#233 Matt Price: How Crescendo is Disrupting Customer Service with Gen AI

In this episode of the Eye on AI podcast, Matt Price, CEO of Crescendo, joins Craig Smith to discuss how generative AI is reshaping customer service and blending seamlessly with human expertise to create next-level customer experiences. Matt shares the story behind Crescendo, a company at the forefront of revolutionizing customer service by integrating advanced AI technology with human-driven solutions. With a focus on outcome-based service delivery and quality assurance, Crescendo is setting a new standard for customer engagement. We dive into Crescendo's innovative approach, including its use of large language models (LLMs) combined with proprietary IP to deliver consistent, high-quality support across 56 languages. Matt explains how Crescendo's AI tools are designed to handle routine tasks while enabling human agents to focus on complex, empathy-driven interactions—resulting in higher job satisfaction and better customer outcomes. Matt highlights how Crescendo is redefining the BPO industry, combining AI and human capabilities to reduce costs while improving the quality of customer interactions. From enhancing agent retention to enabling scalable, multilingual support, Crescendo's impact is transformative. Discover how Matt and his team are designing a future where AI and humans work together to deliver exceptional customer experiences—reimagining what's possible in the world of customer service. Don't forget to like, subscribe, and hit the notification bell for more insights into AI, technology, and innovation! Stay Updated: Craig Smith Twitter: https://twitter.com/craigss Eye on A. I. Twitter: https://twitter.com/EyeOn_AI (00:00) Introduction to Matt Price and Crescendo (01:49) The rise of AI in customer service (05:34) Using AI and human expertise for better customer experiences (07:47) How Gen AI reduces costs and improves engagement (09:37) Challenges in customer service design and innovation (11:32) Moving from hidden chatbots to front-and-center customer interaction (14:08) Training human agents to work seamlessly with AI (17:02) Using AI to analyze and improve service interactions (19:15) Outcome-based pricing vs traditional headcount models (21:53) Improving contact center roles with AI integration (25:08) The importance of curating accurate knowledge bases for AI (28:05) Crescendo's acquisition of PartnerHero and its impact (30:39) Scaling customer service with AI-human collaboration (32:06) Multilingual support: AI in 56 languages (33:49) The vast market potential of AI-driven customer service (36:28) How Crescendo is reshaping customer service with AI innovation (42:42) Building customer profiles for personalized support

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Speaker 00

  Companies are terrified of opening up a new channel, which overwhelms their support teams. And their support teams are constrained by budgets and and the budgets are constrained by how many humans they can. So, you know, customer service leaders have been in this challenge whereby they've been trying to move pieces around and optimize to try and get the best type of service they can. But often this translates to trying to squeeze the most possible out of a bot that's not very effective. Or trying to negotiate the rate of a BPO agent down to as small as possible. And what you end up with this is this very disjointed assembly of parts.

• 0:41Speaker 00

  And, you know, unfortunately, bringing in a generative AI bot and just dropping into that isn't going to change the picture at all, unless you take a look at holistic service design and make it simpler.

• 0:50Craig S. Smith?

  Go ahead and introduce yourself, how you got to Crescendo, what Crescendo is, how it got started, and then I'll start feeding in with questions.

• 0:59Speaker 00

  I'm Matt Price, I'm the CEO of Crescendo.

• 1:04Speaker 00

  Crescendo is a customer service company that was assembled by some founders who were really excited about the potential that generative AI can bring to to customer service. And what the company does is actually provides all of the technology and all of the people that automatically handle all the peaks and valleys in support demand across all channels. Anytime you want, twenty four by seven. And what we've found is this integration of the technology and the people is the only way that you can ensure that you can deliver, you know, the best possible quality for customer service. So it's better by than people by themselves, and it's better than AI by itself.

• 1:49Craig S. Smith?

  Yeah, and and AI, generative AI chatbots have really taken over

• 1:57Craig S. Smith?

  all sorts of functions, but customer service, it's moving in a customer service pretty quickly. How good are the the chatbots? Are your chatbots based on API calls to?

• 2:15Craig S. Smith?

  To one of the big proprietary models or have you taken a, an open source model and fine tuned it? And how generally do you think chatbots are going to perform in this market?

• 2:32Speaker 00

  The short answer is yes, they can be excellent. The longer answer is that

• 2:42Speaker 00

  there needs to be a lot of care and attention and expertise to make sure that they can be excellent and, and live up to the quality expectations that, that people have. So there's been a big gap on moving from experiments to real life production environments. We use all of the great work that's been done by the companies such as OpenAI and, and the other models. Those off linguistically and, and the ability to actually assemble information and deliver it and converse with

• 3:21Speaker 00

  an end user or a customer are second to none. And so what we do is we stand on the shoulders of those giants. And we've delivered a huge amount of IP that makes them work in real life and integrates them into

• 3:41Speaker 00

  the, the people part of the, of the equation and really just takes away a huge amount of the risk and complexity that exists if you do it yourself.

• 3:54Craig S. Smith?

  Yeah. And until now with, with the generative AI chatbots, which are both, both voice and, and text, right?

• 4:08Craig S. Smith?

  You've said in the past that, that, that customer service was more about deflection than engagement. Can you talk about that, about, about what still exists? I mean, I was on a call yesterday. Very frustrating call with, with a, actually not a call, a chat with

• 4:32Craig S. Smith?

  a chatbot, some rule based chatbot that was not getting me where I wanted to go.

• 4:39Speaker 00

  You know, the the challenges is the reason why

• 4:46Speaker 00

  most customers are faced with this is is twofold. Firstly,

• 4:53Speaker 00

  they haven't been able to get the generative AI into production. And there are a number of reasons for for that most equality. Secondly, is there's a misalignment of incentives. There are the old chatbots are provided by technology companies who are making a lot of promises on how much that chatbot can stop people reaching the humans. Now, and then on the other end of this, are the BPOs who are trying to get as much human interaction and time as possible because that's how how they get paid.

• 5:33Speaker 00

  We've discovered by blending the two, you you take away this misalignment of incentives and you can really optimize for the very best, you know, customer customer experience. And so

• 5:50Speaker 00

  you don't try and make the AI do more than it should do or it can do at that at that point in time. So we actually constrain it quite significantly to really just handle the things that can. But what what we do then is make sure that when it does hand off, it's handing off to somebody who is at a level beyond what the AI has actually been doing.

• 6:18Speaker 00

  And this integrated experience and being able to tune this integrated experience because because we we can design the service as such means that you don't end up repeating yourself, you don't fall through cracks, you don't end up going to, you know, multiple layers and the results are really encouraging and surprising. Going back to your question around then on deflection versus deployment, we are not trying to deflect people from stopping them from talking to humans there. What we're trying to do is have the AI do the best possible job it can. And if it can't, then hand it hand it to a human.

• 7:03Speaker 00

  In practice, what we then start to see is because of that quality and when people get get excited about this and by focusing on quality,

• 7:14Speaker 00

  companies start to deploy it in many, many different places within their organization. They move it from being something that's hidden on the website because they don't really want to talk to people to putting it front and center in their product.

• 7:27Speaker 00

  And because the AI can actually resolve many of the inquiries, they can do that for the same budget that it took to do or less than it took to deliver the old type of experience. So we've seen dramatic increases in the level engagement for a lot lower cost per interaction for businesses.

• 7:47Craig S. Smith?

  Yeah, and this is a point I don't think, I mean, I think a lot of people have felt this intuitively, but that don't necessarily understand that it's really has been baked into these customer service platforms is one that BPOs historically have been paid by headcount, which means that the more people they throw at a problem, the more they get paid, which which isn't really aligned with the customer, I mean, with their client, not not the customer that's calling for customer service.

• 8:30Craig S. Smith?

  And that a lot of organizations deliberately in the past do deflect away customer inquiries. I mean, I was trying to get in touch with a company yesterday and there's there's a Twitter link and a LinkedIn link. Neither the Twitter nor the LinkedIn can you message to. And there's no email, no phone number. You're just stuck with what they have on the webpage. And and then for companies that do employ a BPO, oftentimes those calls

• 9:12Craig S. Smith?

  are maddening or unsuccessful. And and there's also all of the

• 9:21Craig S. Smith?

  Uh, the, the phone menus and, and hold music and recording, all of that is uh, sort of deflects customers away from uh, the company. And, and did you think that, how intentional do you think that has been?

• 9:38Speaker 00

  It's been very intentional because companies are terrified of um, opening up a new channel, which overwhelms their support teams and their support teams are constrained by um, budgets. And, and the budgets are constrained by how many hu- humans they can. So, you know, customer service leaders have been in this challenge whereby they've been trying to move

• 10:07Speaker 00

  pieces around and optimize to try and get the best type of service they can. But often this translates to trying to squeeze the most possible out of a bot that's not very effective. Or trying to negotiate the rate of a BPO agent down to as small as possible.

• 10:28Speaker 00

  Um, and what you end up with this is this very disjointed assembly of parts. And, you know, unfortunately, being in a generative AI bot and just dropping into that isn't going to change the picture at all unless you take a look at holistic service design and make it simpler. Um, it, it, it isn't going to change it. So, you know, I, I come from a, a, a, a software, customer service software background. My co-founders come from contact center background.

• 10:59Speaker 00

  And by fusing the two organizations together and really trying to think of this as an end-to-end product, product, um, we've found so many different places where we can optimize uh, the, the experience. And, and basically rebuild the experience from the bottom up. So customer service leaders can focus on being service designers.

• 11:23Speaker 00

  In partnership with us, rather than being, you know, systems integrators or, you know, or procurement agents or people like that, these different sources.

• 11:33Craig S. Smith?

  Yeah. And as you were saying that then, uh, if the, the, once you have a, a system like that in place, that, uh, that instead of deflecting customers engages customers, uh, you want it out front. You don't want to hide it.

• 11:51Speaker 00

  And that's how, that's how, that's really is our mission is that we want to, the first experience that we create is some, something that company is incredibly proud of and, and can deploy further. And, and that's what's happening. Um, you know, it's, it, it's very exciting to see. Uh, it's very exciting to see the potential business impact of when you can lean into engaging with customers and have more conversations with customers, what you uncover of, uh, as all of these hidden things that the customer does want to talk to you about, but hasn't been able to. And there's been a lot of studies, but

• 12:36Speaker 00

  more customer engagement leads to better retention and leads to better sales.

• 12:40Craig S. Smith?

  Correct.

• 12:41Speaker 00

  You know, it's, it's a classic and very simple model.

• 12:44Craig S. Smith?

  Yeah, yeah. It's, uh, I'm sure there are studies, but it's also a sort of common sense, right?

• 12:52Speaker 00

  Exactly.

• 12:53Craig S. Smith?

  The more you engage, uh, and, and so in, in, uh, your solution, you have, uh, generative AI driven, uh, chatbots or the voice or text. Uh, how, and then you have, uh, human agents with the, under the same umbrella. Uh, how much training is there with the human agents to work with the, uh, with the AI? Because I can see with a bolt-on solution, uh, that, you know, a company, uh, you know, buys a chatbot and puts it on their website.

• 13:32Craig S. Smith?

  Uh. And then you run into a problem and the chatbot has to hand off to a BPO. That's not in the same organization. I can see that the, um, yeah, there, there are problems with that. Uh, and but to get around those problems, how much training do you give the human agents with uh the AI? I mean, are they familiar uh with AI, how it works? Do they see the, the conversation or hear the conversation when it's handed off? I'm curious about that.

• 14:10Speaker 00

  Yeah, um, your first point, by the way, i- i- is really interesting is that, and again, this is on service design, is that constantly recalibrating what the AI, the skills of the AI are are. And then handing that off to a human that has skills that are of next level is a i- i- is something that's challenging in itself and something obviously with the fact that we have a very extensive um, um, set of human capital a- a- and the AI that we can merge, we're constantly redesigning that service and, and, and understanding that calibration. So that, that's really important. Um, then when you start to look at

• 14:55Speaker 00

  the AI to human interaction, um, there are some very basic things like you suggest is that making sure that w- w- when there is a, a, a transfer to the human agent, they understand and they can view the context. Um, they, they have tools that we use using same AI that can do language, um, um, comprehension and, uh, uh, and response. So that, that's the core level. But what we found in some of our early product design and work, and when I say product design, it's not technology. It's the technology plus the, the, the human interaction. Some very interesting things happen. So the team leads become accountable for the

• 15:40Speaker 00

  quality of the AI and the humans in interaction. So this very much incentivized closed loop of making sure that the AI quality is there and the human quality is there and constantly improved. But you can take it to the next level then and say, okay, what if the whole team was accountable for the quality of the service? Then you suddenly have all of the service agents being your quality control monitors and update us as part of that loop. And you start to get this flywheel going that dramatically raises the quality of service and constantly innovates those interactions. And because we provide that service, those

• 16:22Speaker 00

  iterations happen very, very quickly. Whereas actually, if you're working with different segments, like a bot company who is then integrating to a CRM system, which is then going to BPO, those cycles can be weeks as change processes. And so the, which doesn't work in the rate of innovation that's happening with AI technology, right?

• 16:48Craig S. Smith?

  Right. And you have not only use AI, not only in the conversational interface, you have AI analyzing the conversations on the backend, etc., right?

• 17:03Speaker 00

  Yeah, this is, yeah, this is a reflection really of how the whole service stack, both from technology and human, gets redesigned and needs to be continually iterated. So the first thing that we did was we understood the idea that to get generative AI into production, it has to be super high quality. So we actually built our own technology to analyze and review every interaction, score it across a number of criteria, and then adjust very, very quickly and trap any errors and really score that quality. That started from really just the

• 17:48Speaker 00

  generic system, but then that gets used for every customer that we bring live is that we're iterating and testing them such that the quality is incredibly high.

• 18:02Speaker 00

  What became apparent then was that the same system was also good at assessing the human elements and the end to end. So our customers can get full visibility end to end of the quality of service, whether it's being delivered by the AI or by the human. It happens on every interaction. And we obviously build best practices around that. So it reinvents how quality assurance is done within organizations. Our customers don't really need to know that or how we do. What they do like is the dashboard that they get, which allows given full transparency and scoring of every service interaction. And they do like the fact that because we only charge by outcomes,

• 18:47Speaker 00

  we will commit to if something dips below the certain quality of service that they would expect, or we would expect to give them, which by the way is very high, then we'll credit them back for that interaction. So a simple piece of AI technology

• 19:02Speaker 00

  provides so many different opportunities for service improvement and you know, bringing together the economic incentives between us and our client.

• 19:15Craig S. Smith?

  Yeah, so that's interesting. You you charge by outcome as opposed to by headcount and that that sounds that just makes a lot more sense. I mean, I was really surprised to hear that BPO is charged by headcount because what's the incentive for the VPO to be efficient? But in this case, by outcome, that aligns really well with with your your customer.

• 19:50Craig S. Smith?

  And and how has this affected the jobs in the call center? Because historically, those jobs were grueling and there was very high turnover because people don't want to stick around. It seems like this would make the job more interesting for the call center employee.

• 20:16Speaker 00

  Yeah, when we first designed the service, we went and spent a week in a contact center. The whole team in the Philippines and we sat next to agents. We looked at every role. And it's true, the way that

• 20:43Speaker 00

  custom service contracts or outsourcing contracts has been structured have been in such a way that the drive towards metrics leads to behaviors that and job roles, which are not really very fulfilling for humans. So what you see is people copying and pasting chat answers from notepads into chats.

• 21:10Speaker 00

  That really, you know, just the service agents really just performing very manual tests. What's interesting then is if you observe agents where escalations have come through and tons, or if they move on to certain things, once you unlock the ability for them to actually use

• 21:34Speaker 00

  their depth of knowledge or their empathy or deeper skills, how much more fulfilling that those roles are. And the, you know, it's not unusual for a traditional contact center to have 50% attrition of custom service agents in every year, which is huge compared to most industries and very expensive for the businesses. And that cost obviously gets passed on to the clients overall. What we're finding is that with our approach whereby the AI is handling a lot of the repetitive work and in many cases.

• 22:17Speaker 00

  Generative AI is very good at it. It can take context, uh, they're in conversation of historical contracts. It rephrases every time for the, for the customer and it's very adaptable. And then hands off to a, a service agent who has the tooling and, and has more meaningful work. The, the retention goes up, the satisfaction goes up as well. So, uh, again, a lot of it's, um, a lot of this is just rebalancing and continually rebalancing between the capabilities of the AI and human and making sure that the experience is integrated very well, not just from the customer, but for, for the human agents as well.

• 22:58Craig S. Smith?

  Yeah, uh, but, but that's an important point because there's such a drumbeat, uh, around AI that it's, that it's replacing or that it will replace humans. But in this case, there's a natural attrition in call centers. Because people don't stick around, but once you implement, implement this kind of a solution.

• 23:21Speaker 00

  That's right.

• 23:22Craig S. Smith?

  Uh, people do stick around. So, uh, uh, it's, it's kind of the opposite of, of what one would, or the media predicts.

• 23:33Speaker 00

  Uh, that's right. I mean, you know, we're, we're one of the fastest growing, you know, companies that delivers AI technology and we expect to be hiring, um, more people, uh, in, in the next 12 months.

• 23:48Craig S. Smith?

  Yeah. Uh, it, the, um, the training that goes into, um, setting this up for a particular customer, let's say it's a, a bank. Certainly the human agents are trained on, on whatever part of the banking, uh, service, uh, the, the customer service is focused on. Uh, but how do you train the chatbot? Are, are you using, um, sort of, uh, traditional, I mean, traditional, it's only been around for a few years, but, um, you know, retrieval augmented, uh,

• 24:31Craig S. Smith?

  generation where you're, you're, uh, you have a vector database, you load up with the customers.

• 24:40Craig S. Smith?

  Data and then the chatbot answers from that or you

• 24:47Craig S. Smith?

  just fine tuning a model to talk about a particular industry? How do you handle that?

• 24:55Speaker 00

  Yeah, no, we we take a customer's set of knowledge and we will use that, you know, in a in an R E G approach to

• 25:06Speaker 00

  to then help provide the answers and the what we focus very carefully about though is how that knowledge, making sure that knowledge is accurate and it's contained and the A I is trained in such a way that it will only use what what you give it.

• 25:30Speaker 00

  And again, here are some of the challenges of making this work because in order to do that, there's a lot of tooling. There's human expertise on how to craft that information and a lot of the early attempts are were, okay, we've got these fantastic L L Ns, we're just going to train them on our knowledge basis, that our whole knowledge base that exists.

• 25:50Speaker 00

  Almost certainly, in fact, in our case, every knowledge base contains inconsistencies. And it contains hidden information, contains old information. And so the curation of the information that goes into it is very important. So what we tend to do is very much contain

• 26:08Speaker 00

  the set of knowledge to begin with, and then we'll iterate and we'll grow that. And that gives us far and away the best quality. And the reason we can do that is obviously, we don't mind about handing off to one of our humans to answer the question. If the A I can't again, you know, the alignment, but there's there's a lot of work to do that now. And this is part of the transformation and why a lot of experiments within companies on generative A I for customer service get stalled and we tend to pick them up here. So what you also have to do on that is then you have to have

• 26:45Speaker 00

  A I experts who are training, getting right models, you have to redo how you do knowledge expertise and and knowledge management.

• 26:56Speaker 00

  Change how you do workforce management within within an organization. So Um. There are so many jobs that need to be upgraded and changed in order to actually make this work. Um. Obviously.

• 27:11Speaker 00

  That's part of what we can bake into the service and it means people can go live very quickly.

• 27:16Craig S. Smith?

  Yeah, um, and I I was looking at um. Um, one of your press releases before the call and you you've grown very quickly. Uh, you you, there was a recent acquisition. Um, um, uh, maybe you said it was, would you call a, at a BPO or a company with, with a lot of call centers that then you brought into the tent. Uh, and and you bring along with that. Those call centers, all the customers that they've been servicing. Uh, so have you, have you, uh, seen, uh, uh, an increase in satisfaction among the customers that you've brought in through that

• 28:01Craig S. Smith?

  uh, acquisition?

• 28:05Speaker 00

  Yeah, the, the interesting thing about doing, I mean, maybe to provide a bit of context on this. So, you know, crescendo startups, technology plus people company. We, we were growing fast and we were hiring, um, our own service agents, uh, uh, and deploying and got to a point whereby from the delivery of service that we, we were looking at ways to e- e- accelerate that. Um. Coming from the technology side myself, um, working with our partners on there. It blew my mind how well operated this company was, you know, how optimized and how good it was managing people and and and building models around, you know, to the extent that

• 28:47Speaker 00

  it would be very, very hard to replicate, you know, i- i- i- in-house, uh, for organizations. And then also how things could be organized to deliver a, a lower cost service or a flexible cost of service. So, um. The idea is you can put a bot on twenty four by seven and it can speak Chinese to somebody in the middle of the night. But what happens when you do a live transfer to, to a human?

• 29:16Speaker 00

  Typically, in order to stop a live transfer for a particular language, you need to employ 24 people. Just for that one dimension. The advantage of using an outsourced, you know, a BPO is that

• 29:31Speaker 00

  there is this pooling of resources or this ability to scale that that makes that scale, scaling happen. So

• 29:38Speaker 00

  I was incredibly excited about, again, this next level of being able to provide a differentiated seamless service and have and just wowed by the level of expertise that we can deliver that that you probably most mid-market customer service organizations wouldn't be able to, wouldn't be able to do.

• 30:00Speaker 00

  So going back to your question, the

• 30:04Speaker 00

  the customers that we're engaging with, who are really just had had a labor only relationship with this business. Companies called Partner Hero, that one of the, you know, top.

• 30:17Speaker 00

  And the reason we really wanted to merge with them is that they had very much focused on this high end quality end to the market, which fits very well with our solution.

• 30:27Speaker 00

  I think what's interesting that we're seeing is

• 30:33Speaker 00

  the ability for us now to handle their requests in a very different way. So

• 30:41Speaker 00

  now we're coming up to holiday season now, and many customers are asking, many companies are asking, oh, can can you add some more agents, please, as more labor. We'll see it, you know. How about we talk about this in the capacity that you need? And then how about we address some of, we address that by committing that we'll handle your capacity. But we'll do that with a combination of technology and people. And oh, and by the way, at the same time,

• 31:11Speaker 00

  your cost per interaction will go down. And at the same time, by the way, we're ready to switch on these new channels and then you are in these new languages. And then and shifts that and.

• 31:23Speaker 00

  Immediately they get it. This is these the service improvements that I've been trying trying to achieve as a customer service leader for a very long time. And and now I have a Ben or somebody have a trusted relationship with that can help me make that happen. And it's, I think it's, I mean, it's obviously very exciting for us and it's, it's, it's exciting for us to see the how all of the people who are working, the operations managers who are working with these customers eyes light up. Because they are now empowered to solve these problems with their customers too.

• 32:06Craig S. Smith?

  Yeah, you mentioned Chinese. How many languages can you handle?

• 32:12Speaker 00

  Fifty six.

• 32:14Craig S. Smith?

  Wow. Uh, so the bot is your, your AI is trained to to respond in fifty six languages. Do you have AI human agents who can speak all those languages?

• 32:30Speaker 00

  Um, there might be one or two more obscure ones that we that we're not servicing at the moment. But I would say we're servicing most of those languages. And if, and if there's demand for additional ones, then yes, we can do that. The which again is goes back to just the scalability and quality of a of an incredibly well-designed and well-run, um, you know, people operation. It's, it really opens the doors to a lot of opportunity.

• 33:04Craig S. Smith?

  Yeah. So the market seems to me is virtually endless because not only do you have all of the the bad customer services still using phone menus and understaffed call centers. So you're on hold. And not only is that your market, but there's a lot of people that have never really done customer service. Uh, who, if it's outcome-based pricing, presumably that's cheaper than the headcount-based pricing. Uh, now have this available to them. So how how big do you think the market is?

• 33:51Speaker 00

  I mean, the outsourced BPO market alone is is half a trillion.

• 33:57Craig S. Smith?

  Wow.

• 33:58Speaker 00

  Dollars. The.

• 34:01Speaker 00

  I think there are a couple of other vectors there that we think that using this approach, more companies will move from in-house to external. There because they won't think about it as offshoring. They'll think about it as just.

• 34:18Speaker 00

  Using BPO or business process outsourcing, using those exact words, they are they are finding an expert partner who can actually deliver something that would be is harder and more expensive to deliver in-house. I mean, BPO has become synonymous actually with please find me some cheap off source labor, you know, and which is absolutely not the case. So we think the market will grow through that. And then the market will grow because

• 34:48Speaker 00

  the results that are being seen from increasing the number of interactions now. We see companies who are turning on voice for the first time.

• 34:58Speaker 00

  Because it's an incredibly powerful way, you know, to interact. The number of interactions, service interactions will grow exponentially as well. So.

• 35:10Speaker 00

  Exactly. There's the current market. There's the expansion of the market by providing better service and and then the growth of the number of interactions. So it's

• 35:20Speaker 00

  it's very large.

• 35:22Craig S. Smith?

  Yeah.

• 35:25Craig S. Smith?

  And and you were saying that

• 35:29Craig S. Smith?

  that, you know, you're you're sort of built on the top of these giants that have created this. This generative AI technology.

• 35:42Craig S. Smith?

  And it's it's still very new.

• 35:47Craig S. Smith?

  And as these models progress and we're going to see, even though there is talk of the the progress slowing down, but but certainly they're going to get better.

• 36:01Craig S. Smith?

  How do you see that impacting customer service where where these

• 36:10Craig S. Smith?

  models get to the point where they can do complex reasoning or

• 36:18Craig S. Smith?

  or even take action as agents develop?

• 36:23Craig S. Smith?

  How how do you see that impacting customer service?

• 36:28Speaker 00

  The

• 36:32Speaker 00

  from an end customer perspective, if you have a good service that you've kind of placed where the where you have AI and humans seamlessly interacting with a human can do the job and the AI can do the job. Um. You won't see much difference, except more work will be done by the AI now. As we've discussed, very few services actually look like that, but from a crescendo customer perspective, you might not see too much change because we're providing a high level of service end to end.

• 37:06Speaker 00

  Obviously, as as the AM proof week, we expect that more and more of the work can be done by the AI. We will adapt our models such and our training of the people and our staffing of the people. So it's complementary to that. And they're doing they're doing few, you know, fewer tasks.

• 37:28Speaker 00

  And and we'll constantly iterate and grade that, but that's

• 37:34Speaker 00

  probably the only thing that the customer our customer needs to see is that quality stays super high. And probably their incremental cost per so their incremental cost per unit will go down from us.

• 37:47Speaker 00

  Time goes.

• 37:48Craig S. Smith?

  Yeah. At this point, when you're talking to one of the voice agents, can you tell it's AI?

• 37:57Speaker 00

  Yes, you can. And

• 38:01Speaker 00

  and we are somewhat deliberate in that. So it needs to be a comfort conversational experience, but you do know it's AI.

• 38:12Speaker 00

  And part of the

• 38:15Speaker 00

  privilege of being involved in this is understanding is also seeing some of the social dynamics and social changes that are happening. So our voice AI has been live now for a number of months and obviously in part of our research team. And actually, when I say a research team, it's the extended research team, it's the people that we talked about, it's the agents and it's everybody's looking and understanding of what these interactions like and feeding back as to what what's happening. But

• 38:46Speaker 00

  there's another dynamic, I'll give you an example, we had

• 38:52Speaker 00

  we went live with a voice bot for for an event. It was actually the Albuquerque Balloon Festival and it was something that said lots of inquiries such as where do I park? Can I bring my dog? And and the AI is, you know, very good at handling those questions. And you listen to some of the conversations and

• 39:14Speaker 00

  initially when people come on, they think that they've got a voice IVR. And then like, oh, got to go through a tree and they'll say, speak to agent. And and we train the AI to say, I'm more than happy to transfer you to an agent, but I'm actually quite knowledgeable as an AI. If you give me a try or, you know, or respond, respond to that. And then they'll say, question about tickets, because they think they're still in in the IVR, in the IVR. And the AI, I'll come back and say, give them an answer. After one or two questions, such a suddenly, you see this transfer from the person calling in saying, actually, this might be helpful to me. And this is maybe a little bit of fun. And

• 40:00Speaker 00

  what we see then is the time that the people are spending on the line now is a lot longer. Because actually, they feel like there's not somebody at the other end trying to cut them off, or or or should not, they're not wasting anybody's time. And we see calls of fifteen, twenty minutes with thirty or forty questions of people interacting with the AI. And

• 40:25Speaker 00

  and it's that level of change at every level, you know, of the interaction stack that's very interesting. And another of our customers

• 40:37Speaker 00

  Uh, provide secure routers. Um, and when we first went to market, we thought, okay, these would be bought by phone automation, technical people, you know? And so the AI would do some work and then we would have the human. It was a unsurprisingly, it's it, the product was bought by people who have who are had high degrees of concern about security. So um, the population was um, a lot of over seventies were buying.

• 41:16Speaker 00

  And that was an interesting experiment for us. So how how does that demographic start to engage with?

• 41:23Speaker 00

  Um, and you know, they it would chat and occasionally they would, people would say, are you um, are you real or are you a robot? Uh, comes back and says, I'm a robot and I says, and then it was like, oh, okay. And it carries, they carry on answering questions.

• 41:41Craig S. Smith?

  Yeah.

• 41:42Speaker 00

  So this shift such a shift and to people and if the AI is good,

• 41:50Speaker 00

  people, people will love it and they will continue to engage. And it's a such a shift that we're seeing now, you mentioned it before, from deflection to engagement whereby it doesn't cost our clients anymore uh, to spend more time on the phone, have more interactions, do it through multiple channels and multiple languages. It's what customer service has been waiting for, you know?

• 42:20Craig S. Smith?

  Yeah. And and uh, do you, do you uh, build a profile of the uh, person calling in? So when they call in next time, uh, you know who they are and know. Uh, you know what their past problems are, something like that.

• 42:42Speaker 00

  Yeah, that's uh, we really just started to do that with some class. The the first part was really just handling um, you know, just handling the inquiries uh, very, very well. But now we get to this new horizon of of understanding prior context um, and and and grouping that information uh, together and making the uh, digital agent aware of of what's happened before. And really, the problem is no different from solving the problem of handing off uh, doing a live transfer to a human. You know, i- i- you're just retaining context and and and adjusting, but

• 43:21Speaker 00

  historically trying to do that

• 43:25Speaker 00

  within these very brittle, process-driven pieces of software that you have to piece together in customer service was incredibly difficult and nobody was really able to attain. You could get some customer history, but

• 43:40Speaker 00

  you couldn't get, you couldn't understand the previous tone of the customer or previous context or the other information that he gave you as part of uh, as part of that service interaction, but the answer is yes. I mean, the the opportunity there is really exciting.

• 43:58Craig S. Smith?

  Is there anything I haven't asked that that you want to uh, leave with listeners?

• 44:05Speaker 00

  I um,

• 44:08Speaker 00

  no, I think I would just recap is that um,

• 44:15Speaker 00

  you know, that this is generative AI is transformative.

• 44:21Speaker 00

  There is,

• 44:23Speaker 00

  but you've got to think ju- beyond just a lot that gets deployed into the current architecture. Thinking more broadly about, you know, the opportunity to redesign the services um, how they happen, and then figure out the best way to do that um, is uh, is what a lot of people are overlooking. And I would encourage people to look deeply into what it actually really takes to get this live and actually maintain it.