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The Agile Brand with Greg Kihlström®: Expert Mode Marketing Technology, AI, & CX
#806: NiCE Cognigy VP of Marketing Alan Ranger on agentic customer service
00:30:56
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- [00:01]
Alan Ranger
The agile brand.
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Greg Kilstrom
Welcome to Season eight of the Agile Brand Podcast.
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Sponsor/Ad Voice
This season we're going all in on.
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Greg Kilstrom
Expert Mode, MarTech, AI and Customer Experience, talking with the people and platforms behind.
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Interviewer/Host
The brands you know and love.
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Greg Kilstrom
I'm Greg Kilstrom, your host and I help Fortune 1000 companies make sense of martech, AI and marketing ops. Hit subscribe or Follow to make sure you always get the latest episodes and leave us a rating so others can.
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Alan Ranger
Find us as well.
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Greg Kilstrom
And make sure you check out our sponsor, Tech Systems, an industry leader in full stack technology services, talent services and real world applications. For more information, go to teksystems.com now let's dive in.
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Interviewer/Host
We've spent years trying to make our.
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Sponsor/Ad Voice
Chatbots sound more human, which is great.
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Interviewer/Host
But but what if the larger goal.
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Sponsor/Ad Voice
Should have also been to make them.
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Interviewer/Host
As useful as possible? While we're at it, agility requires more than just adopting the latest technology. It demands a fundamental rethinking of customer engagement, moving from reactive responses to proactive problem solving. Today we're going to talk about the next evolution of AI and customer service as more companies turn to automation to manage scale and efficiency. The real challenge isn't just implementing a chatbot, it's ensuring that technology actively solves problems and enhances the customer relationship, rather than just deflecting tickets.
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Greg Kilstrom
To help me discuss this topic, I'd.
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Interviewer/Host
Like to welcome Alan Ranger, VP Marketing at Nice Cognigy. Alan, welcome to the show.
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Alan Ranger
Thanks Greggy, it's great to be here.
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Interviewer/Host
Yeah, looking forward to talking about this topic with you. Definitely atop lots of people's minds. Before we dive in though, why don't you give a little background on yourself and your role?
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Alan Ranger
Yeah, sure, I'd be delighted to. So yeah, I'm lucky enough to lead marketing at Cognigy, which is now a nice Cognigy. So I joined three years ago and have taken the company through the Series C and then the acquisition by Nice, which was in September of 2025. Nice.
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Sponsor/Ad Voice
Nice.
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Interviewer/Host
Love it. So yeah, let's dive in and we'll start with the strategic view here. And you know, as I teed up in the intro, talking about this idea of certainly we want automation and there's lots of benefits to automation, but you know, the idea of AI and customer service isn't even a new thing. But the use of agentic AI certainly represents a significant leap beyond the typical chatbot experience that I'm sure we've all had. So from the strategic lens, what's the fundamental business shift that makes this kind of proactive, action oriented AI. Not just a nice to have, but now a necessity for large brands.
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Alan Ranger
That's it. You know, the, the whole sort of meaning behind agentic is that these AIs have agency to actually do something. So going back to your introduction, it's all about completing tasks and doing it properly. And now it's relatively easy these days to take a large language model and put a wrapper around it and create a really good conversational chatbot. But it might not do anything. It might not be integrated to the back end of the enterprise systems. It may not have been given the guardrails of how to operate in an enterprise environment. So I think it's one of those things that we did an awful lot with AI in customer service before with the more traditional, as it's now called, the deterministic flow based AI. And you could achieve great things. I mean, one of our major customers is Lufthansa, the German airline. And the stuff they did with flow based deterministic AI was remarkable. Everything from rebooking flights to taking recommendations, inquiries, all that sort of stuff, it worked really, really well. But what we were so surprised with when we launched the agentic was that they just took it to the next level. And it's the AI's ability to reason almost like a human and to be able to have specific tasks it's going to complete and just do that at scale in a way that's really good from a customer experience perspective.
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Interviewer/Host
Yeah, yeah. And so when leaders are, certainly there's a lot of leaders already either considering this or actively adopting it. When they're, when they're doing this, there's often some internal resistance. Right. I mean, as you mentioned, these agentic tools, they're good at what they do and they can certainly do some things that humans know formerly were doing or even are still doing in, in some capacities. So there's, you know, there's a natural fear of being replaced. But you know, how do you advise leaders to frame this integration as not really replacement, but as a force multiplier?
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Alan Ranger
That's it. I mean, it's just about automating the tasks that humans never should have done. You know, if you're a human advisor, you shouldn't be sitting there resetting passwords or, or looking up account balances. Anything like that should be automated. And you should really think about using the human advisors as being your brand ambassadors and doing the work of highest value. There's some industries obviously, like financial services, where, you know, it's regulated and you can't have an AI providing financial advice. It has to be a regulated human being that's been certified and is accountable to financial services authorities and that sort of thing. So we will never see the end of human advisors. I think that they will be involved in the higher value stuff, working in partnership with the AI. You know, most of the conversations that our agentic AI is now having, not all of it is entirely autonomous. There's an awful lot of it where it goes backwards and forwards to a human. And then the AI can even change roles and go from being consumer facing to being agent facing and work in the background, just making sure that they're given the prompts and the help and the information they need to have a fantastic conversation. And it just lets the human focus on having a great conversation, which is what human advisors are really good at.
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Interviewer/Host
Yeah, well, and it also, it gives them more time.
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Sponsor/Ad Voice
Right.
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Interviewer/Host
I mean, if they're not, to your point, resetting passwords, even if it's a relatively quick process, that takes time and it takes time away from solving a nuanced and perhaps, you know, sticky situation that AI may not be adept at handling. Right. So, I mean, it's actually elevating that role. Right?
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Alan Ranger
Yeah, that's it. And to be honest, none of our customers have actually laid off human advisors. They're all suffering from a huge shortage of great advisors since the pandemic. Pandemic, it's almost been that nobody wanted to go back to the contact center. You know, they all found different types of employment. And so, yeah, typically, you know, churn is high still, recruitment is a constant battle. And so what they're doing is filling the gap because, you know, unfortunately hold times have gone up. Despite all of this new technology that's available, the availability of the humans has gone down and it certainly can't cope with sort of a peak transaction. So, you know, going back to our friends at Lufthansa, you know, they have a snowstorm and an airport shut, all of a sudden 10,000 people call to rebook their flights. You can't predict that. You can't scale up with humans. So you need an automation that's going to take those peak things, take over all of the out of hours stuff, and also take over some of the multilingual capabilities. So you don't need a multilingual contact center anymore. You can have real time, simultaneous translation happening. Even if it's human to human rather than human to AI agent.
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Interviewer/Host
Yeah, and I think that's a good part of the conversation to have, is that yeah, it's exactly what you said. There's, there's roles that humans aren't able to, there's not enough humans to fill the roles and, and things like that. And I think, you know, that, that can often get overlooked in some of those, some of those conversations as well. I guess to, to make it more practical to, to those that are either in that consideration stage or just, you know, trying to think of how this could look at some point in the future. Can you walk us through a practical real world example? You know, how does agentic AI interaction, you know, fundamentally differ from, you know, a more standard chatbot journey, you know, taking you know, complex issues into play?
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Alan Ranger
Yeah, so with the traditional AI, the deterministic one, it was, you know, very good at construct or being constructed to solve very simple tasks. So you know, as I said, the flight rebooking one is a perfect one. The there's not too many things that can go wrong or deviations on the path where you can build a really good deterministic flow based one that just resolves it at scale, does the job. But as soon as anybody would then go off the path and maybe, well, I've rebooked the flight but now I need to change the number of passengers or can you tell me what my allowance is? Can I bring a pet? All this sort of thing, the deterministic ones only built to follow the flow and can only do that. We just have to. I don't understand which is the most frustrating thing in the world, talking to an automation. It's happened to all of us and it continues to happen and it shouldn't now with the agentic stuff because it's using the large language model. It understands absolutely everything that's being said to it and if it's able to, it can then resolve the issue that the consumer's calling with. If they can't resolve it, it can just say, look, I've not been trained on this, let me pass you over to my other agentic AI, has been trained on this or maybe I'll pass you on to a human being. So a great example is one of the world's largest bus companies or coachlines company. Unfortunately I can't say the name but I think people will guess it anyway. They did their first AI automation using the deterministic stuff. It took them about six months but they picked India as their launch market, which has got to be one of the world's most difficult places for ghost travel. The road system is chaotic. You never really know what's going to happen and they built a really good deterministic bot that actually resolved all of the things like timetabling, where's my bus ticket buying all that sort of thing, very high adoption rates. They then moved on with the same technology to launch in the US this was probably about eight, nine months ago and it failed acceptance testing because it wasn't good enough in users and experience. So within a week they rebuilt using AgentIQ technologies and launched and it's gone down an absolute storm. And the reason they were able to do that, I think it's because they had the experience of building the deterministic bot and they knew how to do the integration into the backend system. So it was enterprise ready, it was on a proven scalable platform. And then when they launched it was just understanding everything and using its own capabilities to answer questions. There was one person, for example, had called in and said, oh, I'm buying a ticket for my friend, but they've lost their mobile phone. And so it automatically went, well that's fine, you can just print it out. And we hadn't trained it on, you could just print. We knew the knowledge of the world that this was a solution. So it's actually solving problems but only focusing on the problems it's allowed. Had you asked it, you know, who's going to be the next president of the usa, you would go, that's very interesting, but I've not been trained on that and I can't give you an answer.
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Interviewer/Host
Right, right. Yeah, well, and I think, you know, to your point, the, for the company to have been through the process of doing it in a more, I'll just call it, you know, deterministic, to use your word, or a more manual way of, of, of routing these. If this, then that kind of kind of process, it, it does seem valuable to have gone through that exercise almost like a flowchart exercise before you do the generative AI or the LLM based version, just so you have a kind of knowledge of overall things. But obviously one of the big components here that really helps it is also having access to data. Right. And so how does, you know, how do you recommend that an organization think about, you know, maybe having mapped it out for the, for the deterministic model helps them understand some of the processes. But what about the data component? You know, what should a company prepare as they, as they embark on this?
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Alan Ranger
Yeah, the data component is huge. I mean the, our friends over Gartner have put out, this is probably again about 10 months ago a doom and gloom report saying 95% of AI projects fail.
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Interviewer/Host
Right.
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Alan Ranger
And it's pretty much because the data underneath isn't correct. I mean, you can consume any data now and, you know, convert it in a way so you can have a conversation. So anything from a book to a PDF to, you know, the FAQs, they can all be consumed into the knowledge base and then, you know, using agentic capabilities, it can just be questioned in a very human like way. But if that data is out of date or wrong, then yes, that's a huge issue. And also, you need to make sure that when you build the AI agent, it's grounded only on the data you give it. You can't allow it to use its knowledge of the rest of the world to have the conversation. It has to be completely anchored and grounded on the data. So yeah, the key thing is really to. If you have had experience of building deterministic, Everybody knows the value in structured data. That's correct. It doesn't need to be so structured with agentic. It just needs to be up to date and there needs to be a process to make sure the latest thing is up to date. I mean, typically when an AI goes wrong, it's because the data underneath has been incorrect. I mean, it was before the agentiq version. There's the famous Canadian airline that promised a refund because the data was wrong. It wasn't anything, it wasn't hallucinating, it wasn't making stuff up, it wasn't even, you know, a large language model plan. It was traditional deterministic one. But the data just hadn't been updated. They changed the policy and nobody told the AI.
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Interviewer/Host
Yeah, yeah, that's, yeah, that's a. For the, for those listening that aren't familiar with that story, that's definitely a case study to pay attention to.
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Alan Ranger
Yeah.
- [12:45]
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- [13:46]
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Interviewer/Host
So let's talk about measurement here as well. And so certainly classic customer experience metrics are still going to be in play. If you use csat, nps, average handle time, things like that. Are there other measurements that also either need to be added or maybe become more important when agentic AI is introduced into the market?
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Alan Ranger
Max yeah, I mean what we're seeing more and more is people are measuring by outcome, so they're actually throwing away all of the traditional measurements because they were there for the measurement and performance management of human advisors. When you've got, you know, AI agents that have unlimited capacity and scalability and are available 24,7. A lot of the metrics go away. So the classic one is average handling time. It really doesn't matter anymore how long it takes because it doesn't cost any more to have an AI agent having a 10 minute conversation as it does having a 30 second one. And equally, if you're measuring the humans then you probably want to get rid of average handling time anyway because they'll only be taking the more complex cases and the highest value cases and they will take longer. So yeah, what we're seeing is a lot of people actually measuring it on percentage of tasks completed, fully automated, end to end, those that aren't. But another thing we're seeing more and more is a huge sort of focus on CSAT and customer experience. Everybody's now seeing that's the differentiator and many people are actually going for that. Rather than operational sort of cost savings, it's much more about csat. Particularly as we're moving outside the inbound contact center, we're now seeing increasingly that they're using agentic capabilities to do outbound sales and marketing. It's something you could never have done with a deterministic flow because you can't tell what somebody's going to say when you call them or message them. But authentic, it understands the whole conversation, it's been given the task. And yeah, we're seeing more and more people now doing sort of outbound stuff. And again, a lot of that is measured on customer satisfaction and the repeatability of business and the loyalty that they're gaining.
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Interviewer/Host
Yeah, and I mean that makes a lot of sense because I mean certainly, you know, consumers are, they're time challenged like we all are and so they want time back in their day and stuff. But I mean, I'm sure there's a statistic out there that supports this. I think I've seen a few things but you know, if it takes five extra seconds to deal with an issue and it's actually resolved and I don't have to go back and ever talk to that company about that issue again, I'm going to be way more happy than it taking 10 seconds and I'm off the, you know, off the chat, but my problem isn't resolved. So to your point, average handle time is probably directional, but it's not, it's not the end all be all.
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Alan Ranger
The, the one thing it gets rid of completely is hold time though, which is magical. Nobody likes.
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Interviewer/Host
Yeah, yeah, yeah. I mean think about that. Yeah, definitely. And so you know, to your, to your point, about the, the upselling or cross selling or just the, the, the, the commerce part of this too because customers also want good opportunities and offers and things like, you know, it doesn't always have to feel like they're being sold and things like that. So you know, this also gets into both the loyalty aspect of okay, my problems get resolved in a, in a timely manner and in the right way. But also you know, customer lifetime value increases. If we're also able to upsell, cross sell and add real true value to the customer relationship. How do you work with an organization to kind of paint this fuller picture of, you know, yes, we're solving the traditional customer service challenges but hey, there's this opportunity you already mentioned which is we also can present new opportunities to.
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Alan Ranger
Them and you know, in no way done with the inbound customer service. You know, it's still pretty terrible in most organizations. Sure, still to be done there. But no, normally we'll sort of paint the bigger picture of looking at some of their outbounding and look for some high value, high volume automations that we can bring in. So a great example is one of Europe's largest banks. Whenever they sell a financial services product, they need to basically have a conversation with a regulated human advisor. So what happens is somebody fills a form in on the website saying they want to take out a personal loan to buy a car or do some home improvements and then they need to have a quick chat with a financial advisor to make sure that the right product is sold. And typically what was happening is these financial advisors were given a big list of leads in the morning of the people that have filled in their, the application forms and they were just outbound calling and really they only got a 20% pickup of people they wanted to talk to. So really expensive, highly qualified, you know, regulated individuals making these outbound calls with a 20% pickup. So what we did was built them a pretty simple agentic AI. Outbound caller and it was called, would call through the list and say, you know, hi Greg, I'm just calling about the application you made three weeks ago for, for the bank. You'll just need to have five minutes with one of our advisors. Is now a good time? And it was hyper personalized. You know, you were expecting the call because you'd filled in the form. They could just say no, now isn't a good time and it would reschedule and then it would call back and if it still wasn't a good time, it would reschedule and it would go back. It wouldn't get frustrated. It would be very polite and very personal and all that sort of thing. And then eventually when the person who had filled in the form was ready to speak, they'd be transferred to the human advisor who would then complete it. And that then resulted in 80% of the people that the advisors were talking to actually completed the loan and took out the financial product. So that's a huge value for them, you know, in terms of making them more efficient. The advisors loved it because they were on commission. So they weren't wasting the time, you know, having dead end calls. They were only talking to people that they wanted and another customer. Again, in sales marketing, it's a subscription fashion brand and you pay your subscription. So they built a retention automation that when you wanted to cancel your subscription, it would talk to you and work out how to retain you. You know, it would understand when to make an offer of, well, how about you have a payment holiday of two months, this sort of thing, within six weeks of launching, it was outperforming the humans that used to do the task of retention. So yeah, it's all that type of thing. So you pick those big pictures and then for the, those brands that typically haven't had a relationship with their consumers. So the fast moving consumer goods say shampoo. You know, a shampoo manufacturer has no relationship with the user of its shampoo. Its only relationship is with the retailer. And then the consumer maybe has a relationship with the retailer. But these days, you know, you could have put a QR code on the back of the shampoo bottle, somebody uses it and it makes the hair go frizzy. So they scan the bottle with their phone, start a WhatsApp conversation directly with an automation at the brand. The automation knows which product you're looking at because of the QR code and you've said it made your hair go frizzy. So it knows what the problem is and it can work with you to then identify which shampoo you should be using. And the great thing is that then creates a lifetime relationship on your messaging because unless you as the user delete it, it persists. And then maybe in three weeks time, if the permission's been given, the shampoo company go, hey Greg, how's the frizzy hair? I've got this brilliant new conditioning product that you would love for your hair. Here's a voucher for freezing 50% off. Show this on your phone to the retailer and that way they're actually. It's the marketeer's dream, it's a personalized one to One relationship with every single one of your consumers. And I think that's really going to be where the future is going to take us. It's going to go way beyond the front office of the contact center, right the way through the middle and back office. And every relationship that every consumer has with the brand can be enabled through conversational AI.
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Interviewer/Host
Yeah, yeah, I agreed and I think thinking about the future what really struck me lots of, you know, I was keeping up with the holiday sales, retail numbers and everything like that and you know, certainly there's, there's other things to look at there. But what really struck me was just consumers comfortability with using AI tools. And so you know, to bring that into this conversation, you know, I think certainly again we've all been, we've just like there's the phone tree doom loop kind of thing you can get into. We've all been on those chat bot conversations that go nowhere as well. Well but I think humans are a lot, are a lot more comfortable interacting with AI and they probably will continue to do that. And they're going to have their own agents. Yeah, if they don't already, you know, a handful of people already are doing that I'm sure but that's going to become more and more commonplace. Where do you see things going over the next, you know, three to five years here of how does customer service evolve when you know a, you know, consumers are more comfortable with AI? Consumers have their own agents, companies have their own agents. You know, how does all this kind of evolve?
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Alan Ranger
I think the first thing will be in customer service itself we'll see pretty much self building automations. So you know, we'll be able to take all of the data from the human advisor conversations, all of the data from the automated ones and we'll be able to work out which are the most popular intents and then automatically build an AI automation using the agenta kit capabilities to actually resolve those issues. So we'll get to the point where I don't think there's pretty much any customer service inbound use case that can't be solved and automated pretty much end to end. So I think that will then result in you know, a much better customer service. Get rid of all the hold times. Pretty much everything you need to do when you interact with a brand can be handled by AI. But what I think we'll also see is a complete change in the way that we browse and get information. For a start, everybody will use generative search rather than traditional search sort of web search. But what we'll see is that we'll have conversational websites. So you'll start with a big chat window and you'll, you'll ask about something and the whole window will change based on your conversation. So it might be that you're looking to upgrade your mobile phone. So the, the offers as you speak to the, the AI agent will change in the window. And so it won't be a fixed website anymore where you actually navigate around with clicks. And you know, the odd thing here, it will actually dynamically respond to the conversation you have and it'll just be an amazing experience. We're piloting this at the moment and I really think that's going to be the future. Definitely within five years, but maybe within, you know, the next couple of years.
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Interviewer/Host
Nice, nice, love that. So one, one thing and certainly I, the, the automation and all of that sounds, sounds amazing. How do we keep this also feeling? Not too automated, not too inhuman, but also, you know, keep the, keep a human aspect to all of this as well. Like what's, what's the right balance to play, knowing that, you know, again, consumers, they want, they want speed and efficiency, but they also want to feel seen and heard.
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Alan Ranger
Yeah, there will always be human oversight and there will always be the capability to be transformed to a human advisor. And sometimes there may be a human in the loop without even actually having direct contact with the consumer. I mean, that fashion brand I was talking about, they have a returns policy. And so you take a photograph of the product and then the AI tries to work out whether it's a warranty claim or whether actually you've damaged it. So it might be a broken zipper on a jacket, something like that. And if the AI can't work it out, it actually sends a teams message to a human in the background with a picture. It says, hey, I can't understand this. And the human can go either, yeah, that's warranty or no, that's damage. So that will always. So people know that they've got the human with the oversight in the background. And certainly in Europe and places like that, there's regulations that insist there is human oversight. And I think if it's something like medical or if it's financial services, all the regulated industries will still have humans directly talking to other humans to resolve their problems. So I think we'll keep that. But also with the way that we now build the agentic AI, you literally describe its personality and you can adjust its tone and even its accent in terms of the way that it interacts. And it can have Sort of, I suppose, fake empathy. It can never have real empathy because it's still a cold hearted machine. But it can understand the sentiment of the call as it's going on or the messaging conversation and adapt in a way that a human will as well and actually just, you know, provide that, that human touch. But you know, just at scale.
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Interviewer/Host
Yeah, yeah, well and I mean I think there are websites or mobile apps that were designed with empathy. Right. So I don't think it's that far fetched to say that AI could have, you know, it's, it's not exactly the same as talking with a human, but it's also again designed with, with empathy. And so the, the human that's experiencing it will feel that, will feel that.
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Sponsor/Ad Voice
Right?
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Alan Ranger
Yeah. And they can even understand sarcasm. I mean, you know, you heard the classic example of, you know, you were an airline and you get a message back saying thanks for the upgrade, positive sentiment. And then somebody might equally say thanks for losing my luggage. That would be a positive sentiment. But the AI understands that it's not because context of what's been said. It understands that the airline has lost your luggage and you're not happy.
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Interviewer/Host
Right, right, absolutely. Well, Alan, thanks so much for joining today. I got a couple questions for you as we wrap up here. First one, if we were having this interview one year from today, what is one thing that we would definitely be talking about?
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Alan Ranger
I think we'll be talking about what the humans are still doing. Inbound customer service. Which of the tasks do we still need humans and which ones haven't we automated? I hope we're not. But we're probably still going to be talking about why some customer service still sucks and why people have been resistant. Hopefully, you know, because the technology is out there, it's now proven and the adoption rate is remarkable. It's quicker than I've ever seen in my great big long 30 year career. So I think we will see that. But hopefully we won't be talking about what's not been automated. We'll be celebrating the success and maybe we'll even be laughing about the old metrics like average handling time and hold times, that sort of thing. Right?
- [28:53]
Interviewer/Host
Yeah. Well, last question for you. What do you do to stay agile in your role and how do you find a way to do it consistently?
- [29:00]
Alan Ranger
All right, so at the moment I'm in Florida, I'm at ccw, the event here. So what I do is I spend as much time as I can either presenting on stage or just joining in the forums and communities of the people whose issues we're solving. And I find that, you know, there's a lot of geographic differences and cultural differences. So I try and, you know, get over to the US at least once a month all over Europe. I'm now expanding into apac. So it's just being with people and hearing what they've been told, helping them with the education and just becoming a trusted peer and part of the communities that everybody's in. And yeah, that keeps me excited every day when I wake up. I love meeting people and just hearing what's going on and this being able to use that to make sure that we're shaping the product in the right direction.
- [29:41]
Sponsor/Ad Voice
Yeah, love it.
- [29:43]
Alan Ranger
Thanks Greg. It's been an absolute pleasure joining you today.
- [29:45]
Interviewer/Host
Yeah, thank you. Well, again I'd like to thank Alan Ranger, VP Marketing at Nice Cognigy for joining the show. You can learn more about Alan and Nice Cognigy by following the links in the show notes.
- [29:59]
Greg Kilstrom
This episode is brought to you by Tech Systems. They're leaders in full stack tech services, talent solutions and helping companies put it all in action. You can learn more@teksystems.com and thanks again for listening to the Agile Brand podcast. If you like the episode hit subscribe and drop a rating so others can find the show too. And if you're interested in continuing consulting, advisory work, or if you need a speaker for your next event, feel free to reach out. Just visit GregKilstrom.com that's G R E G K-I H L S T R O M.com the Agile brand is produced by Missing Link, a Latina owned, strategy driven, creatively fueled production co op. From ideation to creation, they craft human connections through intelligent and engaging and informative content. Until next time, stay curious and stay agile.
- [30:55]
Alan Ranger
The Agile Brand.