Max Clark: [00:00] I press the record button, don’t worry about it. I just do it so that way I don’t have to think about it again. Um, there’s, uh, I had hired a producer years ago that wanted to do these things, like in seasons, know, and try to do like, um, you know, like, oh, let’s do a season of this topic, you know, and,
Brent Wilford: see.
Max Clark: and no offense, but like, if you talk about CCAS for like 15 episodes in a row, like, I, I, you know, I wanna kill myself, right?
So, a lot of it just comes down to scheduling, you know, like how do things get scheduled? We, we run a very straightforward FIFO kind of thing first in, first out, you know, um, and, um, I’ve got, you know, a big sprint before the summer break and then a bunch already scheduling in, in, in August. So we come back and forth. Um, let’s see, what else should I tell you? Um.
Brent Wilford: put that cat in another room or are you gonna take an over under?
Patrick Russell (Glia): Well, it’s ’cause I just got home. So they get, they want a cat tax, they wanna get paid and some treats and stuff. And I, I gave ’em like shit load like way more than usual. And, uh, that she’s, [01:00] she’s just kind, she’s kinda the boss of this house. So. And there’s another,
Brent Wilford: uh, we, we have a cat too, and she tells the three pit bulls what to do.
Patrick Russell (Glia): yeah, there’s a, another one I’ve got calling back here. So
Max Clark: Um, last thing, last thing I should say, and this is, goes in the preps. Um, this isn’t a channel podcast, right? Like, I’ve had a couple people on that all of a sudden think they’re doing a commercial for like, channel agents. It’s not a channel podcast. You know, the audience is end users. We use this with, with actual end users of like, hey, know, I mean, like literally I’ll been in a conversation with somebody and say, Hey, go watch this podcast and talk to me if you’re interested about it.
You know, like we can get into more details. So, so
Patrick Russell (Glia): is it end users and channel or, or just end.
Max Clark: channel will watch it. I don’t care, but like
Brent Wilford: I
Max Clark: that,
Brent Wilford: would consider it primarily end users.
Max Clark: I’m not, I’m not a TSD, I’m not trying to sell to a channel agent
Brent Wilford: If
Patrick Russell (Glia): Yeah. Got it.
Brent Wilford: it’s ’cause they’re trying to steal
Max Clark: that, you know what? I don’t watch it. Great. You know, like, this is not.
Patrick Russell (Glia): I’m trying to do something to get her to leave [02:00] me alone, but
Max Clark: She is not gonna leave you alone. ’cause now she knows you don’t want her around, you’re
Patrick Russell (Glia): yeah,
Max Clark: Um, let’s see here. Normally I would, I would say everybody get down, do 10 pushups, get the blood glowing, you know, because, uh, um,
Patrick Russell (Glia): if I could,
Max Clark: uh, otherwise if you don’t have any questions, we can, we can get, we can get cracking.
Patrick Russell (Glia): let’s do it.
Max Clark: Um, let me see here. What else do I want to ask you guys? Uh, and I, if I remember, uh, Marissa wanted to talk about a Heritage Federal Credit Union. guys on board with that? Right?
Patrick Russell (Glia): Yeah. Mm-hmm. Yeah.
Brent Wilford: Heritage you.
Max Clark: Okay. Um, okay. Lemme think about how I wanna start this one off. I usually try to write a script out a little bit, but I didn’t do that with this, so we’re just gonna wing it. Um, you know, in, in the words of Bill O’Reilly, we’re doing live.
Brent Wilford: Fuck it. We’ll do it live.
Max Clark: it. We’re gonna do it live. We’re gonna do it [03:00] live. I mean, can, I mean, I can’t, I just
Brent Wilford: up.
Max Clark: like, you just know, like I can just, I can just imagine like where you got to that, that’s just what happened, you know, like it’s just,
Brent Wilford: How many times they recorded something and he just got
Max Clark: oh, it’s like Christian Bale freaking out.
He’s in some like, really intense scene and there’s some like lighting guy going like, turn the light on and off of him and he just, you just like lose your mind. What do you do,
Brent Wilford: was one other one, there was a, I forget, it was like a really, really famous like act like, like a Brando kind of thing where he did the same, he did, you know, something similar. And there’s a lot of like Shatner doing that stuff.
Max Clark: Oh, for sure.
Brent Wilford: me how to, how to do it. Okay. Well, let’s hear you do it, you know?
Max Clark: Um, okay. Uh, and we obviously can name this company by name so I don’t have to, I don’t have to bite my tongue on that one. Um. The best thing about this case study that you guys have on your website is this nice little corner image of the, one of the branch locations with like the [04:00] FedEx truck and the reflection. So it’s like, you know, fed Federal Express.
Brent Wilford: a quick one.
Max Clark: Um, okay. So, okay, I’ll just do it this way. Um, Brent Patrick, thanks for joining. Um, we’re gonna have a conversation, talk about, uh, a credit unit, heritage Federal Credit Union, and, um, would be great. Let’s just start at the top, like,
Brent Wilford: Okay.
Max Clark: like what, um, background story, quick overview before you, before you started talking to Heritage, what was going on?
Where were they at? You know, what was, what was the observation that they were making about their business?
Patrick Russell (Glia): Yeah, so they were using a legacy CCAS providers technology, and they were also going through, at that time a single, um, merger acquisition, uh, but which would end up being multiple, uh, mergers and [05:00] acquisitions. And they recognized that that time that the technology that they were using was not going to, um, deliver the results that they were targeting as a part of this merger.
Um. And so they started, they started the, the search for the, the correct technology provider. And, and for them it was, from what I understand, uh, after talking with them a lot is, uh, it was a pretty exhaustive, uh, search and discovery processes and all those kinds of things, examining different providers and, uh, eventually they ended up landing with Glia.
Max Clark: Okay, so what I, uh, not meaning results, like when you say looking, their technology is falling short.
Patrick Russell (Glia): Mm-hmm.
Max Clark: Specifically, what does, what does that mean? Right? Because there’s like the, there’s the technical answer to that question, and then there’s like the business answer to that question. So, you know, are we talking about, you know, callers not being able to get through, agents not being able to work?
Like what, what was the disconnect that they were having? Mm-hmm.
Patrick Russell (Glia): it’s a great question. I mean, a, a lot of it is that they, they had needed a very [06:00] strong digital offering. They needed that digital engagement, you know, financial institutions, all of us, I would imagine first engaged with our banks through some sort of digital engagement on the website. Through your phones, whatever it is chatting in.
So they needed the provider to be very strong in digital, which has historically not been a strength of a CC, A provider in that they all were born in a voice and in, in a, a telephony based environment. And for most of them, I think all of them, perhaps they, they acquired their way into the digital. And that created kind of a fragmented experience for the agent and for the end customer when engaging with those businesses.
Max Clark: Digital experience has become this, um, I, I really hate all, like the buzzwords we get into, right? And so, you know, digital experience is definitely one of those things that we talk about, right? And it’s, but it’s, it’s, you know, it’s true in the sense of like, your customer is trying to interact with you in some manner, [07:00] and the customer interaction and how the customer wants to interact with you changed and expectations have changed with this, right?
So now this, this whole thing, we start talking about like digital experience. You know, a couple years ago we earlier talked about like omnichannel or multichannel, right. And, you know, and that was more like, you know, can your contact center take voice and text and chat and SMS and WhatsApp or whatever the difference, you know, things are and, and, and seamlessly, you know, move from one environment to the other with the, in, with the customer.
Right. And now, so how does that, how does it change, how does the conversation change from, you know, omnichannel into now a, a, a digital for, you know, digital experience is like the first or native out, you know, uh, outreach or approach
Brent Wilford: the, um, I think that, know, I’m gonna have plenty of terms for you coming up here,
Max Clark: please. Ac I love acronyms. Throw ’em at me.
Brent Wilford: Looking at the context in our world in general, right? Patrick’s right, it all started very voice first. ’cause that’s the primary means of communication. We [08:00] all relied on growing up several decades ago, but as website, you know, became very popular. As people go there looking for information, someone’s on, someone’s on a website, trying to buy something, trying to acquire more information, trying to make a decision and forcing them to call an 800 number or even a local number and wait to talk to a human being is just not the way people expect customer service to flow.
Today. They’re on a website, they’re on a digital property. They’re looking for an immediate answer, because that will translate to a buying decision generally. multi-channel was the, we have all these channels, but they’re very separate, right? They don’t interact at all. So if you chat here, can’t connect it to a voice, can’t connect it to a video, right?
They’re all, they’re all, uh, siloed and bifurcated. Omnichannel is the definition of omnichannel is, was meant to be that those are all now connected. So I can take my voice call and I can layer on chat, I can layer on SMS, and I can layer on video seamlessly between the agent and the customer. But even then, as we know with, even with cellular, like [09:00] 5G, 4G, right?
Marketing terms get conflated with reality a lot. Marketing says one thing, but the experience for the end user is different or less than unfortunately. But the glia, um, channel this architecture, right? What we offer is really what omnichannel was supposed to be or what was promised from the contact center industry. So when a customer is calling in or chatting in, or however they’re reaching, right? They’re on a website and they’re at a digital decision point, they’re trying to acquire something or get information to acquire something, meeting them at that website, offering service, offering a communication pathway where they are as opposed to forcing them to go somewhere else. Is really where Glia succeeds and kind of what Heritage and other banks and credit unions that come to Glia are looking for. They have a PBX in the closet. They have an old voice system that they’re just gonna run into the ground, right? Because that’s the way they’ve always done it. But younger and younger customers are going to the website looking for information and they don’t want to call. And so they’re losing revenue. They’re losing out to bigger banks, they’re losing out to [10:00] people who are offering communication methods that are non-voice. And so how, you know, omnichannel and digital, uh, communications that you talk about, really just the way things are moving today. People of all ages, even me, I’m a Gen Xer, I don’t want to call unless I, I know if I have to call, I’m gonna sulk because I don’t know how long I’m gonna be on hold. But more and more people, all the different, you know, gen X, uh, gen Z, gen millennials, and then Gen Alpha, the teenagers of today are not waiting in a queue tomorrow. And so the more you can do to put a communication method where they are, will only create that trust and that recognition of that brand recognition with the end user.
Max Clark: I mean, I, I, I when you say that. It’s so funny. Like I have, I have actual, I think like repressed rage when I get into like, hold now where the, and it’s like, and it’s like virtual hold is a real thing. Like it exists. Just, just click the button and turn it on. You know? Like I know what, you know, like, and you can identify [11:00] most of these platforms just by, know, there’s, there’s always, it’s like the Audis from a long time ago, there’s like always some indicator.
It’s like, what’s your default hold music? It’s like, okay, I know what you’re running, you know? Yes, I know you have virtual hold. I know you don’t have to license the feature. Just can you just check the box and, and call me back. But I really need to sit on hold now for 45 minutes. You know? What’s the other one I love? You know, due to an unusually high number of phone calls, it’s like, look, I know you just have that as your permanent recording. Can we just not play this game anymore? You know? Can you just,
Brent Wilford: listened to your own IVR in five to 10 years and yeah, that, that’s how I feel a lot of time when I’m on hold.
Max Clark: um, so, so we start, you know, we started with this, with a, you know, the technology wasn’t meeting their needs and wasn’t meeting the results. And then, and then you start like layering other stuff onto it, right? Okay. So we have this existing platform. It’s not doing and not giving them what they want. And what they want really is, is how do we, service existing customers and capture more revenue and, and, and create a better experience for people because now this becomes a, [12:00] a, a selection process, right? Do I pick you versus do I pick somebody else? And if I can’t talk to you, I can’t pick you. Right.
Like, it, it becomes this whole thing of like, you know, jumping somewhere else. And this, I think this creates this an, an opportunity for a lot of, uh, organizations they don’t really think about. It’s like, you making technology decisions that are actually supporting revenue growth or not? Right. And like, how much does that factor in at this point when you start talking about like, the change from omnichannel to digital experience of like, this is a revenue driver.
Brent Wilford: Mm-hmm.
Patrick Russell (Glia): Yeah, I mean, I, I, it was huge, especially for Heritage and, and many of Glee’s customers. But you know, what they were looking for wasn’t just solving the problems that they knew that they were facing. It was also addressing problems that they thought they would face in the future. And it’s a lot of what you’re, you’re talking about Max, the, they needed to.
Find a way magically to, uh, manage their volume, which was about to double as a result of these mergers, uh, without adding headcount, which sounds like an impossible challenge. Um, but [13:00] because of, you know, the way that Glia addresses, what is the legacy providers call omnichannel as, as Brent was saying, we, we call it channel list.
And that channel list approach, it does deliver on the legacy promise of omnichannel, and then it adds more. And the things that it adds are practical, useful, highly, highly, uh, successful AI components throughout the entire, uh, interaction, that customer journey or whatever. And that is what really enabled them to accelerate their objectives and, and really eventually achieve and exceed them.
Because of the ED added layer of AI being worked into every step from the, before the customer even calls, there’s already something that’s going to. Um, increase the probability of that customer engaging with ai. ’cause you know, I’m, I’ve always been one of those mashing zero kind of people. I’ve been in the content interface a long time.
I, it’s like human, human agent that’s me. And so whenever we are building technologies, [14:00] um, we’re always looking for ways to, to mitigate the, those people like us. And, and that’s, that’s really what we, we’ve been focused on is one of the many layers of AI that we brought in.
Max Clark: Uh, you, you know, okay. back to this though. ’cause I, I, people are smart. Your customers are smart. Like, like, like nature finds a way, right? Like the quote from Jurassic Park, right. You know, like it’s, I, I know people that, that figured out that they could call into a different language, you know, phone number for an organization because it was always staffed differently, but it was bilingual agents, so they could call in and bypass the main, like English based, like nightmare, call this other one, get an agent on the phone and be like, oh, I’m sorry I speak English.
I know how I got you. And they’d be like, oh, okay. How do I help you? You know? I’m like,
Patrick Russell (Glia): Yep.
Max Clark: you know, if I, you know, to figure that one out as a, as a, as a business. KPI, you’ve said something here that I, I, I think is, I. I want to, I wanna dive into it more, right? Expecting [15:00] to double volume without adding headcount, right?
Like, this sounds like nightmare fuel,
Patrick Russell (Glia): Yeah.
Max Clark: And like, there’s some business leader somewhere that is getting like the, the, this, like as a, oh by the way, we just did this. We’re buying this other organization our sub, our subscribers are doubling in size, which means we anticipate our call volume to double in size.
And oh, by the way, it’s gonna be a merger, which always goes perfectly with no problems whatsoever, right?
Patrick Russell (Glia): Yeah, always.
Brent Wilford: employees know everything about the new company
Max Clark: There, there’s gonna be no increase in call volume because the integration is gonna go perfectly in the first place. Oh. And you don’t get any more, you can’t, you can’t grow your team, right? Like, so. I mean, we can, we can go deeper in this, right? But like, starting from a not meeting technical needs, right? Like that, that sounds like a pretty compelling, like, okay, what are we gonna do here? Kind of moment. And then you start talking about, um, [16:00] integrating AI in a lot of different places. So I wanna connect these two thoughts, right?
So the, the ai, I, I, it’s, it’s an abused buzzword, right? Before it was AI being the abused buzzword. We were abusing machine learning. And machine learning was the abused buzzword. And there’s like, there’s this always this train of like, just abused acronyms in the tech marketing world.
Patrick Russell (Glia): Yeah.
Max Clark: Um, talking to customers, talking with clients. The perception of AI, I think for the most part is like, oh, I don’t need people.
Patrick Russell (Glia): Mm.
Max Clark: but what I’ve found with a lot of people, it’s not that you don’t need, can get rid of people. It’s, we can make people better.
Patrick Russell (Glia): Right.
Max Clark: Right. And, and I, and, and this, I’d love to dig into this a little bit of like how you actually, you know, use ai, right?
Like, what does this actually mean? Oh, it’s integrated every step of the way. Like, what does this actually mean in practice? For, in this case, we’ll just, we’ll keep with heritage, right? Like, you know, how how do they use you [17:00] to double their capacity, you know, their call capacity and their experience capacity without increasing their team.
Brent Wilford: Yeah, I’ll, I’ll
Patrick Russell (Glia): Sure.
Brent Wilford: a stab first, pat here, and then jump in. Um, if you, the good news about ai, um, in Context Center is it’s fairly mature for being early on, right? At least it’s adoptable, right? You can put it into use pretty early on. And when businesses like Heritage have doubled the volume or an in increase in volume of some sort, and no additional headcount, you continue to offer the same communication methods to your customers and the same limitations to your agents, you’re gonna run into a problem, right?
You’re gonna run into really long hold times, you’re gonna run into abandonment rate. People are gonna stop trying to call you ’cause they can’t get an answer, right? They can’t get in touch with a human being. And so artificial intelligence, like you said, has the ability to make human beings better, right?
We’re really trying to workforce optimize with a, a digital assistant, if you will, a digital [18:00] coach, however you wanna refer to it. And so if a customer is savvy enough to know the two or three things that everyone calls in about that is super easy. What’s your routing number? What are your branch hours?
Right? Human beings used to have to answer those questions. ’cause that was the only way to convey that information to the inquiring customer. Artificial intelligence is really good at handling that, that simple stuff, right? You can give it an answer and you can give it all the different ways that people can ask that question. so you have 50 different ways to say, what are your branch hours? And you tell the AI that. So it can automate that process. So if the call volume goes up, you’re now taking 20, 30% of those calls out of the human calculation because. AI supplying the same answer a human being would, you can even get so good that you can increase the, um, areas of complexity that AI’s able to handle after a while, right?
People really need to crawl a lot longer when they institute ai, especially in a customer facing environment, [19:00] because you’re really worried about the hallucination, right? You’re really worried about the wrong answer. Uh, you know, the 0% interest on a $10 million loan kind of mistake, right? That would cripple a business. those problems existed in human beings anyway. You won’t, if you listen to all your recordings of all your human agents over the year, there’s a lot of really bad stuff in there you probably didn’t know about, about what human beings are saying to customers. So that getting over that fear, that hesitation, you know, is, is, is realistic, but it’s doable. So you have the ability to have a customer facing AI that takes the simple stuff off the plate. Then the things that make their way to the human are more complex by nature, right? Just because we’ve eliminated the really simple things. So having ai, being able to listen to that call, transcribe that call, provide guidance based on trigger words, natural language processing, nice buzz word for you. understanding of ai, of what the customer’s asking for, and the predetermined company response or guidance to that agent. if I’ve been in the seat three years, I kind of know [20:00] everything, right? There’s a lot of tribal knowledge that I’m in possession of. But if Patrick’s been here for three weeks and he gets hit with an angry customer with a curve ball, he’s gonna have to say, um, a lot.
He’s gonna have to put him on hold a lot. He’s gonna have to check with his supervisor a lot. so AI being able to listen to that and be there and provide that answer to say, Hey, here’s the talk track to this. really simplifies the first call resolution, the customer satisfaction, the ability to pro, to provide a good customer experience to that customer in the spot, opposed to elongating that call withhold and research and looking up different internal databases or talking to the manager who’s already helping another agent. So. AI has the ability in the contact center in those two first buckets being able to not only offload questions that don’t ever need to make it to human again because they’re so simplistic in nature. And then also providing real time guidance to a human with a complex, uh, customer interaction could have taken 20 minutes with all of the different delays in research and hold and get that down, you know, [21:00] to three to four, five minutes.
Because it’s listening, it’s providing the same guidance. If you’re a human supervisor, we’re sitting next to you providing you that same guidance. So AI in the context center is really interesting, because it’s very, it’s mature enough to handle those situations and really simplify and automate a lot of things in the contact center that just weren’t able to be done prior to its introduction.
Max Clark: We talk about, we talk about this a lot in terms of like terms, right? Csat, you know, first call resolution, right? Like customer happiness as a metric of scoring the contact center. How much of customer happiness is really a reflection of agent happiness and agent productivity within the contact center.
Patrick Russell (Glia): You know, I, I think that, that, whatever that is, that number, I think it’s changing. I think that, uh, if you really boil down what makes great customer experiences, great customer service, it’s time. How do you get that customer on their way with the thing that they needed resolved quickly, [22:00] uh, or as quickly as you can.
I, it, the faster that interaction is with accuracy and, and of course the politeness and all that, the higher likelihood of them being satisfied. So I, I think that it’s probably changing the, I think the happiness from the agent perspective is still very relevant, but it’s more in how are you, how are businesses, um, making the job that those agents are doing less stressful.
Less difficult. Being a contact center agent is a hard job. If you guys have done it, I’ve done it. It’s not easy. You’re, it’s very repetitive, high volume. You’re measured at the second of everything you do. Imagine if we were measured at the per second level, when we do our jobs now, there’s gonna be waste of, of, uh, labor.
There’s going to be misuse of time at times, and we don’t get dinged for it, but those agents do. And so I, I think that the way that we do it in the future is to really surround those agents with, uh, incredibly intuitive tools that are doing all the legwork for them. So they’re really just that human interface for the customer.
They’re no longer having to be the [23:00] primary thinker to resolve the customer need.
Max Clark: Well in this, uh, you know, I think it’s, it’s okay. We can go inside baseball here a little bit. Right? You talk about agent, um, business leaders that are not directly involved in managing their contact center. You know, like, are they aware? Like what’s your churn rate, what’s your attrition? How long does it take to hire?
How long does it take to train? How long does it take to get a productive person in the seat? Right? And this isn’t a, you know, you can’t, even if you, if you go and decide to hire A BPO and like outsource this entire thing, you still have the same problem. You still have attrition and retention and churn.
Brent Wilford: Else’s problem.
Max Clark: And training, you know, and, and, and all these other things, right? Like, so, you know, how, how is AI changing that equation, you know, for, for contact centers?
Patrick Russell (Glia): Let me, let me take this one, Brad. So just to start, so when we think about heritage, they, they, and so that data from the Heritage case study is from 2024. The, the, the, their results have of course gotten better since then, [24:00] but. At that time, they were at 90% of every interaction that AI touched 90% in 2024.
So the way that that happens is that, uh, at the very beginning when the customer contacts the, the business, we already have AI looking at their history and serving them up with a custom greeting. So, you know, saying, welcome, Hey Max, we think you’re calling about one of these two or three things. Is that right?
And as long as those two or three things are accurate and that those are the things they’re contacting about, you’re gonna increase their engagement. So you increase the usage of self-service. But more importantly, uh, glia has many things that we’re trying to solve with their ai. One of them is never to make a customer repeat themself and to by always carrying forward context.
So whether that context is from history or from what we capture, um, at the upfront messaging and that first engagement, all that context has to keep moving forward from AI to agent, from agent to agent, whatever it may be. So that the, the [25:00] customer knows you’re not repeating yourself, you’re continuing to solve the problem.
You’re reaching that end point quickly. And I, I think by taking that approach, it really shifts the perception of ai and it makes the job easier for agents, makes the experience better for customers and so on. Uh, the last quick mention, I know I, and everybody else mentioned talk too, but, uh, uh, glia focuses a lot on using our AI for, uh, as a system of understanding.
Max Clark: Mm-hmm.
Patrick Russell (Glia): if you ever have an inter, uh, someone talking to an AI and they say two things like, I need to, uh, check my balance and cancel a check, or whatever the two things are, uh, most of the legacy providers that are, that are bolting on ai, those systems will only catch one of the two in intents. But by, by glia focusing so much on our AI of, of a system understanding, it’ll recognize there’s two needs here.
I can solve one with an AI and I need to get to a human for the other. By having that context and deep understanding of what’s going on, it really changes the engagement.[26:00]
Max Clark: Just a couple of years ago, again, we’ll use the AI moniker, right? You know, this push required a massive amount of time, energy, professional services, configuration. You know, like somebody might say that they had ai, but really what you’re doing is building the most. Complicated IVR system of, of, uh, you know, like, you know, makes UML modeling from the two thousands look like a piece of cake, right?
You know, and, but you know, you’re, you’re, you’re here. No, you’re in this, this process where it’s like, okay, we wanna try to like, you know, answer some basic questions or you’re calling about your account balance, right? Like, well now you need integration with whatever your backend platform is, that can then answer that question.
You need to be able to authenticate the caller, should I be able to get access to this? Like, how do you validate that I am who I say I am? And, you know, so just, just right there, that’s like, you know, there’s a compliance issue and a risk and a security and privacy and all these, you know, like kind of like [27:00] spongy things that you have to deal with.
And then you’ve got the technical side of it. Like, can this system physically talk to this other system? And then how do we train the system in between to actually understand am I calling in, what do I want to do with it? And then how do I get you that answer, right? And like, and, and I find this be a big miss. And a lot of these, you know, like engagements of like people not really understanding, like, well, how do you plug this in? How do you turn this on? How do you train the system? How do you create this understanding of a tent? Like how do you, you know, are you, you know, going through and, and you know, um, uh, classifying your, um, your wrap summaries properly so that way you can then, you know, figure out where you focus on, like how at, at a, at a, be at a, at, even like at a, a found more foundational level, like how do you actually start that process with somebody and say, you know, you’re a, you’re a credit union.
We know you have these problems and this is how you solve them. Because, you know, even though you know you’re unique, you still have a, [28:00] a, a basic commonality with other credit units, other banking organizations.
Brent Wilford: The, um, there’s a lot, there’s a lot in
Max Clark: Oh, yeah,
Brent Wilford: statement. Um, so I’m, I’m trying to play it back in my head. So whether we’re talking, you know, healthcare is similar too,
Max Clark: Mm-hmm.
Brent Wilford: we focus on healthcare as well hip, you know, the HIPAA VI or HIPAA security, you know, understanding of drug names and, and you know,
Max Clark: Oh geez.
Brent Wilford: vernacular, things of that nature.
Right? It’s, it, it’s a lot of training. Um, glia Hass been around for about 13 years, and for 12 of those 13 years, we focus specifically on banks, credit unions, and other financial institutions. A lot of center players would say you’re limiting yourself, right. From a, from a revenue standpoint because there’s all this other business out there you’re not going for. And while there’s an element of truth to that, there’s also the other side of that coin is a highly valuable and, uh, deep understanding of the financial services market and the components that you talk about that go [29:00] into that. So if I’m a human agent and you’re calling up Max saying, Hey, I want to check my balance. who are you? How would I authenticate you in a, in my previous life or five years ago, right? So the, the bank’s authentication, uh, process is still there, but when you have an ai, so that’s a human being doing that. does an AI bot get permission, right? To do the same authentication? So now we’re talking about APIs talking to each other, right? And some of these customers are still on prem, some of them still have a legacy. I. banking system, that’s a box, right? That they are not moving to the cloud yet. So that adds additional complexity to how we do these things. So, but our ability to understand these steps in the financial services world is really, really deep because it’s all we focused on for 12 years.
So when we approach a bank, we approach a credit union, we’re giving them a sales rep who understands their back office, right? So there’s the core banking systems, FIS, Fiserv, Jack, Henry, those are fairly standard. That’s the [30:00] engine of the car. you drive a car, you don’t interface with the engine directly, right?
You enter engaged, engage with a dashboard. dashboard is what we would call an online banking provider, right? So Bank of America, Wells Fargo, they have huge staff IT developers, they can make their own website, do what they want. Your heritage credit unions of the world don’t have that. They don’t have that expertise on staff, nor could they afford to keep those kind of people around. So they go by and pre-built online banking. Um. Uh, product that they give their customers as that dashboard, as the interface. So when they log in and authenticate, they can see their money, they can transact, they can do all the things they want. So we have the ability and we have prebuilt integrations and conversations with, I don’t know, Patrick, is it dozens of, of online banking providers?
I forget the actual number,
Patrick Russell (Glia): Yeah, it’s probably dozens
Brent Wilford: yeah,
Patrick Russell (Glia): say.
Brent Wilford: there’s way more than I thought right before I joined Glio. Um, and so knowing that our success furthered our success in this space, because we learned that to get deeper into these crate [31:00] unions and help them more with their contact center, we had to work both in a public forum on authenticated forum.
Well then how do you get to work in the authenticated forum? Well, you go make relationships with these online banking providers, the Q twos, the alchemies, the canes of the world. There’s plenty of others. But, so when we go talk to a customer, you’re getting a sales rep that knows the Q2 environment and knows the glia pre-integration and what, what, what’s been done and what can be custom done. So we’re approaching the customer from a knowledge of their tech stack and what is difficult for other contact centers to do. Starting from zero has already been predetermined and pre-work and done with glia. So we approach the customer with a, with the understanding that you have a public forum and authenticated forum. We’re working well in both from a digital, uh, standpoint as well as a voice standpoint. They are different, but the integrations are done separately. because of our focus on financial institutions, we know the backend system that almost all of them have. We know the challenges they have with using those systems with [32:00] unconnected, uh, contact centers and what that means to the customer. So being able to get AI or a human to speak with another human in these complicated, secure, compliant relationship driven ways adds complexity. But we’ve done that work. trained our bot on financial institution interactions for 12 years. We’ve pre-integrated our services, both voice and digital to these online banking providers as well as the core banking providers. So when a financial institution, when a financial customer right, is looking for a contact center, a lot to figure out that they probably aren’t aware of until they start seeing what they need, you know, from, from a standpoint, um, from understanding what their human agents do every day. And when they’re able to speak to Glia, they’re dealing with someone who’s already worked on those problems 600 times.
Because our customers are all, you know, mostly financial institution. We’ve seen, we’ve heard, we’ve helped these kind of customers before in both voice and digital. So whether it’s human based [33:00] technology or artificial intelligence, we have the ability to help. We’re, we’re at a stage two, stage three, right?
We’re at a higher level talking to that customer on the outset because of our, our deep experience in this, in this vertical.
Max Clark: A business leader that has an on-prem system, right. You know, legacy businesses, legacy phone system that’s going through this and, and in the banking and the financial services. But, you know, vertical, let’s just stick with that, you know, and, and wakes up one day and realizes like, like there’s a wall coming, right?
Okay, we just bought something else. We’re gonna, we’re gonna double our capacity or double our membership base. You know, we can increase our team. We have to go, we have to go solve this problem. A lot of what I’m hearing you talk about is interesting to me because the natural inclination from that business leader is gonna be to go find, you know, an analyst report, you know, that’s gonna score a bunch of logos, you know, on, you know, somewhere in some square and say, oh, I should go [34:00] talk to these people.
Right?
Brent Wilford: maybe.
Max Clark: Wave quadrant, know, whatever you want to call it. You know, like, like, uh, um, but that is such like a surface level response here, just, just listening to you talk about it. Right? Like, so, so why, you know, what, what, what’s the like, know, because like, it’s like, you, you, how would they even know?
Like, like, oh, well this, this company is great, you know, like the analysts love this company, but like, you know, I’m gonna call up and say, Hey, you know, like I’m, I’m, I’m looking for a context center that sales person’s not gonna be like, no, don’t talk to us. Right? Like, how, that’s, that’s a pretty big failure pattern, right? Like, how do you know, um, how, how does this change, you know, in, in organizations so that way they, they’re, they’re not walking into this repeatable trap. I.
Brent Wilford: The, um, I spent, I [35:00] spent the last five years kind of living in that world, right? Understanding the decision patterns of small. SB, mid-market enterprise, right? And the larger the customer, the more that those rankings or third party, you know, analysts, uh, analysis, make, make sense, or at least guide the initial, um, evaluation decision. And I think in general, it was fine for a while, right? You have a contact center platform that can be applied to any vertical, right? We’re a retail shop, we’re a, you know, restaurant chain. We’re, we’re a bank, we’re a healthcare. And you just take that really broad based, widely focused contact center and you make it as personal as you can to that business in that vertical.
But we’re getting to a spot where that’s harder to, to be effective. Um, the amount, like we talked about, the integrations, right, between online banking and, and core integrations, those things start to exist now in different verticals, right? We have Epic and Cerner in, in healthcare, right? There’s certain [36:00] retail industries.
There’s more. ServiceNow and Zendesk usage. Right. In other, in other verticals. So the ability to be all things to everyone and then really, really focus on you on, based on what I get in a discovery call, is becoming a lot harder to make more beneficial to the end customer. And so the, you know, the Gartners, the, the foresters, right?
We talked about the different analysts. They do a decent job of understanding the overall capabilities a contact center platform.
Patrick Russell (Glia): And the other part to that, Brent, is that the foresters and the, the garters, they’re trying to write a report that is saying these products are, uh, trying to solve everything for everyone. And they also have requirements of being on three continents with certain percentages of revenue. So if your business, your operation is exclusively North American based, exclusively US based, potentially those, those are gonna be likely misguiding for you.
’cause they’re trying to serve a user group that is very [37:00] different than you if you are US based.
Brent Wilford: Yeah.
Max Clark: So Glia Hass been doing this for over a decade, focused on healthcare, focused on financial services. How much of the secret sauce is that specialization? How much of that secret sauce is that technology? I mean, you’re like saying you, you know, you’re able to train your AI against, you know, keywords that would come up in a banking situation, right?
Like, how much of that is technology and how much is that just a byproduct of specialization and focus?
Brent Wilford: it’s the two sides of the same coin. As I say, I’ll, I’ll, I’ll let Patrick, um, get a little more detail on the, on the programming, right. Of, of the financial services bot that we have. But because when you start specializing in a vertical, you start understanding the needs of that customer, not just from a technology stack, but you hear common problems, right?
We’re trying to increase revenue, we’re losing membership, right? All these, these things that we’re trying to do to compete against bigger banks or more national banks, or even online banks. So the specialization in the sales team guy and, and the product. Is one aspect, right? So our product is specialized on [38:00] fixing these needs that we repeatedly hear, and we know in our customer service to us, our sales team becomes a lot more fluent in this language.
So they, it’s not a, I just talked to a pizza shop and a shoe shop and a gas station, and now I’m talking to you, I’ve talked to banks for the last five years, right? So they’re just, there’s more familiarity in the conversation and the way they approach the, the challenges of this specific bank. But when it comes to programming, you know, a bot, the wonderful thing about artificial intelligence is it can be anything you tell it to be, right?
Once it has a foundational understanding of what language is and how to respond and interpret things, tell it. Okay? For you, this specific, you know, is a pizza shop and you’re, we’re the best pizza. And you know this about Papa John’s, you know this about Domino’s. And here’s a source of information over here about why our pizza’s the best. And it takes time for that bot to understand that information and relay that information in conjunction with questions, right? That come in.
Patrick Russell (Glia): Mm-hmm.
Brent Wilford: because of our specialization, that work’s already done, [39:00] our bot, um, I is the number 900 now, uh, Patrick, that
Patrick Russell (Glia): We’re,
Brent Wilford: goals that
Patrick Russell (Glia): yeah, we’re approaching a thousand, but yeah, it’s, we still say a 900, but it, it is still going up.
Brent Wilford: So I mean, go, you, you’ve been more intimate with this, uh, than I have, but our bot doesn’t need to be programmed to know what it’s supposed to do because that’s all it knows.
Patrick Russell (Glia): Yeah. It’s outta the box. Truly outta the box. Yeah.
Brent Wilford: And so we’re
Max Clark: I mean, I mean really it’s really outta the box. Like no, you don’t have to go through and program it. It’s not outta the box after six weeks of customization.
Brent Wilford: Right. Well, so the caveat general, right, the nesting period for an artificial intelligence, whether it’s a voice bot or a chat bot, right? a couple months, right,
Max Clark: Mm-hmm.
Brent Wilford: to understand, oh, here’s some questions. Here’s the, you know, yes. This answer was right. No, this answer was wrong. Right? To guide it, train it like you would a human agent. Because we know the top 900 user goals that customers are gonna call a bank about. Right? I need to order checks. What are your branch [40:00] hours? I need a loan. What’s your mortgage rate? Like? Where do you know that stuff? All a customer has to do is give us their answer those questions. So we’re not using a a, we’re not using generative AI to go say, here’s a big source of information. Summarize your information from here. Hallucinations in healthcare and financial services cannot happen.
Patrick Russell (Glia): Well, and.
Brent Wilford: Drug interaction,
Patrick Russell (Glia): We even add AI into the mix to figure out the answer. So we have all these, uh, historical interactions and as the, the, the bot is deployed or AI is deployed, as your agents continue interacting with customers, the bot’s gonna continue to learn from those interactions. So if,
Brent Wilford: specific interactions.
Patrick Russell (Glia): yeah, exactly. Exactly.
Max Clark: so, um,
Brent Wilford: glia bot only gives the answer. A glia customer has approved it to give,
Patrick Russell (Glia): Precisely. So there’s zero chance, zero chance of hallucinations. We use LLMs and generative AI on the understanding side of things.
Max Clark: okay.
Brent Wilford: and, and one, one second Max. I know you have a question. I
Max Clark: I’ve got tons of questions. [41:00] I’m trying to, I’m trying to sit on my hands here. It’s hard.
Brent Wilford: I know. And I apologize. So instead of going to a customer saying, Hey, we’ve earned your business as a contact center, and you’re a shoe, a shoe store, and now we’re gonna sit down and think about all the questions that you want your, the bot to answer for your shoe store, and how those, how those responses work, or where’s the information they go get it from, we’ve already, we go to the customer, say, here’s the top 900 questions.
Here’s 200 that are the most frequent of those 900. Give us your answer to those 200. And your bot is proof, proof, you know, time to value day one. As soon as you give us those answers, your bot is giving those answers. It doesn’t take time to learn and train and be wrong and be fixed. We’re
Max Clark: I mean, I, I love it. I love it, but at the same time, I’m thinking about the like, here’s 900 questions that you have to answer in order to onboard on our
Patrick Russell (Glia): Well,
Max Clark: Like
Patrick Russell (Glia): yeah, I, I wanna clarify that. I mean, it’s not,
Brent Wilford: first date for
Patrick Russell (Glia): it’s not that they have to give us the answers. We, we basically give them the answers. They have to approve them
Max Clark: Okay.
Patrick Russell (Glia): we have a very high likelihood of already knowing the answers, but we need to make sure we’re saying it in their way. So it’s [42:00] more of an approval push button kind of thing, not a give me an type out an answer.
Max Clark: I I’m gonna circle back to this when I have some more intelligent questions to ask you. So, um, what was it about Glia that won this business with Heritage? Let me, let me, and I, I, I want the, I want a little bit more than just that. I want, you know, I wanna talk about this backstory a little bit because, know, I don’t, you know. Thousands of members probably, you know, you know, like the stats, the stats on your case study are 65,000 members and a billion in a UM, right? Like, this is a sophisticated business. It’s not a, it’s not a top 10 bank, right? But like, it’s a sophisticated business and they’re gonna run a sophisticated process to, you know, and evaluate, right?
And so they have legacy and incumbent players, I’m sure at the party. And you’ve got, you know, there’s gonna be lots of different things, including whatever platform they were on is probably in there trying to sell them. Like, Hey, you know, we’ve got this, this solution to you, we can just upgrade to and, and turn it on.
And it’s great. So what is, what was the, what was [43:00] the engagement like and at, and what were the triggers that, that, that started, you know, coming across either questions from Heritage or responses that became like this, you know, narrowing of focus and the eventual, like, this is our solution.
Patrick Russell (Glia): Yeah, I mean, when, when, when Heritage first evaluated and eventually selected Glia, a lot of it came down to the expertise in financial institutions. That certainly played a big role. Um, when you look at the big box providers, the legacy CCA providers, they’re, they’re just now coming up with specialization, but it, it, it’s not quite as sophisticated, certainly not as deep.
Is what Glia does. So, so that’s one big component. Um, a couple of the other ones are that Glia brings the account owner, the customer success person, into the implementation conversation very early in the process. So that there, the handoff from implementation to permanent, um, management is very seamless, that the business [44:00] already understands who they’re gonna be working with.
So having that relationship early and knowing it’d be the same relationship throughout, that also played a big role. And then I think one of the other big reasons why Heritage selected Glia was that they could see the innovation. So anytime I’m talking with a prospect and they’re trying to determine who to, who to go with, one of the things I always tell ’em is, ask those providers for the last 12 to 18 months of what was delivered, what are the new things you’ve done in that timeframe that gives you a very clear indication of velocity of innovation?
And are they actually innovating? Are they just copying ev everyone else on what they do? Lots of copiers out there. And I, I think that when, when Heritage went through that kind of evaluation, examining the innovation on top of all these other things, um, from what they’ve shared with me, it was a very clear choice.
Once they realized the relationships were stronger, the innovation was significantly faster. And then one thing I didn’t mention is the nickel and diming that we see from all of the legacy C cast providers. You know, they’re all [45:00] still seat based, which is really flies in the face of the modern approach.
Um, they have tons of usage charges, which Glia doesn’t believe in, uh, and a lot of ways of nickeling and diming customers. I had one customer that’s using one of the publicly traded legacy c cast providers. They had a $500,000 increase in one month’s bill because they had a surge in demand. Glia doesn’t believe in that kind of thing.
And so, so those kind of parts of our philosophy really play in our, in our, uh, sales process and helping customers make decisions.
Brent Wilford: And there, there’s two kinds of customers, max. I
Max Clark: Mm-hmm.
Brent Wilford: that simplistic, right? But there’s, there’s customers when, when they evaluate technology, just replacing what I have,
Max Clark: Mm-hmm.
Brent Wilford: my goal. there’s customers that say, I need to replace a lot of what I have today ’cause it’s important to me, but I also need to evolve the way my customers evolve.
And I think of the things Heritage, um, expressed during their, their evaluation was that our, that their customers have changed, right? Their end customers. So they realized that [46:00] replacing a voice for voice solution wasn’t going to serve the evolving needs of either their current customers or their new younger customers. So when they looked for a contact center company, they certainly brought forward the must haves, right? The things that their legacy system did that need to continue. But they were very wide-eyed and, and open-minded to expanding the communication pathways, to expanding the ability for the agent, to gather information, to provide information, and to communicate with the end customer at the cho, at the channel of that customer’s choice. So this customer was not rooted in a, like, for like replacement. They were much more focused around what is the customer of tomorrow? How do we acquire them, how do we communicate with them, and what technology we need to give our agents to facilitate, you know, tomorrow’s transactions.
Max Clark: Technology replacement. Conversations are usually a technical team, an IT team, a telecommunications team, whatever, you know, um, that have an existing platform, right? And they wanna move one platform to another, and they have a budget [47:00] already allocated. start getting into conversations around digital transformation. you’re at a different level of the organization, right? The organization has made its decision. We’re gonna do, we’re gonna change the way the business works. Digital transformation is changing the way the business works. And now you have people that are stakeholders that have a lot of influence, power, and control, right?
’cause board level decisions carry a lot left more different weight than an IT director, right? Um, that aren’t necessarily all technical savvy in an evaluation process or understand like, you know, there’s a lot of, um, you know, long tail impacts to technology decisions.
Patrick Russell (Glia): Mm-hmm.
Max Clark: How has the drive towards digital experience and digital transformation. Created opportunities and pitfalls for companies that are going through this because now, you know, it’s easy to get, you know, wind and dine in the sales process with a, like, nobody ever gets fired for buying blank, which, which is a big part of the risk evaluation for technology selection. Like, am I staking [48:00] myself personally in my job and my career reputation, you know, on selecting this platform, oh, they’re the largest one on the market and they’re the whatever top right.
Or, you know, like they’re safe. You know? How does, does that factor in, you know, with this process?
Brent Wilford: It’s a great question, I think, and I think the bigger the company, the bigger the enterprise, the more right. That that
Max Clark: Mm-hmm.
Brent Wilford: now we’re talking about of thousands of employees, right? And tens of millions of dollars. But for financial institutions that aren’t, you know, a Bank of America or a Wells Fargo, um, there’s an intimacy that, um, they per, that they not portray, that’s the wrong word, but that they give right to their end users. And so the mindset of most glia customers isn’t one of, well, we just want the one that, that, that someone said on a ranking is, is is better or, you know, or, [49:00] or is it a big name? Um, because they’re fighting big names all the time, right? As their core business. I think they’re, while you’re right that the technology decision usually is rooted in the IT team, ’cause they’re the ones supporting it and deploying it, what have you? Um, there’s a more, there’s a, there’s a broader focus on bringing in the people who actually are in charge of customer acquisition. Right. Whether that’s a marketing person, whether that’s a chief experience officer, whether it’s a sales, you know, CRO kind of level. have a different understanding of the fight in their space to acquire customers and bring assets under management, you know, that they talked about with Heritage. And I think they just approach it a little differently because they approach their customers, um, a little different. It doesn’t mean we don’t fight the same, or not fight, use the word fight too much. We’re not being compared to the same context center players, right. That you mentioned. Right. The Gardner leaders or the, the bigger names, the, the big four that’s out there. [50:00] That’s always, um, that’s always a competition, right. That, that we face it’s smart, um, of customers of all sizes to look to them to start. There’s a reason they’re successful. There’s a reason they’ve been around for so long, there’s a reason they’re ranked where they are. Do those things matter to me as an individual business?
And I think the customers that we focus on, the ones that aren’t gigantic, you know, corporations are, that are competing with those evaluate technology differently because they, they view their customer differently, right? They’re not a number to them. an individual. They’re a community member, right?
They’re a valued guest. I think that that mindset of their own customer helps them link the connection between the technology they offer and how they communicate with those customers a little bit more intimately than, you know, maybe a larger customers do. What do you think, Patrick?
Patrick Russell (Glia): Yeah, I mean, I, I think a lot of the legacy in this day and age where we are with the advance,
Brent Wilford: hear you [51:00] say legacy CA or C. C, you know,
Patrick Russell (Glia): I, I think,
Brent Wilford: by the.
Patrick Russell (Glia): I think a lot of the, we’re at a point where, I don’t know if there is a provider where it’s, uh, you know, nobody gets fired for choosing. A lot of those, I would dare to say maybe almost all of the legacy CA providers, anybody that was founded in CAS before 2015 for sure. Uh, I, I think that they, they have a lot of tech debt and the amount of money that they spend on r and d is, is governed by a ratio that they have to serve to their shareholders.
So, you know, there was, there’ve been, we’re in earnings call season right now, so any of ’em that are public and, um, I think most of them spend around 10 to 13% of their revenue on r and d. Um, that can be limiting if you have a lot of tech debt. ’cause if you’re trying to innovate and help businesses automate, you need to invest in r and d.
And if you have [52:00] tech debt on top of that, I would, I would dare to say that a lot of those providers that are still follow, are governed by a ratio of what they can spend on r and d. I bet you less than 20% of that is on truly innovative, truly automated things, um, that will help these businesses. So if you choose one of those legacy providers, there’s a good chance that you’re not gonna get the automation that’s gonna let your business thrive in 2030.
There’s a good chance that you’re gonna, you’re gonna enter, uh, uh, a trough, uh, of, of progress because those legacy providers cannot move as fast as a more nimble operation.
Max Clark: How much of it is tech debt and how much of it is just not. Breaking existing customer integrations, right? You know, because like Windows, you know, a Apple and Mac os at some point was able to say, Hey look, you know, we’re gonna abandon the old, we’re gonna go to OS 10. We’re have a new thing and we’re go out to the market.
Right? And as much as you know, like you can, you want to like attack Microsoft and bash Windows software that was [53:00] written for Windows 15 years ago still runs on Windows 11, right? Like there’s, there is at the same time value to the enterprise in having that kind of longevity and consistency of it. Now it exposes a whole bunch of other problems, right?
Like, it’s not, you know, it’s not, you know, this isn’t like absolute good or absolute bad, right? In terms of decisions. But, you know, every time I get into this conversation around tech debt, it’s like how much of it’s actual, you know, tech debt, quote unquote, and how much of it is just like, oh, nope, we have, you know, 500 customers that need this feature and we can’t get rid of this feature.
’cause if we do, it causes this other problem, you know, and, and off, off to the races we are right.
Patrick Russell (Glia): I think it’s a very fair question. I think a lot of it, a good portion of it is what you’re describing and you know, don’t touch the fragile thing, but the reason you don’t touch the fragile thing is because it’s using. Technologies, whether it’s PHP or some old language that they maybe not, don’t even have anyone that really knows how to program that anymore.
And, and a lot of it is a combination of don’t touch it versus tech debt. But it still boils down to the same thing that [54:00] you have resources in one way or another, being allocated to something that’s dying and that is preventing you from building something that will thrive in the future.
Max Clark: So for a company like Heritage, you know, you’ve got like table stake success. We successfully turned on the new platform and our agents are now using it to interact with our customers. Right. But beyond that, like table stakes, like we flip the switch and now we’re on this platform. What, how do they define success? Is it, or, you know, and, and I make this more confusing, which is. A lot of games, you’re just actually trying to avoid failure. Right? So it’s like success, avoiding failure. And what is the metric of failure or success actually defined a success? Like, you know, contact centers want to have, you know, first call resolution or csat, you know, and some people talk about driving down time, you know, but like, is that good?
That could be bad. Like you’re rushing your agents to get off the phone with the customer and then the customer’s pissed off at you because like they don’t feel like they’re getting helped. You know? Like, so how, you know, [55:00] what is the real measure of success for heritage or, or the avoidance of failure.
Patrick Russell (Glia): I can do a quick, uh, response then, Brent, you can add, but the, I mean, I think a lot of it comes down to automation and how much of the total experience, not just the part where we’re talking to a human, how much of the total experience is being automated. And, you know, one thing that Glia is doing now is that we’re, we’re, we’re doing, uh, studies, it’s still kind of in a pilot period, but we do studies with our clients before they implement glia, and then we come up with a commitment of what we believe.
The automation or whatever the given, uh, success criteria are, uh, will be. And then we measure ourselves against it to hold ourselves and our technology accountable. So success is really about the actual tangible change to your business of how much are you automating, how much are you improving first contact resolution, and are you doing those things while at least maintaining the current, uh, quality standards?
Max Clark: So what’s a good baseline number for that? Right. You know, if somebody’s, uh, [56:00] going through this process and they’re looking at this and saying, okay, now you know, we think it’s gonna be this X number, right? Like, what is, what is a good baseline and, you know, nominal improvement that they’re gonna see.
Patrick Russell (Glia): Yeah, I would say if, if you’re automating at least 25% of all interactions and you’re reducing your handle time by at least 25%, those are probably baseline good baselines. I would expect those numbers to be much higher, uh, especially with glia, but, but I would expect those numbers to be higher over. A burn period of a few months.
But, uh, you have to have minimum success criteria. And I think those are, are two very standard, uh, achievable minimums.
Max Clark: and when you, and in this case, and you say 25%, um, automation, this is 25% of all interactions being handled by the platform
Patrick Russell (Glia): Mm-hmm.
Max Clark: hitting an agent for manual intervention by a human person.
Patrick Russell (Glia): Yeah,
Max Clark: That seems significant.
Patrick Russell (Glia): it is. And it gets much higher than that [57:00] actually. But these are the kinds of numbers that we often commit to and, and hold ourselves and our technology accountable to.
Max Clark: I mean, with heritage here, you’re saying like 90% of interactions enhanced by ai, 34% fully admitted, uh, automated, and 54% agent assisted or AI assisted.
Patrick Russell (Glia): Yeah, it’s a fantastic, I mean,
Brent Wilford: instead of 25.
Patrick Russell (Glia): yeah, exactly.
Max Clark: of your call volume. Like that’s, that’s, I mean, when I say call volume right, the third of your customer interaction, right? Like, how do you, how do you, as a business, how do you introduce AI customer service without pissing people off? Right? Because there is, there is definitely that line.
Like
Patrick Russell (Glia): true.
Max Clark: my favorite is when you know, you’re on hold and, and it makes it like the, the fake typing noise. Like ta
Brent Wilford: Mm-hmm.
Max Clark: ta, you know, like, and you’re just like, oh, do we have to just do the fake typing? Can you just not do the fake typing? You know, like,
Brent Wilford: not, yeah, it’s
Max Clark: you know, I mean, how do you, how do you introduce AI and automation without, because it’s, it’s, it, there is a balance, right?
The balance is like, I’m calling in to get something [58:00] done and my, my happiness is whether or not I got it done. But also like, did I feel like, you know, like a cog in the machine while it happened, right?
Brent Wilford: Um, it’s a, it’s a, it’s the question of, of the day, right? With artificial intelligence. People hear about it, the C-level people want it, but what does it mean for the individuals, right? What does it mean for the agents and the supervisors, the core people that interface with customers all day? And I think the big fear is replacement, right? AI is gonna take your job, right? It is gonna do your, your job’s so simplistic that AI’s just gonna do it and see you later. Um, and that’s not the case, right? There are several factors specifically in contact centers that, um, AI is here to help far more than it is here to hurt anyone, right?
Or replace or eliminate anything. And how do you introduce a new technology to a group that might be hesitant or fearful about its impact, right? On the human element, um, of a business. And I think it’s a very legitimate question, especially for those [59:00] that can potentially impact and it’s a, you know, potentially fraught conversation for the person selling it.
You know, you might be viewed as, um, you know, um, uncaring, but if you take time, you know, you don’t, you don’t just walk in the door and say, here’s a bunch of ai, now you’re more efficient. Congratulations, gimme some money. Um, you gotta take time when you’re selling any technology to a customer. To understand the business challenges they face, what is the financial impact of those business decisions, right, from both a money standpoint and a, and a and a labor standpoint. And what is their temperament and appetite to automate certain things or use technology to change those things. know, introducing the PC to a paper-based business in the eighties was similar. Introducing internet could potentially be, you know, a, a challenge as well. So this problem we’re having today is a similar problem we’ve had for decades in business.
It’s how does a new technology that has the ability to do things better, smarter, faster, potentially human [01:00:00] get adopted without pissing off or scaring the humans that it’s gonna sit next to? And so AI isn’t here. It’s a handle of 50 minute complex conversation, about 17 different topics. AI is here to answer the, what’s your effing routing number? What’s your branch hours like if you went and talked to your agents, Hey, what is the top five stupid questions you get all day? And what, what did you wish you’d never had to answer again? You would get those answers,
Max Clark: Mm-hmm.
Brent Wilford: that’s what AI’s here to do. So when you take time to listen to people, and sales is no different than, than just human interaction, right?
I, I always compare sales to dating, and I promise you, I’m not gonna take this podcast in a weird way. But if you listen to people, they’re more willing to interact with you, to trust you, to want to tell you more, to open up more to you, and you build a relationship and you build trust. just walk in and tell someone about yourself for two hours, you know, you’re not getting a sale and you’re not getting a second date, but it’s the listening to the people that the technology will affect and [01:01:00] benefit that helps them accept the technology because you’re starting with their pain mind.
You’re starting with their dissatisfaction, their repetitive, you know, uh, troubles. Whatever it is. And if you show them how AI will help them eliminate the things they don’t want to do in their job, and it will actually help them do the things they enjoy about their job, taking an angry or a dissatisfied or a scared customer and making them happy, um, you build internal champions, right?
And that’s a sales term, that’s a, a term usually meant for buying something. But I truly believe an internal champion is everybody who uses the platform, whether it makes their job easier or better, or makes their shift, you know, a lot more welcoming. introducing AI is no different than introducing any other technology in that you start with the problems of the business. You associate the benefits of the technology, and you show them how the tech that will make their day to day, their eight hour shift, whatever it is, better than it was without that technology.
Patrick Russell (Glia): I, I had two quick points to add too. I mean, I, I think, you know, introducing [01:02:00] ai, first of all, you don’t have to introduce all the ais all at once. You, you can do it in a stepped fashion, and I usually suggest, uh, introducing AI to the internal teams first. You know, get them comfortable with how it works.
Then push the customers. Many customers do it the opposite way, customer facing AI first, but you know, glia really focuses on ensuring that. Transition of introducing AI is smooth because the moment that you’re, the customer’s greeted, they’re engaged with knowledge about them. Um, Hey, max, right away we know your name.
I think you’re calling about X, Y, or Z. And the moment that you have that kind of greeting, it changes the perception of, of from the customer, of what that experience is about to be like.
Max Clark: Patrick, it’s funny because you, like, you say that, but at the same time I, I’m like, how much of this is just table stakes? I mean, if I call in any business I’m doing business with and they, and I, they, and they’ve got my phone number associated with my profile and they don’t know who, I mean, it’s like, like screen pop will [01:03:00] tell you like, like, hi Max.
Like, you know, like there, there’s, it’s, it’s so funny to me when I, when you get into these things where it’s like. How bad is the common state of affairs for most of these? Like, like deployments, if we’re talking about like, just like, oh, you just know who I am when you call in is like, is like a, is a win.
You know,
Patrick Russell (Glia): Yeah,
Max Clark: just
Patrick Russell (Glia): I think it’s the combo though of knowing who you are and what you’re likely calling about. It’s not the kind of thing where you have like a problem in your account where the business could have been proactive. It’s just saying, you know, max often calls this first week of the month and it’s about one of these three topics almost every time.
Maybe we just greet Max with, Hey, max, are you calling about X? And he says, yes. And we just go straight to
Brent Wilford: a
Patrick Russell (Glia): resolution,
Brent Wilford: or whatever it is. Yeah,
Max Clark: The um,
Brent Wilford: you, you laugh. I laugh too, max. I mean, I had to switch healthcare providers
Max Clark: oh, geez.
Brent Wilford: of this year. I’m still dealing with it and it’s, it’s disconnected. It’s
Max Clark: Mm-hmm.
Brent Wilford: They have to, you know, you can hear them. Let me open this up or let me check over.
Like, [01:04:00] this person that’s trying to help me is looking in multiple systems
Max Clark: Yeah.
Brent Wilford: figure out who I am. Even though I’ve just told about it, even though I’ve told another human it. still have these very basic problems in 2025, on the technology that an agent is being given on how they know who I am and what I’ve called about. They should know I’ve called about this one medication three times, ’cause it, it’s keep getting denied or it won’t get delivered. But I still have to go through a lengthy authentication process and a lengthy explanation of what I’m doing and which medication is it. Like none of this is a gigantic healthcare company that has money to provide better technology, and they don’t. And so I, and I am acutely aware of what they’re dealing with and what the problem is getting me my answer. And so I give them grace because I know that they’re not being given the right technology. But it’s still prevalent today.
Patrick Russell (Glia): Mm.
Max Clark: If you’ve been around or involved with contact center operations, it’s very common for them to be organized. And you have like [01:05:00] tiering, right? You know, it’s like tier one, tier two, three tier, and you can call ’em different things, but it’s usually like level sophistication goes up like the frontline versus like, you know, and then this inevitably leads everybody to be like, oh, can I talk to your supervisor?
Because they have like the magic access to like do what I need to get done, right? And then you get in the phone calls where it’s like, sorry, I don’t have a supervisor. And you’re like, oh, come on. You know, like, do we really have to play this dance right now? But, you know, so you had that and then there was a technology innovation that gave you, um, you know, like persona based routing. Like, oh, now you could classify your customer base and say this is a higher value customer, or some sort of integration. So they’re automatically going to a different department or a different team because we wanna give them better service. How much. Of innovation related to ai, and we start talking about what Glia is bringing to table is equalizing that experience for everybody calling it.
Patrick Russell (Glia): Um, yeah, interesting question. I mean, I, I think that [01:06:00] the experience is, um, similar across customers in the sense that the personalization is there, it’s real, it’s more than a, an old, uh, CTI pop, uh, and that the resolution times are getting faster. I think that it’s noticeably different, uh, for the customer.
When they are engaging with the business, using glia versus engaging with the business, using someone else in that upfront greeting, in that carrying context forward and making sure that customers aren’t repeating themselves. You know, we were talking a second ago about, um, how things, some things haven’t changed fast enough or at all.
In 2013, I, I remember writing, uh, co-writing a blog, uh, with, uh, ICMI about pet peeves in contact centers and repeating customers, repeating themselves was always in the top two or three, always. And to this day, I still hear it from customers. You know, we, a customers are always having to repeat themselves.
We’re not carrying context from X to Y [01:07:00] and that is a problem. And I, I think those kinds of things, eliminating those kinds of things, start giving a, a, a unified experience for, for the customers that also improves their satisfaction, loyalty, whatever, whatever you wanna choose there. But ultimately it comes down to making genuine progress on genuine problems.
Max Clark: What percentage of companies do you think look at their contact center as a cost center versus a
Patrick Russell (Glia): Hmm.
Max Clark: and how do you, how do we flip that evaluation or perception?
Brent Wilford: You bring revenue people into the decision process.
Patrick Russell (Glia): Hmm.
Brent Wilford: Um, it was, you know, for, since the inception of Con Contact Center was almost always support, you know, something’s wrong. Something is the way I want it, I want it to be fixed. that as a cost center, right, you’re hiring people to not generate revenue, potentially not lose revenue, right.
But generating revenue, unless they’re an upsell, right. Or, or a sales line, right? Generally support is a, is a cost center, [01:08:00] but that is a very legacy way of thinking about your interaction with the customer, especially in today’s day and age, right? Post pandemic, we are less a brick and mortar society as far as going to a store to acquire something, um, or to ask questions, to acquire something or compare whatever.
I’m, I’m, it is, I’m buying. And you only look at the, you know, usually this is a, a numbers person, right? I don’t wanna say CFO specifically, but if you’re looking at a spreadsheet. You could very easily look at a contact center as a cost center because it’s myopic in that way. But if you start to talk to the people around it and you understand that this is a digital front door, right?
Going back to digital, where younger customers or even customers of all ages, right, are using your website or using your customer service to inquire about buying something or making comparative, um, inquiries, it’s very easy to bring the revenue focused people in. So the CRO, the sales leader, the marketing people, [01:09:00] they’re spending money left and right trying to acquire people.
Well, these are people calling you. These are people reaching out to you proactively about your goods and services, it’s they have one, they want more of it, or they’re thinking about leaving it. There’s lots of different ways people bring revenue to a business. So if you look at the technology as simply reactive to problematic situations, then it’s a customer. you look at the technology as a fluid communication tool to all shapes and size of customers and all wallet sizes. It’s very easy to get those decision makers in, invested in the technology decision to say yes, there’s a certain percentage of our contact center uses that will be reactive and supportive and generally not, uh, producing revenue. But there’s a good chunk of it that we can use as a sales tool, as a re, as a upsell tool, as a renewal tool, whatever. It’s, so looking at it as a cost center is understandable, uh, from the point of view of whoever’s making that determination. But there are more people inside a business that can look at [01:10:00] that same tool as revenue generating, the same information.
And those are the people that need to be brought in to the contact center evaluation decision because their yeses will outweigh the, you know, the one you know, no, if you will, uh, of a, of a labeling contact center as a call center because they see the different size of the business and they see the interaction and the potential of, of the customer, uh, interactions through that platform.
Patrick Russell (Glia): Yeah. When I, when I got into the contact center space in the early two thousands, it was ops, I was in operations and we were very much a cost center. It was cost and quality. Those are the two things that were measured. I, I actually think that. This whole cost, uh, center versus revenue generating center, whatever, it’s really rooted in reporting.
If, if a business isn’t tracking the revenue that’s being touched by the co, by the contact center reps, they’re almost certainly gonna be viewing it as a cost center. It’s a labor resource, uh, you know, taker. And whenever we’ve been in the past, as we’ve been rooted in labor being [01:11:00] like the root of contact centers, you know, if you grow more labor, if you have a problem or some sort of influx, more labor.
And so it’s very easy to see it as a cost center if you’re only tracking labor and it’s only fluctuating based on growth or problems. It’s feels like a cost center. But once you have technologies and reporting that allows you to track it as, you know, what revenue’s being touched by these people and the technology that can start to fight against this, always add more labor, uh, then I think you can really start to shift it from a cost center to more of a revenue generating or revenue retention, uh, center.
Max Clark: One of the common, there’s a, I mean, AI is a, is a complicated topic, right? And one of the responses that come out are, are fear centric, right? You know, of course there’s like the whole like terminator fear centric of like, AI’s gonna become sentient and like, you know, we’re all dead. But
Brent Wilford: I’ll be very mad Max if that happens
Max Clark: be very mad, I’ll be very angry. Um. [01:12:00] The, but in the, in the context center world, right? The fear around AI is, you know, they’re coming for your jobs, right? Like this is a technology that’s coming after people’s jobs. Um, I, I understand it, but I find it curious because BPOs have been coming after people’s jobs
Brent Wilford: Mm-hmm.
Max Clark: decades, right? Like in terms of, you know, shifting labor forces and what’s happening and, and what’s going on. How do you, you know, how do you answer the, like, I don’t wanna say the fear around ai, but have that conversation with somebody, you know, that’s, that then has to go and communicate that inside of an organization. ’cause like you’re only talking with the people at the table and they have to go and see the people in the hallway, right?
And have the, have the internal town hall meetings and like, what does this actually mean? And how do, how does this get communicated in a way that’s actually, that’s, that’s, that’s fear alleviating and not in inducing.
Patrick Russell (Glia): I, I go first here. I mean, I, I love your point about BPOs, ’cause I totally, totally agree. You [01:13:00] know, as far as taking jobs. BPOs, it’s a 90 to a hundred billion dollars space. Well, they’re not BPOs with onshore labor. Most of them have very little or no onshore labor. So those jobs are already leaving. But I, I think a big part of it is that, uh, well, in my experience, the, the companies that Glia is working with, I don’t know of anyone that’s actually laid off or reduced headcount after automating or increasing the efficiency of their operation.
They’re redeploying those people into other roles. You know, you’ve got a lot of business, have a lot of investment in these individuals, uh, company knowledge. They know where the bodies are buried, wherever you wanna, however you wanna think of it. And that’s incredibly valuable if you put those people in other roles.
Um, I think that that will enhance those businesses as a whole. Um, but I don’t really, I don’t really see at the moment where the jobs are disappearing. And I, last point I wanted to make is that, um, I’m fairly confident that every business I interact with. Um, they struggle to hire. So even if there [01:14:00] is a, you know, fear of jobs going away, it’s jobs that nobody wants.
It’s jobs that there isn’t a market to fill those jobs.
Brent Wilford: Yeah. I was gonna say the only, the only realistic fear of AI taking jobs in a contact center is a company that has zero attrition.
Patrick Russell (Glia): Mm-hmm.
Brent Wilford: and I think most contact centers are dealing with a ton of attrition because, we’ve talked about, this is a difficult job. It is not a job most people go to college for and say, I’m gonna be an agent and I’m gonna, this is what I’m gonna do. Um, people flow in and out. Um, they move to different companies for, you know, pay increases or, or, you know, other, deci decision factors. So if you are spinning on a hamster wheel, replacing 30, 40% of your agents every year, we’re not taking jobs, right? We’re just automating the things that you don’t know need to go get this labor to answer these x amount of questions anymore.
The, the pool of questions have shrunk because we’re automating those answers. Again, the routing number basic, you know, branch hours, [01:15:00] locations, what have you. we’re not taking jobs away. We’re simply reducing the HR strain of constantly replacing human labor to solve simplistic problems. And we’re solving it with artificial intelligence.
So in general, it usually doesn’t take jobs away. It simply reduces the, the, the need to continually hire because agents is, agents move, they quit, they go to something else. It’s a symbiotic relationship, right? Between the things AI is able to handle and, and contain, uh, versus the need to throw human labor at that same problem in previous, you know, previous years.
Max Clark: I mean, that number is incredible when you actually start thinking about it and breaking into it, right? 30 to 40% attrition,
Brent Wilford: And that’s on the, that’s low,
Patrick Russell (Glia): Very low.
Max Clark: I mean, that’s, that’s a, you know, 30%, not terrible for a contact center, right? Like you’re not, but at 30%, when you think about it takes on average six months to have a, an agent productive.
Like, like really, really good.
Brent Wilford: tell when you have a new agent
Max Clark: Oh, for sure. Right. But like, [01:16:00] you know, so if you’re turning 30% of your workforce annually and it takes you six months to train a new person to make them productive, I.
Brent Wilford: Then you have to overhire.
Max Clark: You’re, you’re never, you’re never catching up. Like you’re never catching up in that world with heritage. Um, what does crawl, walk, run like with Glia? know, walk me through implementation and deployment. You, you know, I mean, we’ve, we’ve talked about the fact that you’re gonna give somebody a thousand questions that they have to answer, right? Like, here’s your homework on a ream of paper. Right.
Patrick Russell (Glia): Yeah.
Max Clark: But, you know, it’s, I, I say that, I say that in Jes because, um, I’ve been through so many where they, people will show up, and this isn’t specific to contact center, this is just technology in general.
They just show up and they’re like, okay, what do you want it to do? And you’re like, I have no idea. I hired you. Like, you’re supposed to tell me what to do now. Right. Um, you know, I, I mean, I would imagine that just, just being able to say, you know, like, what’s, you know, what’s your [01:17:00] routing number? You know, how should that. Do you have a different one for wires and electronic and aach h you know, like what’s the address? You know, like those things are important, but, what is crawl, walk, run look like? And, and, and what does the implementation deployment look? I mean, there’s some that people are like, we wanna do this right this second, like, move, right?
And, but like, you know, on average implementation cycles, you know, what, what is, what do these things look like?
Patrick Russell (Glia): Yeah, I mean, so implementation, uh. I’ll start with crawl, walk, run. Um, it, it really, the, the actual crawl stage is based on what the specific business’ needs are. If, if the needs are more around automation, we would start with some sort of customer facing ai. If the needs are more around internal, uh, efficiencies, we would start with some agent facing AI as part of the crawl stage.
But it essentially means getting turned on, getting turned up. Uh, that’s probably in the crawl stage. Turned up could be, uh, the base offering with no ai, or it could be that base offering [01:18:00] with one, uh, element of ai, whether there’s customer agent or manager or executive ai. Those are kind of the four buckets that we label our AI with.
Um, and you can start to get turned on, turn on the one AI that, um, is safe for you. Um, but depending on your problems, your, your crawl may be, Hey, we’re drowning our service level’s in the toilet and we need help today. Our very first thing that we’re gonna do is say, we need to get. The unauthenticated, virtual assistants up asap, that’s part of your crawl.
And then we’ll probably move authenticated to part of the walk. And then the run is where we enable the AI on the agents and managers and so on. So, you know, there’s not a single path on that with glia. It’s really deterministic on what your pains are, what your objectives are, your near term objectives, uh, and then we, we kind of build up a plan from there.
We have conversational consultants that are part of every deployment of our virtual assistants, and they will work with our customers to figure out the right [01:19:00] cadence and, and timeline of what needs to be automated first and, and what what can come, uh, after.
Max Clark: Tell me more about customer versus manager versus executive ai.
Patrick Russell (Glia): Yeah, sure. Love it. I spend my whole day in those things. But, uh, so customer AI is
Brent Wilford: right guy for that
Patrick Russell (Glia): probably, yeah, it’s probably the most obvious one. It’s any AI that’s customer interfacing. So whether that’s a digital engagement, a voice engagement. It doesn’t matter. You know, customer AI is customer engaging, AI interfacing.
Um, agent AI is more of those assisting tools. So whether it’s an agent assist, um, we have a heads up feature, which is kind of like the old CTI pop, but with a historical context summarized in two or three bullets. So you, you know, you have that context quickly. Um, manager AI allows you to automate things like quality evaluations, uh, to automate things in reporting.
So you don’t have to do analysis. You can just pose a question conversationally, have a report dashboard built in real time right in front of you, or [01:20:00] ask a question and have like a what if scenario question and have the answers pulled out and answered for you. So you’re not doing any of that legwork of analysis.
Um, and exec AI is similar to manager, but it’s really just allowing those execs to ask executive level questions conversationally and get their answers immediately. It’s like having a, a. A whole bunch of analysts
Brent Wilford: Mm-hmm.
Patrick Russell (Glia): your, in your org that you can just pose questions to and get immediate responses so you’re not having to, you know, run through circles of people to get answers.
You just like a chat GBT experience, you’re just posing your question, getting answers, getting reports, getting data.
Brent Wilford: The, um, when managers ask questions about contact center platforms and evaluations, it’s always reporting, right? I mean, there’s a lot they ask, right? But one, the, what’s important to them is, can I get the information I need to then what? Go do a bunch of work and calculations and work with other people to figure out what do those numbers mean and what do I have to do differently? from a, from a human [01:21:00] standpoint, from a agent standpoint, from how many people, you know, they make all kinds of decisions off that information. So the GPT rather, the generative AI front layer that we’ve put in there allows them to save time, right? We talked about saving time for customers and saving time for agents, but managers have very little time, right?
Two, three supervisors for dozens if not hundreds, of agents, managers wanting to know what does it mean? Why, why are people calling about this product? Or why are, why are we getting this many calls about X? And instead of taking all that raw data and then allowing a team of full-time employees, or even just valuable manager, time to go crank out, well, hey, we’re running a campaign next week and we think we’re gonna have two times the volume, but we mandate that we answer every call in 30 seconds.
How many people do I need and how much, how long do I have to go look at our, my historical data to generate that agent count that I think will be right? You could pose that to our cortex, right? We call our, our, our glia AI cortex. that question to Cortex. Go get a cup of coffee. Go let the dog out, [01:22:00] or go read an article and you have your answer. Um, in, instead of going, working with a team of people for half a day to go figure that stuff out. So it is very much taking the gold mine of data that is inside the Glia platform. Obviously after you’ve used it a little bit, it’s giving the managers and the executives the ability to generate business impact and decisions very quickly, as opposed to taking too much time or too many people to come to that, that same conclusion.
Max Clark: You mentioned quality control and quality assurance. And, you know, this is a horrible process that have to do in the contact center.
Brent Wilford: Mm-hmm.
Max Clark: And a great win for AI is just being able to listen to every single interaction
Patrick Russell (Glia): Mm-hmm.
Max Clark: interactions. Um, at what point do the ai, what, at what point does AI get sophisticated or intelligent enough?
However, what, whatever the correct phrasing is actually start learning and seeing different patterns. Like, Hey, I’ve just listened to a thousand interactions and 25% of that are calling about this thing we’ve never seen before. Like, we have to do something about this [01:23:00] now. And surfacing intelligence back into the organization.
Right? You know, people are calling for this feature, they want this product, they’re asking this question, this is going on. know, it’s strange that every single person, know, in this region is calling, wondering about the hurricane. You know, like, like how, how, when, when does this get from like reactive to more proactive?
Patrick Russell (Glia): Uh, I mean, it’s there. Uh, we, we actually just released, uh, a feature called, um, 360 Insights, and what it’s doing is it’s evaluating all the interactions, looking for types of interactions that it feels it can automate. I. It’s bringing both the question that, that it thinks it can automate and the proposed correct response as a suggestion.
And, and that’s basically like a, an intelligence flywheel. So the, the more conversations that your agents have that are AI assisted, the more the AI is gonna learn and it’s going to find more types of interactions that [01:24:00] it can automate and it’s gonna bring you the suggestions, I wanna automate this type of interaction, I wanna use this type of response.
What do you think? And, and it’ll, it’ll basically become more of a consultative AI at that point to help you continuously imp improve the number of things you can automate.
Max Clark: And at that point, when you accept the answer or you prompt the answer, it’ll either surface that to the customer if you’ve got it. Doing interactions with a customer, it’ll surface it to the agent or the manager
Patrick Russell (Glia): Yeah.
Max Clark: the
Patrick Russell (Glia): Yeah.
Max Clark: context
Patrick Russell (Glia): And I actually misspoke, sorry. It is learning 360, not 360 insights. One, one’s a, a more of a client related thing.
Brent Wilford: Too many, too many internal acronyms, mass.
Patrick Russell (Glia): Yeah. Yeah.
Max Clark: What, what comes next in the, I mean, you know, like the, we talked about modality, right? And this like, push to text, and part of that is just efficiency, right? Like, you know, part of it was like customer, like, hey, you know, you have a, you have a generational gap where people like to text message on their phone versus call.
And you can, you can, you can kind of, you can peg people instantaneously just based on like, [01:25:00] DI, you know, do you text, do you call? What do you wanna interact with? Um, but the other side of it, and the, the dirty secret of course is that you can, you can, a one agent can drive a lot more textual conversations than they can drive, you know, invoice, right?
So like there was, there was also an efficiency and a utilization factor within a contact center. But, but like, what, what is the trend? What comes next? know, for digital experience, you know, because we talk about personalization, we talk about awareness, we talk about context. Hey, max is calling in, he has this pattern, or he just had this thing, he was on the website, or we have this other information.
He’s probably calling about these things, but what, like, what’s the next here that we have to look forward to? Or what? Or what’s like the next hurdle that we have to, we have to cross.
Patrick Russell (Glia): I mean, I think there are many hurdles still, but uh, I think some of the things I’m excited about that I expect or anticipate coming in the medium term. It’s a lot around authentication. You know, that hasn’t evolved a ton. There’s still [01:26:00] voice a authentication, which is great, you know, it’s very useful. But is that really the best thing?
Like we don’t voice authenticate on our personal phones, but they’re locked all the time. We use our face. And so I think there’s gonna be things around authentication that are gonna start to change, which once you change authentication, then it has downstream effects, uh, of other things that could be innovated on.
Brent Wilford: And I think personalization is probably the next, right? Businesses have all sorts of databases, um, of, of information about a customer, right? Support, history, purchase history, you know, website, viewing history, what have you. So where the customer chooses to communicate, right? Whether that’s. Uh, digitally or, or through voice, um, is, is, you know, giving everyone the ability to communicate how they want to, but then making sure that every agent has the ability to understand who they are, how they came to you, um, is probably where improvements, uh, will, will be focused.[01:27:00] Because what we know about today’s younger customer is that they are more tech savvy, their more, uh, ability to, to gravitate towards non-voice communication methods. But they, they research you before they reach out and they’re expecting you if they’ve communicated or bought or done anything with you to know about that.
And I don’t think that’s an unreasonable request. go back to my healthcare example, right? I’ve communicated a lot with them about different stuff they should know,
Max Clark: Yeah.
Brent Wilford: but I, what I’m, or at least anticipate what I’m calling about at this point instead of me go through all of these questions and to say, I’m just trying to get, see where my prescription’s being denied and what, where can I get it mailed out?
Right? So. The ability to take multiple sources of internal data, surface that up cleanly, uh, and, and summarize it easily for an agent allow them to provide a fluid conversation with this customer as to what we know about them. I think that’s, that’s still an area of challenge.
Max Clark: call frustration. That’s worse than hold time. I mean, like, you know, I don’t care if hold [01:28:00] time is one minute and then you have no absolutely nothing about me, and then I have to go through the whole spiel again. Like it’s, it’s frustrating. Like it’s
Brent Wilford: things very specifically because it’s being recorded and because I hope they have the product right, that Patrick just talked about for Learning 360, whatever we call it. I say things like, thank you for being empathetic today. Or, you know, I’ve already authenticated with you a different way, but I’ll do it again for you.
Like I say things very specifically ’cause I hope it makes a difference, but I know
Max Clark: uh,
Brent Wilford: doing these things repetitively, they’re not listening to the recording on the other end.
Max Clark: uh.
Brent Wilford: but all we can do is try, man.
Max Clark: Yeah, I, I know you’re, you’re optimistic, you’re holding out hope. I, I appreciate it. Um, for, uh, let’s, let’s do it this way for, for our credit unions or, or regional banks that are looking at this and trying to figure out how do they bridge this digital gap that they have and modernize and come into a new world, or, or how do they service their customers better?
And what advice would you, would you give somebody watching this?[01:29:00]
Brent Wilford: I think any contact centered decision, right? Whether it’s a healthcare, whether it’s financial services, right? I think they need to understand their employee experience, right? That there’s a lot of people focused on the customer experience. Who are they? Who’s our target market? Why are they buying? What are they buying?
What are our competitors? And that’s all very, very important. But unless you know the day to day of your frontline employees, whether that be a store employee or whether that be, you know, an an agent in an office or at home with technology. Finding out what they see on a daily basis gives you an insight as to what the customers right are, are asking about interacting with.
So any evaluation I think really does itself a disservice if you don’t sit down and take an honest assessment from the people using your legacy technology today, they like about it, what they want it to be different. Um, a lot of evaluation, [01:30:00] going back to the, you know, the quadrants, right? The rankings.
If you just go, well, they’re the top right one, ’em, go get them. ’cause they’re the best obviously, and they’ll be the best. For me, that’s a real blind decision if you don’t take into account information that your frontline employees have. So being a sales engineer, speaking with customers for 25 years, I’ve just always found it to be far more impactful to the business and to find the right technology. If you have an honest conversation about what your frontline employees want and need, and then tailor your. Um, business attributes, your technology attributes to those problems, because then we’re dealing with a holistic, um, situation. So any credit union or bank evaluating technology should first just have an honest conversation internally about what they see as far as good and bad. that with the information you have about your target customer, right? And then look for technology that’s gonna make things seamless for that anticipated customer, for the employee that’s gonna be working [01:31:00] with them and speaking with them. And then what information do your managers need to make changes on a weekly, monthly, yearly basis to continue that cycle to be positive?
Patrick Russell (Glia): I, I would’ve four, four pieces of, uh, advice. And the first one is if you’re gonna use those, any analyst reports, make sure that that report is targeting a business that looks like you, not one that looks 10 times or a hundred times bigger than you. Um, the second one is to always get references from, uh, vendors.
I, I would always ask for five, and I would personally suggest asking for a specific, uh, age of those customers. One that’s been with you for five years, one that’s been with you for three years, and a couple that are there for less than a year. So you can ask the same question and see how things have changed over time.
Um, I would also suggest really making sure that you understand how that provider is innovating by asking for a 12 or, or 18 month look back of, of innovation and features to see are they really innovating and what’s the velocity. And then the [01:32:00] last one is when you’re talking with the references, uh, ’cause unfortunately you can’t always trust, uh, vendor uptime reports, but when you’re talking to your references, ask them about reliability and outages.
Um, I’ve unfortunately been tracking one of the legacy providers and they had a five hour outage or something like that, that we know of. And it’s not even on their, their, their uptime report still shows perfect. So it’s like you, you know, you gotta find other ways to sniff that out.
You like those? A little juicy on some.
Max Clark: oh boy.
Brent Wilford: got a
Max Clark: Uh, that, that’s another hour of conversation that we just don’t have time for right now. Guys, thank you very much. This is fantastic. Really appreciate it. Um,
Brent Wilford: thank you.
Max Clark: a lot. I mean, there’s so much to dig into here and I think, you know, we got, we got pretty deep in, in the time that we spent.
Brent Wilford: Yeah, thanks Max. We appreciate it.
