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Josh Lupresto (00:00)
Welcome to the podcast designed to fuel your success selling technology solutions. I’m your host, Josh Lupresto SVP of sales engineering at Telarus and this is Next Level Biz Tech.
Everybody welcome back. We got a special episode for you. Some new things coming out in the news, some acquisitions, some updates ⁓ of which today’s episode is titled Behind the Deal, Why NiCE Bought Cognigy and What Cognigy Means for Customer Experience. So on with us today. We have got Hardy Myers, VP of Global Partnerships for NiCE Cognigy. Hardy, welcome on,
Hardy Myers (00:37)
Thank you, it’s great to meet you Josh and it’s great to be on the podcast.
Josh Lupresto (00:42)
So we got a lot to talk about. We do a lot of CX around here. So I know the advisors are itching. They got a lot of questions. ⁓ Before we kind of kick it off about kind of the Cognitive Story, talk to us about you. ⁓ How did you get into technology and partnerships and end up to where we’re at now? I always love hearing everybody’s origin story.
Hardy Myers (01:01)
Yeah, that’s kind of interesting. I was involved in the aerospace business and manufacturing for many years. And I was working on a huge global contract with Boeing and a smaller company. And we got wiped out by a big company. And at that exact moment that I got that email, the phone rang and it was in the dot com era. a partner at a large county firm called me and said, Hey, I’ve got this communication startup.
Would you be interested in in steering it and advising it and I said well given that I just lost my biggest customer or biggest prospect in my current position that sounds pretty interesting and of course it was you know 2001 and so with the dot-com the peak of the dot-com bubble and so I got into communication software Before it was really a raging big thing. So I mean, no don’t get me wrong contact centers had been around
⁓ you know voice messaging and call processing had been around but not not the internet was pretty nascent as you guys know at that point still it was was pretty early times and so it got into it and this is way before cloud is my point and so we were we were really designing an O1 a SaaS solution for a market that you know in O1 cloud wasn’t really
what we’re talking about today, contact centers of service, et cetera, really didn’t exist. So was pretty early and pretty exciting and that led me down the journey that ended up where I am today.
Josh Lupresto (02:32)
love it. Aerospace. I don’t know if we’ve had anybody from aerospace on before. love the stories. We’ve had all kinds of stuff on here. what’s a if you flashback and you think about, know, let’s call it maybe hard lessons learned or a key insight, a great mentor, what’s what’s something that you have carried with you along the way?
Hardy Myers (02:54)
Yeah, I mean, I think one of the things is persistence is probably become, I would say, a hallmark of the success of my career and something that I would just encourage people who are on a journey like we’ve been at Cognigy that, you know, it takes time and it takes persistence to be successful. excuse me, Cognigy you know, started in 2016 and I wasn’t there from the beginning, but I got involved starting in 2019 and I’ve been here ever since. So.
⁓ If you talk to any one of our co-founders, they would all tell you the same thing, that they expected to create some sort of outcome, but they didn’t know when, and that we knew if we continued to execute it with the focus and the level of strategy that we had, that we would be successful, and that, fact, is what’s happened.
Josh Lupresto (03:48)
Let’s frame up AI and just kind of the CX market, right? You’ve been in this space in the 2000s. You’ve taken it now into CX. Why do you think, why now so many AI-driven CX conversations? mean, give me kind of from your seat and your perspective as you’ve seen transformation.
Hardy Myers (04:06)
Yep.
Yeah, I think so. You know, the technology has been, I would call it somewhat stagnant over the last ⁓ decade. Excuse me. Prior to the the the entrance of generative AI chat GPT. And and what I mean by that is a speech recognition was pretty much the same and it was getting better. The models continue to improve, but it was OK, but not.
great and it was very linear. So you had that very robotic experience and all of us had that experience where if you went into a speech enabled solution, you had to say the right thing for it to do what it could do. And by the way, it could still do some pretty cool stuff. We’ve all had great experiences with automation that before this agentic era. And I’ll give you a very simple example, which I’m sure you’ll appreciate prescription refill. Well, like when the first time I ever did it, even though it was touch tone,
It was so transformative compared to say waiting in line at the drugstore for an hour and a half because you’re the 12th guy to get in line for your pick up your prescription or whatever. So, you we’ve had really good experience with automation, but the speech version of that, which is if you want to think about what we’re doing today, that was really the early stage of what we’re doing. Or even the bots on the digital side were very, what we refer to as deterministic, which meant that the programmers or the creators of that technology really had to
create a list of everything you might say. And if you didn’t say it exactly the right way, the bot or the speech enabled auto attendant would respond exactly the way it does that you and I get frustrated with and push zero or yell operator or whatever we do to keep to jump the queue and talk to a human because it just didn’t know what we were saying. So the most significant advancement I would say in the last three years has been the transition from that deterministic very, you
required to be very predictive sort of interaction to you can pretty much say anything and the system would respond would know what you’re saying and know how to resolve it and that’s the excitement about what we’re dealing with today is this creating these truly human-like experiences which of course the synonym for that at this point is is agentic
Josh Lupresto (06:21)
Yeah, I think nobody thought that even if we got to probabilistic that it would be this good, right? We expected it to stay, you know, I’m trying to get ibuprofen. Did you say you need a taxi? You know, those are the experiences that we’ve had historically, but it’s overnight. It just seems like it changed, right? I mean, it didn’t happen overnight, but.
Hardy Myers (06:26)
That’s right. Right.
Yeah.
You’re right. mean, it started at the end of 2023. So here we are, the same time in 2025, so two years later and the reasoning. So the combination is the accuracy and latency of the speech models. So consider it kind of the core tech, the cognitive services as we refer to them, plus the reasoning capabilities of the large language models and the error rates decline the large language models, that combination and the economics of course, which is critical.
Those three things coming together has now created this very fertile ground for what we can now deliver, which are truly amazing, transformative experiences at scale, by the way, not like, okay, we got one right. I’m talking, we’re doing ⁓ customer solutions where we’re doing tens of millions of conversations a year as we refer to them.
Josh Lupresto (07:31)
Yeah. So let’s get into the mechanics of the deal. And then maybe a little bit into the tech fit. first of all, just the question on everybody’s mind. Here’s nice. Here’s Cognigy What was it about Cognigy? You know, what made that a good fit for both sides?
Hardy Myers (07:45)
So ⁓ I would say every large ⁓ contact center provider, leading contact service provider, was either going to build or buy this technology to augment their contact center of service. in my opinion, and in our opinion, the future is a harmonious balance of human and digital assets creating the perfect customer experience. That is really what we’re talking
And what Cognigy, of course, the wave we are riding was the megatrend being AI enabled automation. So we were bringing that to the party. so the reality of it is like a lot of markets, there’s some best of breed players that evolve or emerge, should say, like Cognigy. And then the incumbents, all of the CCaaS providers in this particular example, ⁓ either go, OK, we think we can build that or if not, man, we’re going to end.
Thankfully, Scott Russell, our CEO, had the vision, in my opinion, ⁓ and saw, hey, I have the leading contact center as a service solution in the market, and I want to augment that with the leading, or if not the leading, one of the leading AI-enabled automation platforms to create this amazing set of solutions that all customers not only need, but if we tell the story properly, which we’re working very diligently to do,
will want and so you know, know, sometimes you don’t know you need it, but sometimes you because of the quality of the experience you go, I want that. The good news in our cases, in both cases, those two are intersecting at the same time in the market, which is people want it and they need it. So.
Josh Lupresto (09:25)
That’s what I’m thinking of, right? I’m kind of envisioning, you know, two parallel paths were happening, right? Cognigy was building and designing and front-ending and NiCE has got this giant platform, this known name in the space. I mean, I guess walk me through then at least how do you envision it from a tech stack perspective? If we know the NiCE platform already, where does the conversational AI component of Cognigy plug into the NiCE CX environment, the vision, all of that stuff?
Hardy Myers (09:45)
Yeah. Yep.
Yeah,
yeah, so we’re so and don’t get me wrong. NiCE has already spent an insignificant amount of investment in ⁓ preparing, I would say, and delivering in many cases, particularly around the agent experience with AI enabled solutions. So they’ve got an incredible portfolio of technology, as you I’m sure remember or might know.
they were one of the emerging or one of the leaders, should say, in workforce engagement management, workforce management, workforce optimization. They then bought InContact and transformed that into the leading contact centers of service platform in the world. And so this was kind of the natural next step in my mind, either to build it or buy it. ⁓ And, ⁓ you know, the vision that Scott has laid down is really this powerful combination of the
incredible AI, ⁓ I would say it, insights, analytics, data sets that they’ve developed over the years of interacting with customers. have this amazing, I say they, we, I don’t mean like that, but.
Josh Lupresto (10:53)
know do you say I
know what do you what do you say do you say they we us them back then is it’s all current I don’t know yeah
Hardy Myers (10:57)
I didn’t mean it that way. It’s really we. Yeah, yeah, yeah.
And part of the way I keep saying they is because Scott’s, let me finish and then I’ll answer your question because it’s actually kind of funny. The data sets that have nicest developed enable us to analyze interactions at any scale, at any customer level. And from that, identify where the pockets of productivity can be. And then,
The vision is in real time to instruct Cognigy to create or hire, if you want to use that terminology, AI agents to actually deliver on that promise. So Cognigy can do that today. Obviously, we can build that. NiCE has all the insights. You put that together and make that. We’re automating the automation is the way you want to think about it, which is incredibly powerful.
So, and that’s the vision that we just laid out at the nice analyst, industry analyst conference ⁓ a week or so ago. And ⁓ I will be, think they just did that at the financial services day and they’re doing it with, ⁓ next week there’s a big announcement, a big launch that we have.
Josh Lupresto (11:52)
That is, I like that.
I love it. No, it fits in. ⁓ It makes sense. Yeah.
Hardy Myers (12:14)
And the reason why I was going to finish the other question, to answer your question, why I said we and
Ray. The reason why I said that is because Scott’s other vision was he wants a version of Cognigy to be able to be sold independently in addition to the integrated solution and in addition to nice context-centered service still being able to be sold independently. And I think that’s brilliant. And I’d say that not because he’s ultimately my boss, which of course you could argue I probably have a little bias, but ⁓
The reality of it is the customers are in different places in their journey. And so there are a lot of customers out there that may say today, you know, my contact center is fine where it’s at, but I need a really powerful AI enabled automation platform to drive my automation forward to transform my customer experience. And so, or they may say, I want to do CCaaS first and I want to add automation later. Any version of that, however the customer wants to consume the technology we can deliver.
And that I think is really smart.
Josh Lupresto (13:13)
Yeah.
Super powerful. mean, our TAs love to hear that, right? I mean, I’m just going to kind of go down this, the value and the opportunity for the TAs and I’ll come back to that. But I think the biggest thing that we love and our TAs love is what can I wedge in with today in my existing customer base, as I’m prospecting, as I’m whatever, right? mean, short of furniture at this point, we could sell just about anything, it seems like, into some of these accounts. And so, you know, we opened up the kimono of
Hardy Myers (13:40)
Yeah.
Josh Lupresto (13:42)
Look at all the products that we have in cloud. Look at what we have in CX. Look at what we have in security. So it’s just a matter of, Mr. customer, did you know that I could help you with all of these things? And then, know, of course, if you go to the Teleris solution map, it’s where always we guide the advisors of these are all the bullets in each of those respective products. Maybe it’s IVR today. Maybe it’s conversational AI front end. Maybe it’s WFM. Maybe it’s, know, so we get very specific in that. So I love hearing about this, you know, the ability to wedge in anything and everything over time. Cause yeah, to your point,
⁓ To me, it’s a do the door knock, see where they are, wedge in with what you can now and load it in the CRM for a conversation in 18 months if they’re under contract, right? Because you know, if you stay tight with that, they’re going to need help.
Hardy Myers (14:22)
Cool. Yep.
That’s exactly right. And the second thing I would add, which is really, powerful, is this, there is a virtually a limitless list of use cases that customers can adopt over time. And what I mean by that is it’s a great ongoing long tail expansion opportunity with this product. And I know that also your TAs love to hear that because they can go back.
to the customer next year and have another conversation about what else, by the way, there’s all these other interesting incremental use cases you can adopt. And when I say interesting, I mean time to value high outcome based solutions that are gonna drive the customer experience. And that’s what customers are all really clamoring for right now in our experience.
Josh Lupresto (15:12)
No, I agree. mean, there’s the wedges are the value. The fact that this just uplifts and multiplies and opens up, well, what else can I do with this? Well, you know, I got my data in order. got the, ready to kind of plug into that. What else can we do from an analytics perspective and a front end perspective? And how do we improve the of our own data over time? Right? So it just gets to your point. It gets more probabilistic. gets more all of those things. And that
that ultimately makes the TAs a hero in the customer’s eyes because the customer’s just going, I don’t know how to figure this out. I’m just sitting here trying to run a contact center. I’m just sitting here trying to run a customer service department. I am not diving deep into technology every single day, all day. That’s exactly where our TAs play. That’s exactly where our vendors play. So it’s a great match.
Hardy Myers (15:56)
Yep.
And the other thing I think the other piece for you and the TAs is that Scott’s other piece of his vision, which I think is so critical, is it’s a partner led vision. And so, you know, we’re going to continue to focus on how do we enable our partners to be successful, educating their customers or prospects and then selling this technology. And I think that’s I mean, you can have great technology, but you have to have a partner led.
mentality in my mind to make you and your partner successful. So that’s something, of course, I value very, very deeply. And ⁓ I know Scott does too, so that’s really exciting.
Josh Lupresto (16:35)
So let’s talk about, you know, we’ve said the words, the letters AI, but now let’s maybe get into a little more ⁓ agentic. So if you think about, okay, CX improves over time, outcomes chatbots, and then outcomes AI, and now we’ve got this idea of agentic. So walk me through, walk the advisors through, Cognigy has this flavor of agentic AI. How is that different from traditional chatbots?
Hardy Myers (17:03)
Yeah, sure. And we started that conversation a little bit earlier, the evolution that Cognigy has been on, which is the same evolution as the market, that we were obviously, and our claim to fame has always been orchestration, just FYI. And what I mean by orchestration is that we served, we were in the middle, this middleware, if you will, that
took inputs and created outputs that created amazing customer experiences. And part of our claim to fame was speed to value. And the reason why we did this is we had all these pre-built integrations to systems of record. We supported every contact center on the market. You could plug in any text to speech or speech to text in the platform, now large language models. All this interoperability that Cognigy had was really, really important to be able to create these amazing experiences.
So fast forward to where we are today and you know the world flipped over if you will and now agentic is the term du jour. But really what it is it’s not just the agentic it’s hybrid. OK. And what I mean by hybrid and I’ll give you a good example this is what the agentic brings to the party if you want to say it that way is this really powerful human like experience with autonomous decision making and reasoning. OK. And empathy frankly which is the important part of the puzzle.
So the difference between a bot and an AI agent, a bot from yesterday and AI agent today, is when you call, it sounds like a human, it reasons like a human, it actually has empathy like a human. So if you say, hey, I need to book a flight because I need to go to a funeral in Indiana, the bot understands what that means, and the agent, excuse me, AI agent, says what that means, and they will say, I’m really sorry to hear that, let’s focus on getting your flight booked right now.
It actually can show and it feels very human-like and the most important thing in that whole story and one of our really smart sales engineers calls it the magic moment, which is where you create this relationship between the AI agent and the human, if you will, in the journey. And they don’t feel that compelling need, which we’ve all heard a hundred million times to press zero for a live agent. And of course that is the goal of automation is to, you know,
Josh Lupresto (19:17)
Yeah, yeah.
Hardy Myers (19:21)
solve a problem, not like force you because you’re so angry to move out of the journey, right? So the other piece and what’s really important, why this hybrid matters is that ⁓ there are certain elements of your journey, your conversation where you don’t want empathy, you just wanna make a payment or you wanna sign a document or whatever. so hybrid means it’s a combination of this really powerful, agentic, you know,
call it autonomous reasoning, empathetic experience, combined with those very linear things that need to be done to actually make a real transaction happen or to solve a problem. you know, look up a balance, take a payment, you know, book a flight, all that is very linear. So it’s actually a combination of the old technology a little bit combined with this really powerful stuff to create these amazing, agenti experiences.
Josh Lupresto (20:18)
I love that example. ⁓ think it’s a great ⁓ way to frame ⁓ it. Empathy always considered but prescribed as needed and repeatable and not subject to change based on somebody’s mood behind the scenes.
Hardy Myers (20:34)
Yeah.
And then the last piece I would say that I didn’t mention, I’ll, well, actually two, one context is super critical. so like, you seen it in any of our demos? It’ll be like you call in and you give your number, but then you go, actually, no, I forgot a nine or ⁓ excuse me. I, you know, or no, I don’t want to leave that day. want to leave this day. So like this, you know, in previous. Bod experiences that would never work. It would just be a disaster that would say, I don’t know. I’m sorry. I don’t understand.
It’s incredible like how fast we can do this and the fact you can, you know, like a human, you change, you know, not like a human, like a normal conversation, you can change, you know, where you’re going to change your mind. can say, I don’t want to do that. I want to add a kid. Can I add my dog? You know, like, what do I need to do? All that kind of stuff. You can just throw it, throw that at the AI agent and they can handle it. And it’s really cool. And then of course, the other part, which I know I’m sure your, your TAs would want to know about is we’ve also by virtue of the engineering of the product.
in guardrails so you can’t, it won’t do things like say like if you were to ask a question that was off color or something like that. All of that we’ve engineered the product to be able to prevent that from happening so that just doesn’t happen anymore or at least in well engineered solutions I should say. So, good job.
Josh Lupresto (21:50)
It shouldn’t, yes, for
sure. I love it. Okay, let’s think about maybe, let’s get into an example here. So maybe walk me through, we talked about kind of the application and what it’s designed to do. Walk me through a real-world example, where Cognigy came in, how it improved the results.
Hardy Myers (22:11)
Yeah, I’ll use a large insurance company just to sort of set the bar. And this actually is a great story because it also ties into not only the long tail, but also how you want to get started when you’re having conversation with customers. So all enterprise customers or all customers period ⁓ have pain points that they’re trying to solve. the key to success in this deploying AI-enabled automation is to find a very high value
low risk use case to start with and generate enough savings from that that fuels the transformation. So these are not three year, you know, stories where hopefully after the third year, something pops out the end and you know, everybody’s happy and it’s two years of pain and anguish and you know, maybe we make it, maybe we don’t kind of conversation. This is real time or darn near real time. I’m talking weeks and months, okay, of investment of time to deploy.
and then a real time return based on that ⁓ relatively short term investment. Real time return, high value return. And so in this particular example I’m going to use is the service company. They identified identity and verification and intelligent routing.
as a very high value, low risk use case to start with. And they had, let’s say, over 100 million calls that they wanted to do this to. So if you take that ⁓ example and what we did on that one, we were able to save this particular customer 90 seconds a call just on identity and verification and then intelligent routing. Of course, our automation rate was through the roof. was like high 90s, meaning our success rate of
figure out who the customer was and what they wanted and putting them in the right direction. ⁓ then obviously the savings of 90 seconds a call, when you multiply that times 100 million calls, you’re now talking millions and millions of dollars of savings, which was then reinvested into drive incremental automation use cases for that particular customer ⁓ experience. With the end state being the goal for them, fully automated claims processing, which is you can imagine having been, I’m sure,
at some point in your life through an insurance claims process would be delightful is the way I would say it because it’s super painful. So and of course we’re on that journey now where we’re like they did ⁓ sort of ⁓ like let’s call it accident reporting automation. They did ⁓ you know.
policy reminders and renewals. They’re doing all sorts of really interesting incremental use cases. Each one of those reaching deeper into the organization, maybe moving back into the back office to, know, or the mid office and the back office to connect additional processes, et cetera. And that’s the journey that these customers get on. And that becomes from your TA standpoint, as I would use the terminology, which you would understand, of course, the gift that keeps giving. it really ends up being an ongoing
Josh Lupresto (25:03)
Yeah.
Hardy Myers (25:07)
massive expansion opportunity over time. ⁓ And of course that volume of conversations keeps going up and up and up because you’re expanding across different channels, you’re expanding across different geos, you’re expanding across use cases, maybe you’re doing different languages. So all of those dimensions end up creating a very, very nice long tail of expansion like we talked
Josh Lupresto (25:29)
So if we think about what you just framed up about that example, I it seems kind of like the blueprint of the right way to find the right opportunity. if I’m a Teleris advisor, what I guess, what are the signals, kind of a big question here, what are the signals that I should listen for that would indicate, hey, this is a Cognitive NiCE opportunity? And we know the kind of nice fundamentals, but this opens up such an even broader bucket of web services. Is it, you mentioned,
high value, low risk, potential improvement. But if you don’t know any of that going in of where that might be, how do you want advisors to, how do you frame that up? How do you think about it?
Hardy Myers (26:05)
Yep. That’s a great question.
I think it’s a great question. Well, first of all, I think AI is top of mind for everybody. And there’s a lot of angst in the market. know, MIT study came out that 95 % of all AI, you know, there was all this negativity around this stuff. I can tell you as Cognigy, we don’t have failed transformations. Everything we do creates outcomes. That’s our, and last year we had no churn. None. Not like a little churn. No churn.
Josh Lupresto (26:22)
Yeah.
Hardy Myers (26:35)
So of our enterprise customers. So the point is that you know, if you have the conversation customer number one, AI is top of mind. Number two, they’re looking for something to do that they can show success. Number three is everybody’s got budget for it, which of course is very important. And this story. ⁓ And so it starts with just a general discussion about are you aware of, know, where are you on your journey? What do you think? Obviously AI is top of mind.
have you thought about potential applications of AI with your customer experience? And the two most logical applications, of course, is agent augmentation use cases, which many of your TAs, I’m sure, are very familiar with. Auto-summarization, next best action, things like that. And those are all very high value targets, by the way. And that’s a relatively low risk, under the assumption that they have a nice brand new training, ⁓
brand new, shiny, nice contact center to the service, adding that capability is a relatively light lift and a nice revenue driver. ⁓ So on the agent augmentation side, think your TAs are probably all very familiar with that. Everybody uses the term agent assist. Obviously, it’s pretty popular. But on the customer facing side, that is, in my opinion, really pretty easy too, because the conversation then becomes, well, what are some of the most painful things that you guys have had trouble automating or trying to solve?
From that list, can find, I’m guessing, I’m quite confident, a high value, low risk use case that you can get started with. And away we go. I mean, it really starts with that conversation. We come in ⁓ as the trusted advisor to your TAs and as trusted partners, probably where to say it, right? And we walk in, we come in working together hand in hand and we find, we figure out what their infrastructure is. We figure out how to architect that. We get clear on the volume and…
put together a proposal and I can tell you ⁓ it’s really surprising how fast we can deploy this, number one. And then secondarily, normally, I would say normally, whatever the expectations we set for the customer, we’re able to exceed that. ⁓ With a little bit of time and a little bit of refining, it ends up being a very, very positive outcome for the customer.
Josh Lupresto (28:50)
I love that. And it was, what did you say? What are some of the workflows of things that you struggled to automate and solve? Is that how you worded it?
Hardy Myers (28:56)
Yeah, when I say that, it’s not that they can’t automate them. They just have not been able to find a solution that can do it well. And that probably just has to do with what they were looking at as the tools to do it. I’ll give you real example. There are certain ways you can do this in the market where you probably have a guy that kind of knows a little bit about a few things. We all have a guy, right? And he tries to experiment with…
Josh Lupresto (29:09)
Immature tech stack. Yeah, immature tech stack. Probably when they tried.
Hardy Myers (29:25)
call it off the shelf stuff maybe ⁓ and build it. this is, know, it’s like having an integration SAP is not something that just falls from the sky. Being able to integrate with every context on the market. These are not like easy, trivial tasks. All that stuff’s been done. So if you can walk a partner like NiCE Cognigy into the conversation, who has all this expertise, has done this hundreds if not thousands of times with some of the biggest companies in the world.
Josh Lupresto (29:34)
Yeah.
Hardy Myers (29:52)
You and has it’s all referenceable by the way. So it’s not like you you go you look at us and say well does anyone ever done this? We’re not doing guinea pig stuff here. This is all stuff we’re doing at scale globally. We’d love to do it with your TS.
Josh Lupresto (30:07)
I love it. Final couple thoughts here. You pair this up, put this marriage together, what do you think is next for NiCE and Cognigy over the next year or two?
Hardy Myers (30:16)
Yeah, I think it’s delivering on Scott’s vision, which is this combination of this partner led go to market, which we’re working very hard on. Obviously this is really a great part of that story. ⁓ Combined with the execution on the vision of creating this amazing single solution set that leverages all this powerful insights and AI that NiCE already has combined with the orchestration capabilities and the AI of Cognigy to create these amazing customer experiences. Like I said,
From my perspective, the future is this harmonious balance of these technologies. And it’ll change over time. Maybe more of it comes automated, less human. But remember, the way the world’s evolving, and this is also an opportunity for your TAs, and this is NiCE’s vision, is that it’s not just the front office. It’s the mid office and the back office. And all that tied together is truly an enterprise workflow.
the more of that we can tie together and create and automate and make more efficient combination and bring more humans in at the right place, subject matter experts, et cetera, all seamlessly ⁓ ends up creating a really, really powerful customer experience. And most importantly for your TAs, an amazing business opportunity. mean, the magnitude of this, I’ve never seen an opportunity in dollars as big as this opportunity candidly in my career. And that’s why I’m here, because I am not.
I thought of course the money and the magnitude is exciting, but it’s more exciting about being on the front wave of what I think is perhaps the most profound opportunity for transforming customer experience in my career.
Josh Lupresto (31:56)
All right, final question. This is a complete the statement exercise. So for Hardy’s prediction here. So in three years, the customer experience will be defined by what?
Hardy Myers (32:14)
⁓ I would, to me, it’s a huge increase in customer satisfaction as a result of the integration of both automation and humans. And the reason why I answer it that way is because I believe we relieve the humans of a lot of the tedious stuff they’re doing today. And we solve a lot of the low hanging fruit problems. It frees up the agents to really
who know the company and know their products probably better than anyone to actually add the value they can add that when we all have had an amazing customer experience, it was with a agent who didn’t feel time compressed, who knew what they were saying. You know what I mean? I think you get what I’m saying, but that’s what I say is the future.
Josh Lupresto (33:02)
I it. That’s it, Hardy. That brings us to the end, man. There’s a lot of good nuggets in here. I really appreciate you coming on. This has been great stuff. Good for the TAs to hear.
Hardy Myers (33:04)
Yeah.
I’m to do it.
It was great to meet you and I look forward to working with you and your TAs in the future.
Josh Lupresto (33:16)
Awesome. All right, everybody, that wraps us up for today. As always, don’t forget, wherever you’re coming to us from, Apple, Spotify, these drop every Wednesday, every other Wednesday, so you can get these and make sure you get this competitive intel before anybody else does. So until next time, I’m your host, Josh LaPresto, SVP of Sales Engineering at Telarus, Hardy Myers, VP of Global Partnerships for NiCE Cognigy, fills you in on what the acquisition means. Until next time, thanks everybody.