Spend Advantage Podcast

Save 20-30% For Your Contact Center with AI

March 21, 2023 Varisource Season 1 Episode 31
Spend Advantage Podcast
Save 20-30% For Your Contact Center with AI
Show Notes Transcript

Welcome to The Did You Know Podcast by Varisource, where we interview founders, executives and experts at amazing technology companies that can help your business save a lot of time, money and grow faster. Especially bring awareness to smarter, better, faster solutions that can transform your business and give you a competitive advantage----https://www.varisource.com

Welcome to the Did You know podcast by Varisource, where we interview founders and executives at amazing technology companies that can help your business save time and money and grow. Especially bring awareness to smarter, better, faster solutions that can transform your business. 1.5s Hello, everyone. This is Victor with varisource. Welcome to another episode of the Did You Know Podcast. Today we're excited to have Chris Crosby, who is the CEO and founder of Exact. Exact is an AI solution that helps companies deliver dynamic experiences across all digital channels in any industry. Welcome to the show, Chris. 

U1

Thank you, Victor, for having me. 1s

U2

Yeah, no, I love our chats the last couple of times. I'm super excited to have you on the show to talk about AI and contact center and customer experience going to be great. So usually we like to start with give us a little background about Chris. How did you kind of your history and kind of that founder story. 

U1

Okay, awesome. 2.1s I've been in call centers now for about 32 years, which means I was two when I started kidding, of course. But no, actually, my very first job was a telemarketer 

U2

part time in high school, 1.6s in college, and then took the opportunity, really, to just stick with that as a career. So I worked in a number of outsourcing, call center outsourcers BPOS on both the inbound and outbound side. So I kind of spent my 20s, if you will, opening and turning around call centers and then ended up being the guy that understood the business but could also speak geek. I had a strong venture for the technology and ended up in roles where I was really taking the technology and applying that to solve the business problems. And so 1.9s the week before I turned 30, I told my wife that I wanted to start my own company and so built a 

U1

company that was really the first business intelligence platform purpose built for call centers. So I saw an opportunity. 1s Data everywhere. It's a familiar theme, even. 1.6s 18 years 

U2

ago. 3s The tools at the time were either kind of hard coded, here's what you get or they were very high end analytic applications, and they were just expensive and required a lot of time and money to build, to deploy. And so I found a business partner that could code and developed a company called latigant, which was again, really focused on operationalizing data and intelligence. And we were doing big data before we know it was big data. And cisco systems acquired that company back in seven, and that became cisco unified intelligence center. So if there's any cisco customers out there and you've ever looked at 

U1

reporting that started on the back of an applicant in kansas city, wow. After my time at cisco, so I spent some time running their global go to market for contact center. Did another company not in the space, 2s that was NLP, basically sort of natural language processing for social network monitoring, for reputation management detection. We ended up selling that company to experian just a few years ago. And then exact was founded actually in smart cities. So we saw an opportunity to take all this new data that was coming about with parking sensors and traffic sensors and really translating that back into outcomes for each department inside the city. Think public works. We were great at predicting potholes, and we had started to I saw an opportunity a couple of years ago where conversational AI was starting to come out. Amazon, lex, and google DialogFlow. We said, you know what, our customers, our city customers and county customers have call centers. So what if we started testing this and applying it and helping them save money and be more efficient in their in house call centers? And it worked. And then about that time, three years ago now, almost every city in the, in the country shut down within the same week. And they no longer had parking and traffic problems to deal with. They had to respond to a pandemic. So we pivoted, we leaned into the conversational AI play and haven't looked back. Frankly. We helped a number of large counties and municipalities with their COVID response primarily through voice call automation, people calling in, asking questions. If you think back three years ago it was what businesses are open? What are the rules? Can I go to the 

U2

heart? We're able to automate a lot of that. And then when the vaccines came out, we built out conversational Automation IVRs to help people get scheduled 1.1s for the vaccine. Because again, two years ago now, there were waiting lists, right? And large call centers being stood up to handle that. And so we were able to assist with that. But then also we had a couple of counties come to us and say hey, would you just staff and operate the call center for us? We love your tech, but we need people too and we need the expertise and competence to do this well for our citizens. So we did that and we launched our own BPO. We actually spun that out last year. So inflection CX is our contact center outsourcer powered by AI, powered by Exact and some other tools. And today Exact is really what we look at is the holistic opportunity for 1s AI and natural language processing machine learning to apply to every dimension of a contact center. So 1s whether that is agent assistance or automation of customer experience or additional tools throughout that, which I'm sure we'll talk about as we go. But 

U1

now 1.3s Smart Cities is pretty much in the rearview mirror and we're very focused, laser focused actually on data infrastructure, analytics infrastructure, as well as these AI applications which really have the potential to transform the industry. 1.6s

U2

Yeah. So first of all, you're a serial entrepreneur, and anybody who's built their own company know that 1.2s building any company of any size is very difficult. Right. And so you've done a couple of times, and you've exited a couple of times. So that's amazing. I think you and your family should definitely be proud of that. But that you're going on your third sounds like opportunity now. And also, from your story, it sounds like you being kind of using AI when AI was even a thing, right. When it was even hot. Right now. I mean, it's so fascinating that myself, I see myself as a technologist meaning. I've always loved technology. I always looked at Google and tried to understand what's the technology behind it more than just the search engine and what you see on the surface. Right. And so it sounds like even before AI was hot, you're talking about ten years ago, you're talking about five years ago. You're already kind of having that vision of using AI. And obviously, technology may not be as good at that point, but what was it that gave you those vision to be able to kind of, I would say, ahead of your time to implement some of these things in those products you were building? 2.2s

U1

Yeah, great question. 1.5s I think the answer is in really having a deep appreciation for the problems that contact centers and customer experience executives need to solve for, I think today. 1s And it gets noisier every day that there's a lot of companies that brand themselves as AI and they're really solutions looking for a problem. It's like, hey, we've got this cool, shiny tech, let's go sell it. 

U2

Well, we always start with what is the problem we're trying to solve? And if you spend more than a day in a call center, you start to see pretty quickly there's a lot of problems that need to be solved or a lot of things that can be made better, particularly now in a virtual environment, right. Like managing agents and workforce engagement is challenging and the tools are changing. And so I think it starts with that deep appreciation and respect, I think, for the industry. And then on the other side of that, it's really an understanding and appreciation of the new tools that are emerging. And you've got to strip out the buzzwords to be able, I think, to see what the true opportunity is and look at the set of capabilities that like OpenAI, which at GPT have opened up or the conversational AI 1.2s have presented themselves, and then really just look for the ways to put those two things together. And that's where I think the magic happens because we tend to not get too caught up in monikers and buzzwords like, hey, we're an AI company, we obviously have it on our website and we talk a lot about it, but it means different things to different people. 1.1s And so I think really being 

U1

able to play that middle ground between customers and emerging tech and become that trusted advisor is really what gets me excited, right. And really where the vision started initially was like, okay, these things are coming to play. They're not fully matured yet, to your point, they're better now than they were three, four, five years ago. But being willing to experiment with that and to make it better is really what's driven us and our customer success. 1.9s

U2

Yeah, for me, 1.6s actually, a lot of people ask me, why do we name our podcast did you know? And I always felt that people that were successful in anything real estate or finance or technology or anything, a lot of times, yes, of course, you got to work hard and you got to have a good idea. You have all these things. But a lot of times when people are able to do something cheaper, better, faster, easier, more creative, it's also because they know things that you don't know. Maybe it's hacks, maybe it's tricks, maybe it's certain tools that they can integrate with that you don't. 1.2s Chat GPT, I think, is a fantastic example of that, because I've been playing with OpenAI Gpt-3 GPT-2 for years, it's been around, and there's many companies utilizing their API to build products three years ago. Yet when now Chat GPT comes along, like, this is the most amazing thing I ever seen in my life, just from overall, that virality, right, and has completely changed everybody's interaction with it, even though it's been around for really three years, right? And so it's just they didn't know. They didn't know it existed, they didn't know it was possible. And to some degree, some of that iPhone as well, like Microsoft look at it and say, what do you mean? We got like, touch screen ten years ago, how come nobody wants it? And now iPhone comes out and it's like, that is awesome. It's like, it's timing, it's virality, it's really fascinating. But what's kind of your quick thought before we get into the question of that sudden virality of AI in the last three months because of Chat GPT and just the whole world now thinking about it or not, it but AI, and now obviously, every company on Earth is trying to integrate with it. But what's kind of your quick kind of thought on that? I think your assessment was spot on. Even us, as an emerging tech company, very focused on the technology and the tools and bringing those to market. We looked at those OpenAI APIs for a while. Like you said, they weren't born with Chat GPT and we had been kicking around and poking at different use cases. But then what GPT did, what Chat GPT did was really just put the right interface in front of those models to be able to ask it questions, to interrogate it, if you will. And I think that was the it was definitely the eye opening moment for me, because I could drop a call transcript in there and I could start asking questions about the transcript, like, who are the callers? Make recommendations for the agent. And once I started doing that, then I was like, oh, there's something bigger here. And I think what. 1.8s And I think that's a narrative when I'm out talking to our customers and prospects, that's a consistent narrative, I think, particularly at the sea level or the executive leadership level, where now all of a sudden they have a tool where they can just play around with it low risk way and then put that to their team and say this is going to impact our business. But how? Right. And I think that's where we're stepping into now is like, what is the how? What's it mean? How does it translate? Because we've now been able to go back, frankly, and say, well, let's try out a bunch of new use cases on this. Right? Because to your point, it's been there. But the ability to just play with it in a way that doesn't require a developer 

U1

or engineer to help get under the hood, business people could play with it before it was engineers trying to build stuff, 

U2

right? Yeah. Now anybody can see the opportunity if they choose to. 1.8s I'll make one other point. I think that 1.6s Chat GPT also has had the downside of when it does make stuff up or it's a bad experience, or that I think it does put a lot of doubt in some people's minds around, okay, well, this isn't enterprise ready yet, which is true. Chat GPT is not enterprise ready. But I think what we're seeing now, and in particular from exact, is what are the use cases that this technology can be applied to today that are better, faster, cheaper, can have a business impact, be non disruptive to the day to day business in the sense that we're not going to put a chat bot in front of your customer. That just hallucinates, right? There's companies doing that, we're not one of them. 

U1

So it's kind of a blessing and a curse, right. I mean, it's open a lot of people's eyes, but at the same time now it's hard to decipher what's real and what's just press release. 1.5s

U2

Yeah, but at least it's got the momentum now. And I just think overall that's a fantastic thing for the world. 1.1s But yeah, no, we could talk hours for that for sure. But obviously we have a lot of executives, obviously procurement, it listening to the show. But if you were talking to a CEO, right? And obviously when you talk about things like contact center Ivr, iva, can you kind of give us a 32nd overview of what is that why companies have it and what do those current technology lack today that your solution? Complements 

U1

yeah, great question. So the first thing I would say to any executive is to say that AI is not a monolithic thing, right? There's a lot of companies grabbing onto that label. It's really about peeling apart the opportunities and understanding where each of these technologies and applications can impact your business. So in particular, with Ibas intelligent Virtual Agents automation, chat bots have been around a long time. I can tell you we build chat bots, but I'm not a fan. The reason for that is because as soon as you throw that on our website, it's got to know a lot of things. And it's got to know a lot of things well. People have customers have a bad experience, whereas where we initially focused and still have a very strong differentiation is in voice automation because one that's hard, 1.2s in order to have a good conversational, Ivr, you have to integrate with the existing environment. So whether they're old on prem stuff or they're in the cloud, you got to get the integrations right, you got to get the data pipes right so they understand what pass the transcript down to an agent if a call fails and be able to analyze that and end customer journey. Invoice also lets you direct the path of the caller so you don't have to try to automate everything at once like you would with a chat bot. With Voice, you can start with FAQs or you can start with order status. We always start with low value, low complexity calls and work our way up. And to me that's really I would focus on two areas as an executive. One is like, what can we voice automate now? Because voice is the biggest cost driver right in the call center, figure out what percentage we could automate. And then the other side is looking at agent assistance and the tools that are not customer facing but can reduce average handle time, they can reduce headcount requirements by giving your agents better tools. They're two sides of the same coin, but they're two different approaches. And we look at it, tend to be more holistically and say, where can we start? That is low risk but can have a material impact. 1.7s Yeah. 3.6s

U2

When you're passionate about it, 30 seconds. 1.1s It felt like 30 seconds to you, I'm sure. All right. But when I look at examples because I want to make this kind of more not from a technology perspective, but business perspective, when I look at 1.1s one great example for myself, anyways, is like calling you United, right, where when I call in, literally, you would consider the Ivr. Iva, which is an intelligent system where I'm not talking to a human. It used to be like, click three for this department and I'm talking to a person. Now it's like, literally the system is doing 80% of the work, right? 70% of the work. And only I would call that tier one or tier two calls where my question questions can be answered. I don't need to talk to somebody because I don't want to wait. I just want to get my answer and go. Right? And if I do need to talk to somebody, then I go. But I think at least from an airline, I'm sure it applies to a lot of other industries, but for me, just like talking even airlines, I get that experience, and I like that experience as a customer. How can these CEOs look at their business that way, to provide better experience? Is that part of what you're talking about? AI or automation? Is that what you've been? I'll 

U1

give you a case study 

U2

on our very first voice Ivr that we launched, because it's just a great story 1s with Kansas City, Missouri. They have a three one one call center. So people calling in to report potholes and dead animals and miss trash and everything in between, right? And they had one of their waste management contractors was missing a lot of trash, so their call center was blowing up. People sitting in queue ten minutes just to call and complain about, you missed my trash. 1.5s So we went in and automated that one call type. 1.1s Now, we started when we first launched. We automated about 40% of those missed calls or missed trash pickups. Three weeks later, we were automating 90%. That's the power of managed AI is that it gets better over time and you train it. We took their cost per call. So if that call were to hit a live agent, it's about 6.50 cost per call. We charge them automation. Wow. And they saw an immediate impact on their service level because once those calls were cleared out of queue, everybody else got answered. Right. The person that was calling for assistance for something besides Ms. Trash was now all of a sudden to get to an agent to handle those problems. And I tell that story because we can all relate to, okay, the city missed my trash, or I got a call and report a pothole. But that's the narrative, right? And the impact is that take your cost per call or interaction where you're at today for a certain call type. Again, something low. Complexity is a great place to start. Figure out how many of those calls you have, and if 80% of those were automated at 20% of the cost, what impact act would that have on your business? Now, let's extrapolate that. Start picking other call types. 1.3s And then the other thing we do is come back on the backside of that and we say, okay, here's a set of calls we're not going to try to automate. High complexity, high value, big sales call, or heavy 

U1

technical call. Right. 1.3s I bet if it's a high knowledge type call, that agent is probably spending minutes searching through knowledge bases or PDFs technical manuals to find customer answers. We put that answer right in front of them behind a chat type experience, which then makes the customer we can take the time to answer a question down from minutes down to seconds, which takes cost out and it improves the customer experience because they're not on hold waiting for somebody to find the answer. So again, we're looking at when we talk about business impact, we're looking at all the different levers that we can pull to drive that efficiency gain and improve the customer experience with the same lever. 2.4s

U2

Why do you think, Chris, you've been in this industry, like you said, 2030 years. These technology have been around as well. Obviously it gets better and better, but why haven't still a lot of companies 1.1s implement this? And to me, part of the reason I think is because when you talk about AI and automation, a lot of these things, it sounds good, but people don't know how to apply it. Just like you give them chat GPT, it's cool to chat with him or her or this AI, but people still don't actually know how to apply it in a useful, productive way. Right. And do you feel like that's maybe one of the reason why it hasn't kind of the adoption hasn't been kind of more mass? 

U1

I do, and 1.9s I think it's hard for some folks to parse through 1.3s all the buzz and really understand what's real and material to their business. And one of the first things we did actually that was different than a lot of companies or vendors was I put my VP of Ops hat back on and I said, well, if I'm going to deploy this bot, this voice Ivr, or this tool, how is it going to impact my customer experience? How do I know if it's working? Are people having to repeat themselves? Because you mentioned United as an example. It can be easy to have a bad experience with United and their Iva, right? And we didn't want that to happen. So we didn't want let's just automate to automate. So we started with the analytics, the customer experience side, and we said, we're going to put this data right in front of you and contact Center Customer Experience Leader so that you can see the impact and you can see the experience that your customers are having now as a result of this. And I tell you, that made a huge difference because I think companies and folks are still adverse or have hesitation when they're like, do I really want to turn my customer experience over to a bot. 1.1s Right? And I think it is that into the unknown. But when we can show them and demonstrate in real time we just launched one for Wake County, North Carolina last week for the Health and Human Services Department and that was the process we went through. They need to conserve resources, right? But they need to improve resident citizen experience. And I tell you that their callers now are raving about it and the agents are because when a call does get to an agent, the caller is telling them hey, I didn't have to spend 3 minutes punching numbers into your Ivr. I got right to you. Now, to me as an executive or customer experience leader, that's what matters, that's driving real impact. And so I think we've got to be able to get people over that the technology of version hopping into no, this stuff is good now and can really impact your 

U2

experience. But Chris, to add on to that a little bit though, I think when you're talking about businesses and I'm just trying to think from an executive side, 1.3s it's all about branding, right? Do you feel like the perception of oh, let's just assume and from what you're mentioning, it sounds like AI or automation is just as good as potentially human interaction. So that part of it is fine, but it's more about 1.6s as an executive, I feel like if my customers are talking to a robot, they would feel like oh, you don't personalize, you don't care about my feeling because you're asking a robot to talk to me. Do you feel like that's one of their fears? And how would you kind of educate the executives in an example like that where even if you prove to them that AI is just as good in responding or responding faster. But the feel that I'm talking to a robot versus a human kind of that as a business, commercial business, I think they have to care about branding, right? I think they care about branding, but 

U1

part yeah, great question. I think the answer though is like what's your experience today? Because we went through this a couple of months ago with the company and they're like I don't want anybody talking to a bot. And so I picked up the phone and I called their toll free number and I sat in 8 minutes in queue and that was an awkward 8 minutes. But it got the point across that if this is the experience that you're providing to your customers today, what message does that send? Right? And the ability to deliver immediate service in any channel that the customer. 1.9s Prefers. That is really transformation. And it does take some folks, I think, a bit to get comfortable with that. But really, I don't think the world's going back. 1.9s I don't think consumers now are expecting a live agent every single time they reach out. What a customer wants 1.3s is to solve the problem. Right. They're calling a call center to solve something. Most prefer efficiency over waiting for an agent. And so when you can provide that, again, not on all call types. We're never out to automate 20 minutes calls. We're out to make those 20 minutes calls better. But when you can start peeling out the easy stuff, what you find is that customers are happy about it. Yeah, 1.6s I love that answer, man. So when people hear AI, hear the transformation, it all sounds good, but then it also gives them the idea that, oh, it's only for enterprises. Oh, it's going to take so much effort to implement and figure out. Can you kind of speak to how can whether it's SMB mid market enterprise leverage this technology, and at the same time, what kind of implementation can people expect and how quickly could they see an ROI, usually? Yeah. 

U2

So I think SMBs absolutely 1.3s can join in the fun. If you've got a 30 seat contact center, we should be looking at agent assistance in a knowledge base that's AI powered. We should be looking at some speech analytics to discover what the automation opportunities are. And depending on the industry and the nature of your calls, automation does tend to work better at scale. Right. But if you've got some low complexity calls, like if you're in ecommerce or retail or something and you got 30 seats, there's a pretty good chance that we could automate a portion of those calls for you. Now, once you get down below ten seats early, just doesn't work right. Like, you got to have core coverage so we can automate away, but you're still going to have to have live agents there to cover the phones for the non automated calls. So typically we'll say, let's start above that, 1015 seats. But. Agent assist usually takes a couple of weeks at most to implement. ROI is immediate because you're immediately taking out average handle time from a call and you're making agent's lives easier. On the Ivr side, the ROI is day one, and that tends depending on the hard part 

U1

about Ivas and automation is always the back office integration. If if we're just automating FAQs or 1.6s something that has we're querying against shopify or something that has an open API that we can integrate with, those are pretty straightforward implementations. But if you've got a custom EMR or something that's like a heavy back end that could take a while to integrate with, that's really where the complexity and expense comes in, which is why we always start with the what are the quick wins that we can use to build momentum? 1.5s

U2

Yeah, even the hearing couple of weeks right is pretty incredible when you're talking about the type of impact and transformation and most importantly, cost savings. And I think that goes into our last question of the day pretty well, which is obviously in this economy, everybody's looking at cost savings and optimization and efficiency. 1.1s So how can they leverage exact 1.3s AI services to really help them with cost savings and efficiency? And again, throughout the conversation, you talked about many use cases and example, but if you were to just summarize in the last couple of minutes of how can companies, what areas can you have impact from savings and efficiency perspective using 

U1

exam? Yeah, great question. So upfront 1.4s analytics and discovery around both your operational performance, because this isn't all just about text. Like, we have machine learning models that will help you identify behavioral patterns with just the existing data that you have. As an example, one customer of ours discovered using our machine learning models that their agents were spending the last five minutes of their shift in after call work because they're long calls. They're 2030 minutes calls and they didn't want to get a call and end up after 

U2

their shift. They were only able to see that when we started surfacing those insights for them. So we always like to start with let's start with where you're at. Do some baseline benchmarking and discovery, identify the opportunities. Then those opportunities tend to branch out into what are the automation for customers. So what are your voice, Ivr or chat opportunities to peel off calls before they get to an agent? 1.4s Then there is once they hit an agent, right? The opportunities there are in agent assistance and I'm not a fan by the way. There's some companies that do like the real time coaching where the agent's screen is moving or there's a whisper in their ear. We don't do that because I think it's distracting to an agent. What we do is empower the agent with the tool in front of them to maneuver that the way they need to. And then we have post call automation. So here's a big one too. So when we talk about after call work time we were able to take five, six minutes out of after call work time for a customer who's the agents are just typing in call notes after a call, right. With the summarization that GPT as an example provides we can transcribe the call, analyze it and now just have the agent copy and paste that directly into the cr. We can automate it automatically 

U1

populate to the CRM. Or if it's a custom portal like this customer where there's no interface, they just paste it right in. So there imagine taking five minutes out of post call processing time for every single call in your environment. So again, it does come back to not thinking of AI as this sort of magic bullet or this monolithic thing but like peeling apart and saying where can we be better and more efficient? And automation post call like that on the customer experience side are dead ringers. And I think particularly when we talk about call summarization and just appending that to a customer record, that's almost a no brainer because it's not going to impact your customer experience and it's only going to take out cost and make agents lives easier and more accurate if. It. 

U2

Yeah, I love those examples and can't wait to I'm super excited to, obviously partner with you guys. We love business transformation type of partners. 1.5s The last questions that we always ask our guests is, you've seen a lot done a lot. Chris, if you have to give one advice, which whether that's a personal advice or a business advice, what's something you're really passionate about or that you believe in, that you would have one advice, what would it be? 

U1

One advice? Yeah. I think it's to really 1.4s gain a deep appreciation of the technology and where it's at and where it's going, because sometimes people, myself included, tend to become fish in water. And you don't realize that you're in 

U2

water 1s until you look around and start seeing the trends. 1.9s Pick up chat GPT and play with it, ask it questions, it's not going to get it. All right. But start to contemplate what would this look like? Because what's going to happen in the market? Is there's questions? Is AI going to replace jobs? Yes. Is it going to replace everybody's job? No. It's going to augment a lot of jobs. Right. And it's going to change even engineering, like how software gets developed internally, we've already started using these tools and we're more efficient is really just stay open minded and look at the opportunities. Don't just do something because you think your competitor is going to your 

U1

competitor is going to do something. And so I think there's two angles. One is, how can you use this to make your business more effective and efficient and profitable? But then two is what should your own AI transformation look like? How should you be bringing better software, better products and services to market that are infused with these new tools? And those are two different things, but I think the latter is really where companies are going to differentiate over the long term. Think about how it's going to transform your business, not just your contact center. 3.6s

U2

Yeah. Chris yeah. That's easier said than done. But great insights, and 1s thank you for all your insights and partnership and excited to have you. 

U1

Awesome. Well, thanks again for having me on. I'm looking forward to to partnering with you guys. And it's been a pleasure chatting with you. 

U2

That was an amazing episode of the digital podcast with Varisource. Hope you enjoyed it and got some great insights from it. Make sure you follow us on social media for the next episode. And if you want to get the best deals from the guests today, make sure to send us a message at sales@varisource.com.