INTRO:
You're listening to CX Confessions, brought to you by Khoros. In each episode, we’ll share the customer experience stories and insights you need — straight from the sharpest minds in CX — to better connect with your customers and create customers for life. Let's start the show.
KATHERINE CALVERT:
Hello, hello. Welcome back to CX Confessions. I'm your host, Katherine Calvert, Chief Marketing Officer for Khoros. Joined as always by my most amazing partner in crime and co-host, Mr. Spike Jones, GM of our Strategic Services business. How you doing, Spike?
SPIKE JONES:
I am good. I was just talking with Vasco about South by Southwest coming up. I'm getting my Olympics on. So many things to look forward to, including this great conversation we're gonna have today. So I'm pumped for it.
KATHERINE CALVERT:
Awesome. That is true, Spike. It feels like we're in an emergent moment for 2022. It’s finally really getting underway.
You mentioned our guest. We have a fabulous guest joining us for a great conversation today. His name is Vasco Pedro. I'll just tell you a little bit about him and then we will dive in.
Vasco is the co-founder and chief executive of Unbabel. That's a company that removes language barriers by blending AI, or artificial intelligence, with real time human translation services. A serial entrepreneur, Vasco has led Unbabel since 2013. He took it through Y Combinator and has raised 31 million in funding so far.
You're talking about South by, the Olympics. I mean, talk about major global events that bring people together from all corners of the world. What better way to have a focus of our conversation than on language — what connects us all, how we communicate.
Vasco, tell us about the story of Unbabel. What was your inspiration? I know you shared with me earlier that your mom was a professor of linguistics. Tell us about what was that inspiration that brought you to technology plus language and the creation of Unbabel.
VASCO PEDRO:
Certainly. Hi, Katherine, Spike. Great to be here. Thank you for having me. So yeah, language. Language has been a part of me for so long. I mean, as you mentioned, my mom was a, now retired, professor of English linguistics and in linguistics and language and it was always something around the house. And it was a recurring topic. I think the essence that really drove me to technology that connected to language was this fascination with artificial intelligence and, you know, the sense of, what's consciousness and how does our brain work and how do we become “we”? Which are, I think, very common questions for kids like you know, of like, in general for human beings of who are we right? How do we become human? How do we think?
And for me, I think the fascination was that this understanding that language was such an important doorway to understanding the cognitive process inside our brains, you know, being the most obvious expression of our intelligence. I think I started seeing language as an opportunity to understand cognition better.
It was interesting because, you know, I started coding when I was six. So coding was also a very important creative expression for me. And as I grew up, those two things started coming together, this idea of, you know, AI, language cognition, and the ability to create things to explore. There was a brief period in my 12th grade that I very briefly entertained going into psychology, and partly it was because it was a different way of accessing or trying to understand the same, the same cognition and human cognition. But I think the beauty of technology and computer science is that it's a creative action, right, it gives you the capability to try and very pragmatically and practically create things that interact and try to explain what you're interested in researching.
And so that ended up being my path. So I did an undergrad major in artificial intelligence and a minor in computation linguistics, and then after that I went to Carnegie Mellon and did my Master's and PhD in natural language processing at the School of Computer Science.
SPIKE JONES:
So a classic underperformer is what you're trying to say.
VASCO PEDRO:
You'd be surprised, you'd be surprised. Like so you know, like, I have kids, and I have four kids — four girls — and one of them is going to go into college next year. And we have this debate, right, because they're actually way better students than I was and I went to military school, boarding military school when I was a kid for a number of years. And when I came out, I was a good student, but when I came out, there was a strong period in my life that I also was fascinated with everything other than school. And so I can see how easy it was to kind of, you know, go into a different path. And so, yeah, like, I always thought of myself as, you know, tending to be a little lazy around certain things. You know.
SPIKE JONES:
I think that's debatable. I mean one of the things that I've enjoyed in our conversations is you seem like a naturally curious person. And I think that's a great quality. That’s a quality I look for in employees whenever I'm interviewing folks. And you said that Unbabel, you know, was built on an idea that you had about 13 years ago that has evolved and changed over the years. Now, hindsight is 2020, but if you knew then what you know now, what would you have done differently, if anything at all?
VASCO PEDRO:
Yeah, so, I mean, Unbabel comes from this idea that language is a massive problem in the world, and it's heavily experienced by companies as they scale and as they start going to different markets and having to acquire and serve customers that don't speak their language. And this is the basic issue that we don't all speak the same language and we never will.
It's sometimes said, oh, we're all gonna speak English. Only 25% of people in the world do speak English. It's a very useful language. It is the most universal language right now, but still, the vast majority of the world doesn’t speak it. So this creates a big problem. And it's a problem that is becoming more acute because companies are expected to go global earlier. There's less and less physical barriers in creating and shipping and consuming products. And so language becomes a bigger barrier all the time.
Now, there's a trend that happened around 2013 when we started Unbabel that AI was starting to become really relevant for what you can do with translation, for example. You know, a couple of years before, machine translation was at an earlier stage, which, if you'd given it to a human translator, they would start by erasing everything. And right around when we started is when you start seeing people taking the output of a machine translation engine and being like, oh, actually, this is kind of useful. I can work with this. And this makes my life easier.
And so there is this sense that AI was going to start having an impact more and more and so one of the — and typically what we're seeing is they're having impact in highly commoditized human-driven tasks, but they are repetitive in nature. And language is a good candidate for that.
And so, when you look forward, you'll see our thesis was, hey, companies in the future will deal with this from an AI centric perspective. It just, AI isn't there yet. And it might not be there for a long, long time. But this will gain ground, right. So we have to rethink the way companies deal with this on like, what are the tools necessary? What are the processes? Where are the platforms that we need to create to enable AI to be efficient within the enterprise to deal with language barriers? I think if I went back, you know, we, doing a startup is a very interesting exercise in search. Some people find it right away. They just have the insight on, the deep insight of what the problem is, what the market is, or sometimes there's a lot of luck involved in being successful.
I think, in our case, hindsight is 2020, right. So what would I have done differently? I would have gone back and maybe spent the first six months just sitting next to a translation agency and seeing how they worked. There was a bit of hubris from our part of, hey, we come from technology, that's the hard part, the actual business of translation, that's easy, right? And so you go in and suddenly realize, oh, wait, there's this whole other area that I need to figure out, and it takes you a while and takes a lot of bumping against the wall to start learning. I think we could have accelerated learning.
I think the other is a bit maybe more intangible which is coming to the realization of what a product is. And when a product actually deals with a real pain investors sometimes say hey, build us an aspirin, not a vitamin, you know, like find something that people have real pain. And so understanding deeply what that means and where's the actual pain takes time. And so I think if I went back I probably would have gotten there faster because I would know more, so it's, you know, stuff that requires experience and attempts to to learn, but I think you're right, I am curious and learning is part of what drives me so I can’t say it’s been a bad a ride so far.
KATHERINE CALVERT:
Doesn't sound like it. You know, our show is about the customer experience. And you touched on this earlier, Vasco ,when you talked about the pressure and the opportunity for companies to think globally, to engage with customers around the world. And that always seems like a huge opportunity, and as a practical matter it's really difficult. It can be a problem that gets solved in a silo or in a function or in a group. And I was curious, as you think about the opportunity and the customers that are most successful, how are you seeing them really kind of bring that through an enterprise lens? How do they think about language from a more of a breaking down the silos within an organization to make sure that language becomes not an obstacle but an opportunity?
VASCO PEDRO:
Yeah, Katherine, you touch on a great point because what we typically see is, as with most human processes, sometimes the problem is the humans in the process, right? I mean, we like to create silos and to kind of contain things and have control over our little part of the world. And that's also true in the way companies deal with this problem. And what we were seeing was, and it’s still true o a large degree, is that you end up having a hodgepodge of solutions, depending on which party of organization you are.
So you might see marketing hiring and having vendor relationships with translation agencies, for example, to deal with certain content and then product might hire in-house translators to do something else. And then customer service actually hires people that speak the language in locations around the world and then sales does something else and and there's not a not a consistent way of providing a consistent customer experience end-to-end.
And I think that's the other thing that we see a trend and a shift in the market is towards how to create this central, consistent customer experience end-to-end. And the same applies to language, which means that there has to be a way to very quickly deploy language capabilities across the different areas of the business that have the same tone and language and at the same rate. I mean, it's very frustrating for consumers if when you sell them something you speak 30 languages and you speak their language, but then when they have a problem, oh, they have to speak English. And this happens a lot.
There's a there's a bit of a typical journey of an enterprise in a globalized product that starts typically with a website or an app, right, it's like hey the thing that you get to consume or, and then you'll see things like, you know, sales websites, and you'll see things like marketing, but customer service a lot of times is the last to be dealt with. And so a lot of companies for a long time end up relying on just one language for customer service while they're already selling in a bunch of languages. And this creates a bit of a customer service inequality. You know, you get the sense that if you speak English, your level of customer service is so much better than if you're not.
And if you're in other parts of the world, especially in developing countries, you might not have — for example, you know, I don't know, situations like you go to an airport in Lisbon. Iberia doesn't have a presence in the airport, right? You have an issue with the flight and suddenly, what do you do? You call Iberia. But then if they're not speaking Portuguese, they only speak Spanish, you know, all of this then creates real issues of how do I deal with problems, right?
And what we're seeing is things, the quantum global phenomenon is becoming almost daily now, right? Things propagate so fast, and you see digital products — you know, one of the examples are PokemonGo and how quickly it became a complete global phenomena. In one week, everyone was doing it. Why? It’s a digital product. It doesn't, you know, doesn't cost to ship. And it's available and gamers are global by nature. And so, that trajectory is accompanied by the ability to do that in a bunch of languages. And so there's a clear impact in growth in companies that can very quickly tackle a bunch of languages and companies that can't. The problem is that right now, it's still hard. It requires a lot of operational overhead to be able to have this consistent experience, which is something that we're working to fix.
KATHERINE CALVERT:
And you have some data to back this up. You all did a global survey, right, on multilingual customer experience?
VASCO PEDRO:
Yeah, it's been a very interesting survey done by the team. We surveyed a wide variety of companies, more than a thousand companies, on different aspects of the importance of customer service across different sectors. I wanted to send — I don’t know if I sent you the numbers. I'm trying to find — I don’t want to say the wrong numbers here. But it was done by our marketing team last year, and we presented the results a couple of times. And there were very interesting findings around the importance of customer service.
KATHERINE CALVERT:
Yeah, I think I have some of them here for you, Vasco. Your team shared them with us. So it looks like — so trust and loyalty, which is obviously a big theme when we talk about what great CX — that's a very consistent opportunity, right. Why do you care about CX? Because it's about retention and an opportunity. It looks like you all found that without native language, customers leave, so you found that 68%, or almost 70%, would switch to a different brand for the same thing if they could get support in their native language. People will pay more to communicate in their native language.
So you all found that 75% of US consumers said they would only spend $500 with a brand that does not offer native language customer support. But 64% said they’d pay a higher price for the same thing if they could get the same solution but in their native language.
VASCO PEDRO:
Yeah, I mean it, yes, in one way the survey reflects a lot of common sense, right. I mean, think from the other side, like would Americans buy products that don't support English? You know, would you go to a website and buy — you wouldn't, right?
And what you see is the stability, or this high correlation to language and trust. That the way we communicate is what enables us to create trust. And if we can't communicate in a common language, it's really hard to do that.
I mean, we see it in our customers — it’s so interesting. We had this, one of our gaming companies used Unbabel to enable on the customer service part when people were becoming paid users. So in other words, going from a free part of the game to the paid part of the game. They switched the way that they interacted to be able to support native languages. And they saw a 30% increase in conversion. It was just, it was immediate. If people like, wow, this is — and the interesting thing is, a lot of times it's not that people feel like — they don't start from the state that you didn't support that language. You know, like when the user comes in, you either support their language or not, right? So the experience happens in their native language or it doesn't happen. You know what I mean? So it's not like you can, you know, you lose that customer at that point, you very rarely have the ability to get it back. And so that ability to create trust with language is, you know, for businesses, is really, really important. And we see that over and over again.
SPIKE JONES:
The very definition of you only have one chance to make a first impression, right. I think that's fascinating — and the correlation between trust and language. That's, I love that and love to think about that. Is there, so either in the AI space or even in the language space, is there a commonly held belief in either of those industries that you just don't agree with? That you might have a different opinion on?
VASCO PEDRO:
Yeah, let me think. So, yeah, there's a few. The one that I'm thinking right now is actually on — there's a common belief right now that AI is — like language is solved. That machines, that Google, has solved translation. And we see this a lot of times. I don't believe one, that we've solved it. But more importantly, I don't believe that in the next 10 years we'll have a machine translation engine that will be on human parity for the majority of the things we use it for.
You know, I think we systematically over — the whole field of AI started really with machine translation. So it was post second World War you had the cipher people that were saying well, what if we think about language as, you know, just a coded thing, and we'll just use the same technologies that, the same techniques that we use to decode Enigma we’ll use for another language and voila, we're gonna have this done in five or 10 years. And this was 60 years ago.
And so we severely always under-appreciate how hard language is and a lot of times we make non-linear assumptions of where we're going to get. I don't believe that we're going to get there in the next 10-15 years of getting to a point where you have a machine being able to translate that kind of levels of nuance that a human does in something that is non-trivial.
KATHERINE CALVERT:
I think that's interesting. That's a real, that's a common theme we hear in the broader discussion around customer experience and customer service in particular, right, there was definitely a moment where bots and AI were going to eliminate the contact center and you would never need people on headsets and agents to manage problems. And that belief was quickly corrected. And I think what we've seen is the customers that are getting this right are using technology in the same way that you're using it: to find the efficiencies, to get a head start, to solve some of the lower-order problems and then using that human intervention and human engagement to solve the more nuanced and complex opportunities.
VASCO PEDRO:
You know, I was just thinking that maybe this is — what's the theorem that, so there's, if I remember, the rule that says that when smart people assume that other people are smart, and that people that aren't smart have a hard time understanding that they're not smart because they're not smart enough to understand that. But there's an actual name for this. Oh, man.
And I think there's a, it's based on this idea that when you do something really well, you stop really perceiving the complexity of what you're doing, because it comes easy to you. And so you assume that it's easy to do.
And so you have this, it's one of the things that's the basis of imposter syndrome. It's a very typical thing. Most PhDs for example, it's like, oh, the stuff, there is a recurring nightmare of PhD students that someone's going to stand up in their PhD defense and be like, you're a fraud. You know, that's super easy. You shouldn't have gotten a PhD for that. And it's very, very common. It's surprising. And it's because when you become an expert at something, it stops being hard for you. You're like, you've just immersed yourself so much in it that you think everybody else can, you know, like is able to do this. And I think with language there's a bit of this. We're like, it's easy for us to do it. So why wouldn't AI be able to do it? Of course, we can do it.
And we don't understand the complexities and I think chatbots and conversational agents are a great example, because not so long ago, everything was going to be conversational agents, right? Like, with that said, we're done. It's gonna be so easy. And what we're seeing is, underneath that there's a piece of technology, it's really about dialogues, about like, how do you manage a conversation with someone and the dialogue technology hasn't really evolved much since the 80s. You know, it's still overall a decision tree. You're kind of doing things like if the person says this, then I say this other thing, but that's not like, the flexibility for humans really doesn't work like that, right?
We're able to jump to so many different topics and create nuances and say things even though we say one thing, we mean a different thing, and there's so much nuance in there that we just pick up automatically that you can't go rule-based in something like this, right?
And there's really breakthroughs that have to happen at the core level of understanding dialogue and semantics that just haven't happened and we don't even know — like we don't even know really how we do this. There's a lot of cool work being done by DeepMind, but when you look at the way humans are able to transfer learning, right, we go and we play tennis. And then after that, if we're going to play squash, people that played tennis will play squash better because there's a lot of stuff they learned that can be reused, right? Or if you play football and then you play flag football, it’s kind of like you know, like it's very similar.
Computers can't do that. AI can't do that. This idea of transfer learning. It's like, well, if I learned something, I get really good at recognizing images of cats, right? And then if I want to recognize something else, I have to retrain the algorithms in the beginning. Transfer learning is definitely a problem. And it's one of the many things at the base of what we do when we do something is, like this, talking, right?
KATHERINE CALVERT:
So I looked it up. I think I found what you were looking for, and I'm obsessed with this now. The Dunning-Kruger effect. That's it. Fascinating. So it's a cognitive bias of — ready for this? Illusionary superiority. I love that I've learned something. The Dunning-Kruger effect. And here's a great summation, which is actually a Shakespeare quote: “The fool thinks himself to be wise while a wise man knows himself to be a fool.”
SPIKE JONES:
Nice.
KATHERINE CALVERT:
Right? Thank you, Vasco. That's fascinating. I was, I didn't know about Dunning and Kruger. Another question we always ask our guests — we just talked about a commonly held belief that you disagree with when you talk about natural language processing and AI and then of the millions of people out there I think you said only 25% speak English. All the biases baked into that. You've got to be flooded with data.
So quite often a question we always ask our guests is, when you are thinking about the metrics and data, what are the bits that are most important to you, whether it's helping you in your business think about the problem you're trying to solve, what do you always look for or reach for when you're thinking about how to wade through the data avalanche?
VASCO PEDRO:
So there's three key metrics that we look at at Unbabel that we’ve consistently looked for since the beginning: cost per word, turnaround time, and quality. The base of this is because if you assume the cost of quality, let's say you start with a human-level quality right? You have a bunch of translators doing translation, and you measure that as baseline. If you're able to maintain that over time, when you reduce the cost that it takes to get to the quality, that cost is really driven by human effort. And so reduction of the cost means that you're driving efficiency typically through AI, right?
So it's actually the most approximate measure of how much impact is your AI having. And when I say AI, this is very general, but it's really a combination of things, you know, it's adaptive machine translation, it’s quality estimation, it’s different things that the cost — like there's a lot of little pieces — well, big pieces — that add over time.
And what we see at Unbabel is that we genuinely, over the last eight years, quarter over quarter, we have reduced cost per word consistently, always. And that has to do with a combination of data and AI and tools and efficiency — all sorts of things, right. So that's one metric that's important for me to look at.
Quality in the sense that, you know, like quality is a subjective topic in language. Until recently, there weren't really standard measurements of quality. Quality was however someone perceived it. You showed it to someone like yeah, that's good or that bad. In the last year, there's been MQM, which is multi model quality metrics. It's rapidly being adopted as the kind of the standard and that's providing objectivity.
So what this does is you have a document that's been translated and then you have a linguistic annotator, a human and expert, go in and annotate the translation according to a taxonomy and so you say, okay, where are the errors? What type of errors and how, what's the severity level? And when you do that, you can generate a score that gives you a somewhat objective measure of how good this is. And this is important to track because there's an expectation of quality from our customers at a certain level, and we need to maintain that, right? So because, you know, if you don't, then it's irrelevant. Like if you're, if you're turning in, if you're translating things in a bad way, nobody wants that. It's like almost, you need to go above a certain point.
And then turn around time because you want to do it more efficiently and faster, etc. So those are kind of three core metrics for us that we keep pretty close eyes on. A pretty close eye.
You know, it's surprising actually. Unbabel — I was a scientist, my co-founder also, we come from an academic scientist, data-driven background, and always, this has always been very important to us, like, data-driven. And I'm surprised at a startup how even the most data-driven startup is way less data-driven than you'd imagine because you're iterating and changing experiments and you have sparsity of data and you have this, in your mind you think, I'm going to do this continuous thing. It's going to provide this amazing set of data, then it's going to, I'm going to take deductions from it. I'm going to look at this you know, like okay, I'm going to try these three things, and customers are going to interact with them, and then I'm going to make a decision.
But what inevitably happens at a certain point in the startup is that you change things so fast that you're never making decisions with perfect data, right? You always have, you look at the data and this, the common feedback that I always have is oh, yeah, for example, in the case of sales, right? We go through a pipeline, so like a set of stages, and salespeople go in and say how many people, how many feeds, how many sales-qualified leads, and what's the demand funnel. And then you want to look at that at some point, wait, but this doesn't mean, this doesn't match. Oh, we have because we change the way we measure right like this is one of the things that happened, right?
So it's been having consistent data, so important, but what I find in a startup is that it's very hard to do that over a significant period of time, because things are changing a lot. And so we end up going back to these three metrics a lot because they are things that we can actually measure consistently over time.
And then other pieces to run the company change frequently. And so, you know, the key metrics that we look at this year are probably different than ones we did last year. They reflect learning and evolution. But you know, I would say for any startup, probably revenue is important. Growth.
SPIKE JONES:
Little bit. A little bit.
VASCO PEDRO:
You know, growth, measures that — are customers happy, net retention. Are they using your product a lot. This is something that you know, it's something they're consuming.
SPIKE JONES:
For sure.
This is CX Confessions. So we do ask this question to all of our illustrious guests. Along the way, 2013 to now, along the way, you know, there are lessons learned. Sometimes they are hard lessons. So could you share with us a hard lesson, or maybe a misstep that you corrected down the road that made Unbabel who they are today?
VASCO PEDRO:
Yeah, well, so many.
SPIKE JONES:
No worries. That's all of us. That's all of us in our careers, for sure.
VASCO PEDRO:
Yeah. Now, I think for me, one of the most relevant perhaps hard lesson on how long it takes to iterate to get to a product. I think, you know, it's easy to imagine a certain mental model of the world and think the world is going to be like that. And you kind of base all your strategy on, I'm going to build this product, we're going to have customers, this is going to happen by this time. But it always takes longer, right, and so how do you create those buffers? How do you bring people along? I think it's, you know, it's easy sometimes, I don't know I know the answer and this is where we're going. But if you, if you don't bring people along with you, you're going to find yourself alone in a boat, right, and you need other people to row with you — and so, which is much harder to get to the other side of where you need to go.
I think one of the — there's been hard moments at Unbabel, like every other startup. Moments that you almost don't make it, and you look back and like early on, I remember this really early on there were 15 people, and we were trying to raise capital. And there was one moment where we're like, oh, it's gonna be hard, but we were trying and we could see that things were moving forward and doors, we were adding a lot of features. And we had a big meeting and we came out of this with the realization that we need to actually kind of hit on the brakes, right, we need to kind of reduce burn. And so we ended up letting go almost half the people, which was one of the toughest things. It was seven people so it wasn't a huge amount of people, but it was, they were all really close friends. They were the people who were with us from the beginning.
And then the next day, I talked to an investor and they had talked to another investor and they got excited and an hour later we had our round done. It was literally like, this was happening. It was such a cognitive dissonance. I remember that we were having these meetings with, so half the company at the time, saying hey, look, we're gonna have to let you go. Just not, like, we need to reduce burn. There was one position that we needed to fill that we realized this is, we absolutely needed. So halfway through this, I was interviewing someone and convincing him to join as I was letting other people go, and my brain was like, what the hell? And then one day later, I'm talking to an investor and he's like, no, no, we're in. This is great.
So the lesson that we learned right away was let's really make the money count. Let's not rehire everybody and go back to the burning we were because we've seen how fickle this can be and we need to conserve cash as much as possible.
SPIKE JONES:
Yeah, definitely a hard lesson.
KATHERINE CALVERT:
All right, Vasco. It is time — this has been a fascinating conversation, thinking about language in a whole new way and I learned about the Dunning-Kruger effect. It is a time where we talk about you. So this show is called CX Confessions, as Spike just reminded us. We believe that all customer experience is fundamentally personal. And so we always like to end with a little insight on our guest.
So we have our five quickfire confession questions to let us learn a little bit more about Vasco Pedro. So we're going to start with: what was your first concert?
VASCO PEDRO:
So, I’m trying to remember. Technically my first concert, I think it was, I took my godson to Slip Knot.
SPIKE JONES:
Okay, that's a good one for him. Yeah.
VASCO PEDRO:
No he wanted to go, and I was like, okay, sure. You know, you seem kind of young. But let's do it. I don't think I'd been to a concert. I wasn't much of a concert going kind of guy, but then it was like. It was interesting.
SPIKE JONES:
That's it. That's it. That's a good introduction. That's an interesting introduction. Just hopefully you stayed out of the mosh pit. So that's good. How about your first job?
VASCO PEDRO:
My first job — technically when I was 14. So I worked in the meat factory.
KATHERINE CALVERT:
Wow.
VASCO PEDRO:
Yeah. For a summer. I was, I literally got to see how the sausage was made, which was kind of interesting.
SPIKE JONES:
Wow.
KATHERINE CALVERT:
What, if you couldn't do what you're doing today, Vasco, what would, what other profession would you attempt?
VASCO PEDRO:
Yeah. So as I mentioned, I briefly entertained going into psychology. I still like the space a lot and understanding people. I am naturally curious, as you said, and so human beings fascinate me. I don't know, there's something interesting about that, that I might attempt.
When I was a kid, obviously I wanted to be an astronaut. And then I realized that my definition of astronaut was Star Trek and this idea of like gloriously traveling galaxies, and the reality is being cooked up in a small capsule for days on end are like, no, let's, let's do something else.
SPIKE JONES:
Little different. What is your current favorite app on your phone?
VASCO PEDRO:
WhatsApp. I think I run 70% of Unbable on WhatsApp.
SPIKE JONES:
There you go.
KATHERINE CALVERT:
Wow, that is fascinating. Okay, last question. What is your biggest indulgence?
VASCO PEDRO:
I don't know if it's the biggest, but I would say it's up there. I love anime. And you know, my co-founder and I, one of the things we bonded over is that we both discovered that we were completely obsessed by Naruto. And we were watching it, you know, at the same pace.
KATHERINE CALVERT:
Oh my gosh, all of a sudden now my son's gonna want to watch this episode. Yes, Naruto.
VASCO PEDRO:
Yeah, Naruto was, you know, to me it’s the best anime TV show and it's a guilty pleasure.
KATHERINE CALVERT:
That is amazing. It's so nice to meet you. Thank you for joining us. Thank you for sharing the story of Unbabel and letting us think differently about how sort of the foundation of great customer experiences is really communication and trust, like you said, which starts with being able to communicate in the first place. So thank you for joining us.
Thank you to our listeners. We hope you enjoyed the episode and we hope you'll tune in next time for more CX Confessions.
VASCO PEDRO:
Thank you for having me. It's been a pleasure.
KHOROS:
Your customers expect to be understood — their likes and dislikes, their history with your brand, and their communication preferences. But so many companies struggle to connect the dots of the interaction across their own teams and channels and its creating customer experience challenges and disasters. That's where Khoros can help. Khoros is the award-winning customer engagement platform built to turn those siloed interactions with your customer into enterprise value. Khoros works with more than 2,000 of the world's leading brands and powers more than 500 million digital interactions every day. Khoros is the award-winning platform for digital-first customer engagement. Ready to create human connection across the digital customer experience to create customers for life? Learn more at Khoros.com.
Thanks for listening to CX Confessions, brought to you by Khoros. If you enjoyed today's episode, make sure the hit subscribe in your favorite podcast player and give us a rating. See you next time.
