BizTech Next Level BizTech Podcast

Ep.122 AI Overload and the Mind-Blowing Ways Artificial Intelligence Elevates CX with Ashley Hobson

June 24, 2024

Subscribe to the Next Level BizTech podcast, so you don’t miss an episode!
Amazon Music | Apple Podcasts | Listen on Spotify | Watch on YouTube

Today we’re talking AI in Customer Experience with Ashley Hobson of TelNet Choices as we discuss CX2.0 & The Mind-Blowing Ways Artificial Intelligence Elevates CX. Ashley kicks us off with some of her back story how she got a very early start into this space and realized there were incredible areas jump back in, and she did just that! You’ll hear about some key and unexpected win stories and how not only did she go against the grain of what the customer was expected, she ultimately found a great solve for the technology gap in CX when it didn’t appear there was one. You’ll also hear about she uncovered a way to help the business generate more revenue that prior because they weren’t able to see the story the data was telling them. Jump in and don’t miss this episode!

Welcome to the podcast, designed to fuel your success in selling technology solutions. I’m your host, Josh Lupresto SVP of Sales Engineering at Telarus and this is Next Level BizTech.

Hey, everybody. Welcome back. We’re on today talking about Customer Experience 2.0, and we have to talk about AI. So we’re going to talk about how AI is reshaping the CX landscape. Today on with us, we have got the amazing Ashley Hobson of Telnet Choices. Ashley, welcome on. Thank you, Josh. It feels very full circle because this podcast has helped me in many ways in talking about AI. So I’m excited to be here. Thank you. Love it. All right. So let’s jump in. Let’s hear your story, Ashley. How did you get into the field? Where did it start? Windy, direct path, what is it? Well, actually, so I got into the industry when I was in fifth grade.

My mother, who started Telnet Choices, she was programming Blackberries for one of our customers. It’s still a customer today, and she walked out of the room and she was on with Verizon and said, “Ashley, I need you to just sit here while I go to the restroom.” And so I did. And then she came back, and I was actually programming Blackberries for our customer. And she was like, “Wow.” But honestly, though, it obviously did not start in fifth grade. I had helped her throughout the years. And I always said, though, growing up, you know, I was never… It wasn’t that I didn’t want to work for my mother. It was just I wanted to create my own path and kind of create my own journey. And so I graduated from UC Berkeley, and it was during the pandemic. And I didn’t know what was next for me. There was a lot of uncertainty. I was talking, you know, I was going to go into the tech world, but didn’t know what was next. And so I started helping her. And a month later, I was heading all of our advisory services, really building out the way that we were helping our customers. And it’s been four years and it’s been the best four years. And I’m very excited. I love it. I love that there’s Blackberry in this story. And I think it just proves that this industry sucks you in and it’s constantly looking for good people and it will not let you go. So love that you’re here and love that story.

Thank you. So tell us a little bit about… Let’s get everybody who’s not familiar with Telnet choices, you know, walk us through kind of what your go-to-market is. Give us a little bit of commercial about you guys and how you stand out. Awesome. So we actually… It started out as more on the cost containment side. And then over the years, it’s really transitioned because of understanding the technology landscape, you know, the evolution that’s taken place. I mean, even in the past four years that I’ve been a part of this industry, it’s transformed in different ways that I could not even imagine. So really our go-to-market strategy, as I like to say, is we’re kind of like the for organizations, but we take it a step further in allowing for the IT to not be seen as a cost center and rather a revenue driver. How can you make an organization better? We see so many customers that are struggling with growth because they cannot back the technology with that growth. And so really just being a strategic partner, we’re not coming in to tell you you’re doing anything wrong. We’re coming in to really provide that guidance to allow customers to be where they want to be and maybe provide some extra value of, you know, we’re seeing what other companies are doing and what’s working and what’s not. Awesome. So let’s go… Lessons learned from a mentor here. So take us back, I don’t know, two years, five years, 10 years, however far back you want to go. Either A, a really hard lesson that you learned on your own from a mentor or just something great that you’ve learned along the way that’s helped you guide through.

Yeah, so it was actually four years ago when I had started out in my, what we like to call career path. And one of my… I had to learn very early on that you can… You are the only one that can define your success. It cannot be defined by the others around you because it was actually one of my first events ever. And I was told that I was young and I was a female and I would never make it in this industry. And so for about four months, five months after that, I was chasing what I believed as what everybody else deemed a success. Trying to prove myself to others and obviously, you know, just starting out, a lot of people think, you know, your experience isn’t there, but at the end of the day, you really have to under… And I had an aha moment of really understanding that I need to be the one that defines those parameters of success. And so I hope if anybody’s listening, whether you’re young or whether you’re far in your career, is it’s never too late to start defining your own success. I love it. I think you’re doing a bang up job. And I think what you find out is that you have these preconceived notions of what success is supposed to look like and what you’ve been told success is supposed to look like. And you obviously learn as you get into this, it’s just different. And I think you find that is you just…

What you think everybody does, that are the basics, you find not everybody even does the basics. So sometimes just doing the basics, you set yourself apart. So you do a little bit above and beyond that. You’re amazing and magical, right?

Exactly. No, I couldn’t agree more. And that’s what I think it’s… It gets hard because, you know, there’s so many different areas that organizations focus on, you know, whether they’re small or large. And so it’s really just being able, like you said, is the basics really can help to drive kind of that day to day and also make you excited to wake up for work. You know, not feel those pressures because that’s what I think is like the anxiety then kicks in and it makes you less excited to wake up. And so… Yeah, good point.

All right. So topic today, we’re talking about AI. You know, specifically, we’re talking about customer experience 2.0. So let’s talk about a challenge that’s out there. So it seems like AI has, I guess, right now, recency bias. It’s productized very quickly in CX. So with all these evolutions that are out there, you know, the customers that you’re talking to, how do you feel that we got to where we’re at right now?

You know, I think we got to where we’re at right now with the limitations that these great customer, you know, the contact center platforms have. You know, I think what happened was they were they were trying to get there, but they didn’t get there quick enough. And so what we’re really seeing is kind of that layered on approach to companies are now starting to realize, obviously, with the general term of AI, a lot of it has to do with untapped data that organizations have. And so I think where we’ve gotten to an point, especially in the customer experience space, is that the contact center has so much data that can actually drive revenue, can actually help an organization be better, you know, regulate their agents compliance. Like there’s so much that can be untapped. And I think that’s where we’ve gotten to today. But I think a lot of companies, though, don’t understand the potential of AI in the contact center space. And so that’s what we’re seeing.

Are you finding, I mean, as you talk to these customers out there, are you finding that they have a good understanding of the products yet that are out there? Are they all, you know, I would like to think the value that we all add in this, right, is we see a lot of things and we get to see what customers are doing. I mean, what’s that perspective like as you talk to customers about all these evolutions that are happening in the last, you know, two years?

Yeah, so I, you know, it’s crazy because, so I’ll give you an example because we went through this and it was actually about nine months that we were going through and analyzing it. And so kind of from the journey, what happened was one of our customers came to us and they said that they were looking for a survey tool so that they could. And so, you know, obviously at first we were kind of just doing what they were wanting was, you know, understanding what survey tool they were with NiceCX1. And so we, as we started to uncover and also with the help ofTelarus is that we were actually able to uncover that they were trying to understand the voice of the customer better.

And even though they are, I think they just got ranked number seven in Forbes for customer experience, that’s their bread and butter. That is what they hone in on. And so really being able to untap and understand the voice of the customer a lot better. And so when we actually brought on LevelAI and when we initially did the demos and we actually brought in the quality analytics team that was using the NiceCX1 platform on a day-to-day basis, they looked at it and they were just like, “We already have this. You know, what value are you bringing us?” And so it took a lot more uncovering and understanding that, “Hey, you don’t have to put in all of these key words to actually find the data. This is generative AI that’s taking snippets, different types of conversations and allowing you to actually get the data that you’re spending hours and putting those keywords in.” And so they were able to actually see their data once we went through a proof of concept and they were sold on the call. They said, “Okay, you know, this is what we need.” And so it’s also, too, is, you know, when you’re actually able to see your data and being able to see that there was, you know, the issues with the orders or all of your agents are actually upselling and cross-selling, that you didn’t see that before, that’s revenue to the business. Yeah, I like that. I love that example, right, where it’s often you have to convince them, you’re just, you’re passionate about what you think the solve is and it just takes a little while for them to see it from a couple of different directions. And I love the story, or I love the adage of data doesn’t lie, people do. And so you just let the data tell the story, right? And I think that’s what this AI journey is about. It’s, you know, whoever first gets unstructured data in a way that’s structured and valuable wins this next, you know, trillions, billions of dollars in the AI race. And so it’s just, it’s conversations like these that it takes to drill down, right? And it’s because you knew these products and you knew their limitations once you got into a good spot. Oh, it’s those “aha” moments, right? Mm-hmm, exactly.

All right, so I want to talk about maybe what you see customers complaining about. So is there any kind of common threads as you get into, as you’re talking to either, you know, current customers, you’re talking to prospective customers? Is there any common threads here when we look at, you know, what’s coming, AI, you know, rapidly innovating? Are you seeing anything complaint-wise from customers?

Yes, so I would say complaint-wise is a lot of customers, though, when you look at AI, is some are very excited and some are also very scared because they feel like you have less control over your data. And so there was the, I think there was an airline that it went rogue and then they had to, you know,

refund based off of that. And so that is definitely a complaint that we’re seeing in terms of the AI is being able to make sure that you’re able to control from a brand awareness perspective. But we’re also seeing the complaints on the side of limitations within what they currently have today. And so you’re kind of bundling those two together of combating, you know, why AI is not hopefully going to go rogue for you or, you know, being able to implement the best practices and making sure that the data that artificial intelligence is using is data that you would want to be shared. That’s where a lot of companies, you know, we’re seeing that a lot of, you know, don’t share like what your secret sauce is to your organization probably within AI or making sure that you’re creating the right parameters around what data is being used. And then on the other side, though, is the complaints from the limitations of being able to use kind of those current technologies to be able to untap that data along with, you know, not not replacing as well. The agents is something that we are seeing is to. Yeah, I think as we go down the you know, the people that come to us and say, I want to do AI, I want to do large language model. And then so we always have to figure out, all right, what are you trying to accomplish? Where do you want to start? And I think the reality is there’s some assumptions around what stepping out from CX for just a second, there’s some assumptions around what some of these generative AI tools can do. Right. The thought is, let it analyze my data, let it feed my data and let it learn. I think the reality is the model was trained to know how to talk back and forth and give common answers. Yes, but the model hasn’t yet been trained on how to interact with your data. And so maybe we don’t want to give it all that exposure because it doesn’t know what’s sensitive. So there’s a seems like there’s a big push to we can understand it, but then it comes back to data classification. And so there’s there’s I think going to be a big push with things like Microsoft Purview and other DLP tools out there to help classify and tag that data appropriately. And I think once we once we start to solve for that, it lends itself back to CX, it lends itself back to, you know, a tool I can give my sales team to ask questions about, you know, customers and QBRs and all that good stuff.

Exactly. Have you seen the multi model, the chat GPT with the example with the shoes for customer experience? Have you seen that with the high? No, no. OK, so basically what happens is I would so I would have my video on and I and and Microsoft is now going to the day that OpenAI came out or announced it. Now it’s going to be something that can be start building in Microsoft Co-Pilot. But essentially what would happen is what my experience would be is I would jump on to I’d be on my computer or on my phone and I’m on a website. And let’s just say I’m buying this is the example that they use the demo. I’m buying shoes and so I need hiking boots. And so I’m like I and so basically what happens is I have my video on and I just start talking and I’m like, OK, this needs to be really quick. I’m leaving tomorrow for I’m leaving this weekend for a trip and I need new hiking boots. And he is like, these are the hiking boots I and you know, I have it immediately acknowledge the exact hiking boots that they had. And he was like, I’m going to be, you know, going down this trail. And they were like in the A.I. basically is having a human conversation saying, you know what? I don’t think those are the right shoes. He’s like, well, can you just add the right shoes to my cart? And he’s like, yeah, you got it. Adds the right shoes to the cart. And and then all of a sudden he starts speaking in Spanish and the chatbot replies in Spanish.

It’s a yes, that’s a beautiful thing. I I watched some of the four point roll out and some of the multimodal. I hadn’t seen the shoes example. Yeah. I think it’s just the part about A.I. is we’re going to have to have, you know, 500 use cases at our ready when we’re talking to customers, because it’s so amazing. You can’t envision that it actually works already. And so, of course, your mind’s not going to think to look at that, right? But think about how you come in with this conversation of yet already does that. Like, let’s get that built for you.

No, and that’s so true. And I think what a lot of people know now they have. And obviously, when chat GPT came out, it was like a rollercoaster of emotions for everyone, me included. You know, is you know, is is A.I. going to take over the world? Is it going to replace our jobs? And, you know, I think a lot of that like that noise has definitely come down a little bit. But I think where a lot of organizations, though, and people have to have the mindset, though, is that look like we’re here. It’s here to help you. And at the end of the day, everybody has probably used A.I. in some form. It just became a lot scary because like Siri, for example, you know, artificial intelligence is a part of that. You know, Alexa. So I think it’s it’s definitely an exciting time. But it’s also being able to make sure that people are innate, that you’re enabling organizations to use it effectively and efficiently, because you can’t just like throw co-pilot into an organization and not, you know, set it up correctly or have that expertise and that knowledge to manage it. And also training as well as the actual users. Yeah, yeah, that’s that’s another component of it, too. How to talk to it, how to ask questions, how to use it. And, you know, I could prepare for some of the varieties in that certainly. But, man, you can just make it so much more effective if you can teach your folks how to talk to it and you get the real maximum benefit out of it. I love that. All right. Let’s let’s jump back into a case study here. So give us an example.

Easy one, complicated one. What I want to draw here is, you know, what was the business problem in the tech stack before? What did the customer say that they needed and really how did that environment look after?

Yeah, so I definitely want to go back to the use case I used before, because I think there’s so much so much a part of that that is actually very transformative from an organizational standpoint, because in the customer experience base, you know, there you are. So today, a lot of customers are limited and they don’t realize it. They don’t realize that data kind of what I talked about before is they don’t realize the data that could actually transform an organization. And so when going through and having that conversation of understanding it was really voice of the customer, they didn’t they didn’t you don’t know what you don’t know. And so during the proof of concept, we were actually able to see is, you know, there was based off of specific carriers, there was so there was a lot more damaged products with a specific carrier. So then you take it back to the business and, you know, should we should we be using this carrier? You know, what does that lost revenue look like for our organization? And then you could take it even a step further. And from like the sales side, for example, is there was they have free shipping promo at seventy five dollars. And so they were able to see actually the the agents that were upselling and cross selling. And then you start to be able to see is, OK, how could we teach all of our agents to be able to upsell and cross sell, especially with seasonal employees, for example?

So that so it really it created from a voice of the customer to actually more of a business case, being able to understand from a business perspective, how can we take this data and take it even a step further? And during the beginning of implementation, too, is they started wanting to untap so much more data that we didn’t even recognize to then be able to implement new technology. And so you can take it from being able to look at it from understanding the customer experience space, understanding what’s being said during the contact center and now make that a business case for other technologies within the organization that are not even a part of our ecosystem.

Yeah, I you know, I think you bring up a good point when we, you know, in our sales field, we generally have this notion of, OK, this thing that I’m going to sell to a customer, even though it is something that they need is a net new cost. So do they have the budget? You know, you got on all that process or the people aligned. But as you get into an example like that, you’ve unlocked their ability to sell more than they were selling the day before. So essentially, you have negated the cost of this program and helped the company innovate in a way that they could not have done on their own. It’s a tremendous example.

Yeah, exactly. And I think it’s and I’ll say it, too, it’s not easy to allow a customer to understand that because when you think of investing in a new technology, you think of the costs and the dollar signs. And it takes a lot of conversations. It takes a lot of data being shown to actually have that business case. And we even had that with a customer. And this wasn’t even in the customer experience space, but we had a customer that all of a sudden they got a partnership with Kaiser. And they were needing to grow exponentially. They were still on prem. All of their servers were on prem. Their phone system was on prem. And it was like, you know, basically overnight, we need to be able to change our whole entire tech stack. And so we and they had a small team. So it went from having a conversation about a phone system to virtual desktops to enable them to hire more efficiently and effectively. And then from a new, you know, from the phone systems, being able to communicate more effectively with the end users, being able to move offices, it just became. And there’s so much more that was a part of what we were able to solve for. But it becomes so much different of a conversation.

Yeah. Yeah. Love it. Keep doing it. You’re doing great work. So as we think about, you know, there’s there’s a lot of awesome marketing collateral out there about it. But at the end of the day, it’s our job to figure out how the productization of this over time makes it in a way that we go, OK, we can help customers do that. We can sell that we can deliver that. So I mean, for anybody that’s listening out there, right, what do you want the channel to be doing with regard to productization of AI to help yourself and help partners and help customers understand it better?

Yeah. So I think obviously today is there’s a lot of and, you know, looking at our entire technology ecosystem. There’s a lot of different, you know, quote unquote, AI tools that are a part of that. So when we look at customer experience, it’s, you know, the layered on like I was talking about with like the level, the observe, you know, you you’re having the chat bots, for example. And then you look at IOT and now you’re you know, now you’re talking about smart security systems being able, you know, so there’s a lot when you look at it, when you’re looking at it from the entire technology ecosystem.

But where I see in terms of productization in the channel, I think it’s going to be a lot of professional services really enabling customers to implement technologies that might be outside of our wheelhouse or building in-house. That’s what we’re seeing a little bit more now, too, is well, you know, you have this conversation and Josh, you said it earlier is we want to implement AI into our, you know, and into our technology ecosystem. We’re like, that’s great, but, you know, it’s such a broad topic of conversation. We need to narrow it down a little bit. And so we’re seeing a lot of a lot of companies that are looking to build on top of their existing ecosystem in-house. And so I think that is also going to be a part of our conversations in terms of productization that you can enable them to implement more effectively and efficiently, but also keeping up to date, making sure that they’re utilizing it more effectively. And I think even just from a technology standpoint, if you are a company that’s selling some type of AI tool, you really need to make sure that those quarterly business reviews that you’re making sure that they’re using them to their best ability. Love it. All right. So if I’m a partner, I’m listening to this, I want to get a little bit deeper in AI. I want to expand my knowledge. You know, we’re talking about CX, but broadly about AI. I mean, what’s your advice for anybody to get out there, learn, dive deeper and understand this? Honestly, listen to the next biz podcast.

We’ll take that. I’ll take that. I mean, that helped me begin my journey with level AI.

But I think obviously on top of podcasts is really just, I mean, really just understanding and going to even the conferences that are all around AI. Companies are loving to hear what AI has to offer. It does not mean, though, that they’re ready to implement AI into their technology ecosystem. But if you can start putting those feelers out for your customers that look, you know, I’m up in this game and I am staying ahead of the times and I’m here to help you when the time is ready. That’s where I think you’re going to be able to really set yourself apart and really just understanding whatever organization has to offer. But also understanding, too, is what actually is a part of AI, because AI could mean so many different things and especially from, you know, large language models and, you know, with the generative AI is really understanding the technology behind it, because some companies will say like, we’ve got AI, you know, and might not be a true AI product. Yeah, you bring up a good point. I think the playbook of how we help people and how we ask a big, you know, questions promoter, right? So I think if you’re asking these questions, if you’re meeting with the customers, I don’t care if you’ve sold them CX before, if you’ve sold them security, if you’ve sold them network, if you’ve sold them whatever, you know, the thing, you know, what’s on their roadmap, the things that they’re asking for, but just ask, keep asking the why. Oh, what do you, why are you looking to do that? And understand that business reason. And I think then that allows you to understand maybe where you need to dive deeper, where you need to understand. I think to your point, as long as you’re showing, that’s so huge to customers when you’re just showing, hey, I’m staying in front of this for you so that you don’t have to do it as much. And then I can, I could be that one that you lean on. Exactly. And I think, and that exactly what you said is asking the why is because you’ll be able to uncover so much more if you just ask why, you know, customers tell us all the time is that, well, you just, nobody asks me why, you know, it’s just like you, you tell you, you say something and then you’re immediately responding with, well, this is what you’re going to do. And it’s like, you don’t know if that’s actually the right, you know, you create that collaborative approach and you can bounce off of one another to actually get down to what’s going to help an organization.

Yeah, I, you know, I forget what, what book this is from, but it might’ve been from power questions. That was one of my favorite ones that I always talk about. But you may have an agenda of what you think you want to talk about when you get in there and sit down in that meeting with that customer and you maybe dead on right with all the things that they want to know. But if you haven’t gone through this kind of psychological questioning process, that customer doesn’t feel heard. There are people on that meeting that are already tuned out. And so if you ask that and you uncover that, and then they feel that you’re now articulating the things back to them that were asked in the questions of what they wanted to learn. There is a better way, I think, that that just helps it absorb that, oh, okay, all right. That this team gets me. They understand. They know exactly what I’m looking for. And all in all, these are two journeys that were destined to end at the same spot, but you would have just got there through the way of asking. The questions and listening. Exactly. And I couldn’t agree more with that. We we see that all the time, especially even when you’re at a conference, even, you know, everyone will come up to you and they’ll say, what’s your sales pitch? I’m like, well, I have to ask you the question first. What do you do? You know, what what is what’s important to you? And then I can tailor that towards what you’re specifically looking for, because I don’t want to sit here and tell you sales pitch that maybe doesn’t pertain to you.

I love that. I love that example. All right. Final thoughts here, Ashley. So let’s look out into the future here. Our crystal ball as it relates to customer experience just over the next couple of years. Right. We got a I coming at us. We got large language models. We got robots. We got all this cool stuff.

Where do you think this experience is heading over the next couple of years? Innovations, things like that. You’re looking most forward to. So I think there’s going to be a TV show with catfish in the business world with all of these AI LinkedIn profile photos going on.

But serious and all seriousness, I think that it’s going to be a tremendous amount of revolution within organizations. I think there’s going to be a heavy investment in technology.

I think from the perspective, though, of kind of just where where I think it actually is headed is I think that a lot of organizations are going to consolidate, especially in our space. I think there’s going to be a heck of a lot more consolidation. And I think it’s just going to become a kind of competition of whose AI is smartest. You know, what’s going to be most effective because you’ll see, like even today and on the IVR is the amount of times that I’ve wanted to tell them to stop talking because they’re not listening to me. And I just need to speak to somebody. And obviously, you know, that’s that’s already going away. But I think that’s where from a revolution perspective is I think that organizations are going to be implementing technology in so many different ways that they never thought that they could.

And really being able to transform organizations. I think the one thing that is a little bit scary is I don’t know if I’ll be talking to a real human or if I’ll be talking to AI. I mean, we’re already seeing that with there’s that there’s that video or there’s the platform where you can basically train now. So if like I’m coming on as a new employee, I’m the manager, I already prerecorded my video and now I’m teaching, you know, now I’m telling it, you know, the onboarding process, which obviously from onboarding perspective, that is very expensive for organizations. But I think it’s it’s exciting, but it is a little bit scary because what does that mean from the human interaction approach? You know, we feed off of human energy. We really do. And so how are you actually able to still have that human interaction and also be able to make organizations more effective and efficient, but being able to keep that human approach? Because I think that’s what makes us better every day.

Beautiful. What a good spot to wrap it. All right, Ashley, that’s all the questions I got. Awesome content. Awesome stuff here in CX. Thanks so much for coming on. Really appreciate it. Awesome. Well, thank you, Josh.

All right, everybody. As always, don’t forget, wherever you’re listening, go like, go subscribe, Spotify, Apple Music. You’ll get these that drop out every Wednesday. And that wraps us up for today. CX 2.0, how AI is reshaping the landscape. Ashley Hobson, Telnet Choices. Until next time, I’m your host, Josh Lupresto SVP of Sales Engineering.