How many times have you felt misunderstood by customer service? Imagine if your brand could solve every communication barrier, regardless of language, in real-time. Could that transform your customer experience?
Welcome to today’s episode, where we’re discussing how to break down language barriers in customer service with Mike Clifton, and Max Schwendner, both Co-CEOs at Alorica.
About Mike and Max
Mike Clifton, Co-Chief Executive Officer (CEO)
Mike Clifton joined Alorica in 2021, and most recently, was the Chief Growth & Transformation Officer, responsible for the global sales organization and the company’s overall transformation strategy. With deep transformational leadership and technical experience, Mike delivered profitable growth by scaling highly effective sales & product development teams. Prior to that, he was the Chief Information and Digital Officer, where he led the IT organization including the design and delivery of Alorica’s digital technologies and strategies.
Mike brings a wealth of experience in technology, market and business development. As clients’ demand for outcomes requiring digitization, consultation and innovative business models grows, appointing a co-CEO with a sales background and deep technical experience across these domains is a unique Alorica advantage. Prior to Alorica, Mike served as Chief Information Officer and as Chief Innovation Technology Officer at Cognizant, one of the world’s leading professional services companies. He has also held C-level positions at Federal Home Loan Bank of Boston, Hanover Insurance Group, Nobilis Software as well as other organizations.
Mike graduated with a Bachelor of Science in Industrial Engineering at the University of Massachusetts. Additionally, he earned an Advanced Certificate for Executives (ACE) in Management, Innovation and Technology from the Sloan School of Management at the Massachusetts Institute of Technology. He and his college sweetheart wife share two adult children and a dog; they live in Boston where they are die-hard Patriot fans and root part time for the Red Sox and Celtics.
Max Schwendner, Co-Chief Executive Officer (CEO)
Max Schwendner has been a member of Alorica’s executive team since 2019, serving more recently as Chief Financial Officer & President of Alorica Global Services overseeing Finance, IT, Legal, Pricing, and other Corporate teams. Under Max’s leadership, Alorica has achieved its strongest financial positioning in many years and has developed extensive relationships across the private and public capital markets.
Max brings to the table years of expertise in Corporate Finance, Investor Relations, and Operations. With clients increasingly pursuing creative deals and structures, appointing a co-CEO with deep financial and operational expertise across our business enables us to adapt to changing needs and an evolving competitive landscape. Prior to Alorica, Max spent over a decade on Wall Street – primarily at J.P. Morgan – where he held leadership roles within its Investment Bank and Private Equity divisions. During his tenure at J.P. Morgan, Max was actively involved with Alorica following its merger with EGS in 2016 and served on Alorica’s Board of Directors.
Max graduated Summa Cum Laude from Lehigh University with a Bachelor of Science in Finance and Accounting. He and his wife live with their son and a varying number of rescue dogs in New Jersey, where they root for the Yankees and, just for fun, any team that plays the Red Sox or Celtics.
Resources
Alorica: https://www.alorica.com
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Transcript
Note: this was generated by AI and only lightly edited.
Greg Kihlstrom:
How many times have you felt misunderstood by customer service? Imagine if your brand could solve every communication barrier, regardless of language, in real time. Could that transform your customer experience? Welcome to today’s episode, where we’re discussing how to break down language barriers in customer service with Mike Clifton and Max Schwendner, both co-CEOs at Alorica. Mike and Max, welcome to the show. Hey, great to be here. Awesome. Thanks, Greg. Yeah, looking forward to talking about this. Definitely, definitely interesting topic here. So it would be great to get started here if both of you introduce yourselves and would love to hear a little bit about Alorica and what you do. Sure.
Max Schwendner: Well, hello, Greg and everyone. It’s nice to speak with you today. I’m Max Schwendner. I am one half of Alorica’s co-CEOs. Alorica is a global CX provider that operates in 17 countries with 250 clients around the world and across 10 different time zones and around 100,000 people around the world. It’s Mike and my privilege to lead the company. Mike?
Mike Clifton: Yep, everybody, Mike Clifton. I am the bigger half of the half of the co-CEOs of Elorica, only in height. But as to Max’s point, one of Elorica’s biggest differentiator with that geographic and number of clients and country support is that we are aimed to be the best customer experience company in the world. focused on brands that want to differentiate by treating their customers differently through whatever channel, whatever capability. So we aim to raise that bar and differentiate ourselves by doing that at a global scale.
Greg Kihlstrom: Let’s get started. We’re going to touch on a few things. But first thing I want to talk about is just this concept of language barriers and how they can create barriers and customer service and sometimes result in unresolved issues. So I think we’ve all experienced some customer service interactions where it feels like nobody really understands what the other is trying to say. Obviously, that’s going to lead to a poor customer experience. So how prevalent would you say that this issue is in today’s global marketplace? And why is it such a challenge for brands?
Mike Clifton: Hey, great. So Mike, I’ll start off. It’s prevalent. I mean, you, you’re the best use case and how you frame the question. Consumers get a varying degree of channels to interact with companies now. And so if you think about how the best channel is, uh, in terms of economic value, you go towards your digital channels first. Um, but eventually someone is the modality they want to interact with is kind of built into their DNA. I’m used to talking to a person or I started in this channel, but I really want to talk to a person because I can’t get what I want done. And then ultimately you get to a person. And the biggest thing we hear about is it’s a time sink. It takes a while to, you know, in effect, educate the person to the problem. And then it takes even longer if there’s, you know, sensitivities towards language barriers or nuances towards certain phrases, where it creates an even longer time sink. And, you know, time is money, as everybody would say. And so I think people get frustrated by that and they and they want to solve that problem for many reasons, right? Both the economics, but also a better CSAT. And that’s that’s where I think those two pieces come together and what we’re talking about today.
Greg Kihlstrom: So what are some of the, I mean, you touched a little bit on the economics of it, so I want to talk a little bit more about that. What are some of those expense challenges and even geographic challenges that companies face when they’re dealing with some of these multilingual customer service issues?
Max Schwendner: Well, hey, Greg. It’s Max. It’s nice to meet you. I’m sure Mike and I somewhat look alike, and now we’re going to sound alike. So apologies for those playing at home. It’ll be hard to keep track of who’s who. But I think to your question, it seems intuitive, and it is. Some of the biggest expense challenges and geographic challenges are one, placement of where the work can be delivered from. especially languages that have smaller populations of people who know what they are, how to speak it, how to identify those problems, the recruiting of those folks is challenging. And there is an increasing amount of, let’s call it a shortage of labor for selected languages and a need for companies and providers to have very wide and diverse operations around the world where we get a varying degree of quality. So if you’re answering the same question at different times of the day in five different languages, you might have today five different people, five different workforces, five different locations around the world where those questions are being answered. And so that’s an operational challenge and a management and a training challenge. To think about maintaining a certain level of quality across different languages in different locations and different time zones. And not to mention, as Mike alluded to, the nuances between languages. Like, for example, French Canadian and French are very different in their nuances and cultural norms. And so that can lead to some challenges.
Greg Kihlstrom: So next thing I want to talk about with you is Alorica’s Revolt platform and really how this relates to what we just talked about in multilingual CX. So I think it’d be great to get kind of an explanation of how it works, what it is, what sets it apart from other translation tools that might be currently on the market.
Mike Clifton: Yeah, so I’ll just, Mike, I’ll go through a little bit of how it works and give you a little sense of the interaction. So in order to make real-time translation for language work, You need a cloud scale technology platform. You need some machine learning and AI capabilities in order to translate the spoken word on one end to a receiving language on the other end by keeping dialect as well as some nuances in context. So the reality is that That is an inline voice capability through a rapid translation in cloud to an automatic zero latency, almost zero. to the receiving end. And so a spoken word on one, you can expect to be within microseconds being received on the other in a translated language so that it can be responsive. Because in the early days of these capabilities, latency in global communications couldn’t keep up with that latency. So you always had this drag or lag, and conversations and time were really elongated because of it, which is money. So this capability we’ve built will give you the 75 languages. It has 200 dialect capabilities within it. So to the point of nuancing around dialects, it’s already got built in the dialect and nuances of those things in order to sort of make that translation work in real time. And to the clients that are using it, the value has been almost immense in terms of being able to take out what would have been a human coming into the equation and adding a language translation on top of an already existing call. And so that time sink, as we call it, elongates that call and then makes the experience and now a multi-agent experience. And that’s the point I think people find the most value in is we can get to a single person in real time. And then more importantly, we can capture the transcription of the call in both languages so that you have what was sent and what was received and both capabilities. So you have a system of record capability in your CRM systems are always updated with the right answers. And so you get both in real time and languages.
Greg Kihlstrom: Yeah, and I mean, that real time, and I know we’re going to talk about a little bit more about the real time component in a second here as well. But I mean, you know, just given this, I mean, and going back to this, this idea of, I think we’ve all been there with I know, I have very recently been through a customer experience issue, where, you know, there was definitely a disconnect and the best of intentions on all sides. still, you know, there’s there’s still some gaps. So you know, the matter of seconds, or even a matter of understanding dialect and nuance, right? I mean, that that can make a huge difference. So you know, with with 200 dialects, I mean, that seems that seems to be, you know, a game changer, right? Very much so.
Mike Clifton: I mean, if you just look at English, and then just use that because it’s the basis of most probably your listeners, you got US, UK, Australian, you got Indian who speaks English, you’ve got Kenyan, Irish, Ireland, Singapore, South African, but you have these nuances. And I think you inferred in the way you asked the question, um, is, is nuances and then slang, which is another set of capabilities. Are those translated? The answer is absolutely yes. The important part of the call is that what is said on one end has to be received and translated almost perfectly in the other side in order to make both tonality and emotion come through as well. You cannot rip that out because that, that is about CSAT and that is about your NPS scores. So it’s really important to keep as much of that consistency in that language translation into the receiving end as much in both cases. So to your point, that is the game changer, which is it’s time, it’s literally spoken word to spoken word received. And then there’s transcripts and system of record follow. So that single journey is, I’ll call it, the integrity of a single journey is kept.
Max Schwendner: And the thing I would add to that as well, Mike I think did an excellent job outlining it, is if you just take a second and go backwards to what happens today, right? So let’s say Mike is calling to ask a question about his bank statement and he speaks Dutch. And so then the phone connects to me, the agent, and let’s say I speak Spanish. And so someone would need to come on the phone to listen to Mike, who speaks Dutch, and then who also can translate a person to Spanish. In this, in this example, you think about that three leg of that stool, and if anyone’s played the telephone game, you know exactly what we’re talking about. So Mike says something to Greg the translator, Greg says something to Max the person handling Mike’s issue, then Mike says something back to Greg, Greg says something back to Mike and so forth and so on through the conversation. Now instead Max and Mike just talk and Greg is a machine that never makes a mistake and can seamlessly translate Both word, context, dialect, and sentiment, which is an important part of that, right? So there’s nothing that’s lost in translation, so to speak. And despite the other tools that have been in the market for a long time, and what some others are saying their tools do, I think the Revolt functionality that we have is that game-changing technology because there is no latency. The nuance ability to handle different dialects, different styles of language, and the like, is all done seamlessly.
Greg Kihlstrom: Yeah. And so, you know, the power of this, I mean, you know, certainly customer service teams are under pressure to be quick and efficient in their work, but kind of to this point, sometimes being quick means things get missed, right? So, you know, to me, again, hearing this, like that, you know, nuanced language, all those things are kind of solved for even it sounds like grammar mistakes and, and other things are solved for as well. And brand specific jargon, you know, could you talk a little bit about because that’s, that’s even beyond dialect and nuances, okay, you know, I’ve got this product calls called this very specific name, or, you know, whatever other jargon is, can you can you talk a little bit more about some of those things as well?
Mike Clifton: Yeah. So, um, great points. So let’s talk about where we, as a company, we have, um, we, we go to market in a vertical structure. Um, so we try to put our solutions in the frame of our clients and we verticalize our industry segments because it actually aligns to this product kind of nicely. If you, if you think about what you just said. The nuances between an energy power company, a major retailer, and a banking fraud collection or loan cards payment company, they all come with these things called acronyms. or nuances about their market, their bill, why people would call, right? And so those kinds of things, if you were to think about that, they’re language, but those have meanings behind them that are not necessarily spoken word translated. So when I think about my bill and I’m talking my EBT number or my SS number, those are volume on one end equals the voice on the other. But there’s actually an implied meaning where action could be taken from those. So what we have is the ability to take our models on the machine learning and AI models. And then layer on top, I call it a customer nuanced model. So you have the ability to frame a very financial wealth management company’s nuanced language on top of the layers of what’s already been built in terms of the languages themselves, the nuances, and then your own specific layer. So if you’re a device company with a very complicated thermostat, You can then layer on the things that are, you know, we can pull in your data from into our LLMs. You can pull in your data from your product catalogs. You can pull in your data from your website, your SKUs, your model numbers. And now those become interpretable things, but also actionable things. And what I mean by that is if I’m talking as a client on one end where I’ve said, I’ve got my thermostat set to X, but my eco keeps flashing. By definition, we’re listening to that language coming in, and I’m actually transporting the language to the right other side language receiving. But I’m also taking actions from that natural language. I’m actually doing knowledge-based searches for the word or the acronym ECHO. Well, ECHO will then pull up a knowledge base for the agent in a different language to use. And by the way, we pass that language to the knowledge base as well. So you’re seeing it in the language they can process on. And so now I’ve got this ability to not necessarily just translate the language, but action from the language into the systems that support the agent to be able to actually help drive an efficient call. And those are what I call nuances on top. We can do that within five days. Usually turn those nuances around and add them as a layer on top as value add to most of the clients. And we’ve seen that take off in terms of adoption.
Greg Kihlstrom: Yeah. Yeah. Well, that’s yeah. And that’s really powerful in, you know, when we’re talking about the enterprise and so many specific. There’s a lot of things that can get misinterpreted that are beyond even dialect and all those things. So, yeah, it’s that’s great to to be able to account for that, that brand specific stuff. I wonder if you could give maybe an example of how Revolt has already helped a brand to scale their operations and do some of these things. Sure.
Max Schwendner: We have revolts in place with a lot of our clients around the world today. They’re trying various different what’s called work types or interactions, transactions that they have with their customers. So I’m not going to give you a specific company name out of confidentiality of course, but we have examples of outbound sales where we’re making sales for travel and hospitality clients. We have examples of banking clients that are using inbound inquiries, fraud disputes and the like. examples of technical support as well. So it really isn’t a question necessarily of the use case. It’s more of a question in our mind’s eye on what the clients want to achieve. And most of our clients want to achieve a richer, more satisfying customer experience. And so it isn’t a specific work type per se, but it’s really more the diversity of language and the complexity of the interactions that they’re having where we’re seeing the biggest bang. And what I mean by that is if you think about the natural, let’s call it endgame of what we’re talking about here, it matters less where the language is delivered from and more the education and the quality of the agents and the people handling the requests than possible. And what we’re seeing is an increase in CSAT, an increase in not only the ENPS of the people actually handling the interactions as well. So it’s been very, very, as you said before, game-changing to how we think about approaching our clients, who, as Mike said, operate in lots of different verticals across lots of different interaction types.
Greg Kihlstrom: Last topic I wanted to talk about is, you know, we’ve talked a lot about the benefit to that end customer. Certainly, you know, they’re getting quicker answers, they’re getting relevant answers, all those kinds of things. But, you know, even from a business perspective, there is a talent shortage in multilingual customer service, right? So there’s, you know, there’s some gaps there that are really hard to fill. And so, you know, something like this seems like it can really help companies to scale and and be able to fill those gaps without, you know, without the customer suffering. In fact, the customer can get what they want quicker and all that. It sounds like so. Could you talk a little bit about, you know, just how does this how does this resonate with companies and just this need again for, you know, given given a talent shortage here?
Mike Clifton: I think we’ve talked a lot about revolt, but let me broaden the sort of landscape a little bit because I think your question is, there’s a geographic dispersion of agents that many companies in our industry have done where a location to support a language, it’s scaled heavily And in those reaches, maybe you have 50 locations throughout the world. Therefore, your language portfolios acts and you’re really governed by capacity of getting more agents into those facilities or whatever model you deliver them in. And what this does is it sort of turns that on its head a little bit. What you really have to be is great at a base language. And in that base language, you have to have then skill to use technologies like this to deliver the best quality call. And when I say best quality call, you then have to think about how to deliver it clear and consistent voice. And to do that, you probably need making sure you need great pipes from a technology perspective. You need great machine learning and cloud infrastructure to make sure it’s delivered right. But you also have to have noise suppression. And then you have to think about, are there other tools within that that would increase the velocity of the call in that you’ve removed the language barrier issue, right? It’s how do we use what is coming into the AI and machine learning to drive a knowledge engine to drive a AI bot? And then how does it become something that can be virtual? So if you’re on one end speaking the language, well, then why isn’t NLP on top of the same models, a response engine for the first easiest questions, and then for the more complex become the human interaction, right? So you can see the layer of this model is a hugely disruptive one. Because eventually, what you’re solving for is a, I’ll call it omni channel single agent experience where language isn’t the barrier anymore. It’s what is it that you need, and I’m working through the stack. to be able to get the questions answered, whether it’s an AI model or a natural language virtual assistant or X. And then I’m getting to the human to support the transaction and make that time sync very quick, because all of that data that I’ve used throughout that journey is now served up. to the human who can speak to you and get it done very quickly. So we’ve spent a lot of money and investments in many ways, both venture and others, to get ourselves in a position where it isn’t geographic dispersion of people anymore. It’s people in the right locations, the best of our agents. We have the best in the world, as I talked about earlier. getting to the right pain point for the client to get them out of the transaction as quickly as possible, but as happy as possible. I think that’s unique about us in the way we come to market.
Max Schwendner: I think the thing I would add is the challenges you said that companies face trying to staff multilingual support infrastructure is one of recruitment and geographic dispersion, as Mike said. I would not necessarily say that our technology would make our lives or our customers’ lives easier in that regard because if you think about it, if you remove language as the barrier for an excellent experience, You now need even better people to answer those questions, to solve those problems, to have empathy. And so your recruitment challenge isn’t specific. Is Mike a good Spanish speaker? Is Max a good Dutch speaker? No. Is Mike a person who has capability of learning, being empathetic, and understanding what the customers need solved? That becomes the challenge. And so the recruitment becomes a little bit more nebulous, let’s say, than just purely, is Mike a Dutch speaker? Yes, no, check.
Greg Kihlstrom: Right? Yeah, I mean, I so I love this. I love this train of thought, because I mean, you both touched on this a little bit, but I’d love to take this maybe a step further and say, what does the what is the next step then? So you mentioned, you know, kind of hiring for empathy, and for, you know, almost emotional intelligence, as well as other things. What else does this, you know, this kind of stepping stone allow companies to be able to do them? Well,
Mike Clifton: I will go to sort of think about the future of an agent first, and then Max made a really good point. An agent isn’t just interviewed anymore for their ability, for the skills they have, for the language support. Do they have the ability to be a prompt engineer? Do they have the ability to use tools that knowledge bases, prompt engineering, I’ll call it assistive search and modality being, you know, jumping from a channel to a channel to make sure the call’s there. Those things are nuances to the way we’ve changed our hiring and recruiting profiles. Are there people with degrees at higher levels? Because that’ll make a difference in a very nuanced healthcare engagement where that last mile of that quick transaction I’ll serve throughout all this technology is I need a pharmacist on the other end with these skills to be able to do it in 30 seconds. So we’re changing a lot of our DNA around those vertical segments to make sure that those nuanced skills are there. We can be the best at that in CX. The other side of the question I think you had is, listen, this technology is evolving. We are, I’ll call it pioneering with this capability and a few others that haven’t come to market yet. And I think we’re learning and we’re transforming as we go. And I think clients who try this with us. are in the same mode, which is, well, this is a bit of a huge impact. It’s sort of like the pebble in the pond, right? That keeps going. And sometimes those learning labs that we’re engaged in are the better answer then saying it can be tomorrow’s economics on this is different than today’s. So the way we talk about in the sales environment is, yes, it solves a geographic problem and it solves a translation economics problem from elongation of calls. But if you thought two steps and then five steps and then even, God forbid, a year on the switches in the hardware have translations embedded in them. If you think, right, I mean, look at look at Samsung on the phone today, it can talk 12 languages. So I think this technology will evolve. And now it becomes what else can we do? And I think we’re Max and I are spending a lot of time about where does this go? Like, we don’t see an end. But how do we start predicting a little bit with certainty in a year, probably less how we this could affect the market. And it’s it’s pretty, it’s pretty profound.
Max Schwendner: Well, and if you think as well on the customer side, right, for a second, not just the cost benefit or what kind of the model looks like as a change. If you were primary, let’s say previously all you did was sold. to one specific kind of customer that spoke one specific kind of language, your customer pool just increases multiple fold, right? You can talk in any language. You can talk in any dialect. If you can get your product to the hands of your customers, you can handle their questions, engage with them more profoundly in much more of a mass customization than is possible today. Whereas if someone speaks English or Spanish, it might take a few seconds to get an answer to their question. But if they speak Japanese or Dutch or Swedish, it might take a lot longer to get their questions answered and they might disengage from that customer relationship with that company because they don’t feel that sense of affinity that someone who has a more commonly spoken language might otherwise feel. And so I think it broadens the – some of the companies we’re working with, it broadens the aperture of what they can do from a sales perspective, not just what we can handle from a service perspective.
Greg Kihlstrom: Yeah, yeah, I love it. Well, yeah. And, you know, everybody, we talk about various aspects of AI quite a bit on the show. And, you know, everyone that I talk with kind of underscores one thing you touched on there is we’re early days here. You know, it’s easy to think that, okay, we’ve come a long way. I know AI has been around technically for decades, but we’re still early days in this kind of adoption of of this kind of AI. So, you know, definitely curious to see what’s coming down the pike. And I think, you know, I think you’ve both given us a little bit of a preview here as well. One last thing, you know, I really appreciate both of you joining today. One last question for both of you. Before we go, I’d like to ask everybody, what do you each do to stay agile in your roles? And how do you find a way to do it consistently?
Max Schwendner: Well, I’ll start. So the good news is that I’m a lot more agile than Mike because I’m younger and more handsome. But aside from that, I think a lot of things that Mike and I think a lot alike, and I think Mike may answer this question in a very similar way. We’ve been asked different versions of kind of questions along this vein. And what I often say is curiosity has been my biggest asset or tool in my toolbox as I’ve kind of gone through my career. If you’re curious about lots of different things, you can remain agile and remain flexible in your decisioning and your thought process. And the mental models that you run to come to decisions are dependent on one set flow of information or one source so to speak, right? And so to be agile in thinking and action and in management I think really requires a certain degree of curiosity of all things. Things in your work life, in your personal life and just to keep pushing the bounds of what your brain can hold onto and thankfully I haven’t found the limits of that quite yet.
Mike Clifton: Yeah, I agree. I mean, at an EC, the way Max and I, or at least the way I think about it, I won’t speak for Max, is we’re ferocious readers. We really love to be challenged. And we have this one phrase that, you know, if everything’s under control, I think this is a quote we read one time, if everything’s under control, we’re not moving fast enough.
Greg Kihlstrom: Yeah.
Mike Clifton: And so that usually sums it up for people who get to know us, which is we are decisive people with conviction and a passion to make this thing the brand that people would say, wow, there’s a big differentiator. We don’t have to be the biggest. We don’t have to be, uh, you know, I’ll call you in the boldest. We just have to be the best. And so that, that’s what fuels the engine. Uh, and the agility comes from, like I said, a little bit of that, if we’re not moving fast enough and therefore everything’s under control, our job is to, to move faster. So let’s, let’s go, let’s go and get bold about it.
