Upgrade Your Contact Center Using AI with Darryl Addington

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Upgrade Your Contact Center Using AI with Darryl Addington

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In this episode of the Customer Service Secrets Podcast, Gabe and Vikas are joined by Darryl Addington from Five9 to learn about integrating cloud support and AI into the CX space. Darryl has been involved with AI for years and is an expert at teaching leaders how to fully integrate these new systems into everyday operations. Tune into the episode to learn more.

Hot Take: How Artificial Intelligence Promotes Human Interaction

What would the world be like if AI were to be completely integrated into business practices? Would the human race be eradicated? Would there be lasting world peace? Or would there simply be streamlined customer journeys? The answer is: most likely the third option. It’s fun to fantasize about an AI-driven world, but that future is probably beyond our reach at this point in time, regardless of the advancements being made in the industry. The AI used in most businesses today is there simply to help the customer and the agent.

You might be wondering how AI drives human connection when artificial intelligence is, well, artificial. The purpose of AI is to support agents in a way that allows them to further personalize customer experiences by supplying them with the right information necessary for success. Even though a person might be dealing with a bot when they first contact the CX team, that bot can collect information from the customer to help the agent learn more about what exactly the customer needs. Interactions like this help the customer to feel listened to. They feel like their needs are being taken care of promptly and accurately when the agent is already aware of their purpose for calling in. Personalization is key to adding in that extra layer of humanity to CX and AI is one sure way to get that.

The Benefits are Endless and Profitable

Some of the most evident benefits of integrating AI to CX are the time and money such software can save a company. For example, customers are habitually upset when they have to constantly repeat their purpose for calling every single time they’re transferred from one department to another. With the help of AI, these situations can be entirely avoided because the software along with cloud systems contains all of the information departments need about their customers to make the journey just that much smoother. Darryl recognizes that as a leader in the contact center world, it can be difficult to fully buy into the idea of AI services when some existing processes are alright as is. Many leaders question why they should even buy into AI when innovation is already happening within their contact centers. As Vikas says, “The cloud has matured significantly. In the early days, people had fear about data security, data privacy, up time, and things of that nature…Those are no longer or less of an issue now with the maturity of the contact center space in the cloud.” With the combination of AI and the cloud in CX, teams are better equipped to serve the customer.

A Future Where Agents and AI Collide

With the endless possibilities facing the world of CX, one can’t help but imagine a time where agents and AI work together to handle customer situations. Darryl believes that this could be the future of contact centers because AI software has the capability to suggest next steps during interactions based on an analysis of what the customer is saying at the moment. It doesn’t just stop there though. AI can analyze tone and situation through a customer’s phone call to suggest potential products that meet their needs as well as suggest articles that answer any questions the consumer may have during the call – further personalizing the experience. Darryl then explains how AI is an awesome investment for the agent side of CX because it shortens after call work and takes notes for the rep, so they can give their undivided attention to the customer. “It’s practical. You can find vendors that are using that technology in ways that are allowing you to solve business problems you have today.” So while leaders anxiously await the development of CX technology to something as grand as in the movies, they would be wise to look into integrating AI. Innovation awaits.

To learn more about artificial intelligence in the workspace, check out the Customer Service Secrets podcast episode below, and be sure to subscribe for new episodes each Thursday.

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Full Episode Transcript:

Upgrade Your Contact Center Using AI with Darryl Addington

Intro Voice: (00:04)
You’re listening to the Customer Service Secrets Podcast by Kustomer.

Gabe Larsen: (00:11)
Welcome everybody. We’re excited to get going today. We’re actually joining Facebook. Kustomer’s joining Facebook. So if you haven’t heard real exciting news for the Kustomer crew, go check it out on our blog, pending regulatory review. Some real fun synergies that I think will continue to push forward client services, client success, and the overall customer experience. I’m so excited about that news. But today we’re going to be talking about five secrets to practical AI in the contact center. And to do that, we’re going to bring on a couple of special guests. You know Vikas, Head of CX and SVP of Sales over here at Kustomer. Who you probably don’t know is Darryl Addington. He’s the Director of Product Marketing at Five9. So Darryl, thanks for joining and how the heck are ya?

Darryl Addington: (01:14)
I’m doing great. Thanks for having me. It’s super exciting to be here. I love AI. AI in the contact centers, this new technology. So I’m stoked to talk about it today.

Gabe Larsen: (01:23)
Yeah. Yeah. Well, let’s jump in, but before we do, you got to tell us a little bit about yourself and then how do you know Vikas? You guys seem to have something in your history, nothing inappropriate. I want to keep this above the belt please. Above the belt.

Darryl Addington: (01:37)
Yeah. So I’ve been in the contact center industry for most of my career, which is I lose count because it changes every year, but it’s somewhere around 25 years. I started at a company called Edify, which was a self service company. So they had one of the first 4GL development environments. And it’s actually not too dissimilar from some of the stuff that’s out there today. I spent some, I spent quite a bit of time at Genesys and then Vikas and I met when we were at 8×8.

Gabe Larsen: (02:02)
You were at 8×8? They’re still doing well aren’t they? 8×8’s still doing well.

Darryl Addington: (02:08)
Yeah, they are. They do seem to be doing well there. From what I’ve seen, they’re attaching quite a bit of contact center to their UC sale, which is a big part of their businesses is unified communications. Yeah. They had a little bit of news today about a new CEO. That’s going to join the company and take them on to the next part of their journey.

Gabe Larsen: (02:28)
Oh, I didn’t see that. Interesting. And then it was 8×8 to Five9, or was there a step in between that?

Darryl Addington: (02:34)
That was it for me. Yeah. I came over here, I guess getting close to four years ago and that’s been a super, super interesting ride. Five9 has a great cloud contact center. And the market is certainly looking towards the cloud for their contact center technology. And so it’s been great. I mean, it changes every single quarter, as I like to say. What happened? What did we do last year? Well, it doesn’t really matter what we did last year because things are changing so fast, but it’s great to be in a market where people are using the technology and at a company that’s so great like Five9, the people there are really great, and we have really good processes and things, and our customers love us, which is a spectacular position to be in.

Gabe Larsen: (03:11)
Interesting. You want to add anything to that, Vikas? Did you guys actually work together?

Vikas Bhambri: (03:16)
We did, we did. Obviously I led an enterprise and mid-market sales at 8×8, and Darryl was in product marketing. And we worked very closely together in terms of a lot of our rollout, particularly around our contact center solution there. And I’m glad to get reacquainted with Darryl, obviously Five9 being a key partner for us here at Kustomer. So excited to have the discussion around AI and what’s going on in the market.

Gabe Larsen: (03:42)
So you guys didn’t have any of the typical sales and marketing fights then, huh? It was all rosy.

Vikas Bhambri: (03:47)
I mean, it was just like you and me, Gabe. There’s never any fights between sales and marketing when it comes to me. I know how heavily dependent I am on both you guys in individual lives for success. So trust me, there’s no fighting here.

Gabe Larsen: (04:02)
That’s fair. It’s been fun to partner with Vikas. And truthfully Darryl, Five9, I got to admit, it sounds like you’ve been there for awhile, it’s just a great story. How many employees are you guys up to? I don’t want to go into anything.

Darryl Addington: (04:13)
Yeah, I believe we’re at around 1300, I think that’s correct. Yeah, when I joined it was seven or eight, something like that. So, yeah.

Gabe Larsen: (04:23)
Yeah. Right. I mean it is a growth story. If you haven’t heard about Five9, the innovation they brought to the contact center, the dialing solutions, I remember we actually used you guys in a couple of places in some, in more of a sales area. Maybe five, I don’t know.

Darryl Addington: (04:41)
Yeah, that’s right. That’s actually been around since 2001 and for the first eight to ten years of its existence, we did quite a bit of outbound, which was who was buying cloud0-based solutions at that time. And then, six years ago, the contact center said, “Okay, I’m ready for the cloud from my inbound contact center.” And that’s most of what we do today.

Gabe Larsen: (05:02)
And that was such a, I don’t know if you call it a pivot but I remember when you guys started to kind of go that direction and it’s obviously turned out really well. So a lot of cool stuff in the contact center. Let’s jump into AI. Maybe just start with a super big picture. I mean, obviously a buzzword. What does that mean to you? What is AI? Give us kind of why people should even care about it, what it is.

Darryl Addington: (05:22)
Yeah. You know, AI is interesting because like a lot of industry trends it’s, people have gotten a hold of a term and they’re using it whether it’s appropriate to use or not. The other thing about AI is because there’ve been so many movies and TV shows about AI, people’s first inclination when they hear it is, “Well, this must be something magical.” And there may be a point where we have some voice in the cloud that we talk to and it knows everything about us and it knows everything about the business that we’re communicating with and can magically solve all of our problems for us. And if that happens in the future, that’ll be interesting. It’ll probably change every aspect of lives, but it’s not something that businesses can invest in today. It doesn’t exist today. And so what they can invest in now is technology using this idea of machine learning, which we can talk a little bit about. They can invest in that to solve the types of problems that they’re suffering from today, which there’s lots of them. And especially if you look in the contact center, tons of room for improvement in customer experience, as we all know, and tons of room for improvement in terms of operations and improving efficiency and things like that.

Gabe Larsen: (06:22)
Interesting. Yeah. I’ve got a nine-year-old boy and I’ve let him do a couple of things with the Avengers, Ironman, and he did ask not long ago, he’s like, “When can we get this Jarvis?” Like, “When does Jarvis come to our house?” And you can just –

Darryl Addington: (06:38)
He walks around, right?

Gabe Larsen: (06:40)
He changes everything, cleans the house, and makes everything great. I’m like, “Well, that’s probably not going to happen anytime soon.” So when you think about artificial intelligence, I’m really trying to lay the foundation, is there certain things you need to be or have in place to make sure we’re actually set up to implement this in a structured manner?

Darryl Addington: (07:00)
Yeah. There are a few steps that you can take. There’s actually a lot of low-hanging fruit for a lot of the contact centers out there to help them with customer experience and efficiency, and the first one is moving to the cloud and there’s a few reasons to do that. It sounds a little self-serving, but the reality is that all the innovation that’s going on in the contact center in terms of software is happening in the cloud. You might’ve seen a couple of years ago that Gartner ended their MQ for on premises contact center. And they said that the technology had reached its peak point and it wasn’t evolving anymore. So there was no reason to have an MQ. And that’s because all that innovation is now going towards the cloud. So that’s one good reason.

Darryl Addington: (07:39)
The second big reason is that the cloud is where the data’s at. So if you look at what machine learning is, and if I can just jump into that for a second. So machine learning is basically, it’s not magical. It’s basically an algorithm – it’s just math. And what it does is it allows machines, but the really cheap compute power that we have today to be able to go through a whole bunch of data. So in the example of text-to-speech, right, machines being able to have natural sounding voices, Wavenet, which is Google’s text to speech, they sample voices, millions and millions and millions of hours of voices at up to 24,000 samples per second. So if you think of all the data points that you’ve got along that human voice, and then you multiply that times all the needs of hours that the computer has gone through, it has so much data about the way that we articulate, the way that our voices sound. Just what we’ve been, I’ve been talking about this for a minute, right? Like how many samples do you have in there? And what that’s done is it’s generated these really super realistic, like, you can still tell it’s a machine if you’re listening closely, but it sounds so good that it doesn’t get in the way of the communication between a machine and a human anymore. And so that’s just one example of how machine learning is adding to this technology. And anyway, the data is in the cloud, right? And in an on premises world, all those voice conversations are trapped in servers somewhere in an enterprise, and you can’t get to them. And so you can’t really improve the AI with that data.

Gabe Larsen: (09:08)
It seems like Vikas, you’re out there on the front lines a lot with people and the move to cloud has obviously been accelerated with the pandemic. I mean, why is somebody even, no offense if you’re on premise at the moment, but why is someone, are there actually people who are on premise still? And if so, why?

Vikas Bhambri: (09:26)
There are. Obviously the legacy vendors are still in existence and making a lot of money off of the maintenance revenue from people being on-prem. I think the key thing is, look, change is hard, right? And I think it’s A, the fear of uncertainty. Two, it’s the effort to actually go through that migration process. And then there’s a lot of unknowns and hearsay in the market and look, as Darryl said, the cloud has matured significantly. In the early days, people had fear about data security, data, privacy, up time and things of that nature, right? Those are no longer or less of an issue now with the maturity of the contact center space in the cloud. So I think those are some things where businesses have a lot on their plate obviously, and so this becomes a matter of where does this fall on your priority list? The challenge, I think most people don’t see is all the upside that Darryl alluded to by moving to the cloud because that’s where the innovation is. So at some point, yes, you need to bite the bullet, but it’s not just about doing as is, right? And like, “Oh, I can run my contact center on-prem today and I’m going to,”

Darryl Addington: (10:44)
That’s right.

Vikas Bhambri: (10:44)
“What are all the additional things that I can take advantage of once I move to the cloud?” I think that’s what a business should really be thinking about.

Darryl Addington: (10:52)
I completely agree, Vikas, and actually the integration to Kustomer that you guys have created using our SDK is an example of something that’s completely different in the cloud than it is on premises. And anybody that’s been on premises and is connected their CRM or customer information system to their contact center, knows that you own that integration, regardless of who did that work when it breaks, it’s, you’re the one that’s responsible for that breakage. And Gartner calls it fragile infrastructure. It’s this connection between all the different systems in an on-premises world. And basically what it does is horrible for the contact center, but it causes people to not make changes to what they’re doing. So they can’t iterate. They can’t transform. They do changes every three months or six months, or over years sometimes because in the past, they’ve made a change and it’s broken and what the worst thing you can possibly do is roll out a change to all your agents and have it break. Your phone’s going to light up. You might do it twice. You’re not going to do it three times. And all that’s super, super stable on the cloud, like that has gone away because the cloud vendors, like yourselves and ourselves, we own that. We have thousands of customers using these integrations and using the software. So it behooves us to make sure that it works because now our desk is, our phones are lighting up when it doesn’t work, not the person that was responsible for the context of your integration in the first place.

Gabe Larsen: (12:14)
Yeah, that’s so interesting that Gartner and I didn’t realize they’d gotten rid of that on-prem, that’s interesting. I didn’t realize that, Darryl. That’s funny. Well, let’s talk about some of the practical uses. You gave kind of the general idea and the foundational, but how did that translate for the agent and the customer? Maybe you can just start at a high level, where do you feel like people are seeing some of those benefits from moving to the cloud, and then the data, the machine learning, and ultimately the artificial intelligence?

Darryl Addington: (12:37)
Yeah, so the net result of machine learning and AI, and there’s a couple of use cases that I think we could talk about here. So one is automation. How can you take some of the things that people are currently doing with agents and automate them? And then the second is agent’s assistance. How can you make the agent’s job easier? And there’s lots of benefits that you get in terms of what the customer experience is like, but also some benefits around agent training and things like that. So if you take that first example, automation, there’s a lot of things that you might try and do in an IVR, but as we all know, using, pushing buttons on the DTMF is not a lot of fun. Most customers won’t do it. Later, we can touch on a customer case study that had a DTMF auto-attendant replaced with an AI-based auto-attendant and saw some awesome results.

Gabe Larsen: (13:25)
Really? Interesting.

Darryl Addington: (13:27)
And then the other element is you might, speech reco exists today, but it’s so expensive and hard to put in and it takes so much energy to maintain over time that it’s only been available to the high end of the market. So if you call Southwest Airlines and you call your bank, and it’s a big bank, you’ve probably interacted with a speech recognition system to automate some of the things you do, transfer funds from checking to savings, et cetera. But those are expensive and so the average business can’t really adopt them, but with this AI stuff, it is actually a lot easier to implement. We put in that auto attendant that I referenced in about two weeks, two weeks of PS, like one person for two weeks, which is crazy different from what the old speech reco was.

Darryl Addington: (14:10)
It was six months to nine months just to get the thing up and running. In some cases for the larger companies, like two years before you could actually put the thing into production. Really, really amazing. Anyway, so automation is like the first one and in any business, and you can kind of break down automation versus assistant, right? So customers know when they need to, when they need some automation versus when they need some assistance from a human being. So for example, if I’m going to go into a business and I’m going to, I want to know, is your store open? Right. Very, super common for COVID right now, is the store open? When is it open? Like, what hours are it open? These are all like things that you know you can just figure out, you should be able to figure it out from our website or from an IVA.

Darryl Addington: (14:51)
What’s the status of my order? I need to change my address. These are all things that you would expect to be able to do without a human being. But, “Hey, I ordered a piano bench 20 weeks ago and for the last 20 weeks, every two weeks, you’ve said it’s coming, but it’s not here yet.” So like, let’s have a conversation because I know I’m not going to get this resolved on self-service. And so that’s sort of, if you think about it from that perspective as a business, you can kind of think about what do I want to automate versus what I want that has something to do with the human experience that you’ve got. It has something to do with the relationship that you have with the business. You want to get to a human being because they’re going to be able to smooth all that over and make it better.

Gabe Larsen: (15:30)
So in a lot of ways, you’ve been able to take that complex voice recognition and be able to simplify it so that you can automate some of those more mundane tasks via phone if they want to. It’s just a [inaudible].

Darryl Addington: (15:42)
Yeah. Speech reco is a good example. And then I guess, let me just talk about IQVIA which is one of our customers. They did the auto attendant. What they found was that their customers weren’t willing to hit the tones. They weren’t willing to hit the buttons on the phone. And what that resulted in was that they got to agents that weren’t necessarily skilled to solve their problem. And then, like they probably had access to a CRM, like the great one that you guys have, but they maybe didn’t know how to navigate through it in order to find what they needed, et cetera. So when they implemented the flat menu, essentially, right, just tell me what it is that you’re calling about, customers were willing to give that a shot. And what they found was after those two weeks that I talked about, 87% on the first utterance, the first time that they just said, “Hey, I’m calling about this issue,” they were able to identify that and transfer that to the right agent and 93% after the second utterance. So if it didn’t get it the first time they were able to get to 93. They reduced their agent transfer down to less than 1% from agent to agent, meaning it got routed correctly to the agent. And then the other big stat for that one that was amazing to me was their average handle time decreased by 15% because the agents were actually trained on the issue of the customer. Yeah. So like really cool stuff. And the fact that a medium size and not these big organizations could implement something like that to me is, that’s like wow, right? Like that’s okay. It’s not quite magic like Jarvis, but it has such a big impact on the business. It’s super compelling and interesting and it solves the problems that the businesses have today.

Gabe Larsen: (17:18)
Interesting. Thoughts on that Vikas?

Vikas Bhambri: (17:21)
No, I think the key thing is that it opened up the opportunity for all types of businesses to deliver that optimal experience. You know what Darryl said, if you look at speech recognition, something that was primarily kind of started by, primary adoption was large financial services institutions. So the flagship banks, and as Darryl said, it took the number of years to roll it out. And frankly, the effectiveness of it, I would still debate, right? So now being able to offer that up to a medium size, small businesses I think is fantastic because as consumers we don’t only want to have a great experience, we used to joke that everybody talks about Apple delivering this amazing experience and everybody said, “Yeah, sure. It’s Apple,” right? Trillion dollar company. Of course they can afford to. So now I think of an opportunity for every business owner or every leader in every business, to think that they have the capabilities within their budget to go deliver an Apple-like experience, which I think is great because as a consumer, I think that’s the ideal that we’re all looking for.

Gabe Larsen: (18:30)
Yeah. It’s interesting. And I assume Darryl, that found that often the touch tone versus the speaking, it’s that big of a difference. We’re that lazy.

Darryl Addington: (18:43)
Yeah. Well, most people don’t understand why they’re doing it. You know there’s actually a website and it’s been around for forever, it’s called Get Human. And it tells you how to bypass the IVR so you can talk to a person, but what the consumer doesn’t realize, generally speaking, is that they’re then going to get to an agent that isn’t skilled to help them and so they’re going to get transferred around after that in order to solve their problem. But whatever. Speech reco is much, much better now with this AI. And even saying they don’t even call it speech reco anymore but it does recognize what you’re saying. Potentially yeah, to just be easy and usable which is great.

Gabe Larsen: (19:19)
I didn’t realize that was such a difference. And then you mentioned a little bit about agent assist-type capabilities. Do you want to talk a little bit about that? Or what does that look like?

Darryl Addington: (19:27)
Yeah, so agent assist is now, so now we know the consumer knows and the business knows that an agent needs to be involved. You’ve got something that is relational. So you’re onboarding a customer, for example, you don’t want to do that really in self-service. Some businesses can do it just because of the nature of their business, but a lot of businesses want you human beings involved. Or it’s something that is going to break the relationship. Hey, it’s been, like I said with the piano bench or travel-wise, I called Southwest Airlines recently. I was going to go to Kauai over the break and they closed the island and Southwest canceled my flights. So I wanted to talk to somebody about that. So you know you need a human, okay. So now you get to the agent now, how can you help the agent? And there’s a number of ways that AI can do that really easily today. So one is around call summarization and dispositions. So dispositions is this funny word, right? A disposition is essentially like, what was the call about? It’s a pretty simple thing. And the agent typically in a contact center has got, it’s easy to do. They just click on one, except that the list is usually a hundred items or longe. They have to scroll through the list at the end, right, and figure out what was the call about? And with a hundred items and the fact that most calls, not all calls, but most calls have multiple things that they were about, the agent does something called satisfaction. They just pick the first one that looks pretty good and their management doesn’t want them on after call work. They don’t want them sitting there for 10 minutes optimizing that disposition, right?

Darryl Addington: (20:50)
They want him to get onto the next phone call. So they just pick whatever. So that just totally ruins the reporting. Like you don’t actually know what that call is about. You know what the agent saw, the first thing the agent saw that looked close is what you know about that call. So AI can help with that because it listens to the whole call, listens to the conversation between the customer and the agent, and then they can pick multiple dispositions based on what that call was actually about. Now, you got this awesome reporting that’s more accurate and can actually tell you and let you fix problems around what your customers are calling about. So that’s number one.

Darryl Addington: (21:20)
Number two is call summaries. A lot of time gets spent by agents trying to capture what’s happening in the call and write down notes. With AI I can just capture all of that. And one of the things that Five9 is doing that’s interesting is that we actually summarize the call based on the dictation. The AI is not perfect, but it gives us enough details that we can then use NLP to summarize what that call was about. And at the end of the call, the agent just goes, “Yeah, yeah, yeah, yeah, yeah. Oh, let me crack that one real quick. I’ll be cool.” And they hit the button and it automatically gets written into Kustomer, into the CRMso that they don’t have to do all that. So shorten, it does two things. Shortens the after-call work, but then it also allows them to focus more on the customer because they’re not busy trying to capture all the notes during that.

Darryl Addington: (22:05)
Darryl, are you seeing an ability in the voice world to whisper to the agent and obviously prompt them based on the conversation that is taking place on potential solutions? So as you said, the AI is listening to the conversation going back and forth between the consumer and the agent and actually recommending, “Hey, maybe you want to say this. This is the solution to that problem. Like they should reset their cable box,” whatever it is. Do you see, is that something that exists or is that something that is still in flight?

Darryl Addington: (22:42)
Yeah, no, that’s something that you can do today and a great example. So there’s a whole bunch of different things that you can do around, like, so you might have legal statements that you need the agent to say, so you can watch for those. You can actually watch to see if they didn’t say them and then you can prompt them to say it, and then you can see if they actually said it like, so it’s like so awesome using the technology. And then there might be the next best action type of things. Like what should they be doing? So for example, it might be an example of if you’re in a business where the usage is important to the customer using the product, there might be examples, “Oh, have you tried using it like this?” Or it could be cross sell up sell-type opportunities where it’s saying, “Hey, customers that purchase that product that you’re talking about now, 85% of them purchased this product next.”

Darryl Addington: (23:25)
So talk to them about that product. So yeah, lots of examples there. The other thing that is happening is knowledge base. So being able to go on a knowledge base and pull up articles and present those to the agent, and man, talk about it being easier for the agent to your point, Vikas. You’ve got, and now you’ve got an AI that’s right there saying, “Hey, here’s what to do next.” Or, “Here’s an article that you can use to solve this problem.” It helps the agent because they’re not distracted with, and as you know, as you guys both know, one of the big problems with agents is they’ve got stuff everywhere, right? So they spend a lot of time putting the customer on hold and looking for things and with the AI just suggesting –

Vikas Bhambri: (24:03)
Not if they’re using Kustomer, but that’s a different discussion.

Darryl Addington: (24:07)
No, you’re right. But the you’re replacing environments that are like that with –

Gabe Larsen: (24:12)
Yeah, i’s funny. As I look at that, Darryl, I’m like, how did the agent ever function without these things? Like, what were they doing? They must’ve been, I guess they were –

Vikas Bhambri: (24:22)
Going back to what Gabe’s son was saying about Jarvis, right? We often, when we think about AI, it’s always still today, it’s very much a handoff conversation. It’s like, “Okay. The bot tries to solve the issue if it can. It hands off to human agent.” And yeah. I mean, we suggest things too. Do you envision a world where, especially in the voice world, it’s slightly different in the digital world where we’re talking about chat or social or whatever, where bot and agent are actually solving the problem for the customer together? And what I mean, I’m just thinking out loud, right? So from the perspective of I’ve got a generalist agent or, and maybe we have, but the bot is the expert in mortgages and we’re trying to solve the problem, but for the consumer, it’s seamless. Like a consumer feels like they’re talking to two people, but reality it’s one human agent and a bot who maybe is a specialist bot around mortgages if I was to look at financial services.

Darryl Addington: (25:24)
Yeah. So absolutely. I think the way that that’s manifesting today in the market is that you are able to get agents out on the floor faster. So they’re not a mortgage expert and maybe they don’t have to take the month long training in order to get them out on the floor because the AI is going to support them. They’re going to support them visually, not necessarily communicating directly to the customer while the agent’s communicating with the customer. But one of the things that we’ve focused on since the very beginning and the integration of the customer helps with this, is that context level between the automation, because it always exists, that’s what consumers know like we talked about, right? They know if it’s self service or automation, they’re probably going to start with self service if they can, even if they know they need an agent, they’re going to have to pass through the self service to get to an agent.

Darryl Addington: (26:13)
And during that time we can gather this word’s intentions, right? Like what is the customer trying to do? And the identity of the customer and the intent of the customer and any context about what the customer was doing recently can be passed to the agent and that agent then can make that a seamless bridge. And that’s a super, super, super critical part because in survey, after survey, after survey shows that customers do not like starting over when they switch channels and whether that’s from self service to an agent or from text to voice, whatever the case might be, they don’t like that.

Vikas Bhambri: (26:44)
Yeah. And I think when you live in our world and we’re so used to the technology side of it, we take it for granted. And then I think it’s quite often when I put my consumer hat on and I’m engaging all these different brands that I’m almost in disbelief as to the percentage of brands, that very basic nuance that you talked about there, the handoff, is still fundamentally broken I would say for 90% plus of most businesses.

Darryl Addington: (27:08)
Yeah. Well, and that’s solvable today without AI. I mean, that’s a problem that if you get a good pre-built integration between, to cloud vendors like us, you can solve that today and it’s actually relatively easy. You just implement the solutions, which is great. So I recommend businesses go do that.

Gabe Larsen: (27:24)
You’ve got to find that way. Well, let’s wrap up. But Darryl, I’d like to let you kind of finish and maybe pose this question to you. A lot of people out there trying to start this journey, figure out the best way to kind of optimize each part of the customer journey, where would you kind of leave the audience with, how do you start? Like where do I go to kind of get my feet wet and crawl, walk, run, if you will?

Darryl Addington: (27:48)
Yeah. I mean, so move to the cloud for one, because of all the reasons we’ve talked about, stability, better reporting, better UI, as you can control, and you can iterate on your contact center. That helps a ton. Integrate into your CRM, like with a pre built integration. Prebuilt, it’s important. There are great SDKs. We have one, but if you can get a pre built integration into a CRM like Kustomer, awesome. Like, that’s going to help so much in terms of the experience, the agent training, the environment looks seamless across that whole thing, and they can get all that context we just talked about. Three is enabling the agent. Super important for work from home these days, and that’s agent stats. How am I doing during the day? Am I meeting the customer and the company’s objectives for me? Am I not? Gamification and workforce management or another key one so that you can manage your schedule really effectively. That empowers the agent in a way that they haven’t been empowered previously.

Darryl Addington: (28:39)
So those three steps, and then like, that’s just low hanging fruit. Like you can go do that today and really easily, within three months, depending on the complexity of your contact center, could be a week. It could be really fast, might be a bit longer, three months if you were super big, if you got 30,000 agents or something, but you can go do that today. And so those are the first three steps. And then AI, AI is absolutely there. It’s practical. You can find vendors that are using that technology in ways that are allowing you to solve business problems you have today while we all wait for Jarvis to come around and –

Gabe Larsen: (29:14)
Awesome. Awesome. Well, Vikas always appreciate you joining. Darryl, thanks so much for having me. If someone wants to get in touch with you or learn a little bit more about Five9, what’s the best way to do that?

Darryl Addington: (29:22)
Well, the website’s a good spot to start. It’s got a lot of good information. There’s numbers that you can call out there, et cetera. And, uh, yeah.

Gabe Larsen: (29:32)
Love it. Alrighty, man. Well hey, appreciate your time, and for the audience, have a fantastic day.

Darryl Addington: (29:36)
Yeah, you too.

Exit Voice: (29:43)
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