Fred Stacey: 0:00

If you're running a center and somebody comes running up to you, which probably has already happened, and say, What are we doing with AI if you haven't already started down this path,

Rick Denton: 0:09

customer experience wisdom, a dash of travel talk. We've been cleared for takeoff. The

CX Passport Band: 0:14

best meals are served outside and require passport.

Rick Denton: 0:18

Today's guest is someone I've known for a while. So this one, well, it's actually a little extra fun for me to share. Meet Fred Stacy, an honest voice in the world of contact centers and customer experience. He's got nearly three decades of experience across leadership, consulting, operations and tech. Fred's been part of the contact center evolution, really, from every angle. He's led teams, he's built systems, he's launched startups, and he's worked behind the scenes with vendors who are the ones shaping this space. Fred's overarching theme is one that many of us have as their focus right now, but Fred brings a practical layer to it, good old AI. But it's not just the hype here. He's successfully implemented at with practical use cases. Success, practical? Yeah, I like the sound of that. And if you're on LinkedIn, there's a good chance you've seen Fred's Monday videos where he brings a grounded take to all things contact center and customer experience. Fred, welcome to CX passport. It's

Fred Stacey: 1:21

about time. Man, it is about time. I don't know how we, you know, we let it take this long. Yeah, it's great to be on. I appreciate it. Man, cracks me

Rick Denton: 1:30

up that that's like, right off the bat. Hey, dude, you waited too long. Rick, and you're right. Why don't wait too long. You know what it was? Because we just were having good old conversations and realized, oh crap, we should hit record. So today we're going to hit record. And there was something you had said to me in one of those earlier conversations. You'd said that every center that you've been at is exactly the same and fundamentally different. Tell me more about that. How can a contact center truly differentiate for their customers and their customers? Customers, yeah,

Fred Stacey: 2:01

and what I've said that a lot to a lot of people, so it's funny, you picked up on that, you know, fundamentally, it's still the same exact center that I started in when I was 19. We were using green screen applications, and the center was about, you know, making or taking a phone call and communicating with a customer or prospect or, you know, depending on whether you're inbound or outbound, that fundamentally hasn't changed. I you know, every center is full of agents and supervisors and managers and trainers and quality assurance is still there, even with AI, you know, a all of these things are, are still fundamentally the same before I got into the technology side. As you know, I ran centers, right? You know, I was an agent, and then I grew into leadership, and I ran centers and helped companies start ones, and I did a few restarts or recoveries, whatever you want to call it. And the one thing that became very, very obvious to me is, show me a successful center, and I'll guarantee that most of the middle level leaders, the floor level leaders, supervisors and managers, are really good at coaching, working with agents. That's still the same, and it's still same across the board, but every single center is a little bit different, because they all have their own processes. They all, you know, if it's a BPO, it represents multiple different types of verticals, products or companies, you know. And everyone is is has unique nuances, you know. And there's also no standard with a lot of the platforms, even back in the early days of just, you know, a handful of call center. Back then it was call centers. So there's always been, there's always variations. You know, everybody's a unique butterfly, but at the same time, it's all fundamentally the same. You

Rick Denton: 3:52

know, that butterfly examples hits me, because, yeah, butterflies are pretty darn different. If you look across them, yet, they're still butterflies. So we can kind of get that concept there. You said something, and I promise, I want to come back to it, because you talked about the coaching element being the key to the sort of the success differentiator between being same but different. But I can't, I can't wait to talk about this overarching theme of AI, and I know that we have been talking about this in the kind of common space for quite a while now, and then it's been going on for decades, of course, yeah, the real key here, though, is that we've gone through that hype cycle. And it's one thing to say I've implemented AI, it's another thing to be successful at it. You've seen the implementations. You've seen successful implementations. How can a company know before they even get started that they're AI ready for these implementations?

Fred Stacey: 4:46

Here's the beauty there. There are tools out there today. There are products that you can deploy successfully and get a return on investment today with artificial intelligence, the way they train and tune the way they. Grab data and ingest it, you know, for that training that's all advancing at the same time. So, you know, there are absolutely tools that you don't have to do a lot of work in preparation for, you know. And I'll give you and the audience an example, you know, conversational analytics. We've had voice analytics for a long time, that's not new. What is new is conversational leveraging, you know, the more modern NLU, NLP, you know, natural language understanding and processing, you know that really allows it to be significantly more accurate. You know, now, in order to get ready for that, if you're doing POST call analyzation, you know, even if you've got an old premise based system, you can technically analyze those, those recordings, but, but there's always a but, they're, they're a bit mono. So, you know, single one, single recording. And you know this from being a podcaster, you've got voice tracks right for both you and and the guest, right? Whereas with the, you know, the old systems, it was the one single string. So the system has to it's called diarization, where it splits and it tries to accurately predict which ones are the agents and which ones? And then it does it's, you know, analyzing. Why would you need to do that? I mean, sentiment, you know, versus agent versus customer, critical information. You know what's valuable for the actual customer voice. You know that obviously has to come from the customer's side. So, you know, you get, you get, you lose some accuracy enough to make a pretty big impact. So, but if you're going to do live Analytics, you have to have stereo modern APIs. You have to be able to break in and, you know, analyze both voice paths, you know, in order to deliver it. So, you know is, there's, there's some things that you have to take steps for, you know, if you haven't moved from premise to cloud yet, which there's a lot of it out there.

Your CX Passport Captain: 7:12

This is your captain speaking. I want to thank you for listening to CX Passport today. We’ve now reached our cruising altitude so I’ll turn that seatbelt sign off. <ding> While you’re getting comfortable, hit that Follow or Subscribe button in your favorite podcast app so you never miss an episode. I’d love it if you’d tell a friend about CX Passport and leave a review so that others can discover the show as well. Now, sit back and enjoy the rest of the episode.

Rick Denton: 7:39

if you're not in that world, but it's true of almost any business that especially if it's been a long running business, technology upgrades can be hard to do, costly to do, and so legacy technology hangs on for a heck of a lot longer than you expect, right? There are still green screens out there, and even when I was in the banking world a decade ago, there were still green screens, and that seems shocking to think about. And so that that element of knowing that you're ready. Does the legacy technology make it easier because, oh my gosh, it's so old, we've got to replace it. Or is it more difficult because there's that albatross of the legacy technology holding you back as you move forward?

Fred Stacey: 8:24

That's a great question. I like that you went here. Okay, so there are two things. I'll tell you a quick story, because I love stories. You know, when I used to when I took over Europe, Middle East and Asia, our operations were in the Philippines for our Asian market, and I flew into Manila, and the second I landed and got into anywhere around Metro, Manila, I had 3g on my cell phone. I don't I hadn't ever had 3g unless I was in like LA or San Francisco or certain big places here in the country, right? And the reason I tell that story is because sometimes it is a heck of a lot easier to jump from nothing or antiquated to modern than it is to actually take the steps that we have here in the States. Because we had all this fiber, or we had all this copper, you know, we had all these DSL lines, you know. We had all this stuff already laid and we had towers built and three to get 2g for us as a country, was a huge project, whereas in the Philippines, they were throwing 3g satellites up on the the glass towers. Sometimes there, there is an advantage, because you can skip straight from 20 year old tech straight into modern technology. Now, does that help with artificial intelligence? We all know that, you know AI is good as the data that it ingests, right? That's

Rick Denton: 9:56

what's coming to mind is, does that legacy make it harder when it comes. To the suggestion as a as opposed to, hey, I don't have anything it

Fred Stacey: 10:04

could it very well. Could, you know, it depends on what the company's done to kind of prepare move did if they left it in their legacy SQL system, you know, with only structured data really, to analyze no good meta tags on the recordings, you know, there, there can definitely be some negatives, I mean. So I would say it depends if an organization has really taken their, you know, their data normalization and structure and build outs, you know, if they've taken it seriously, they might have already overcome this. So just it, just like every again, every center is the same. But you know, all of them are different,

Rick Denton: 10:45

because you've seen so many of those. If, if I'm a company and I'm seeing all the hype, of course, I have to get into this. Or perhaps my CEO is saying you have to get into this. That's how can I know if I'm that leader of the contact center, how ready I am? What are some of the things that I should be? Almost like a checklist, or whatever that looks like. When you're advising a company, how do you help them know you're ready? Or Hang on, you got some homework to do. It's

Fred Stacey: 11:11

still about people process, then the technology, right? So people change management. You know, have you clearly defined for your agents, your supervisors, your managers, what your AI strategy is, how do you engage them, get them involved. Normal human change management process still needs to be taken place. A lot of centers do not do this. A lot of companies don't do this. When it comes to new technology, it's nothing new, right? It's still you got the processes, you got the people, the change management, the culture you know, are people willing to adopt? Does you know, have you communicated well? Are the agents sitting there scared you know that they're going to lose your their job because you're bringing in conversational analytics. You've got to have the the process and documentation you know, in order to get to you know, proper knowledge management would lead you into agent assist guidance and artificial intelligence, and you know some of the orchestration layers to have, you know, to have your processes documented is important. You gotta be able to teach the system somehow, you know. And you can either manually talk to it and or type it in, or you can ingest digital documents, and, you know, train it on those processes. And then, of course, the technology, which is, you know your data, your infrastructure, you know the build versus buy conversation, you know which is used to be a very small conversation on whether or not we build. But with modern technology and artificial intelligence and development, you know, and the speed at which you can build a new product to 80% you know, the the APIs in the modern world of integrations used to take, you know, weeks, if not months, to get the developers to actually sit down and do the right testing and get it deployed. Now is like, you know, an hour to if it's decently documented, there's all three paths that you have to do. Then let's talk about, you know, the what you mentioned, the CEO or the board demanding that you bring AI into the company, if you're running a center, and somebody comes running up to you, which probably has already happened, and say, What are we doing with AI? You know, if you, if you haven't already started down this path, that's okay. There are point solutions that you can get at, but you still have to do the whole work. A lot

Rick Denton: 13:40

of times when it's the Here's what's next, here's what's new. It's good to you know, let's focus on what has been there Well, since the beginning of human history, humans, and I've said I wanted to come back to it. This feels like the right time to do that. You talked about the coaching aspect of that, and coaching often as a pejorative, I mean it in the very neutral sense. How can you help someone do better at what they are seeking to do better, right? No different than an athletic coach. How can AI be used to amplify that, not replace it? But how can it be used to amplify that so that those who are the coaches are helping those that are being coached in a better way, because AI often has that scary, ooh, anti human vibe. How could it be used to help this very human thing of coaching?

Fred Stacey: 14:29

Yeah, so let's take it down to the floor level, and let's talk through it. So, you know, I mean, typically, you're at a one to 15 ratio, where one supervisor to 15 eight, right? So historically, you know, pre I mean, even with voice Analytics, you weren't doing 100% to the coaching, the reviews, the scorecards, whatever you want to call it. So QA only touch maybe 1% right? So artificial intelligence, the first thing that it does is it scales it to 100% you can. 100% score really accurately calls on your floor, period. And then with that data, you can then kick back out. You know, what are the common misses? You know, where, where can someone work and but some, some companies are also focusing on the agent experience. They're listening to the agents sentiment. They're understanding the agents behavior and recognizing patterns for potential risk of churn. You know, so understanding there's your high performers that can burn themselves out, and you definitely don't want to get them, you don't want to let them turn right money. You know, anytime you see any chance of burnout, you know. And you start working with them and understand what's going on. And then you've got the other side of the spectrum, where you've got your bottom, you know, let's say 10% you know. And you see them hitting that stage of natural churn, you know, that you're going to have to replace. And it helps HR and hiring and artificial intelligence in general, what it what it really gives is the human scale that they've never had before. Yeah,

Rick Denton: 16:09

and if I'm an agent on I think I would want that, because, sure, there could have been some cherry picking in the past of, hey, go, Listen to these goals. But in general, I would imagine that as an agent, there's times that I would have experienced, yeah, no, I know that call sucked, yeah, yeah, but I was angry the customer was a dick, whatever it was. Did you not hear the 99 other calls? Now those 99 other calls are in play, and an agent can feel like that. They were truly evaluated and understood. Fred, I want to take you out of the AI space. We need to take a little break here. Okay, you mentioned the Philippines. I also know that you're a pretty solid Global Traveler. Have been continued to be so, and I love talking to folks that have traveled the globe, especially in the context of customer experience, not so much from a business perspective, but what have you experienced as a customer. When you've traveled the globe, where are the expectations around customer experience? Where they've been different, where have they been same as compared to what you expect here in the US,

Fred Stacey: 17:14

I struggle here in the States. I think we've lost customer experience at a lot of levels, but when I was terrible. Go globally, it's so interesting. So the hotels, first of all, let's talk about the travel experience, right? If you've traveled and flown on some international airlines, the service is amazing. The hotels internationally, I've had nothing but amazing experiences. But yeah, I mean, I've had nothing but great experiences. Love love traveling.

Rick Denton: 17:52

Fred, I too, love traveling. You also mentioned some destinations that are quite a long way away from where you are, there in Colorado. Yeah, it's nice to take a little break in the first class lounge when you get that opportunity. So I invite you to do that with me here today. We'll move quickly. Have a little bit of fun here. What is a dream travel location? From your past?

Fred Stacey: 18:12

From my past, Athens. Athens was absolutely amazing, and I did that one solo, and I walked up down the street to Acropolis, you know, pass through this temple. And, you know, I mean, I did the whole walk by myself. And, you know, just contemplation, and you know, considering where you're at and the path that you're walking that the, you know, millions and millions of people had made over history.

Rick Denton: 18:43

Yeah, there's something about that walk, the contemplative walk, that is such a delight when it comes to travel. What about looking forward? What is a dream travel location you've not been to yet?

Fred Stacey: 18:54

There's a few I, you know, I never made it to New Zealand or Australia. New Zealand in particular. I'm a, you know, those that really know me, I'm a geek, you know, I grew up reading Tolkien, and then they, they filmed, you know, Lord of the Rings in New Zealand. Just some of the scenery there. I would love to see that. I

Rick Denton: 19:19

too, want to get down to New Zealand and Australia. That's one that I've not had the opportunity to yet, but I sure hope to someday. What is a favorite thing of yours to eat?

Fred Stacey: 19:29

Steak, grass fed beef. I spent a lot of time, you know, lifting and the part of fitness and health awareness is also the food intake, right? And steak is the most complete food that anybody could eat. And I make

Rick Denton: 19:51

I love steak, but that felt like brought to you by the the beef ranch Association of America. But yes, I do love a good, good steak. Ache as well. Other way here, Fred, what is something you were forced to eat growing up, but you hated as a kid,

Fred Stacey: 20:07

liver and onions, my old man, you know, I don't know how he ate that, but, yeah, I was forced, you know, really once, maybe twice, but I still remember the texture and the smell and the I and I can't do it. Yeah,

Rick Denton: 20:24

that's one that's come up a few times, and it is, I think there's some generational element to it, that there was a generation that valued it, enjoyed it, and celebrated it, and our generations like it's disgusting. So I'm with you there. Time for us to leave the first class lounge here. Fred, what is one travel item, not including your phone or your passport that you will not leave home without?

Fred Stacey: 20:44

You know, the one thing I will never leave without doing is, is packing a couple of extra of the underwear and socks, right? I mean, when you've traveled enough, you realize that little extra space, it's okay, everything else I can I can live without.

Rick Denton: 21:09

Yeah, there's something about the security of just that one extra pair of draws, that extra pair of socks, and maybe it went for a run that day and they got a little little sweaty, so I need a fresh pair. Yeah, I understand that absolutely. Fred, going back to AI, there's a we hear kind of almost this monolithic AI, and this is how you use it in your company. And you often hear things like, Amazon's got this incredibly high AI technology customer response rate. For me, right when I've had an order go awry, the answer is usually a very quick, easy refund or a credit, just something very simple, very technology, well, that works for a beast like Amazon. Should that same objective apply to a company that's well, not Amazon?

Fred Stacey: 21:56

Well, you know, I think, I think a company decides its culture and and hence defines its experience that it looks to achieve, right? You know, Amazon didn't start out like this, right? They were a book, you know, online bookseller, right? It just Bezos was smart enough to to realize what his product was and what his differentiator was, and to continually, methodically drive the product to be the perfect experience. That's the thing that people miss when they use Amazon, and I do it too. Amazon, it's, it's not, yes, they're, they're customer teams, their support teams, all that stuff. Those are absolutely essential, but they've continually improved the front end of the experience, which is their product. You know, same day, next day, delivery, on time, packages. What they do? You know, they started putting up facilities everywhere. They didn't just get there, though. This is not like somebody magically opened up and he was like, here's the model, right? You know, he had rules about right? You know, teams, size of teams. You know, efficiency, customer always coming first. And he built that into the culture. Now, that may not necessarily be right for everybody, right? And that kind of level of automation and efficiency on the front end, if you're an experiential company, you know, you want people to come in. It's not about getting them in and out. It's about giving them the experience that you come in, you know. So you're building differently, right? But in the end, are, should everybody be looking to automate as much as possible? Well, if, if you're an executive, your fiscal responsibility to lead your company is to still continue to allow the company to have more fuel, in other words, money to grow the organization. So of course, you should be figuring out within your culture and within your vision and mission and delivery you know how to automate as much as possible, and yeah, so yes, everybody should be looking at that, but within the guise of yeah, they're the way that they expect to treat customers, and you know, the experience that

Rick Denton: 24:13

they're building, yeah? And when you're saying that, I'm thinking because you use the word experiential company, and of course, I'm exaggerating here, right? But Viking Cruises, which sells itself as a high touch, high luxury travel experience, probably would not benefit from automating a whole lot inside of its trips. Now, maybe automating some of the front end, the back, that kind of stuff, but when it comes to the actual trip itself. I don't know that automating necessarily is where they'd want to be. And finding to your point, what is it that is their value? What is it that their customer values? And go after that rather than just arbitrarily saying, I need technology? What. Close out with this. And I know it's kind of closing on a negative, but I think you'll find a way to spin this. Yeah, you have seen plenty out there. The Good, The Bad. What are some of your Fave hey, we deployed AI, it failed. Now we're back in the market stories.

Fred Stacey: 25:15

You know, I never want to hear that. Look, hey, but it's

Rick Denton: 25:19

good for you. You're probably the one. They're like, hey, Fred, it failed. Can you help me out? Sorry,

Fred Stacey: 25:26

we should have listened. I love that we've been failing at this stuff for a long time. If I take you back, you remember when Watson, when IBM came into the contact center market and said, AI is ready for the contact center. And we ended up building a supervised based, or supervised learning based, chat bot back then. We're talking 1415, years ago, somewhere in that neighborhood, and we failed, you know, and continually, we have seen artificial intelligence technologies be, you know, pitched as ready. I'll give you some examples that I thought were, were shining examples of why not, not taking your time and understanding the implications of a technology like this has done significant damage and and what to do? You know, we'll we'll make it. We'll end on positive, I promise. So there, one of the examples that always sticks in my head is about, I'd say, early first quarter of 23 post chat GPT launch. Somebody launched an LLM bot that they were a.org for an eating disorder hotline, okay? And at first it worked, right, but then all of a sudden, over time, it started to tell people with eating disorders to just not eat. Oh, no. So we're in a world now where your IT team, right now could be developing and testing and using these technologies without guard rails. There's so many failures in our history with AI in this industry that, you know, I mean, you could anybody. Could name, yeah, probably 100 of them. And the the one

Rick Denton: 27:23

that story that you're sharing there, because I would say the one that I think a lot of folks came to know was the person who negotiated a car with a bot and got it for $1 whatever the the story was, right? That's haha. And we can kind of slough that off as a Oh, yeah, look, oh, it screwed the company over. Yeah, what you're describing can actually be a life and death situation, and I think that I'm glad that you shared that story, because it is a reminder to me and a reminder to our listeners that this isn't just sort of economic business. It is, it is, and there can be real, honest to God, life and death elements to this, with the misapplication of AI and something as simple as a chat bot. Fred, I'm glad you brought that example into this. Fred, this has been a wide ranging ride, and that's the way I like it to be. That's the way our travel should be. On CX passport, if folks wanted to get to know a little bit more about you, your views on customer experience in general, your views on AI in specific, or hey, just where's the best restaurant in Manila, how should they get in touch? So

Fred Stacey: 28:32

LinkedIn is always your best bet. Some people use, you know, all kinds of social media stuff like that. I'm LinkedIn.

Rick Denton: 28:40

Enjoyed this. I enjoyed learning kind of about AI in general. I certainly appreciated the discussion around, hey, don't do it until you're ready. And here's the things you need to consider to be ready. And absolutely, as we ended there, talking about, look, this is real. And if you if you bleep it up, you could really screw things up, not just for your company, but for another human out there. Fred, I'm glad you took us to that that level. It's been a good one. Fred, thank you so much. Thank you for being on CX passport.

Fred Stacey: 29:10

Yeah, thanks for having me.

Rick Denton: 29:16

Thanks for joining us this week on CX Passport. If you liked today’s episode I have 3 quick next steps for you Click subscribe on the CX Passport youtube channel or your favorite podcast app Next leave a comment below the video or a review in your favorite podcast app so others can find and and enjoy CX Passport too Then, head over to cxpassport.com website for show notes and resources that can help you create tangible business results by delivering great customer experience. Until next time, I’m Rick Denton and I believe the best meals are served outside and require a passport.