2024 CX Landscape Report – Digital CxO Podcast EP96

Hello, and welcome to the digital CXO podcast. I'm Amanda Ani, and with me today is Eric Williamson. He is the CCE CMO of Coal Miner.

How are you doing? Good. I wish I was the CEO, but, uh, no Chief Marketing Officer.

Uh, I'm happy to be on, on your show today. Glad to have you here. So can you first talk a little bit about Coal Miner and what services are provided?

Sure. Coal Miner is the global leader in conversation intelligence. Uh, just to sort of give that some context, um, it's essentially artificial intelligence or large customer service centers.

So think of big, huge call centers or contact centers. Uh, they utilize our platform, it ingests every type of interaction, whether it's a chat, uh, a survey, review, a call, obviously, and analyzes all of that. Uh, and then ultimately it's able to provide real-time guidance, uh, back to the customer service agents.

And then the larger value proposition is, um, you know, our platform's able to mine through all those, uh, interactions and bubble up key insights that could help improve the product, the services, uh, so things that the CEO, the chief marketing officer, the, the chief product officer would be interested in. Wonderful. Thank you.

Well, the topic today is the Coal Miner's annual 2024 CX Landscape Report. So first off, who was surveyed and what was the purpose of this report? Sure.

So this is our third annual survey. So we're building up some equity not just in, you know, the name obviously among our audience. Um, but you know, when you do these, the, the field research and these reports, you're able to ask some of the same questions and start to see some shifts over time.

Uh, so the surveys global, uh, and we survey, uh, we work with Hanson Barn who's, uh, a, a, you know, very reputable field research company. And so we glo we surveyed 700 executives across contacts center executives, but also CX executives, uh, uh, around the globe. And their answers to the survey are what, uh, you know, gave us the data to be able to produce the report.

Wonderful. So what were some key takeaways from that report? Can you share some stats?

Sure, uh, absolutely. And I'll, I'll do my best to remember every stat. com and find it.

It's featured in a bunch of different places, so I don't think you could miss it. But, um, so I mean, a, as you might expect, this is 2024 and, uh, I think every third word is supposed to be ai, um, when it comes to pretty much anybody at this point. So it was a heavy dose of AI throughout the entire, uh, findings of the report.

Um, I think some of the overarching thematics, uh, and this won't shock you, but among CX and contact center leaders, uh, there continues to be a massive amount of interest in implementing, uh, some form of AI beyond what they've already got in some of their technology today. Um, and, and in fact, I think it's something around 60%, 62% say they'd either partially implemented, uh, some form of AI or gen AI into their tech stack, uh, or they're planning on it for fiscal 25. Um, and you know, that's, that's in line with some of the same answers last year.

But, uh, I think what we're seeing is, uh, uh, moving away from kind of the, the hype and the fear of missing out of gen ai, uh, to a more responsible approach of how that gets implemented. And we're seeing that come through in a lot of the data as well. Um, one of the major questions in the thematics, uh, I think definitely last year, uh, that we heard more is, you know, is AI going to come and take, uh, all of my customer service agents jobs?

It's gonna take all of my my team's job while I have a job. That question is kind of waning a little bit now. Uh, and people are starting to, you know, after they've become more educated, people are, uh, understanding that really what AI and gen ai if, if implemented appropriately, and b is a productivity multiplier.

So it's really something where you're able to do more with the team that you already have versus it taking your job. Um, and I think roughly 90% of the survey respondents, um, this year had that general opinion about, um, about how AI could be helpful, uh, versus taking away our jobs. Yeah.

Was there anything in the report about, um, skillset is, is there the proper skillset amongst companies to implement AI at this time? So that's a great, that's a great, uh, question. Uh, we didn't have a specific question on this, but I know from talking with a lot of our, our customers and just generally, uh, interacting with, you know, uh, a variety of different companies across our industry, um, what's happening is, I think we're gonna find that any jobs that are lost because of, of, uh, you know, gen ai, uh, eliminating some of the mundane is gonna be replaced with jobs that never existed before.

So if you think about how you interact with, uh, chat GPT or something like that, it really comes down to how well you were able to, uh, architect your prompts. So you're gonna have, you know, I think a lot of, uh, change within a lot of the analyst roles who are now gonna be able to utilize Gen AI for a lot of their tasks versus having to do it manually in the past. So I think, uh, it's really more of a shifting of, of skill sets.

Um, so as you think about, you know, people that are in college now and thinking about a career in CX or in marketing or in, in some sort of data analytics, I think that's gonna look quite differently in two to three years than it has in the past 10 years. Yeah, absolutely. I think our younger generations, they've grown up with computers, technology, tablets, um, all kinds of digital programs.

And so I think they're, they're messing around with all this stuff with no fear, so it's gonna come really easy to them, I feel like. Yeah. So we, we did find, uh, and this is, is supported in the report, but one of the things, uh, in the report, but also just in general we're seeing with our customers is it's a little bit of the wild west right now.

I think people are starting to understand how they can utilize this. But if you think of, think all the way back to, you know, 2007 through 2009 when social media was, uh, making a huge impact across organizations and they realized this is incredible. Uh, we can do a lot of things with this, but we have no policies or governance around it.

So what's happening right now is you're seeing all these companies, especially at the enterprise level, um, you know, a AI committees or heads of AI and uh, governance start popping up. Um, and while this is a good thing 'cause they're trying to put some guardrails around how a company utilizes gen ai, uh, it also creates a lot of process disorganization right now. Um, but I I, I figure in the next 12 to 18 months, most companies will have figured out their policies and we're actually proactively providing a lot of guidance to our customer on this front.

Um, but I think that's something we're seeing happen right now As far as the customer experience landscape. This technology is advancing very rapidly as we've seen. So what do you see for the future of this technology as it relates?

Sure. Um, and, and that's really a good observation as well. One of the things we found in the research is, you know, as I said, there's overwhelming, you know, enthusiasm about looking to implement, um, some form of gen AI or more of it into their tech stack.

But what's, uh, kind of funny, but also makes, makes sense is, uh, on the flip side, a a high degree of them, I think it was around like 30 or 40% aren't actually sure which one they should go with and what they should go with. 'cause there's so many options that are changing so fast. Um, and then on the other part of that is, you know, let's say they have narrowed it down, uh, to a particular selection that they think could have a big impact.

Uh, they're not sure where to look to measure in terms of, uh, understanding if they get a good return on investment or not. So I think our advice on that front one is get to know whoever your new AI are is your AI committee, because if you haven't met them yet, they're gonna help dictate a lot of those policies. Um, that will help inform which AI you should be implementing.

But I think think about it in three lenses, especially if you're a CXO, uh, or somebody involved with the contact center, the agent front. So I think the, the idea here is think about agents, think about what they do every single day, and you wanna look for those mundane, repeatable tasks. So I'll give you an example.

After a customer service call was over in the past, they would've to summarize it and, you know, put their notes and everything else. Now Gen AI can essentially automatically summarize it and they just have to make a couple tweaks. Uh, if you go a little further into the analyst world, like you and I were talking about before, I think, uh, the entire definition of that role is gonna change quite a bit.

Um, but from an analyst standpoint, you no longer have to go through the manual process of creating all these dashboards. You can literally ask an AI agent within your platforms, uh, like ours. Um, tell me, uh, the top three problems that were happening yesterday in terms of customer support calls and it'll create a dashboard for that.

Uh, you can say, tell me over the last three quarters, these are dashboards. I think that then you can make that much more visible to an executive. Whereas before that was two in the weeds.

Um, I think the last one would be, you know, when you think about, uh, just companies in general, there's a big shift to utilizing, uh, we'll call them, you know, AI agents, AI customer service agents, bots basically. So, and thinking of different tiers of that customer support. So if you've got a much smarter virtual chat bot, uh, that's able to tap into the appropriate knowledge base, then you can actually take quite a bit of these repeatable FAQ type questions out of the hands of a human, uh, which allows them to focus more time on actually solving real customer problems versus dealing with the same question over and over and over.

So I think those are some ways in the immediate near future, you're gonna see some changes, uh, you know, especially to, you know, huge enterprise companies. And then, uh, BPOs, which are essentially outsourcers or customer service for a lot of companies, Really some innovative use cases out there. So from your experience in working with companies when they're trying to integrate AI into the company, what tips do you have for them to make it as seamless as possible?

Sure. Um, so first one, uh, I mentioned earlier, now that there's these new committees popping up, I would, uh, I would identify those groups as fast as possible. Um, 'cause we, with the disruption I was mentioning before is you've got, you know, uh, let's say there's someone within CX organization and they've already been given the remit, you need to go figure out how to, uh, adopt AI into your strategy.

And they're doing that on their own because they've been told to, but they didn't know they were supposed to run everything through this new AI committee. So first and foremost, figure out, uh, the changes that are happening within your organization. Secondly, think the biggest thing would be to, if you're not already somewhat educated on just AI and gen AI in general, um, do some one-on-one education for you and your team so you have a general understanding of what the difference is between, uh, the different models, uh, between AI and machine learning, et cetera.

So those are some fundamentals. And then lastly, be very selective about the workflows that you have in the use cases that you have. And identify areas that are repetitive, mundane things that you think you can actually apply gen AI to.

And then pick one or two of those. Don't pick 15, um, and start small, get some wins, but also some losses in learnings, uh, and go from there. Um, the last thing I'll, I'll recommend, and this is really where the governance part of this is coming in, is there's, there is still quite a bit, I think now that we're beyond the fear of missing out and we're into the sort of reality check of gen AI is there's, there's definitely a lot of fear, uh, around compliance, um, especially for highly regulated industries like financial services or healthcare as well as just brand risk.

So I think we've all heard the Air Canada story where the virtual chatbot essentially came up with a brand new policy, um, for someone they were interacting with, and they got sued and lost over this. So, you know, that's a, that's a obviously a, a pretty, um, that's a pretty bad example, uh, of, of what could happen. And I don't wanna scare anybody, but my advice would be as part of this process, definitely be thinking about this in, in, you know, through the lens of compliance and risk and how much risk you're willing to take.

Yes, absolutely. Well, if there was one key takeaway you could leave our audience with today, what would that be? Uh, I think, you know, the, the biggest from a tactical standpoint is what we've been talking about before is don't try to boil the ocean.

Um, really, you know, you, you've probably already mapped out all the different workflows and you know, what the day in the life of one of your customer service agents or one of your analysts looks like. So, you know, have a common sense conversation about where those repetitive, mundane tasks are and pinpoint some of those as your first projects. Uh, I think you're gonna be much more successful in scaling this if you get five or six small projects under your belt versus trying to do some massive two year implementation of something.

All right. Well, thank you so much for coming on our show and sharing your insights with us today. Absolutely.

It's always, uh, uh, it's always, um, fun being on your show. All right. And thank you to our audience as well.

Stay tuned. There's more.