Helpful Cost-Effective Customer Service Solutions for Every Industry With Rowan Trollope, CEO, Five9

It's really a problem that's solved in two halves. Problem one is the talking and the conversation side. Problem two is the actual integration with the backend systems. And so there's two parts of our product. And if that information, you can directly in our product, you can link and we have prebuilt integrations into many backend systems. So if you're using Salesforce, for example, we have a deep integration with Salesforce. So you can, you know, kind of click and drag and you don't really have to be a programmer to do this. To wire up those backend systems.

We've all been there before. Something unexpected happens with a product or service you just purchased. And then whether that be your flight, your order, your membership, whatever it may be, you immediately roll your eyes thinking about the time-wasting, frustrating process you're about to embark on. You know, calling customer service. This all too common roadblock of poor and costly customer service is going to be a thing of the past thanks to companies like Five9 and CEO Rowan Trollope. Their two-pronged approach with cross-industry application is at the cutting edge of providing a better customer experience across all companies in the Fortune 500. Stay tuned to learn how. IT Visionaries is brought to you by the Salesforce Platform. Ready to create better, faster customer and employee experiences? Build and automate rapidly using the Salesforce Platform's low-code tools to click, create, and ship from anywhere. Check out a demo at salesforce.com/platform. Welcome everyone to another episode of IT Visionaries, and today we have a special guest. He is the CEO of a company called Five9, that's F-I-V-E, the number 9, dot com. Rowan Trollope, welcome to the show.

Thank you for having me very much. Great to be here.

It's awesome having great tech leaders always on IT Visionaries, but we're gonna do something a little different today, and that is, Rowan, we're gonna start with the lightning round. The lightning round is brought to us by Salesforce Platform, the number one cloud platform for digital transformation of every experience. Rowan, this is where we ask you questions outside of the world of work so our audience can get to know you a little better. Are you ready?

I'm ready.

All right, so what do you like doing for fun outside of work?

Climbing mountains and skiing down them.

Oh dude, you're one of those guys that you're backpacking up, you find a mountain, you backpack it up and you ski down. Do you guys, you go with a crew or do you do this by yourself?

Uh, usually with a crew. It's a little safer when you're in the mountains, so With a couple of friends usually. And yeah, last one was in Austria. It was super fun. It was very hard and icy on the way down, but it was, yeah, a few days and it was awesome.

Okay. How long does it take you to get up the mountain?

Well, it depends on how big the mountain is, but, you know, some cases in multiple days. In this particular case, it was like kind of 2 days.

2 days up. And of course, coming down is what, 15 minutes, 20 minutes?

Yeah. Well, no, actually, you know, it took a day. And more, yeah, about a day to get down.

Oh, really? Okay. So it's not like a ski run where you're just like shooting down the mountain?

No, you are. But it was like those— it was really icy. It was in Austria and it was just wasn't good conditions. So. Okay.

Do you consider yourself a thrill seeker? Sounds like you very much are.

Definitely. Yeah.

What other thrilling near-death experiences do you engage in?

You know, that's my primary— that's my primary hobby, I would say.

How often you get to go?

Well, you know, not as often as I'd like. My, my main— the main mountain I'm climbing is building the Five9 business, and that's— that takes up most of my time.

Before we dive into, you know, the Five9 business, we also read— we did a little homework on you, on your— we did a little research, and your bio mentions you taught yourself how to program on the Commodore 64 at a local Radio Shack. Is that accurate?

That's right. When I was 11.

Yeah. What did you program? I mean, when I was 11, I was thinking I was still picking my nose. I don't think I was able to.

I was in— I saw that movie. Well, I don't know if anyone watching would remember it, but for those old folks like me, there was a movie that came out in the '80s called WarGames, and it was about—

Matthew Broderick, right?

Yeah. And he was talking to the computer. And so I was trying to recreate that, that conversational experience of talking to the computer. And of course, mine was horrible and mostly fake. So, it didn't work when my parents— I tried to show it to my parents. When they looked at it, I had to type in the exact pre-programmed questions to get the right answers, but they didn't know I was doing that. So, I totally blew them away. They thought I was a genius. Of course, it was just all a script of questions and answers.

How about physical things? We found that a lot of the developers that we work with or tech leaders are also builders in the real world, whether it's gardening, woodwork, or stuff like that. Do you build outside of software?

I like to tinker on cars. So that's my, that's kind of like a little hobby I have, you know, like I definitely, and I find it meditative, you know, kind of working on, you know, mechanical things. You know, it's interesting to code with your fingers, but it's quite something else to get in there with a wrench. And, you know, it's kind of like a big, big boys version of Lego is the way I look at it.

I've been there myself, right? Where I totaled a motorcycle once and I rebuilt it. But you are right. There's a level of satisfaction. It's like, hey, this thing clearly doesn't work. I mess around with it for, you know, an inordinate amount of time. Uh, but then it, it does work and it can transport my body and it's pretty, pretty nice.

Exactly. Yeah. It's very, very fulfilling.

Rowan, thanks for taking a short period of time to dive into your life away from work. Let's talk about Five9. So Five, you know, we, you've kind of shared a little bit about your background. You're a thrill seeker, you're a builder. You got your first introduction in software. It's interesting that you were, your first thing you tried to code was in communication cuz you're, you're kind of deep in it now. For our audience that doesn't know, tell us what is Five9.

Yeah, so we're a contact center company. We make software, software as a service. We're a cloud-based contact center platform. And, you know, that essentially— think about it— every way you want to get in touch with a business or engage with a business as a consumer, we make the software that makes that happen. So it's everything from if you want to call them on the phone, from the moment you hear the ring you know, until you talk to the agent and their experience, the agent's experience, that's all our software. But increasingly today, it's more about automation and digital channels. So if you're texting on SMS or in messaging in an app, or if you're talking to one of those conversational bots, you know, where it's asking you questions and you're answering the questions, that kind of thing, that's all our software.

Yeah. And Contact center software is one of those unique things because I think everyone— it's hard to know how many people have gotten a chance to use or been exposed to a product. Contact center software is one of those things where we've all been on the other side of what it's used for. Of course, we understand what contact centers do. For the most part, historically, it's been a negative experience. Talk about how, you know, the new modern toolkits, AI, cloud infrastructure, how is that going to make my experience better as a consumer? Because this is where you and other people in your industry are trying to get to is like, hey, how do we get ahead of what these people are asking about? I want to hear your perspective on this.

Yeah, I joined this company 4 years ago and my thinking was quite simple was you have, and by the way, my, actually if I back up even further, my very first job, paid job, not writing corny software on a Commodore, you know, was when I was 18 years old and I was in a contact center. I worked in a contact center. In fact, I took 8,000 phone calls for the company that I worked for.

Wow.

And it was a kind of a pretty miserable experience. It was really tough to do. And a lot of it was 'cause you were answering the same questions over and over and over again. Fast forward 30 years later, it's pretty much the same thing. And, you know, 4 years ago, and I thought about this space, what I looked at was the experience that I still had as a consumer 30 years later was still pretty bad. Most businesses, still use telephone, or, you know, some of them had implemented chatbots, which were fundamentally a sort of a bad experience. You know, they had made it harder for people to get a hold of the— to get a hold of companies. You get— you're getting these IVR trees. You have to push one. You know, we all know about push zero to get to the agent now. And so I just thought, look, here's an— here's a space where businesses around the world are spending almost a quarter of a trillion dollars a year in contact centers to deliver a service that basically no one likes. And that felt to me like an incredible opportunity. And it felt to me like the technology was reaching a level of maturity where we could actually solve some of those hard problems. And that's what Five9's been engaged in. And that's the mission that we've been on for the last 4 or 5 years is really trying to transform that experience to make it something that's delightful, not something that's painful and difficult.

And when you think about it, how, how, how can technology make it better? Because, you know, I'll set the stage for what it used to be, um, or what historically we've all experienced. But one of the challenges we've heard from people in this industry is if the first thing is it's very hard to understand what someone says, meaning people talk differently, they approach things differently, they describe things differently, like what they're doing. And people are historically really bad at describing anything that they'll just say doesn't work. It's like, I was like, okay, I can't help you if you just tell me it doesn't work. So you have the problem of language, then you have the problem on the other side of problem of knowledge, which is if I'm the person addressing the issue, if I don't have knowledge on how to solve it, typically what it means is I have to look up the answer or something like that. And then the third layer was like a problem of authority, which is like, now that I can find the answer, do I— am I even authorized to do it? If I know how to solve the problem, like make a, let's say, a credit adjustment to your bill, but I'm not actually authorized, now I have to pass you to another department or person. So it's like authority, understanding, and knowledge. Those are like the three trees that I guess technology is really trying to bridge. I'd love to hear from your perspective. Um, is there anything else adding to that? Because this is one of the areas where we all, like I said, we're all exposed to and we want it to be a better experience. Talk about how Five9, how you're approaching this and with your team, like how are we going to solve this?

I think one of the core problems to be solved is actually cost. You know, when I worked in the contact center, I remember it was a surreal experience where a new manager got hired and he came in and he said, you know, we, you know, I've got an idea. We, you know, we're, every time we pick up the phone, when you guys pick up the phone, it was talking to us in the contact center, small rooms, like 30 people. It's costing us $24. Okay. We lose money every time you pick up the phone because our product only makes like $20 per unit. So, If a customer calls once, like, we just lost money on that customer. He said, and the problem is— and he opened the manual and he said, here's the telephone number. It's like page 1, big, you know, 1-800 number. He said, our solution to this problem is we're going to put— I'm an— just contextually, I'm an 18-year-old kid listening to this, I don't know, gray-haired guy kind of come on and tell me what's what about the business world. And he said, the solution to this problem is we're going to make that telephone number a much smaller typeface. We're going to put in the back of the manual and then less people will find it and less people will call us. And I remember thinking to myself, I'm like, I'm waiting for Ashton Kutcher to come running out. Like, I feel like I'm going to— like, is this really happening right now? And it did. It actually happened. He went on to do that and it reduced the number of calls. But this story sort of underlies or sort of underpins a really important point, which is you can't really service your customers if you're relying on manual people to answer all the questions. And that's sort of at the heart of this problem. And that's where computers really have sort of showed up to the rescue. And specifically machine learning in the last 4 or 5 years has emerged where it can actually start to solve some of these problems. And so the approach today, and I think the biggest single thing we can do to resolve this problem is to make it less expensive. And the way you make it less expensive is you take the routine sort of high volume, but very low value questions off the table. and you can't have them being served by human beings. So for example, if you're dealing with a shipping company, one of the most common calls, number 1, is, "Where's my stuff?" Right? "I ordered it. I have a tracking number. Where is it?" Well, we all know that it's very easy to go to that company's website and punch in the tracking number and get your answer, okay? But a lot of people don't do it. They sort of still go through the old ways of doing things. They're picking up the phone and so on. And, you know, or maybe the tracking number doesn't show up right, or, you know, the information is not all you need. Well, what we've developed is technology that allows the computer to answer those questions instead of going to the human being, because the human being has access to— like, the agent has access to a certain set of tools, and you can ask them all the questions in any way that you want, but ultimately they're just going to go to those tools and kind of get you the answer. Well, we've figured out that computers can do that actually much better, and they can do it in a conversational way. So what we can do today is automate 80% of the work in some cases, you know, less, some cases more, that those human beings are doing. And that automation reduces the cost. And what that allows the human beings to do, like the agents, is then to actually deal with the harder problems and to become more, you know, they actually become happier when they're not dealing with this rote routine work. And as a result, they're able to focus on the things that human beings are good at, the edge cases, the complex things, places where you need real empathy with the caller. And so if you can use this technology effectively, and we're still, I would say, you know, in the early innings of rolling this technology out, businesses can actually reduce the cost of delivering service to the consumer, improve the experience of that service for those consumers. And so that's a win-win. It's a win for the consumer, it's a win for the business. And that's what Five9 is helping companies do really all around the world today.

So one of the things I saw from, like, the Five Dime website is it's, it seems to be broken into industries, right? Healthcare, FinServ, retail, education, sales and telemarketing, and it lists on, anyone can go check it out. I'm curious, is it because, is that, is it because, like, the language of how people talk and the problems that they have are kind of unique by sector? So it's like, hey, if we program our AI to lean towards this type of, you know, to language, it'll make it easier to solve certain problems sooner. Is that, is that the reason why it's verticalized like that?

It is. Yeah, it is. It's, there's very, there's a lot of domain-specific language. Um, you know, so what if you're, for example, in, uh, if you're building an IT help desk, you know, and you work at a big company in the Fortune 100, it's, you know, 80% of the calls into your help desk are gonna be the same calls that come into the help desk in all the other Fortune 100 companies, right? There's not like unique, there are some unique problems, but it's, you know, password resets and, you know, why is the website, so all these things. And what you wanna do is make it easy for an IT help desk to get started very quickly. You don't want them to start from scratch. A shipping company is the same thing. The previous example I used, right? Where, oh, where's my package? You know, cancel this order, like, or take like a service provider. Why is this thing down? Why is my service down or up? When will it be up? You know, when will, you know, how long is this maintenance period? You know, I'm in this zip code. So you can really help in each of these industries, healthcare, financial services, et cetera, et cetera. You can help them kind of get a boost, right? Like to get started so they don't have to start from scratch. 'Cause a lot of these industries look very similar in terms of the language they use, the types of issues that customers have across companies in a given vertical, are actually very similar. So we want to really just help accelerate the adoption of these technologies in those industry verticals.

Yeah, I would just— I always use airlines as my example in this. And I think, like, as an example of we all kind of as a human— as humans, we want a similar solution from that industry. So for example, on a flight cancellation, you can best bet we all would prefer the soonest available alternative flight in the shortest period of time. Like, no one's like, oh, I want to extend that. I mean, it might happen, but it's a— that's probably an edge case.

Exactly.

In the event of flight cancellation.

Exactly. And we can take the learnings across multiple different customers in a single industry and we can apply those learnings. So as our system learns more and more, we can apply them to other customers. So you get the benefit of, for example, start— this is a historical example, but Starbucks many years ago tried to do a, a conversational interface for their app so you could just order a coffee. And what surprised them was, first of all, If you think about machine learning, and I don't know how— this is a kind of more technical audience, I think. Yeah, you need data. Well, where was Starbucks going to get the data for how people ordered coffee? Because you need to have a whole bunch of text strings that says, I want a grande latte with half pump of vanilla, and you need like a lot of those. What was so surprising in this particular, uh, in this particular experience that Starbucks had was the number of variations of the ways that people order a coffee. There are millions of ways essentially to speak to the computer, to speak to a human agent. And humans are very good at understanding all of these variations and asking follow-up questions and so on. God forbid you don't say grande and you say medium, you get locked up in the back. But that was a great learning where they were able— and funnily enough, the way they did it is they actually put microphones in some of their stores to to record asking the questions.

That was the next question I was gonna ask is, 'cause that's not— that conversation's usually not recorded. So how would you even get it?

Now, the benefit in the contact centers, unlike a Starbucks where we have to somewhat creepily record people with microphones, we actually have all of that data. All of that data, most calls in contact centers are already recorded. So we have this gold mine of data, okay, that's just being— it's actually not— most companies don't do anything with it. It just sits in these recorded WAV files, you know, and they don't get processed, they don't get evaluated. Well, we're starting to unlock that data, right? We're applying automatic speech recognition, which has now achieved near-human levels of accuracy, right? Like very, very good. The latest Google and Amazon technologies here are excellent at speech recognition. Even open-source technologies are really excellent. So you can really start to understand these conversations, first getting them into text, then applying natural language processing on top of them to really understand what's being said. And that's just an incredible asset to get started with machine learning because you need all that data. You need to understand what are all the ways I could sort of cancel my flight or find out where's my package or change my password. Once you have all that data and the more of it you have, the better these computers can get at actually having conversational interfaces and being able to just have a natural language conversation with a consumer. Now, what that— and by the way, often that's going to be on text because we all these days just want to text more than call, but sometimes it'll be on the phone too. So you want to be able to handle both cases. That's one of the things that our product can do, is you can handle both of those with the same underlying automation, whether it's text or voice. At the end of the day, it's just a conversation.

Yeah, and as you describe this, two things start coming up in my mind, which is, uh, regarding integration and then, uh, staffing for like talent. So I'm gonna— I'll start with integration. I think it's probably easier. Is the goal of Five9, or do you see this in the future— I would assume that, for example, the call center of course has software, and that's where it collects the customer record or need. But then a lot of times the solution might have to happen in another system. So like a booking system, like we used in the airline examples, like, hey, or the application, right? If the Starbucks example— if I read into an app, it's got to then translate to what? An order ticket at the kitchen that then I can pick, pull, make the drink, and give it ready for Rowan when he comes in. So is that the next level? Is like you guys are integrating into all these existing systems potentially to be like, okay, now how do we execute the solution? Because now I know the problem, I know the solution, but in order to execute the solution usually means another system has to talk to this.

That's right. It's really two— it's really a problem that's solved in two halves. Problem one is the talking and the conversation side. Problem two is the actual integration with the backend systems. And so take the example of the canonical example I used earlier is like, where's my, you know, shipping company? Where's my stuff? Well, I can have the conversation with you, but I need to talk to the backend system to find your stuff and tell you where it is. Um, and so there's two parts of our product. And, you know, if, if, if that information, you can directly in our product, you can link, and we have pre-built integrations into many backend systems. So if you're using Salesforce, for example, uh, we have a deep integration with Salesforce. So you can you know, kind of click and drag, and you don't really have to be a programmer to do this, to wire up those backend systems. And we have multiple different ways that you can do that in our product. And, you know, sometimes you even run across customers who don't have a modern system like Salesforce or Workday or what have you, whatever the backend system is, ServiceNow, and you need to go to some sort of a legacy system. And for there, we partner with, you know, RPA vendors, robotic process automation, where you might be using a legacy system. So there's a whole second half of this problem, which is automation. Many of the cases we solve through our prebuilt integrations, but then we've got a set of partners for handling the ones that we don't sort of solve out of the box.

Yeah, that makes total sense. Now you mentioned this, it sounds like you use low-code, low-code applications as well on the Five9 side so that it makes it easier, I guess, for your customers to build these trees or these like decision trees.

That's right. Our entire product is really a low-code, no-code approach to solving this problem. And that's, Our principle, sort of our belief, if you will, is that, you know, while it's great to be a developer and there are many developers in the world, there are not enough developers. And certainly there's an order of magnitude less developers than there are sort of business operations people. And so if you can enable those business operations people to do the simple stuff, you know, to just to do the wiring together and not have to sort of submit an IT ticket and get your developer involved, That's actually, you know, an incredible way to empower kind of the democratization of this technology. And if it's all relying on developers, it's just gonna go more slowly until the world gets more developers.

Yeah. And we also heard from another person that was in, they, they weren't in what your business is, they were in, but they were in a low-code business and they were talking about how a lot of times in, cuz his use cases, uh, it was Jay Jamison from Quickbase. His use cases were in customer service where he says the service operators are often the best people to know exactly how this problem gets solved because they face it every single day versus a software engineer who's like, well, what's the problem? I don't understand why this is a problem or how often does this problem occur? Like, they're trying to quantify these things. But like, if I'm a service agent and like you said, you were dealing 8,000 calls, you know the problems and you know the solutions and probably can figure out like, hey, this bridge can make it smaller.

That's right. And a lot of this wiring is not— it's not exotic. It's not something where you need a computer science degree to figure it out. I mean, it's just hooking up APIs. APIs and passing variables around. It's very simple stuff.

Yeah, like where— like you said in the original, where's my order? Well, let's pull it into the shipping manifest, um, and figure out where that is. You know what's interesting is the next thing is like the linkages of systems, because so many systems now are, you know, one system links to another. So if we take, for example, an order— an order starts in a warehouse, it probably moves to a 3PL, it might move to the um, like your post office for last mile delivery. So like, let's assume something big like a, like a treadmill. Like a treadmill's a good example. If I'm, or I'm, or I'm getting something custom, which a lot of people did for their homes over this pandemic, which is they were ordering custom things, has to get manufactured. So that's one system probably knows where it is in the status of manufacturing. Another system knows where it is in freight and another system knows where it is in, um, last mile shipping. So like this level of integrations and systems, it's got to be increasingly complicated. Or do you, are you finding it that more people are consolidating into central systems?

No, it is, it is a very complex space. In fact, it's one of the things that I guess it surprised me when I joined this company because we sit right at the heart of the center. Like the contact center is in somewhat of a unique position in that it has to connect to like every backend business.

Yeah, yeah.

And most— in most cases, what ends up happening is that the human being is used as the glue, the agent, and they're swivel chairing. And often they'll have multiple monitors with 20 windows open. It's like, well, I first have to check this backend system for that, and then I go to that other system for this. And businesses often make decisions, the rational business decisions. They say, look, you know, priorities-wise, we don't have time to integrate this system with that. So we'll just do it manually. We'll just ask the agent to do that. And look, that's a normal business decision. And it's often, it's just an ROI base. Like, how much is it gonna cost us to hire developers to go integrate those two legacy systems? You know, and, you know, or could we just do that manually with some agents and we'll just give them two windows? Well, you can make that decision once, but, and it might make sense in a vacuum, but if you do it over and over and over again, what you end up happening is this, what ends up happening is this incredibly complex sort of swivel chair operation that the agents have to do to deal with all these complex backend systems, like the treadmill example that you gave. And so companies are increasingly turning to, I think the term in the industry today is customer data platform, CDP, like a single lens on top of all of these backend systems. So rather than trying to take all those systems and integrate them together into a single source of truth, you just kind of create another layer that sits on top and provides a single sort of view on top of all that backend data. So that's increasingly what we're seeing customers move towards is these kind of view layers that integrate the backend systems and do a lot of that complexity. And that you ultimately like, it's okay to do some of the manual stuff with agents, but it can often become overbearing. And you'll, you'll notice this when you call them up, because you'll ask the agent a question like, I ordered a treadmill. I'm wondering where it is. And then you hear this, and they're like sitting there for a long time and you're wondering what's going on. Well, that's because they're navigating all of these windows and systems and cutting and pasting between systems. So, you know, that's not a good experience. So if you want to have a smooth and delightful experience, you're going to have to implement either a view layer on top of that stuff, or you're going to have to integrate the backend systems.

You know, you're— what you just said where the people are the glue, and that's kind of how we companies historically have deferred to people. I was thinking, I just encountered this. I'm gonna call them out right now, it's okay. I just encountered this this weekend at Ace Hardware. You know when you look up to see if a product is in store and/or on the shelf? Because it was, it was something I needed to fix, make a repair on a door. So I was like, okay, run over and get it, I don't want to wait for shipping. And I show up, it's not there. And so I think, and then whatever happens is that who's the glue? The glue is in the store associate who I had to pull over and be like, is this part available? It says it's available online. Well, let me go in the back.

Right.

Like that's, but that's what it is. Like you said, that's expensive because this person now has to, is with me for 30 whatever minutes. I find out the part's not available. My door doesn't get fixed. I'm not happy. No one's happy. Like this is a problem. So that new layer.

Ironically, the mistake that a lot of modern companies, and I'll point to sort of more tech companies these days, have made, and that example you just gave is a great one. Like the real, like what is at the heart of that story is the real world is complex and messy. Like, yeah, the computer says that the thing's here, but maybe it's lost or it got moved on a shelf or, you know, it's in the back and somebody put it on hold. Well, it's really hard to account for all of these edge cases. And a lot of companies have tried to say, look, if you've called us, it's a failure mode, right? Like we should never be in that situation. We should always try to resolve the problem proactively, which is great. It's great as long as you don't make the decision that you just won't have anyone that you can call at all, because some companies have gone that direction. And they realize this later on and they say, oh boy, we can't do that because we can't account for every possibility. So you still, in every case are gonna need human beings in the mix, okay? For the edge cases. But you don't need to have this massive cube farms, you know, with people answering the same question over and over and over again. That's the kind of shift the industry needs to make is like, you gotta focus on automation. We still leverage the humans for what they do best, dealing with these edge cases and these, you know, kind of corner things that you can't program for in advance, but then try and automate everything else.

Yeah. So it's like the whole world's gone hybrid, right? Like that's a, it's a hybrid model right there in the contact center. You know, one of the things I think about Nexus for that we, I mentioned earlier for a business like what you're doing. So you have a lot of engineers working in language, certainly artificial intelligence, machine learning, how to learn language faster. You have a lot of engineers working in the dev side of how to integrate all these tools and applications so that, you know, if Five9 is a center point for, so people can use, like you said, that single view to, to actually gather the request, service the request easy as possible. What does that mean in regards to like talent? Because, and then there's also future innovations, right? Five9's gonna continue future innovating. So like when you think about the technical talent you need at your company, what type of people are you looking for? What kind of projects and skills do you need to make this product as it is today run? And also some of the future things you're trying to accomplish. What are you looking for? You looking for more data, data scientists? You're looking for more linguists? I have no idea.

Yeah, well, kind of all of the above. And we, we definitely, uh, we, we hire machine learning folks, data scientists. We hire, you know, kind of full-stack developers. You know, our platform, you know, is built in Java, so full-stack Java developers, uh, you know, front-end, back-end, UX designers, all the kind of normal stuff you would see in a SaaS company. Um, but the way I think about it, you know, is, um We're really looking for smart, curious people because this technology is moving so fast and, you know, we're trying to be at the cutting edge of these solutions. And so you can't often hire for someone who's done what you already want, you know, done already what you want to do, because we're trying to do things that haven't been done before. And so for those kinds of things, we're just looking for people who have like an innate sort of passion for programming and, you know, or whatever the what their sort of unique discipline is, and a deep sense of curiosity, so intellectual curiosity, because I think a lot of these things can be learned, and obviously they can be learned fairly quickly these days. So that's kind of more, I think, the focus that we have as opposed to kind of looking for specific, somebody who's already done X or already done Y.

So for yourself, we've seen, when we were doing our homework, we saw some videos of you and some of the speaking and talks you've done. But one thing I didn't hear anyone ask you, which I want to ask you, is what if, if the world's perfect, imagine Five9 hits all the things you want it to hit. What does the future of customer service look like? To give us an idea of how, how do you think your experience, my experience is going to be in the future when, uh, you know, these tools reach like that 5-year benchmark or that 10-year benchmark. I know you're never going to be done because in 5 years you'll have something else to do, but what's it going to look like in 5, 10 years? I have no idea.

It's pretty simple. I don't think about it for me. I think about it for my kids. I have a daughter who's 9 years old today and turning 10. So when she's 20, let's say, kind of, you know, yeah, hopefully, and hopefully in university or exiting university or thereabouts, you know, going into the workplace and showing up as a consumer and engaging with brands in the way that we already do today. So when Penelope is 20, My vision is that she'll be talking to a 10-year-older version of me, and I will be telling her about the olden days when customer service really sucked. And she will look at me and she'll go, "What? Yeah, what are you talking about? I've called, you know, or messaged 10 companies and it's been delightful." And it'll be one of these, like, anachronistic things where I'll be like the old guy, like, "Well, when I was your age, you know, like 10, 20 years ago," you call a company and you'd have to go through this phone tree and push 1 for this. And, you know, and then you'd get someone who didn't understand your problem. And she will look at me quizzically and just go, why would a business do that to their customers? That doesn't make any sense, Dad. I don't even believe you. I don't believe that the world could have existed in that way. It'll be so foreign to her that businesses would sort of have the, you know, that it would be a normal condition for businesses to offer bad service to their customers. Will be just a very foreign concept in 10 years. That's sort of the vision and the dream. Now, maybe it's 10 years, 15, 20, I'm not sure, but I think that day will come. And it's hard to envision for us because we've grown up with things being a certain way. But there's many examples in history of like, it always was this way until it wasn't, right? Like, take the example of the secretary pool. I know that never existed since I was in business, but You know, you— I saw on Mad Men, like, there used to be these, like, you know, these rows of cubicles with, with people, mostly women, sitting in them with typewriters typing documents.

That's my mom's first job coming to America. Yeah, she was 100 words— she was like 123 words per minute on a manual typewriter.

And, and it might have been hard for your mom to envision a world where that just wasn't a part of business anymore, because at the time when your mom got that job I bet you every company had a secretary pool, okay?

Yeah.

Well, in the same way, every company today has a contact center, but do they need, like, but in 10 years, will you have that same contact center in the way that it exists today? Like, in the secretary pool, along came the word processor and poof, it went away. In contact center, along comes machine learning and language interfaces and poof, that field of cubes with people with headsets answering the same question over and over and over again, that goes away. And it's replaced by something really radically different where, you know, it's actually more about engaging with your customers and providing great service and not about answering the same questions over and over again, or worse, avoiding your customers, which is how it was when I was, you know, 30 years ago. My vision of the future is my daughter's 9, Penelope, and when she's, you know, 19 or 20 and going into the workforce, she's going to experience customer service in a really different way than you or I did. This idea that businesses would have bad service is just gonna be foreign to her. I'll be telling her like, "You know, when I was, you know, 10 years ago, you call up a business and you'd get terrible service. You push 1 for this and 2 for that." And she will look at me and just be like, "Why would they have ever done that? Why would any business in their right mind treat their customers that way?" So it'll become really a figment of the past, right? This notion that bad customer service was once a thing in business, just like many sort of inefficiencies have existed in business and now they're gone. This is another one of those things that's going to just really radically transform in the next 10 years, and it's all gonna be enabled by sort of people in the contact center industry leveraging these modern technologies.

Listen, if we get to that point where the solutions are more preemptive, I can't wait because I, I told this story in a previous episode, but like, I'll give you an example, Rowan, that like, I think tools could probably help. I can see in 10 years making your life so much better. And it was, I was using I'll— it's okay to call the company out. We— I was using Intuit TurboTax, Intuit QuickBooks, and I was trying to issue a refund. So the way I searched for that was refund. It says, oh, do you want a refund? It's like, I don't want a refund. I wanna issue a refund. Right? And so it was like this constant back and forth. But what ultimately ended up happening was I was provided a knowledge guide in a forum of which I then had to, like, look up and figure out, and then I manually could do the refund. I'm imagining a future where it's like, oh, this is how you do a refund. Who would you like to do one for? And I was like, oh, well, I'd like to issue a refund to Rowan. It's like, would you like me to do that for you? Yes, I would. Because that's, that, that's, that's where I'd love, that's where I think all of us are hoping for is like when it gets so, it gets smart, it understands and it suggests the solution. And then I think users will always want to be able to say, yes, I want that or no, I don't want that. But to be able to like imagine with one push of a button or a single command, yes, get the thing you need.

That future is here. It's just not very evenly distributed. Like many— some companies are doing it, but not many. And the technology is becoming more and more accessible. And as that technology comes more accessible and more affordable, you're going to see more businesses use it. And as a result, you're going to see this problem sort of slowly recede into the background.

Which goes full circle to where Rowan started this conversation. We said the biggest problem actually is cost. It's not that— it's not like people don't want to provide it. It's like it's too too expensive. So as technology flattens that cost curve, this is the kind of solutions hopefully we all see around our everyday products. Rowan, I want to say thank you for joining us today on IT Visionaries. Thanks for working through, you know, the landscapers getting going ham. It's great. It was great hearing your stories. Thanks for sharing your love of adventure, uh, for alpine skiing. And I— for those that didn't catch at the beginning, Rowan actually climbs the mountain first. He doesn't use a ski lift. He climbs the mountain first Then he skis down them. But I think that what you guys are doing, you know, this is one of those businesses where selfishly I want you to succeed. You gotta make it, you gotta make this happen because I am subject— we are all subjected to bad customer service unfortunately right now. And I think we could unilaterally agree as people, we don't want that to exist.

We're all solving this problem for ourselves and our families. And so that always makes a great— always makes for a good business when when you're— when you can directly experience the benefits.

There you go. Thanks for joining us today on IT Visionaries.

Thank you for having me. Really appreciate it.