Customer Success Playbook S3 E24 - Martin Vogel - AI Predictive Insights

Summary: Welcome to the final installment of our three-part series with Martin Vogel on the Customer Success Playbook Podcast! This week, we dive into the transformative role AI plays in global support frameworks—particularly in the hardware plus SaaS world. AI isn't just a buzzword; it's changing the way businesses handle predictive insights, proactive service, and internal efficiencies. From making sense of massive data streams to optimizing processes and improving coaching strategies, AI is proving to be a game-changer. If you've ever wondered how to harness AI for better customer outcomes, this episode is for you.

Detailed Analysis: In this insightful conversation, Martin Vogel, alongside hosts Roman Trebon and Kevin Metzger, explores how AI is helping companies cut through the noise of massive hardware data and streamline support operations. AI-driven analytics offer a clearer picture of device performance, support tickets, and user behaviors, allowing businesses to shift from reactive to proactive service models.

Kevin highlights how AI can structure knowledge bases, transforming recorded conversations into actionable insights—eliminating the need for manual documentation. The discussion also delves into AI's ability to free up developer time, ensuring that valuable resources are allocated toward customer-centric improvements rather than repetitive tasks. Meanwhile, Roman emphasizes AI’s potential in coaching and training, making feedback loops more efficient and tailored.

As AI continues to evolve, its role in customer success becomes more indispensable. Whether it's reducing inefficiencies, automating routine tasks, or enhancing learning, AI is redefining the way businesses engage with customers. Don’t miss this deep dive into the intersection of AI, hardware, and customer success.

Now you can interact with us directly by leaving a voice message at https://www.speakpipe.com/CustomerSuccessPlaybook

Please Like, Comment, Share and Subscribe.

You can also find the CS Playbook Podcast:
YouTube - @CustomerSuccessPlaybookPodcast
Twitter - @CS_Playbook

You can find Kevin at:
Metzgerbusiness.com - Kevin's person web site
Kevin Metzger on Linked In.

You can find Roman at:
Roman Trebon on Linked In.

Transcript

Roman Trebon: 0:10

Welcome back to the customer success playbook podcast. I'm your host, Roman Trebon joined with me as always is my cohost, Kevin Metzger. Kevin, it's Friday and we're wrapping up our three part series with Martin Vogel. It's your favorite topic. It's AI Friday. Are you ready to go? AI

Kevin Metzger: 0:29

Friday. All right. So yeah, we've been discussing how to set up a robust global support framework and the tension between growth and retention. Today, AI fits into the mix, especially in the hardware plus SaaS setting. Martin, let's talk about AI. With so much data coming from devices, usage patterns, and support tickets, how do you see AI playing a role in delivering predictive insights and proactive service?

Martin Vogel: 0:57

It's a good question. I'm really excited about the, what AI can do in those kinds of settings, right? And you mentioned it, it's the, the massive data is provided by hardware devices, particularly sophisticated hardware devices. And we, we work with ATM type of Equipment, right? Uh, just to give you an idea. So they're really, really chatty. So part of the challenge that we experienced in that context was that it was difficult to see The forest, because of all the trees, that was just so much data at times that if you need to dig into something, it was very, very easy to get lost and sidetracked. And AI, of course, is able to look at that data in a very efficient way and make sense of it. So that is one of the things, of course. And the other thing is more on the, uh, support side, right? Having different people, even here in the U S only, right? If you have five people handling one issue, chances that your notes end up having five different stories is relatively high, right? So you have five different stories, half of them probably wrong. hallucination on the human side and AI. Again, helps to normalize that input and all of that then creates the ability to have better data to analyze, uh, as you move forward, if that makes sense. Now go ahead, Kev. I know, I know

Roman Trebon: 2:33

you're, you're, you're,

Martin Vogel: 2:34

you're ready

Roman Trebon: 2:35

to go again.

Kevin Metzger: 2:36

Yeah, no, I think it does. Uh, it does make a lot of sense. And I. One of the things I was thinking about when we were talking on Wednesday was how we were talking about process and definition of process and being able to really capture knowledge based information and the process of recording conversations and being able to turn that into knowledge articles, basically, um, Is such a, such a game changer in building your process out and really doing lessons learned and basically enabling a structured process by leveraging AI to really start taking your, your learnings and. Building, really using, it's interesting because you can use AI on the front end and then on the back end. So you're on the front end, you're using it for the recording, you're using it to analyze the information coming in, you're using it to analyze the equipment and the data from the equipment. But then on the back end, you can also come in and apply AI and say, okay, how do I optimize processes based off of this? This is what we're doing today. Does it make sense and feed it back in and read, read, optimize your processes on the back end. And that's even before you get it into agents that are doing this work for you. That's that's what you can do today without it's such an interesting thing. Have you seen much success on the process side of it? You know, to

Martin Vogel: 4:03

be honest, I've actually not had the chance to really apply that in depth, but, uh, I'm thinking a lot about it. I think particularly what you're saying now, and I think there was Google that just released a new product, right? Where you take a YouTube video and essentially converts that into structure and there's different tools like that. AI does such a great job in, or those language models, right? To condense information and reframe it, right? The You now have the ability to not have a technical writer that brings it down, but you can do a tutorial, a video tutorial and turn that into meaningful written based articles later on that can be used by all those tools very, very quickly. And that is tremendous, but I think there is a whole other. layer there, right? Going back to the hardware challenge that we've discussed. We always in the company wanted to utilize AI to analyze data. But one of the challenges, of course, was to find the developer time to really dedicate time on that piece. And it always washed down in favor of Customer requested features and so on. But now the exciting turn here is that developer time is less constrained because the developer now has tools at their hands to efficiently develop code. quicker, right? That frees up time. And with that, of course, there is an opportunity now to go beyond certain areas that before just weren't, couldn't be touched because, uh, they were reprioritized or washed down. So it's a great opportunity on the AI end.

Roman Trebon: 5:59

Yeah, I think Martin, you hit on it and the ability, well, I think one thing that AI does is provides time back, right? And things that were super time intensive now don't take as much time, which frees up time for other stuff. And you've talked about training. There's just so many great AI tools that you can, you can do a custom training for, you can do a, uh, a self service training using some AI tools that would have taken teams days, weeks, now you can do it in, in, in a fraction of that time. The documentation, right? Like, you know, spit out documentation based off of what we're talking about, these knowledge bases. Boom. You know, again, that would take a lot of time. Now, that time is very condensed. I love it from a coaching and training perspective as well, to listen to an hour call, like a support call. You've, you talked about, I think, on Monday and Wednesday debriefing and that continuous education. Well, that takes time. Now with AI, it's like, Hey, give me the, you know, where, where in this call or their coaching tips, what should I be focusing on? So then I can go right to those sections, listen, you know, apply my, my thoughts around it. And then I can condense a coaching session again, before our listening, me, comprehending it, me, outlining the coaching. Now that is way condensed and now you can, you know, you can do more coaching, deeper cat, uh, coaching, et cetera. So again, that's where I think this is super exciting because we're, we're just scratching the surface of these efficiencies and we're applying some. And some of us are on different journeys with our, with, with how we're using AI, but it's continuously evolving and it's super exciting. Anything else for Martin on AI Friday before we, um, wrap this series for the week.

Kevin Metzger: 7:38

I think we can wrap for the week, Martin. Thank you so much. It was really a delight to talk with you. You know, you can find Martin on LinkedIn. If you found these episodes helpful, make sure to subscribe and share them with your team. We'll be back next week with more tips and strategies for your customer success playbook. Until then, Roman, keep on playing. I get to say it. Look at that.