#814: United Rentals' Alyse Fuller on driving real impact without being overwhelmed by data

Summary

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Podcast Summary: The Agile Brand with Greg Kihlström®

Episode #814: United Rentals' Alyse Fuller on Driving Real Impact Without Being Overwhelmed by Data

Date: February 16, 2026
Guest: Alyse Fuller, Customer Experience Program Manager at United Rentals
Location: Live from Medallia Experience 2026, Las Vegas

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Overview

In this episode, Greg Kihlström welcomes Alyse Fuller from United Rentals to discuss how CX teams can leverage AI, process change, and data democratization to drive tangible business results—especially within a massive organization and with an overwhelming stream of data. Using United Rentals’ journey as a backdrop, the conversation explores moving from “score-chasing” (e.g., NPS) to genuine operational problem-solving. Alyse shares practical insights into the shift towards root cause analysis, integration of frontline and customer voices, and adaptation of generative AI tools—all with a lean team.

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Key Discussion Points & Insights

1. Evolving From Score-Chasing to Root Cause Analysis

• High and Stable NPS Can Mask Problems
  Alyse explains that United Rentals’ NPS scores were consistently high, giving an illusion of success. But this stability can conceal underlying issues.
  • “It makes it difficult to really pressure test your insights engine... Is it possible there’s something lurking under the surface that I haven’t been measuring all this time?” (Alyse, 03:24)
• Catalyst for Change
  A notable NPS pattern shift in 2023 provided opportunity—and urgency—to challenge assumptions and dig deeper.

2. Bridging the Gap Between Customer and Internal Teams

• Frontline “Huddles” as a Data Source
  Alyse underscores the importance of synthesizing feedback from both customers (external) and frontline employees (internal), since customers can only describe symptoms—not backend delivery issues.
  • “Customers can talk very well about the symptoms that they’re experiencing... But they don’t know all of the logistics. So we really had to look at or get input from people who are already behind the curtain.” (Alyse, 06:18)
• Operational vs. Customer Perspective
  She highlights the need to connect the ‘why’ for NPS back to operational levers for improvement—getting past surface-level analytics.

3. Practical Rollout of AI Tools (“Utility Over Novelty”)

• Ease of Use and Seamless Integration
  United Rentals launched Medallia’s AI-powered Smart Response tool without formal hype or training—focusing on making it available and easy to use. This encouraged adoption and minimized frontline anxiety.
  • “If we make too much fanfare and, you know, hype up the AI factor that can be off-putting to some people when really they could benefit from the tool. So let’s just make the tool available and see what happens from there.” (Alyse, 07:48)
  • “If it’s easy and it works, it will be used.” (Alyse, 09:25)
• Trust and Reliability are Key for AI
  Employees were more willing to adopt AI when it was reliable, integrated into routine tasks, and required minimal change management.

4. Demonstrable Impact: Speed, Access, and Empowerment

• Significant Time Savings
  Frontline managers closed customer alerts six hours faster on average, thanks to automated routing and AI-generated personalized responses.
  • “The customer’s feedback gets straight to the right person immediately... And with Smart Reply, it’s such a great starting point compared to previously using just canned responses...” (Alyse, 12:52)
  • “Our managers... are not having to spend so much time wordsmithing and, and really painstakingly crafting.” (Alyse, 13:56)
• Data Democratization
  AI-generated, natural language insights are accessible across the organization—from senior executives to frontline managers—without the need for expertise in data analysis.
  • “It makes it all natural language... Looking at an Insights report now, it says customers want us to focus on these things. Our teams are talking about these things. It’s all in language that we can just very easily read.” (Alyse, 14:39)
• Real-time, Self-service Insights
  The shift means team members don’t have to wait for periodic reports—they can access and interpret insights on demand.
  • “Now, because the insights are easier to consume, easier to access, more democratized, there’s more enablement... You’re not relying on a report that came to you three weeks ago.” (Alyse, 17:09)

5. Changing Role of the CX Leader

• Move from Data Gathering to Action Planning
  By automating much of the analyst workload, Alyse can focus on action—facilitating cross-team problem solving and goal-setting.
  • “That time spent on the analyst side is what’s been greatly reduced. I can generate these reports... and then spend my time more on discussing what we’re seeing...” (Alyse, 15:51)

6. Conference Takeaways and Staying Agile

• Conference Highlights
  Excitement around new platform features for documenting actions and outcomes, enhancing accountability, and improving continuous improvement loops.
• Personal Agility Habits
  Alyse purposely blocks time in her schedule to review new industry research and ensures ongoing learning.
  • “I build time into my calendar to go hunt for that information. I think making the time and having it actually pre planned means you have that space...” (Alyse, 18:53)

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Notable Quotes & Timestamps

• On the Dangers of High NPS:
  “When your scores have been very good... It makes it difficult to really pressure test your insights engine... Is it possible there’s something lurking under the surface that I haven’t been measuring all this time?” (Alyse, 03:24)
• On the Need for Employee Insights:
  “So we really had to look at or get input from people who are already behind the curtain... They know all the details of all of our systems and what it really takes to deliver that kind of experience.” (Alyse, 06:18)
• On AI Adoption Philosophy:
  “If it’s easy and it works, it will be used.” (Alyse, 09:25)
• On Impact of AI-Powered Platforms:
  “Customers’ feedback gets straight to the right person immediately and then they can respond. With Smart Reply, it’s such a great starting point... it’s so fast and efficient and we’re getting to that highly personalized reaction very quickly.” (Alyse, 12:52)
• On Data Democratization:
  “It makes it all natural language... Looking at an Insights report now, it says customers want us to focus on these things, Our teams are talking about these things. It’s all in language that we can just very easily read it, understand. It doesn’t require as much interpretation or context...” (Alyse, 14:39)
• On Shifting CX Roles:
  “That time spent on the analyst side is what’s been greatly reduced... and then spend my time more on discussing what we’re seeing here, gathering other context...” (Alyse, 15:51)
• On Blocking Time for Learning:
  “I build time into my calendar to go hunt for that information... you have to block it and make sure that you’re kind of getting out for that.” (Alyse, 18:53)

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Timestamps for Important Segments

• Intro to Topic and Guest: 00:49–02:37
• High NPS Scores—Danger & Lessons: 03:24–04:34
• Strategic Challenges Moving Beyond the Score: 04:34–05:53
• Synthesizing Employee and Customer Voices: 06:18–07:26
• AI Rollout Philosophy—Utility Over Novelty: 07:26–09:49
• Measuring Impact, Speed, and Data Democratization: 12:26–17:09
• Changing Role of the CX Leader: 15:31–17:09
• Conference Insights and Staying Agile: 18:10–18:53

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Tone & Language

The discussion is pragmatic, optimistic, and refreshingly candid—focused on real-world applications over technological hype. Alyse’s tone is down-to-earth and strategic; Greg is facilitative and insightful, keeping the conversation practical yet future-facing.

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For CX and marketing leaders, this episode delivers actionable strategies to drive impact, build agility, and harness AI without losing focus or becoming data-overwhelmed.

Transcript

[A]

The agile brand.

[B]

Welcome to Season eight of the Agile Brand Podcast. This season we're going all in on Expert Mode, MarTech, AI and Customer Experience, talking with the people and platforms behind the brands you know and love. 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 find us as well. And make sure you check out our sponsor, Tech Systems, an industry leader in full stack technology services, Talent Services and Real world application. For more information, go to teksystems.com now let's dive in.

[C]

What if one of your most valuable CX analysts isn't even a person? Agility requires not just collecting data, but closing the gap between insight and action at scale. This means empowering every level of the organization from the frontline to the C Suite with the right information at the right time to make smarter, faster decisions. Today we're going to talk about moving beyond the score. We'll explore how generative AI is shifting the discipline of customer experience from a reactive score chasing exercise to a proactive problem solving engineering.

[B]

We're going to get practical about how.

[C]

A very lean team at a massive organization can leverage these tools to drive real business impact, especially when faced with an overwhelming amount of data. We're here in Las Vegas at Medallia Experience 2026 and to help me discuss this topic, I'd like to welcome Elise Fuller, Customer Experience Program Manager at United Rentals. Elise, welcome to the show.

[A]

Thank you very much. Happy to be here.

[C]

Yeah, Looking forward to talking about this with you. Before we dive in though, why don't you give a little background on yourself and your role at United Rentals?

[A]

Sure. So I am our Customer Experience Program manage working with United Rentals. I've been there. I think this is my 19th year now. So prior to this I was in our contact center environment and then we decided to make our CX efforts a little more formal and get a proper CX program in place. And that was eight or nine years ago now. So it's been a journey developing it over time.

[C]

Definitely. And for those that are not as familiar with what United Rentals does, can you give us a little background on what you do?

[A]

Yes, absolutely. So United Rentals is an international construction equipment rental company. We have some other lines of business as well. We do things like safety training for OSHA compliance or equipment operation. We sell new and used equipment. So we've got a few Things going on, but bulk of the business is equipment rental.

[C]

Great, great. So, yeah, let's, let's start at the strategic level here and want to go back to what I teed up in the intro and really just this evolution from chasing good scores. I mean, numbers matter, but you know, simply chasing a score, you know, not, not so much all the evolving from that to root cause analysis. And so your, your case study mentions a shift in NPS in 2023 that really acted as a catalyst here. So before that you had high scores in the upper 70s. Can you talk about the danger of a high, high score sounds good, right? But you know, can you talk about the, the danger of a high and stable score and how it can maybe mask underlying issues that only become visible when that score finally changes?

[A]

Yeah, absolutely. So we had, I mean, it was such a success story. We implemented our program. We're measuring nps, we're watching our scores go up over time, which is exactly what you want to see. We'd have periods of consistency, a little bit of cycles here and there, but they were explainable. We knew what was causing them or what they were related to. Not always even something going wrong, just part of the business when it changed the pattern that we were seeing. The challenge is when your scores have been very good, you're working with a really high performing team for a really long time. There had been such consistency there. It makes it difficult to really pressure test your insights engine. You need some variety and you need some new signals and things to really see. Will all these rules and all these conditions hold up no matter what the circumstances are, or is it possible there's something lurking under the surface that I haven't been measuring all this time? So being able to get a little bit of variety was actually a really interesting moment and a really compelling moment because there was a lot of attention on it. And it gave me that opportunity to really pressure test and make sure we were measuring all the right things and had been for a long time.

[C]

Yeah. And so as a small team in a very large organization, or a team of one, as the case may be, as you just said, you're facing a lot of data to need to pour through. What was the biggest strategic challenge that you faced in trying to move the organization's focus from just that NPS number to the why behind it?

[A]

Yeah. So I think the, you know, we'd understood the why. I mean, when we rolled out Medallia, we spent a lot of time on the change management piece and really training, making sure everybody knew what we're measuring why. We're measuring it, why it matters. So we had a pretty good intrinsic understanding of that. But the underlying why of the NPS score itself, again, we had this kind of catalyzing moment where we said, well, why? And when we look at our analytics, we're trying to do a five why analysis. Right. And we can only get so deep with the customer side, and then the whys start becoming more operational in nature. And that's when I realized we. We might benefit from some additional information to help get to that level of the whys, that we could be more strategic and how. We're thinking about different lever. Levers that we can pull that would have the most impact. I think we knew what levers existed, but being able to map that back to an NPS impact was. Was really helpful. Yeah. Yeah.

[C]

So let's get a little more tactical here and talk about democratizing insights with AI. So a key part of your solution involved synthesizing notes from frontline team huddles. How did you bridge the gap between that internal employee voice and the external customer feedback? And why was that connection so critical for identifying some of those real root causes?

[A]

Yeah, so because our, again, our voice of customer is coming direct from our customers, they're standing on one side of the. I call it the rental counter in our locations. Right. They shouldn't know everything that goes on behind the scenes to deliver them a great experience. They shouldn't know what metrics we're measuring or, you know, all the logistics that go into it. That's where we're playing superhero in the background to make all of those things happen. So the customers can talk very well about the symptoms that they're experiencing for better or worse. You know, usually for better. But they thank goodness. But they don't know all of the logistics. So we really had to look at or get input from people who are already behind the curtain. And they know all the details of all of our systems and what it really takes to deliver that kind of experience that we're trying to make sure we do.

[C]

Yeah. It's like you never want your customers to have to understand your org chart.

[A]

Or all of them.

[C]

Yeah, exactly.

[A]

Or that, you know, just different operational teams and how we navigate together. Right. Like from sales to a delivery driver to a service technician. They all have very different roles and have to be well coordinated.

[C]

Yeah, yeah. So you made a conscious decision to launch Medallia's AI powered smart response tool with no formal training, just relying kind of on its intuitive value. Can you talk about that utility over novelty approach to rolling out AI tools and how it helped you gain buy in and maybe, you know, minimize anxiety on the front line.

[A]

Yeah, sure. So we got and call it a happy accident. I ended up collecting a lot of commentary from employees internally about how they were thinking about AI usage in our existing tools. I wasn't trying to talk about that, but it was an interesting topic and I had the information and then even comparing that with external research in general, public attitudes toward AI. And there's a range of motivations, usually even role specific motivations about what would lead to AI adoption. But a big resounding theme is it just has to work, work. It doesn't matter what kind of technology it is, but it's got to be reliable, it's got to be consistent, it's got to make sure that I don't miss an important step or give inaccurate information. So that trustworthiness was huge. But the idea that, you know, it just needs to work, it's supposed to be easy, it's supposed to be integrated into what we're already doing anyway and make things easier and more efficient. So when thinking about smart Response is the first one we rolled out. It's already embedded in a process that we use all the time. It's an easy button. It should not require a big announcement or too much fanfare, which to your point about anxieties, if we make too much fanfare and you know, hype up the AI factor that can be off putting to some people when really they could benefit from the tool. So let's just make the tool available and see what happens from there. And the natural adoption of that has been a really beautiful upward line just for making it available and not having to train.

[C]

Yeah, yeah, it's a, it's a counterintuitive principle, but I agree.

[A]

Yeah, if it's easy and it works, it will be used.

[B]

Yeah.

[A]

I think in general across AI functions, it makes sense to have some training around things like, you know, we would never put customer PII into an unsecure chatgpt or something. Right. So it makes sense to have some communication on a broader scale. But for individual features, we don't always need to hype it.

[B]

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[C]

So let's talk about measuring the impact and even redefining speed and scale so you saw a significant and measurable impact. As we've talked About a little bit already. Things like Frontline managers closing alerts six hours faster. In your view, how does investing in the right data collection and measurement platforms enable customers to get those faster resolutions and really feel heard.

[A]

Yeah, so I mean the great thing with Smart Reply and Medallia, right, we've got Medallia itself is a really powerful tool with a lot of really great features. So there's efficiency in first of all, getting that feedback to the right person to take action on it and having even a complex setup for who is the right person. We can automate all of that. So the customer's feedback gets straight to the right person immediately and then they can respond. And with Smart Reply, it's such a great starting point compared to previously using just canned responses that had to start off kind of generic so they could apply to anything. Even when we're in a hurry, we're able to let the AI do some of that foundational thinking first. And what is a good response for what this customer has actually just said? And we can tweak it and fine tune it before we hit send. And it's, it's so fast and efficient and we're getting to that highly personalized reaction very quickly.

[C]

Yeah, yeah. So I mean the, the, the repetitive kind of rote stuff is, is you get to take it a step further instead of that taking up the time. Right, right.

[A]

Yeah. And feedback from our managers has been really positive that it is a much better starting point. And yeah, they're not having to spend so much time wordsmithing and, and really painstakingly crafting. What do I think is the ex.

[C]

Yeah, and so data certainly is a key part here. We've touched on this a little bit already, but the efforts that you undertook really democratized data access within the org. How does having a measurement platform that empowers senior leaders with AI driven intelligence summaries as well as frontline managers with those actionable alerts influence how you talk about CX within United Rentals?

[A]

It makes it all natural language, right. It's whether it's the voice of customer, which sounds like the customer and the insight summary, it's in words that our customers use. Makes sense. The internal pieces that we have going, those are in our own lingo. So even things like abbreviations for metrics or process names, we don't have to have a definition for everything, although it helps to define some stuff with LLMs, but it does such a good job of organizing those things in our own terms. So looking at an Insights report now, it says customers want us to focus on these things, Our teams are talking about these things. It's all in language that we can just very easily read it, understand. It doesn't require as much interpretation or context to really get to that place where this is actionable information.

[C]

Yeah, well, and you've said AI's greatest value is shortening that distance between listening and taking action. Now that you've automated the proving of the problem, how has your role as a CX leader changed? You know, where are you able to focus at least some of that energy, if not a lot more of that energy?

[A]

It's getting repurposed into more of the action planning piece where as we're maturing here, my role, you know, it still has the other elements, team of one. So I'm still the administrator and an analyst and a trainer and, you know, all of that still exists, but that time spent on the analyst side is what's been greatly reduced. I can generate these reports, pop them into a PowerPoint or whatever, and then spend my time more on discussing what we're seeing here, gathering other context that maybe isn't included in Medallia, bringing more, just a more robust nature to what that conversation can sound like, and then maybe offering almost a kind of consultative approach with the folks in the rest of the organization, those leadership teams, to try to decide, you know, what, what can we do with this now? What would you like to try to do with this now? And maybe create some realistic goals based on that.

[C]

Yeah, well, and I mean, it also seems back to the data democratization piece, because everyone is able to see, you know, it's maybe a different view, but same data and, and same outcomes and insights, you know, instead of this one person over here talking about, hey, the score is XYZ now everybody can be speaking the same language to your exact point.

[A]

Exactly. Yep. And it's definitely, you know, and I would say a year ago, if somebody wanted a real insights report, they're waiting for a push report that I've automated to come to their inbox once a month or once a quarter, they can't just on the fly. I've got a meeting coming up and I'd like to be able to speak to this. And now, because the insights are easier to consume, easier to access, more democratized, there's more enablement that goes into, can you get to this on the fly in the moments where you need it and you're not relying on a report that came to you three weeks ago or whatever, you know, so they don't have to wait for me to help with that. They can go get it if they want to. I'm happy to help still, of course, but.

[C]

But it's nice to have.

[A]

It's nice to have that real time. Yeah, you can do it if you want to. And it's easy enough that they don't have to be an analyst themselves in CX data in order to get it and understand it.

[C]

Yeah. Yeah, that's powerful. Well, Elise, thanks so much for joining today. A couple last questions as we wrap up here. You know, we're here at Medallia Experience. What's been a highlight so far? I know we're early in the conference.

[A]

Still, but so the opening keynotes is always so exciting in the grand opening where we get to see a little bit of what the roadmap looks like for this year. Speaking of action planning, I'm looking forward to some of the new features that we have coming out here around kind of integrating that documentation side of. Okay, we're having these important conversations. We're talking about actions we can take now. Maybe we can start logging those and seeing what the outcomes are over time. So that sounds like a really cool feature. I'm looking forward to that. Yeah, those opening speeches are always so exciting.

[C]

Yeah, definitely. Well, last question for you before we wrap up here. What do you do to stay agile in your role and how do you find a way to do it consistently?

[A]

I read a lot. I'm constantly looking for the latest industry benchmarking reports or news from Medallia, news from Forester Gardner. You know, as much as I can, I build time into my calendar to go hunt for that information. I think making the time and having it actually pre planned means you have that, that space too. Like it's not something I do when I have time because whoever has time, you have to block it and make sure that you're kind of getting out for that. Or I do anyways. I have to make sure I'm going to look for it proactively.

[C]

Yeah.

[B]

Love it.

[A]

Thank you very much. I appreciate you having me.

[C]

Yeah, thank you. Well, again I'd like to thank Elise Fuller, Customer Experience Program Manager at United Rentals, for joining the show. You can learn more about Elyse United Rentals and Medallion by following the links in the show notes.

[B]

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 [e-mail] and thanks again for listening to the Agile Brand podcast. If you liked the episode, hit subscribe and drop a rating so others can find the show too. And if you're interested in 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, engaging and informative content. Until next time, stay curious and stay agile.

[A]

The Agile Brand.