How TruGreen's AI Agents are Cutting Escalations by More Than 30%

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[00:00:26] And I was fortunate to sit down today with someone who is rethinking exactly what customer experience looks like in an industry that most people would never associate with advanced technology. His name's James Bowman. He is a Senior Director and Head of Experience Analytics and Insights at TruGreen, a business that is serving millions of customers across the US.

[00:00:55] And let's be honest, on the surface, lawn care might feel far removed from AI data platforms and real-time engagement. But as you're about to hear, that assumption doesn't hold up for long. Because in our conversation today, James will share how his team is managing more than 60 million customer touchpoints a year

[00:01:18] and tackling churn head-on by using AI agents in a way that delivers measurable business impact. So, I want to get into today what it really takes to build an omnichannel CX program, why data foundations matter far more than the AI itself, and the thoughtful implementation, how this is crucial in turning what many see as just another cost center into a growth engine. It is possible. It is happening.

[00:01:49] And we'll also explore the reality behind the AI hype, where it works, where it doesn't, and what business leaders need to understand before expecting those immediate results. So, if you've ever wondered what AI looks like when it's applied to real operational challenges rather than slide wear, this episode's for you. But enough from me. Let me beam your ears all the way to the show floor here in Seattle, where you can sit down with myself and James.

[00:02:18] Can you tell everyone listening a little about who you are and what you do? Yeah, great. Thanks for having me. I'm James Bauman. I lead customer experience and customer analytics and retention strategy for True Green, which is a big lawn care company. About two and a half million customers, close to two billion in revenue, and many, many millions of customer touch points. So, it's a pretty exciting CX world. One of the things I always try and do on the podcast, because I do a different episode every day,

[00:02:48] is get people thinking differently about areas that are impacted with technology that you don't automatically associate with tech. And I would imagine that lawns and True Green, you don't automatically think of technology. And we do hear that every business is a tech company. That has now revolved to, hey, every company is an AI company. So, tell me more about the role of technology at True Green. Yeah, we use a lot of technology in different areas.

[00:03:12] In my world, where we're thinking about engaging with customers and building relationships, we use technology to understand really what our customers want and need and how we can impact the moments that matter the most to them and where we can engage with them in a way that maybe in the past we haven't done in a contextual and personalized manner so that we can really build real trust

[00:03:42] and build real relationships with them to create lasting customers, really, who love us. That's the goal. And on that, I mean, you had that goal. So, from that goal, you had this omni-channel CX program. So, tell me about the thought process about launching that program and also the challenges you faced in managing it before we even bring tech and everything into the equation. Yeah.

[00:04:08] Yeah, so our CX program is really about how do we do what I said, which is understanding where customers need us and want us and how we engage with them in the right way, in the right moments, to build lasting relationships. So, the primary challenge was we have 60 million-plus customer touchpoints in a year. Yeah.

[00:04:37] And there's a lot of opportunity there to either get it right or potentially get it wrong. And we needed a way to understand where customers were potentially falling through the cracks and be able to take action on those customers, ideally proactively, but reactively when necessary to build those real relationships. So, that was really the challenge.

[00:05:03] We came from a world where we had high customer churn, and we talk about it as sort of the leaky bucket, where we're spending a lot of money to drive sales, to fill this leaky bucket where customers are not retaining as well as we think they should or as well as we want them to. And so, that was really the primary kind of burning platform

[00:05:30] for building this broad omni-channel CX program so we can listen to customers across all these touchpoints. We can understand what they're saying and what they mean by what they're saying, put behavior behind that to understand what's driving behavior and the outcomes associated with those things, and then really drive action around it to increase our retention significantly. That was the goal. So, you got that leaky bucket, that tremendous customer churn there.

[00:05:59] You want to get technology involved and have a partner with you. How did that relationship with Qualtrics begin? What's the story there? Yeah, we needed a partner who could plug into all the different parts of our business, digital, phone calls, customer service, as well as sales phone calls, and help us make sense of all of that. And so, Qualtrics seemed to be the company that could do that better than anyone else.

[00:06:27] They're obviously the leader in experience management, and having invented the category. I have also worked with Qualtrics in the past at previous companies, at Dish Network and UnitedHealth Group, building CX programs there and having some very good results with Qualtrics. So, I knew what we could do and brought them in. So, obviously, AI, AI agents is now all that everybody's talking about.

[00:06:55] So, tell me more about AI agents in your surveys and this closed-loop program and how you're using that to drive loyalty. Tell me a bit about the tech there. It feels incredibly exciting and almost that you're ahead of the game here for a company that you wouldn't associate with tech. It is really exciting. I get really excited about it. The way we are thinking about AI agents is where, first of all, are the moments that we could plug an AI agent in to respond to a customer

[00:07:23] right in the moment as that customer is thinking about whatever issue they're having and respond in a contextual fashion that can be really helpful for that customer in the moment. So, those are the moments we've looked for. So, our AI agents live right now within our check-in process, which for us is surveys. So, we're checking in with customers really easily and effortlessly across a bunch of different touch points around True Green.

[00:07:53] And that's where we've plugged the AI agent in because that is the moment where the customers are thinking about what's been happening. It's a bit – it is reactive in the fact that it's after the fact, but what we're finding is that we're able to take a lot of proactive actions even though these agents live in this feedback loop right now. And I think one of the things that is particularly exciting is when we talk about AI agents

[00:08:22] and AI and all the different technologies, people will say, yeah, that's great, but what's the ROI on this tech project? You know, and especially AI, there's been a lot of reports that there is no ROI. But I mean, looking at your story, one of the things that stood out immediately was a 30% cut in escalations. I mean, there's some tremendous ROI there, isn't there? Anything else you can shout about there, that measurable difference that you're now seeing as a part of this?

[00:08:47] We've always believed that following up with customers and closing the loop in that traditional closed-loop fashion is really, really important. And so we've done that for years. We've had a fairly large human agent team that responds to issues that are escalating. One of the things we found is that that team spends a lot of time writing emails and leaving voicemails or sending text messages into the ether.

[00:09:17] And customers may need help, but they don't always respond. They're maybe not always able to respond to those after the fact. And so that's, I think, the heart of where a lot of the ROI for us has come from because we're able to have these AI agents respond to issues and take action in the moment. And so the customer is already there with us. They're reading this response from the agent.

[00:09:44] They can see that we really care and are going to do something about it, the agent taking action. And that does a couple of things. It enables our, it frees up our human agent team, first of all, to really connect with customers that really want to connect with them or really need to connect with the human agent. So it makes them more effective because they can spend more of their time building relationships with customers, actually interacting with customers, actually building real trust.

[00:10:14] And it also gives them the context of what's been happening. So it makes them more efficient because the agent has been, the AI agent has been talking to the customer a little bit already. And that context we're able to give to the human agent when that customer really needs to talk to them. And the AI agent can take care of a lot of those issues that the human agent doesn't necessarily need to take care of. And it doesn't feel like a deflection, really.

[00:10:42] I think sometimes the traditional bot experience that many people have is, oh, it feels like that company is trying to just make it harder for me to talk. Or they're trying to reduce their costs somehow, and it doesn't feel like it's a value add to me. What I've found is that the AI agents we've built, because we've been very thoughtful about which flows we're plugging them into, feel like a value add. Because that agent knows the context of that customer. It knows what they've said in the survey.

[00:11:10] It has some history on when their previous service completed with us was, and things like that. It feels like a value add right there. It's educating you on the right things in the moment that you care about. It's telling you, in some cases, I'm going to take action on your behalf, and so you don't have to worry about it. Or we're going to check in with you again a couple of weeks from now. And at that point, we're going to plug you into a human agent if you are still having an issue.

[00:11:39] So I think it feels like a value add. So that's really where the ROI comes from. It can deal with a lot of, about a third of all the issues we're finding up front. Yeah. Without those ever having to go to a human agent. And the feedback is positive. Our satisfaction scores with our AI agent are high, above 50% already. And we're only just getting started, I think. And we've created all of that, about a third of our issues.

[00:12:09] We've created all that capacity for our human agent team now to spend more time reaching out to customers proactively. And so that, we're kind of shifting the flow of our incoming reactive service to being more proactive by plugging this agent in the middle. So that has hugely positive benefits for retention. When we measure retention after these agent interactions, it's about 8% increase.

[00:12:36] So for us, that is potentially tens of millions of dollars. So it could be a very, very large ROI. Yeah, it really is. And listening to your entire journey there from identifying the problem, getting the right partner in place, putting the technology in place, securing ROI. But I'm conscious we might make it sound incredibly easy. And there'll be a lot of people listening that are on a similar journey. And when we start talking about AI agents and complex technologies, it feels overwhelming.

[00:13:04] People start thinking of lengthy IT projects that can take forever. Tell me about that implementation, what that journey was like, and how long that took. Yeah, the building of the agent itself is fairly quick. Yeah. But the foundational elements that allowed us to move very quickly in building these agents took a bit longer. Which, by that I mean, really, the foundation for us was this omni-channel CX program that we had already built

[00:13:31] with many dozens of different data connections flowing to and from Qualtrics, to and from the different survey pieces, from the digital experience pieces, and all of those. So having that data foundation allowed us to give the context of all of that individual customer journeys to the AI agents to make these very relevant contextual conversations happen quickly.

[00:14:01] So for us, the implementation went very fast, but we needed this foundational element of having all of this data flowing for our CX program in the first place. Was your data already in a good state? Because a lot of companies come into the problem where fragmented silo data, etc. Do you have to go with cleaning exercise first? Yes, a bit. So our data engineering team is my closest partner, for sure, at True Green.

[00:14:28] If my colleagues are listening, I couldn't have done any of this without you. But yes, for sure, that is true. And I don't think you need to get it. I never felt like we needed to get the data in a place where it was perfect. You know, we took it use case by use case. So we planned what we wanted to do with CX program ahead of time. We cleaned the data and structured it and did all the transformations we needed to enable those use cases. And that's how I tackled it.

[00:14:59] And for anyone that wants to follow in your footsteps, were there any lessons learned, any challenges you had to overcome, things you would do differently, anything like that along the way? I think the tendency is for CX leaders to, or experienced leaders in general, I guess, to think about, I need to build these things and then convince people of the value kind of after the fact.

[00:15:24] And I think my biggest recommendation is bring your operating partners along for the ride. Let them be, they have an important voice. Let them be an important voice at the table from the very beginning in terms of planning these things. You will create a much more effective program in the long run if you do that. And you will have buy-in from the very beginning.

[00:15:50] And so treat those operating partners as really kind of your main partners at the table when you're planning and building these things. I'm also curious, you're someone that's lived this from start to finish and you're continuing to improve. When you scroll down your news feed, whether it be on LinkedIn, Reddit, or wherever you get your news, you've obviously seen a lot of myths and misconceptions around AI and around AI agents. Do you ever see anything like that that frustrates you? Any myths out there that you can lay to rest maybe?

[00:16:20] And any frustrations that you read a lot when hearing about AI agents? I think there's two ends to that spectrum. On one end of the spectrum, you have these beliefs that you can just turn on AI and it will solve all your problems. And I don't think that's really true. You have to be thoughtful about where you're plugging it in, what context especially you're giving it.

[00:16:43] The more and better context you give an AI agent, the better responses and more consistent responses you're going to get and all the rest of that. So on the one end, it's not this thing you can just flip the switch and it's going to be magical overnight. You have to give it the context and you have to be thoughtful about that.

[00:17:02] But on the other end, the belief that AI, you mentioned it, but AI agents don't really provide any value or it's all just AI slop is just not true.

[00:17:15] When you are thoughtful about the right moments to plug in an agent, to be contextual and relevant in the moment and you empower that agent to take the right actions and you understand what your customers need and want to be able to give it that information and tell it what to do or help train it in what to do. It becomes extremely relevant for customers. And we see that in our data. Customers say it's very helpful.

[00:17:42] Actually, surprisingly to me, way more often than I expected them to, they're saying, yes, this agent was helpful to me. And we see it then in the outcomes where customers are retaining much higher after they've had these interactions. And so I think that's the other myth that I would dispute is like these agents can be incredibly helpful and useful, create real meaningful connections with customers and real meaningful ROI for companies.

[00:18:12] And I also think one of the beautiful things about attending a conference like this is you're surrounded by like-minded souls, also chatting with people you wouldn't normally get a chance to talk with, also on similar journeys. What's your X4 experience been like so far? Who are you talking to? What are people talking about here? Yeah, a lot of conversations about AI agents and how to get value out of them.

[00:18:37] I think the conversation, this is my fifth X4, I think, and seeing the conversation shift from how to build, how to fund and build these traditional CX programs to what does the evolution of CX look like in the future?

[00:18:54] And especially around AI and how do we bring AI in and how do we plug AI into our CX programs as well as kind of, in my take, CX shifting and becoming really more of like a customer engagement engine for companies in a way that is really an integral part of every vertical in a business empowered by AI. That's my grand vision anyway. Like, that's what I see happening.

[00:19:24] I was going to say, because this is not your first rodeo. You've done five of these now. Yeah. All the conversations you've had, everything, if you put all that into one LLM, shall we say, put it all in there. What are you going to be thinking about on the way home? And you've already achieved so much. And you talk about the evolution of CX. What are you going to be taking away from this event and thinking about? Yeah. There's a lot of questions about, in my mind, how you get even more value out of AI agents.

[00:19:51] So I think that's one set of questions that I wake up in the night thinking about. The other one is, and this is another myth, I guess, but around AI is just going to take all the human jobs. Like, the more AI we use, the less human jobs, and that's a bad thing. I don't think that that's true.

[00:20:14] I think, and what we're seeing at True Green is that the AI agents can actually help the human agents do their jobs better and also free them from some of these more non-value-add tasks, meaning, like, non-engaging with customer tasks.

[00:20:34] I want my human agents building real relationships with my customers, and I think the more we can use AI to help them do that, the more happy they're going to be because they don't want to spend all their days writing emails that just go into the ether either. They want to be building relationships and helping customers. And so the more we can help them do that, the better their jobs are going to be.

[00:20:57] So I actually believe AI can help us be more efficient as well as create better experiences for our employees because it's going to help them do more of what they really love doing. So how do I do more of that, I guess, is the answer. That's the other thing that keeps me up at night. I think that is a powerful message to end on. But before I let you go, I will add a link to your LinkedIn page. Anyone wants to connect with you there? Is there anywhere else you'd like me to point anyone listening wants to find out more about True Green, the journey you've been on, et cetera?

[00:21:27] I think there will be a lot of Qualtrics resources. There's going to be some media resources and other interviews I've done with Qualtrics talking about that. You can certainly look at Ben Dunham, who's our CFO, is going to be speaking on the main stage tomorrow morning. And so I think there'll be some resources around that. You can find his presentation most likely. And I'd love to connect with anybody out there who wants to connect and talk more about this. I'd love to collaborate.

[00:21:55] I'd love to talk about how you're using it, bounce ideas off. Please reach out. And I'll add links to everything to the show notes. So wherever anyone's listening in the world, take a look. There'll be a useful link section. I'll add links to everything there and everything that you're talking about here. But more than anything, thank you for taking the time to sit down with me today. Thank you very much. I really appreciate it, Neil. I think one of the things that stood out to me in this conversation today is there was no talk of, hey, we just flip a switch and transform a business overnight.

[00:22:24] Instead, it was much more about identifying the right moments, building the right data foundation, and then applying AI in a way that actually helps both the customer and the employee at the same time. So a big thank you to James for sharing how AI agents are already reducing escalations, improving retention, and freeing up human teams to focus on what they can do best, building relationships.

[00:22:53] And I think it's this shift from reactive service to proactive engagement that feels like a real turning point that many organisations are still trying to figure out. So if you want to learn more about what James and his team at True Green are doing, I'll include all the links in the show notes so you can explore a little further and connect with him directly. But as always, I'd love to hear your thoughts. Are AI agents delivering real value in your organisation yet?

[00:23:22] Or are you still trying to separate the signal from the noise? And will you be doing anything differently having listened to today's conversation? As always, pop by Tech Talks Network. There are 4,000 interviews over there. Many different ways that you can work with me, contact me, and hopefully learn from more insights like the one shared today. But that's it for today. We're out of time.