The Customer Success Playbook · 2025-08-29 · 10 min
Key moments - from our scoring
Substance score
35 / 100
Five dimensions, 20 points each
Adrian Swinscoe wraps up a three-part series on Customer Success Playbook by tackling the central challenge of AI adoption: preventing it from becoming another technology fad. With 60+ new AI tools flooding the market quarterly, companies struggle to deploy these tools meaningfully while preserving human-centered customer experience. Swinscoe argues the industry has it backwards - organizations typically buy technology first and search for applications, when they should start with desired customer experience and work backward to identify necessary tools and data. He illustrates this with an e-commerce company that used AI automation to handle routine inquiries, then reinvested freed-up agent capacity into offering phone support for the first time rather than cutting headcount - directly opposing the industry's efficiency-at-all-costs narrative. The episode also surfaces two overlooked ethical concerns: the massive energy consumption powering generative AI models and data centers, and the exploitative labor practices in data annotation, much of it located in the global south. Essential listening for CS leaders, product teams, and operations executives deciding how to allocate AI budgets without losing customer-centric strategy or ignoring systemic externalities.
Not necessarily. Swinscoe cites an e-commerce company that chose to reinvest freed capacity into offering phone support for the first time, aligning with their customer-first brand values rather than pursuing headcount reduction. The strategic choice depends on your company's vision and values, not just operational efficiency metrics.
Start by defining the customer experience you want to create and your strategic vision, then work backward to identify which tools and data you need. Avoid buying technology first and searching for applications, as this leads to 'tech for tech's sake' and unclear ROI tied to business objectives.
Two issues deserve more attention: the massive energy consumption required to power generative AI models and data centers (some companies are building nuclear plants to support them), and the underpaid data annotation labor, much of it in the global south, that enables these systems to function.
AI should give companies choice - the ability to decide how to deploy freed-up capacity. Rather than forcing a single outcome like cost reduction, proper AI implementation creates flexibility for strategic reinvestment in customer relationships and service channels.
Our reviewer’s read on each dimension, with quotes from the episode.
A few modestly interesting observations emerge - flipping the tech-first approach, using AI savings to expand phone support rather than cut headcount, and flagging data annotation labor - but much of the episode is filler, repetitive hedging, and platitudes like 'be deliberate about what we're going to do.' Useful ideas are buried in low signal-to-noise content across a very short runtime.
we're working from a tech data and experience kind of perspective where actually we should work on the flip is like start from an experience, data and sort of tech
they've chosen to turn the phones on. Because they, they've never been able to do that before. 'cause they didn't have the bandwidth to do it.
The 'experience-first, then data, then tech' reframe and the counterintuitive phone-channel example are mildly fresh takes, but 'don't buy tech for tech's sake' and 'start with your vision' are deeply recycled CX consulting tropes. The data annotation and energy consumption angles are the most original moments but are barely developed.
we're working from a tech data and experience kind of perspective where actually we should work on the flip
that's not part of the normal narrative that's going around the, around the industry
Adrian Swinscoe is a legitimate CX author and podcaster with genuine domain knowledge, but he presents as a consultant-commentator rather than an operator who has implemented AI at scale inside a company. His example company is unnamed and secondhand, suggesting practitioner proximity is indirect.
I'm the me on the Punk CX podcast, do that and hit links or subscribe or buy a book or whatever it might be
one of the best examples I've heard of a company that is leveraging some of these tools was, I think they're an e-commerce company
The sole company example is unnamed, its metrics are absent, and the claim is hedged with 'I think they're an e-commerce company.' Deep Seek is the only named entity beyond the Gartner reference the host introduces. No numbers, timelines, or dollar figures appear in Adrian's answers.
I think they're an e-commerce company and they've used AI and automation to, to free up a lot of their agents from doing some of the simpler tasks
people are talking about building nuclear plants to power some of these data, these data centers
The host bundles three separate questions into a single rambling turn, then responds to every answer with 'I love it' or 'brilliant stuff' without a single substantive follow-up or challenge. No probing on which specific tools, what ROI thresholds, or how the ethics points concretely affect purchasing decisions.
how, how do companies ensure these tools feel human instead of generic? How do they make sure they get operational efficiency without losing that, that, that, that customer experience? And, and how can businesses, I mean, I know I'm asking you three questions in one here
I love it. That's completely, uh, I, I love that example because that's the opposite of what I typically hear
Computed from the transcript - who did the talking, and the words that came up most.
Send us Fan Mail Dive into the rapidly evolving world of AI with Adrian Swinscoe as we wrap up our three-part series on how to keep AI from becoming just another buzzword. This episode unpacks the flood of AI tools hitting the market, the challenge of maintaining a human touch in customer experience, and strategies to avoid the dreaded “tech for tech’s sake” trap. Adrian shares a fresh perspective on leveraging AI for operational efficiency - not by cutting costs but by unlocking capacity to deepen customer relationships. We also touch on often-overlooked ethical considerations, from AI’s environmental impact to the human labor hidden behind the scenes.In this episode of the customer success playbook, Adrian Swinscoe expertly navigates the AI hype cycle, reminding us that technology should never lead the charge without a clear strategy rooted in customer experience goals. Adrian advocates flipping the traditional tech-first approach on its head - start with the experience you want to create, then work backward to the data and technology needed.
Transcribed and scored by The B2B Podcast Index.
Customer success. Hi everyone. Welcome back to the Customer Success Playbook podcast. I'm your host, Roman Reon.
Kevin Metzker, my cohost, still not with us. I don't know where he is at, uh, where he is at. We'll, we'll, uh, we'll, we'll, we have a word on the street. We're trying to find him, but we are wrapping up our, our three part series with Adrian Skoe, and today we're gonna explore how to keep AI from becoming just another buzzword, right?
We've hear so much of a ai, but that is not just become a buzzword. So. Adrian, uh, let's start here. AI tools are flooding the market.
I just met with a, um, one of our partners yesterday, they were talking about the Gartner Magic Quadrant box, and they said there were like 60 some new AI tools in this one box. And they're, you know, just, it, it's, it's overwhelming, right? Um, but as these tools flood the market, you know, self-service and personalization are, are, are to the forefront. But how, how do companies ensure these tools feel human instead of generic?
How do they make sure they get operational efficiency without losing that, that, that, that customer experience? And, and how can businesses, I mean, I know I'm asking you three questions in one here, but how do you avoid tech for, for tech's. Adrian Swinscoe: So I think the last point is a really important one because I think what we, the tech protect sake thing is we see a lot of that, you know, it is like this, this range of kind of like, uh, like hype waves. You know, if you kinda go back sort of like five years, it's like in 2020 the pandemic, it was chatbots, right?
And then I think it was possibly blockchain and then it was the Metaverse, and then it was congenitally and then it's Geogen ai and it's like, it, it's these series of waves. And I think that the. So technology's moving fast. That's that, that, that's true.
But we shouldn't just be buying technology, like thinking it is a spanner and thinking about, oh, where can I apply it? As it were. I think here's the thing that we need to do, is we need to. Educate ourselves on, on the art of the possible.
So we need to kinda like basically upscale ourselves in terms of understanding what this technology is and what it can do. But then rather than actually starting from a tech perspective and thinking about what experience that we can deliver. And so you buy the tool and then think about what you can do with it. We actually need to kind of like educate ourselves on what the art of the possible is, and then start, then imagine what is it that we want to create.
And why? And then work backwards from there in terms of what is the tech and what is the data that we need to in order to, to fulfill that now. Because if you do that, then you're gonna get a better idea of what you're working towards and that gives you a bit more of a, uh, of an insight and what sort of tools you need to employ in order to achieve that experience. Right now, I think we're working from a tech data and experience kind of perspective where actually we should work on the flip is like start from an experience, data and sort of tech.
Perspective. And if we do that, we'll also get a better idea of one, having a strategy of what we wanna do, 'cause it and leads, it'll lead us towards our kinda like vision. But by doing that, we can also kinda start getting greater clarity of how do we deliver ROI out of some of the, our initiatives. Because otherwise it's, it's like, oh, well buy this and then things will get better.
No, let's kind of like. Be deliberate about what we're gonna do, what's our vision, what's our strategy to try and achieve that? What, what tools and things are we're gonna, uh, um, employ to in order to, to do that. And then we can think about, okay, how does that tie to the enablement and achievement of our business and commercial objectives, which will then help us deliver kind of ROI.
Uh, love it. So I, I know you're all over CX and, and, and you're talking to tons of organizations and obviously you're a consumer and customer yourself. For you, Adrian, what's a company that's doing AI right from, from a CX perspective? Adrian Swinscoe: I, so there a lot of people talk about operational efficiency, right?
And their productivity gains. But I actually think what's interesting about this, these new, new version of technologies is it gives us choice if you do it right, it gives us choice. And one of the best examples I've heard of a company that is leveraging some of these tools was, I think they're an e-commerce company and they've used AI and automation to, to, to free up a lot of their agents from doing some of the simpler tasks. So.
The large percentage of the simple inquiries are all automated through either through a chat bot or through an a, you know, an automatic answer engine or, or whatever it might be, and that's freed up all sorts of time for their agents. Now, some people might go, great, we can reduce headcount, or we can redeploy people into other parts of parts of the, the business. They're like going, no, but that's not aligned with our brand. Actually, what we want to do is we want to.
You know, we are, we've always been customer first and actually what they, they've chosen without additional capacity. They've chosen to turn the phones on. Because they, they've never been able to do that before. 'cause they didn't have the bandwidth to do it.
So they're just for a brand. Okay. We're we're just chat and email and messaging and social media sort of thing because that took up all their time. They didn't have the time to turn the phones on.
But now because they've automated a whole bunch of stuff and free up a bunch of space, they're like going, let's turn the phones on, then we can talk to customers, solve more complex problems, kind of get to know them a bit better, build relationships with them. And I think that's a brilliant kinda like way because it's actually not necessarily the normal thing. That you would expect or not, that's not part of the normal narrative that's going around the, around the industry.
So that's what I mean about having that vision about what you wanna do and a strategy to achieve it. 'cause understand that within that you have choice. It will give you choice if done right. And then it's up to you to decide what you want to do with that, that, that, that extra capacity that you're gonna free up.
Yeah. I love it. That's completely, uh, I, I love that example because that's the opposite of what I typically hear. Right.
And, and it's reduced, reduce. Reduce, and then. Yes, you saved some money, but you've created friction other places and, and you know, it's tough. It's tough.
Uh, I love it. Um, so la well last question here on ai. Um, any kind of, from your experience, like any ethical considerations that you think we should be talking about more with it? Uh, you know, I don't, we don't get into this a whole bunch, Adrian, but I'd love to hear your perspective.
Adrian Swinscoe: I think there's two things I would say. First of all, I would say that we're not talking enough about the energy consumption needed to power generative models and just general AI in, in general across the, you know, the, the tech space. Yeah. That's a big deal.
People are talking about building nuclear plants to power some of these data, these data centers and, and then going up at a rate and it's this bit like, wow, that's crazy. Um, I think. That, that's based on where we are right now. I think the, we've sold with people like Deep Seek that have been able to do some, do some things differently on the engineering side and the algorithmic side, which means that the energy consumption is, is much kinda lowered, but broadly, energy consumption is, is a big deal that we need to think about, particularly when we think about the, the broader context that we're about climate change and things.
That's kinda the one thing. And the second thing, um, we don't talk about. A lot. We actually don't, don't think, we don't talk, talk about it at all.
And, and that is a lot of the low paid labor that goes into data annotation, much of which is, uh, located in the global south. So we get all this stuff and all this power and this technology and stuff, but it's relies on. Possibly a lot of exploitation. I'm glad.
Thanks for bringing both those up. Uh, you, those are definitely ones that you don't hear hardly anything about. Right. Uh, and, and, and, and definitely huge, huge impacts on, on, on our world.
So, uh, Adrian, thanks so much for joining us. I really enjoyed getting to talk to you here and, and learning more from you. This has been terrific. I gotta ask before we go, you got a favorite punk band?
Adrian Swinscoe: Uh, I have two. Two. All right. Um, Fugazi.
Fugazi. Yeah. Adrian Swinscoe: And Bad religion. Uh, bad religion.
All right. Well, awesome, ju I, I, I've loved it so much. There is a 99.4% chance I'll listen to God save the Queen from, uh, the Sex Pistols today.
I know that'll be on my playlist at some point. Uh, but, uh. Adrian. Brilliant stuff.
I really enjoy, uh, having you on the show to our audience. Definitely check out Adrian's books. Uh, you can find them. Uh, Adrian.
Where can we, I'll let you, where can our audience best find your books? Where do you wanna direct'em? Adrian Swinscoe: Uh, I mean. I'm just look me up.
It's like Adrian Scoe, you know, S-W-I-N-S-C-O-E. Look me up on the, uh, or whether it's Amazon or the internet, you'll find my website. You'll find me on LinkedIn. You'll find me on the pod.
If I'm the me on the Punk CX podcast, do that and hit links or subscribe or buy a book or whatever it might be. Or send me a message kind of like, and just to say hi, and then, you know, that's all good. That's awesome. We'll definitely check him out.
I was gonna say, I was gonna say Amazon because I know when I, when I pull you up, Amazon's the first thing that pulled up, but I wasn't sure if that's the best place. But you're on there. You'll find them. Grab the book.
Terrific stuff. So that's the end of our three part series to our audience. We really appreciate, appreciate you listening. Make sure you, uh, if you like the show, subscribe, rate it, share it with your friends and colleagues.
You can connect with, uh, Adrian on LinkedIn. Adrian's on LinkedIn. So reach out to Adrian on LinkedIn, like again, check out his website. Uh, myself, I'm on LinkedIn at Roman Trevon.
Ping me, reach out. Let us know what you liked on the show. Guests you'd like to have us on topics, et cetera. We're always happy to connect.
Uh, Kevin, who wasn't able to join us, Kevin Metzker you, he's on LinkedIn at Kevin Metzker and then our Customer Success Playbook page on LinkedIn as well. Check that out. You'll see upcoming shows, clips, what's happening on the show, et cetera, and we'll ha we'll be back with more strategies for your customer success playbook. Until next time, audience, keep on playing.
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