experimentation is a way to brainstorm new and better ways to do things. And the tools with AI give you that.

Yeah. Are there consequences of, uh, I guess, failure or, you know, trying it out with, you know, what, what happens if you try it out and you really haven’t identified what you’re going for?

Uh, yeah. I mean, the simplest thing like I’ve seen this in software development, too, is that when, uh, I worked for a company years ago and they had an idea for a really, you know, interesting product, the marketing team that did the initial market research didn’t really do an in-depth research. So when we got to the end phase of the project, we’re in final testing, getting ready to launch it. They said, oh, we can’t do it because the market’s changed or we didn’t really know the correct answers. And this no longer satisfies those answers. So you have a big risk that if you put any kind of effort into something like this and just, you know, put resources on it, is it going to give you an outcome that is measurable with success? Is it going to give you something that’s going to change perceived value of what product you’re selling or your services? And again, it goes back to understanding that problem. So that could be a risk is wasting resources and time. Uh, other things you get into which depending on how you employ AI, is like a lot of people don’t think about this as the, uh, privacy issues get into data security risks with identity. There’s a lot of things that, you know, impact it because it’s basically sucking up a lot of knowledge from around you in the world, depending on what tool you use to those that you can encapsulate and keep, uh, within the bubble of your company, not go outside. So you got to think about protecting that data. And that’s a huge one that a lot of people don’t think about until after the fact.

Hmm. You know, I think one common place is that people are just trying to better understand it. You know, it’s kind of like, you know, I know what I am doing in my job. I am sure there’s better ways to do it. I’m not sure if AI is a tool that can help me or not. Are there guiding principles that you would have for, you know, learning more about it, trying to discover how it might help you with the problems that you have?

I guess I would I would give a few based on my own experiences. Um, and I’m a, I’m an experimenter with, uh, technology. So if I see something new, I got to try it out. And for me, first, the basic thing is, even if I’m experiment, I’m trying to think of what problems could I possibly solve with this technology. So you may start out defining a clear objective. What do you plan to get out of the AI? If you don’t have a clear objective, you’re just kind of fishing around trying to find one. And just like product design today, a lot of products are basically, you know, fishing around for a solution. But they, uh, they don’t necessarily understand the problem.

And, and another big thing too is are you ready for it? Because do you have if you were to take this on, what would you be able to do to support the effort moving forward, like the, uh, the quality of the, uh, the way you use the AI, do you have enough knowledge internally to embrace it and, you know, maturity even more because it takes a different skill set. And that’s what’s interesting about AI. It’s generating like a new industry, a new industry of people that depending on what type of AI you’re using, if you’re an artist, if you’re using it for, uh, research or whatever you’re doing, you want people who have familiarity with those tools because the ramp up time can take some time. So are you ready for it? Some other things, too, are quality. A lot of AI today that I’ve played with and I’ve played with a lot of different tools. The quality of it is all over the place. For example, I love doing a lot of visualization, so I use a lot of visual design tools, especially Midjourney. I’ve been using that for a long time. Midjourney does the most amazing visualizations on this planet for AI. I mean, I’ve used a lot of Dall-E and a few others, but Midjourney does some great things, but it also has a lot of time you spend with it to try to teach it, if you will, what you’re trying to visualize.

So it’s kind of like this conversation between two different people, and you’re not quite speaking the same language yet. And even though it uses natural speak to engage Midjourney and other tools like it, that language is still you’re trying to figure out what how can I simplify it enough to even talk to it, to give it the proper prompt? So the the end goal is that you’re coming up with something that, you know, could be good, could maybe not be good, but the quality of it, you know, like even if you’re using it for research, you’re going to want to vet all that data you collect with an AI. You know, so like sometimes it may provide accurate information, sometimes it may not, sometimes, uh, it may produce things that seem like it’s hallucinating, you know, like you can’t possibly believe what it wrote up. Then other times you got to ask yourself, okay, before I publish this and put it out there, and we got this research done with AI, you know, did I check the facts? Are all the facts in this content, you know, actually accurate. That that’s huge. I mean, you know, I mentioned security privacy stuff before, but even the accuracy and quality of your data is going to matter. And that’s a big thing if you don’t know what to look for.

Yeah.

So let’s try to think of it in practical terms. Do you have some examples of where you’ve seen AI work well to meet an organization’s goal?

I got a bunch only because, uh, one, I’m actively using it for some projects now and some that I see coming on the horizon. Um, one that I am very excited about is with Serious Games. So you’ve heard of, like, you know, games that you play for fun. Serious games are intended to be very realistic or very much teaching a skill experience to go through. And we’re in the space of helping train, uh, first responders, military and so forth with, uh, basic things like firearm safety training to actual scenarios. And we have tons of benefits with, uh, this type of training. Now, this is a balance between not just AI, but we’re using primarily a VR simulator, and we’re adding AI to it. And with the VR simulator, we can create a space that one doesn’t require unlimited ammo. You can actually go in there and you don’t have to worry about, you know, the expense of ammo. But also you can put people in situations that it’s a safe environment to repeat and, you know, consistently provide training that helps them. But the AI gives us a component we didn’t have before. Back in the days when I trained with firearms, uh, uh, with the FBI. I did this a long time ago for, uh, emergency preparedness work. I do, and we went through a thing called FATS: Firearms Training Simulator, and it was a video based simulator, kind of like you’re on the holodeck of the enterprise, and you’re sitting in this big room, and the screen fits your peripheral vision. And I think we had three screens.

So you had the sides in the front, and you’re basically enacting scenarios with, uh, recorded video. It’s like the old Laserdisc games. And the thing was, is when you went through it, it felt real. And, you know, it wasn’t real, but it felt real. I could remember getting my heart rate going, my adrenaline going, and you get the shakes and everything, and it does make you feel like, what do you do in this intense situation? How do you act? However, we had instructors that were watching behind you and they would change the outcome of the video based on actions you take, the responses you gave either verbally, physically, etc. and they would respond to it. But that was a human being. Now we have AI versions of that where not only does the AI kind of replace that control, it does it more, uh, in a, in a faster, more natural fashion. So if somebody does something like stick their hand in their jacket, you don’t know if they’re pulling out a firearm or a box of cigarets, which is it? And it’s actually changing it up and doing all kinds of crazy stuff to simulate and make it more realistic in a way that a human response might be too slow. It also allows us to do multiple characters in scenarios that we couldn’t do before, because in order to do it, you had multiple people in each one of those, what we call non-player characters or NPCs. Those characters would have to be manually controlled by a human to direct it, to make it change its facial expression, etc.

the AI does this, so that eliminates it. So you can see a little details like eyebrows moving and stuff like that that makes you wonder what is that person thinking? Um, that’s just one big aspect. And I see this, you know, like being hugely helpful and giving us things that provide safer, more effective training environments. We also got I’ll just quickly give you a few more ideas that I’ve seen be really effective. Uh, a big one is print on demand. So if you’re not familiar with this business, think about whenever you bought a t shirt, um, even a notebook or anything when you buy something online anymore. Um, a lot of people look at a catalog or something like that and think, hey, somebody designed this really cool, you know, beautiful visual that I think would look great on a t shirt, and I can actually buy it on a t shirt. Well, a lot of the stuff is now being created by AI. There’s a lot of really good AI imaging tools.

Right.

And and I know because I used to I was an airbrush artist back in my college days. I worked at an airbrush booth, and I remember spending as much as a week doing one painting to make this beautiful, like photorealistic painting. And, and it’s like, man, that was great. And then we turn around, we charge the person who bought it for 25 bucks, and I worked on it all week, you know, so that that was kind of like, of course I was, you know, minimum wage, I was in college…

I can see why you’re not in that business.

Oh, no. Yeah. That’s not the business to make money. But with AI now you get an AI, uh, visualization tool behind it, like Midjourney or something like that you can generate, you know, literally in that same time, I could generate hundreds of beautiful images in that time, each one being unique, each one having a certain style. And you can help define it as you go and pick and choose what you want. But that industry has blossomed and it’s exploded because of AI. That’s actually been a game changer. Some other industries I see huge benefit are uh, with drones. So autonomous vehicles, um, I do, uh, search and rescue volunteer work. And one of the things that we started using a few years back were aerial drones to provide spotting, reconnaissance, you know, out beyond the reach of where we’re at or even in places we couldn’t get to when we’re outdoors. Now, the newer drones coming out have sensors built into them to do some amazing things, but they also have almost like a, like a human life form detector, if you will. It looks for thermal images. It looks for motion. Uh, I think some of them can do approximate size and, you know, speed. So all these things become like it can report back to you. You know that’s not a deer, that’s a human being walking down this trail in the woods, and we redirect our search crews to go find that person that direction. So that is huge. That helps saves lives. So that’s AI being used for something good. And I think those things coming out now, uh, I’m excited about it because it makes our job easier. Instead of like spending a search that could take uh, like we have like, uh, protocols for, like, one day, two day, three days. And to go from that to maybe measuring in hours or minutes, I mean, that’s my dream that we can actually find the missing party faster. That would be freaking awesome.

And those are amazing examples, because you really can understand the impact of how AI is really changing some of the things in our world that, uh, are, you know, awfully important, saving lives and so forth. For, for CX leaders I know there’s lots of applications, you know, something like, you know, take the contact center, for instance. Do you see or have ideas of how AI can be put to use in the CX arena in something like a contact center?

Yeah, I, I’d be happy to take it on. So thinking about like terms of CX, um, one that everybody or most people use, I think online would be familiar with that is a CX component where you think about it is the chat bot. And a lot of chat bots have switched from being kind of like a, a simple, uh, here’s a rudimentary bunch of questions that it went through that would just ask somebody almost like a sequence of events and you have like a yes no decision tree to go through it. And now they have AI powered chat bots that are more intelligent, where sometimes it’s hard to discern between is this a human being or is it an AI? And that’s really interesting. So that’d be the first and foremost thing that I’m seeing improvement, even though I got to tell you, I mean, just to be honest with you, I still as a person, I like getting a real human being behind, uh, the other side, because when I speak to them, either through chat or through a phone conversation, I feel like it’s more readily understood what I’m going through. So the AI doesn’t have the sense of the emotional component. So when you’re dealing with somebody in a high stress environment or something, that could be just they’re frustrated with using a product, it may not understand it or be able to break down that, you know, language, uh, about the emotional part.

It can get it if you speak to it clearly and succinctly. However, a lot of times when you use a chatbot or call in for help, you’re not happy. You’re not calling up to say, hey, you know, Acme Incorporated. You guys are awesome. I love you guys. No, it’s calling up because, you know, hey, your product sucks and I’m having trouble figuring this out. I need help. So the emotional component with the AI is still a tricky one. And I haven’t seen chatbots quite mastery yet. In fact, a lot of times they tell you, hey, hold on a minute, I’ll get the representative. Um, some other things I think were really, uh, key things that CX people would love and probably see benefit is analysis. So when we do like heavy qualitative analysis in UX, uh, it’s very similar. So in CX world, if you’re doing like heavy survey, uh component, you know, details down to like, you know, the questions and atomically throughout like your geo geographic data to base on, you know, people places, time, products, uh, all these factors that you put into it. It’s a lot of stuff to go through, and it’s very time consuming. I see AI is evolving to help with heavy with, uh, doing the analysis and predictive modeling in CX. And I think that’s going to be one of the big things in the CX world to help and be a game changer for CX products.

Yeah, those are great examples because I think, um, you know, it’s it’s one thing to hear about all these, uh, you know, great technologies and everything, but sometimes we’re trying trying to search for ways to use them as opposed to when is the right way to use them. And, uh, you know, not be something that we think can improve everything across the board.

Absolutely.

So we’ve gotten to the point in the podcast, Mike, where we ask for one tip, our take home value. If people are looking at this and they’re saying, I want to learn more, I want to apply AI, or I want to figure out how it can be a tool that could be useful as a CX leader. What is one thing that they could do that would help get them started?

Experiment. Experiment, experiment, experiment. So it’s the the hardest thing is like waiting for somebody else to come up with a cool idea and then find out, oh crap, that’s my market. I should have done that. And you never want to be in that position. So the best way to learn is, you know, experiment, take some time just to play with the technology. Um, the thing that I look at today that I didn’t have back when I was in college, I first started to see this technology or early iterations of it, is that it wasn’t something I could work on at home, and that’s the thing I missed. I mean, it’s kind of like, you know, I started trying to dream up ideas for how to use it. I couldn’t just go, you know, go to my mainframe and start playing with it. I mean, this is stuff the technology wasn’t something I could take home. Now that it is, we have free versions like ChatGPT, Midjourney and others. I encourage people not play with one, play with several, because each tool has its own personality, its own traits, its own, uh, benefits, and sometimes its own risks as well. But if you don’t experiment, you’re never going to know. And I’d say sign up, get on board with a free one if you like it enough, uh, change it up and get a paid account, because the paid accounts will give you benefits like security, privacy to, uh, more, you know, basically, uh, access time AI. But the the big thing is, if you don’t experiment, you’re never going to know.

Yeah. Uh, it makes a makes a lot of sense. And, uh, you know, it’s it’s one that there’s a lot of learning to be done. So you got to start somewhere. And that’s a good way to get started. Well, Mike Miserendino is the founder and president of GravityDrive. Mike, thanks for being on The CX Leader Podcast.

Thank you. Enjoy this very much. Always. Always. Pat.

Yeah. No, you got a lot of great information to share, and I’m certain that there are going to be people that may want to continue the conversation. Uh, is LinkedIn probably the best way if they wanted to reach out to you?

Yeah, LinkedIn would be great. If anyone would like to reach out, just, uh, send me a note. And if you want to connect, uh, feel free to do so. Uh, I do get a lot of random invites, but, uh, please, you know, just say, you know, hey, you heard about this? I talk, and I’d love to talk. Uh, feel free to do so.

Okay, great, great. And if you want to talk about anything you’ve heard on this podcast or how Walker can help you with your businesses customer experience, feel free to email us at podcast@walkerinfo.com. Remember to give The CX Leader Podcast a rating through your podcast service and give us a review. Your feedback will help us improve the show and deliver the best possible value to you, our listener. Check out our website cxleaderpodcast.com. You can follow the show. Find all our previous 300 episodes, our podcast series, a link to our blog which we update regularly, and contact information so you can let us know how we’re doing. The CX Leader Podcast is a production of Walker. We’re an experience management firm that helps companies accelerate their XM success, and you can read more about us at walkerinfo.com. Thank you for listening and remember, it’s a great time to be a CX leader. We’ll see you next time.