destinationCRM’s 2024 CX Megatrends to Watch Wrap-up with Samantha Middlebrook
destinationCRM’s 2024 CX Megatrends to Watch Wrap-up with Samantha Middlebrook
Kicking off the new year, destinationCRM held their annual "CX Megatrends to Watch: Expert Predictions" webinar. Our own Samantha Middlebrook took part in this webinar and shared her predictions for what we’ll see from AI’s impact on customer expectations in service interactions along with changes to contact center operations. In this podcast, Samantha sits down with us to share insights from the destinationCRM webinar and expands upon what she believes will happen moving forward with AI in the contact center space.
Transcript
Pete Wright:
Hello, everybody, and welcome to Connected Knowledge from Upland Software on TruStory FM. I’m Pete Wright. Happy New Year, everybody. This week, we are talking about the trends of 2024 – what leaders in the CX space are pointing toward as tools that will mark the year. Our own Samantha Middlebrook, Senior Director of Product Marketing and Management for Contact Center Productivity at Upland is back with me to share what she learned and shared from taking part in CRM magazine’s Customer Experience Trends to Watch webinar.
Samantha, welcome back. It’s good to see you.
Samantha Middlebrook:
Hi, Pete. It’s good to see you too. And I keep asking, is it still okay to say Happy New Year? It’s the 23rd of January.
Pete Wright:
Yes, it is until February 1st, it’s okay.
Samantha Middlebrook:
Okay, perfect.
Pete Wright:
It’s okay, especially because I believe this is our first episode of the year and so recording of the year and it’s very exciting to get back in the old saddle. And what a better topic I cannot think of than talking about trends to mark 2024, what we are looking forward to in the year. Now, you took a part in the Customer Experience Trends to Watch webinar. Can you tell us a little bit about that before we jump into specific trends?
Samantha Middlebrook:
Sure. I just put in that webinar last week with the lovely team at NICE Software. A woman by the name of Tamson was letting us know her trend analysis and I was letting you know our trend analysis. So, we were thinking about the changing landscape of customer service and customer experience and what people should be looking out for or planning for as they think about the months ahead.
Pete Wright:
Okay. So, I thought we might open the conversation with your thoughts and trends regarding the call center itself, and specifically the contact center agent. Things are changing very rapidly right now. New technology is changing and evolving the role right now. What are you looking at when you look at the call center agent?
Samantha Middlebrook:
Yeah, it’s a great place to start. I started off last week talking about how 2023, by the end of it, it almost felt like I personally was crawling to the finish line. There’d been so many tech advances, new things happening, and my job, Pete, is to literally know what’s happening in the tech landscape. And if I felt exhausted, I can’t imagine how the rest of the world felt. So, if we play that back to what that means for a contact center agent. Every time they’re now interacting with customers, the customer’s expectation has rapidly changed. I know we’re going to speak about AI a little bit later on in the podcast, but generative AI really pulled the rug out from a lot of people and we have customers now really feeling like they can self-service to a level that they’ve never been able to before.
So, what that means for the agent is added pressure. If a customer is coming through to have that high touch moment, whether it be voice or email or live chat, then you better believe that the customer is expecting you to be some kind of superhero when it comes to customer experience.
Pete Wright:
That pressure has got to be extraordinary. It’s been a long time since I was in a call center as an agent, but there was pressure 30 years ago, Samantha. Now, when people are coming, when customers are coming equipped with that kind of information, that resource in their bag, the expectations of the call center agent are extraordinary. But it’s not their responsibility alone. What are call centers, what are the organizations doing to better equip call center agents to do their jobs? What do we have to look forward to the horizon six to 12 months out?
Samantha Middlebrook:
Yeah, it’s a really great question. We talk about the concept of a super agent or a unicorn agent. And prior to maybe the last 12 months, the way that we would create these super agents, if you will, Pete, is through really intensive training programs. So, we would look at you as an individual and we would say, does Pete have the attributes to be this stellar agent to really represent our business? And those attributes were related back to really old legacy KPIs. Could you get the customer off the call really quickly? Could you handle escalations? Were you making sure that your first contact resolution was really fabulous?
So, if you think about your profile, Pete, as an agent. If you think about the call center reporting that the team leader would send out, you would be green, green, green, green, green and all of that Excel reporting. And that’s because you kind of tick the box. You fit in the box that was, yes, I’m a great contact center agent because I meet my KPIs and I’ve been able to become some form of expert. And we think about expert in the business is really understanding the products, the processes, the policies that encapsulate what a business represents. If you think about your bank or your health insurer or your utilities’ provider, those businesses are big and they’re complex. And so for a contact center agent to know all of those things, they need to earn the badge of each function, if you will.
I might start off and I learn about account management, Pete. And then once I get that badge, I might go away again and learn about billing and then I might learn about sales and all of those kinds of fun things. But that takes a really long time. And the tools that people have in place to help them with that is things like robust knowledge management, really clean and simple CRM, excellent integrated telephony, those kinds of things.
Now, as we start to see that evolution of the unicorn agent we’re calling it—it’s a highly empathetic individual. It’s less about you being an expert in everything to do with the business and more about using the tools that you have at hand to have really constructive and open conversations with the customer.
Pete Wright:
Okay, how do we modernize the KPIs then? We have to modernize how these new empathetic unicorn agents are managed. Yes?
Samantha Middlebrook:
That’s right. And so if you think about something like average handling time, average handling time has been a really easy one for us to manage or at least monitor, Pete. For many, many years the call lasted this long and we break down the call into how long it took to answer the call, if there was hold time after call work, what does that look like? If you think about the concept of average handling time, though, that really doesn’t make as much sense when we’re starting to think about the way that we structure inquiries coming into a contact center.
Think about this, Pete. If we are letting our customers self-service really simple inquiries, it’s pretty obvious that the contacts coming through to a human are going to be longer and more complex. So measuring an agent on an average handling time just probably doesn’t cut it as much anymore. But if we think about metrics like the effort it took for a customer to solve a problem, then that’s really interesting. Because if we think about the touch points they accessed, if the human solved the problem, if it was a digital channel, that’s when we can start to understand the effectiveness of the service that you are offering to your customer base.
Pete Wright:
Okay. Do you have any insight on how agents are viewing the changes that are coming to them? Do we see an acceptance that this is the changing role or is it still something of a surprise?
Samantha Middlebrook:
It’s a really great question, and I think it depends on the demographic of the contact center. If we think about, traditionally contact centers have been made up of a pretty young generation, and then you have a pocket of people that have been around the business for quite a long time. If we think about that younger generation, they are completely immersed in new technology, and so their expectations has really changed. The way that they want to consume information is very, very different. If we think about the TikTok generation, I need answers now and I need it in a way that makes sense and feels modern to me. So I think, from a expectation of that workforce, they’re expecting the business to have the tools that they have in their personal life. And if you don’t, you’re going to get into some challenges. Because don’t forget, Pete, the number one problem that contact center leaders still face is the ability to attract and then retain staff. And so, if the tools are not supporting those people, then we have a problem.
Pete Wright:
I like the way you said, but when you frame their expectations of the technology they have at work. It’s built on their expectations of the technology they carry in their pocket, or they access at home.
Samantha Middlebrook:
Exactly, right. Exactly, right.
Pete Wright:
This brings us to some of the new technology that I know you talked about on the webinar and we said we’re going to talk about AI. Let’s talk about it. What are our expectations of AI and how we are adapting to it in a universe that is post-2023, which was global shock?
Samantha Middlebrook:
Global shock, horror, excitement, trepidation, all of those things. Boston Consulting Group put out a really lovely report where they interviewed 1400 C-level executives just recently, and that report mirrors all those things that we’re talking about. Executives want to get started, but only 6% of organizations have 25% of their staff trained on generative AI. And it’s something like 75% of executives know they need to introduce generative AI, but the change management feels pretty terrifying.
If we think about 2023 and the promise of what AI would be, Pete, it was pretty sparkly. It was flashing in lights, changing everything. But what we found as we enter 2024 is that the AI that’s been successful in organizations has been pretty unassuming. It’s within your workflow. It’s just like you blinked and now it’s here and it wasn’t a huge change exercise because it really made sense to you in your role, and so you weren’t as change resistant. But behind the scenes we’ve got big organizations, the Microsofts of the world, working really hard to kind of normalize the AI presence in an organization.
Pete Wright:
It’s the whole idea of all of the news in 2024 is Microsoft consumerizing AI, introducing the first new button on the standard Windows keyboard in 30 years or whatever for Copilot. And that’s the thing that I think is most interesting. The fear that has come from all this new advancement in AI is it’s going to subsume the organization and begin shaving off jobs. Is that a conversation you’re having right now for 2024?
Samantha Middlebrook:
It definitely is. We met with an executive team towards the end of the year and we were showing them some of the AI features in our new products. And point-blank, Pete, the question they asked was, does that mean we can get rid of some of our contact center agents? And in order to adopt technology, there has to be some form of return on investment, and return on investment always has come in different ways. Are we talking about reducing headcount or are we talking about redirecting that effort of resource into other areas?
My prediction for 2024 isn’t that we have a humanless frontline by any means because I still firmly believe that humans need humans. And when your bots fail, you need that human interaction, which is that empathy layer that we talk about a lot. But I think that we will see some redistribution of roles, especially when we think about aggregating data across the enterprise, when we think about having these more subject matter expert style positions, which are really there to coordinate the facts and figures and to corral teams. That’s what the AI is going to be able to do.
So if we think about Dynamics as an example, it’s your AI companion. It’s everywhere that you work. It’s everywhere that you’re doing mundane tasks. It’s about simplifying that. It’s still about having a human in the loop though, Pete—a human, to make a conscious decision of what you do with that data, whether or not you send that email, whether or not it makes sense in that customer interaction. The human is still very prevalent there. The way that I describe it is think about having a really excellent executive assistant or BA who’s pulling everything together for you to help you make an educated decision. That’s what the AI is doing and that’s what it’s doing for contact center agents if you get it right.
Pete Wright:
The peril, the other side of the promise, the peril is that there are a number of business unit leaders who are assuming that it means we can get rid of some resources. And we’ll have to learn the hard way the journey back toward the empathetic leader, the empathetic agent, and that getting rid of people is not necessarily the right answer. But we have to learn first.
Samantha Middlebrook:
That’s right.
Pete Wright:
What are we doing to learn?
Samantha Middlebrook:
Well, I think some organizations learned from the chatbot boom that we had, what, five to 10 years ago where we had chatbots. And this was when AI was new-ish in that format where the concept of empathetic tone was not even on anyone’s radar. If I have a look at some of the latest models around gen AI, thinking about tone and empathy is kind of front and center of what the development world is trying to do. So, at least the bots are emulating humans. We still need humans though to test and to learn and to provide the prompt because it’s really a world of prompt engineering is kind of the space that we’re in right now. If you can provide gen AI with the right prompt, you can do anything. But that’s an art and a science in itself.
So, I think organizations will be a little bit gun shy because of some of the really weird and wacky bad examples we saw over the years with chatbots. One of my team just sent me this morning quite a humorous article. It was all around a delivery service and the fact that the delivery service basically had gen AI working with their customer-facing chat. And then for whatever reason, the chat got into a little bit of a circle of death in terms of trying to help the customer find where their content was, where their delivery was rather. And basically, it created a not very PC and a not very brand conscious poem about how bad the delivery service was for customer service.
Pete Wright:
See, this is the gem of 2024—that AI is going to make the internet weird again.
Samantha Middlebrook:
That’s right.
Pete Wright:
That might be great for a little while.
Samantha Middlebrook:
And that’s basically because the customer was just in such a weird and wacky death circle of trying to get an answer. It said something, the customer says, I’m like, can you tell me a joke? And the AI took it quite literally and then created this poem. I mean, I think there’s still things like that. That’s why we’re saying human in the loop is really important. It’s like if you had, let’s say tomorrow, Pete, you were standing up a brand new contact center in whatever industry and you said, “Hey, I’m going to go out and find 50 new contact center agents,” there is no way that you’re going to unleash them to your customer base handling all the calls without any training or supervision. It’s the same with AI.
Pete Wright:
AI adjacent question or call center adjacent question. In your role, how are you using AI tools right now? Have you adopted them in any sufficient way or a significant way?
Samantha Middlebrook:
Yes, absolutely. I mean, my role is twofold, right? One part is product and strategy where we’re really looking at what needs to happen in the market, not today, but in five years time across our products to make sure that we’re still relevant. And the other one is in product marketing, which is all around messaging and positioning. So, I use AI constantly, whether it’s collating or analyzing data, whether it is around helping with outlining of strategic themes. Even simple things like helping to summarize really complex ideas that we have that sometimes we feel like we word vomit, Pete, and we need that objective view is really quite helpful. So, if you work with me, and my team will tell you this, I am constantly moving at a very rapid pace. And so I will send myself voice notes of my ideation in between my meetings if I’m running to do school drop off or whatever it is, and then I’ll take that file and use AI to analyze it and help me work out what I need to plan for the week or the month and set my priorities.
Pete Wright:
I think that’s a really important thing to recognize and to talk publicly about as we’re talking about AI in a very broad way and how it can force these industrial level shifts. But what does it look like at the individual desktop, on the individual phone? We are adapting to it. And what you just described is, I think, role model behavior for call center leaders to be really exploring. How do you use it personally? How do you use it to help amplify your own ideas and develop clear thinking?
Samantha Middlebrook:
I’ll give you another. So if you think about the pragmatic side, I’ve got these tasks, I’m trying to prioritize, manage my work, what do I do there, then you’ve got the creative side of things. So, if we think about image generation… if we think about literal video creation… We ran an AI certification for our sales team here at Upland because we have AI through a majority of our products in the contact center suite.
As you’re asking me though, how do we make sure our own teams are up-to-date and up to speed with everything that’s happening so they can speak with real conviction to the market around what we’re doing? And so as a little bit of a test, we created our whole certification using generative AI. So, our avatar is AI generated. The look and feel, everything is made of AI to really explain to the team how big this is or how small it can be, depending on what you’re trying to do. And it’s quite interesting because I met with one of the sales team on Friday and they said, “Oh, so the AI though, it’s just you used it to help create the script, right?” And we were like, “No, no, no. That person that you saw is not a person. That is generative AI.”
Pete Wright:
Yeah. Right. It’s incredibly powerful and I think it really does feel like this is still the trend to watch. 2023, AI, we’re not done. What else should we be looking out for on the horizon? What other CX trends should our fair listeners be on the lookout for?
Samantha Middlebrook:
With AI, and I know we keep talking about it, but I think it’s so important, Pete, is 2023 was AI singing and dancing, everyone’s talking about it. It feels really sexy. I read a stat that 10,000 vendors released some kind of gen AI feature in 2023. Now in 2024, it’s like the dust has settled that. Then we’re saying, well, how do we actually implement that within our organization? And if you think about 10,000 vendors doing “something with gen AI,” Pete, whatever the something is, then you’ve got to think about how those 10,000 vendors are working within an organization.
And so what we found out many years ago when we look at technology in business is having a single vendor or a single throat to choke, if you will, isn’t really the flexibility that a lot of organizations need and want because different vendors are really great at doing different things. And we need to be hyper aware of that when we come into 2024. Because if you are working with an organization that’s kind of locking you into only using their AI, you’ve got to think about how does this fit into my technology landscape and where is the flexibility? And that’s where we’re seeing two trends when it comes into the architecture of AI within an organization.
One is that the organization or the vendor must offer what we’re calling a local or an own model when it comes to generative AI, Pete. So what that means for the fearful folk listening is that your data doesn’t leave the infrastructure of that vendor. So it’s not OpenAI. It’s not publicly used. It’s within your infrastructure. It’s using your data. What that means is that you can test and learn and train the model. So, if you think about your business IP and what you actually want to do with that generative AI, that’s how that local or owned model needs to play. So one, you feel like your data is secure, but two, you start to get a little bit sexier with what you’re actually doing with that gen AI because your responses need to match what your teams are doing.
And then the second part of that, Pete is saying, well, hang on a second, what do I do if I’ve got five different vendors all offering me AI as part of their solution? How can I make sure that they talk? And that’s where we talk about the concept of a bring your own AI strategy because I speak to organizations who are on completely different ends of the AI readiness spectrum. One will be, we are so terrified. We know that we need to do something. The executive is telling us to do something, “Samantha, what should we do?” And the other is, “Hey, we’ve already built our own model. Can you plug your product into us?”
And so those are the two things you really need to be thinking about when you’re thinking about AI in your business. Does the vendor have a local or an own model? And two, can I bring my own AI into this story? Does that make sense?
Pete Wright:
It does. It does. And I think what you’re getting at is perhaps the 2024, ’25 story is organizational agency in AI being able to not just be thrilled by the fantasy of what AI could be, but actually taking ownership of what AI can do specifically for you. Am I right?
Samantha Middlebrook:
That’s right. That’s right. And it’s also about getting the right people in the business talking. So if you think about 10, 15 years ago when we started integrating technology. Previously, we would do this weird and wacky and time burning integrations that were bespoke to an integration and customized. And if something changed, then it broke. And that was a nightmare for organizations and many organizations started to move to API models and open source. It’s a similar trend that we’re seeing now. Right.
Pete Wright:
Based on your experience working with these organizations, who is best equipped to own the AI model decision-making process in an organization? Is that a settled decision in organizations? Is there an AI leader, business leader role yet that we can train for?
Samantha Middlebrook:
They’re starting to pop up, right? They’re starting to pop up with a pretty hefty salary package attached to them.
Pete Wright:
I don’t doubt it. Oh my.
Samantha Middlebrook:
Remember, what would it have been five years ago, when data scientists were all rage? And if you were a data scientist, you could basically ask for any amount of money? It’s a similar thing. What I’m seeing a lot of is this concept of an AI council. And an AI council is really like a transformation council. In the old terms, Pete, that has a collection of stakeholders from different groups, security and compliance, your legal team, technology, the business, and they’re really there to help make a decision, a committee to help make a decision. I think who’s leading it in organizations are still those innovators that actually are hungry to learn more about what’s happening in the landscape because things are changing all the time. And if you and I could feel confused about it or the regular person feels confused about it, it doesn’t mean that someone on an AI council has any more knowledge unless they’re really hungry to know about it.
So, I think what’s happening in organizations—it’s a lot of learning on the job at an executive level, or even, as that filters down, we’re still having very basic conversations. What is ChatGPT versus OpenAI? What is generative AI? What is natural language processing? So, just because people are more senior doesn’t mean that they’re more equipped to make those buying decisions. It’s probably the squeaky wheel at the moment. And the organizations that are a little bit less risk-adverse that are kind of trailblazing, and those ones that also have relationships with the big players, the Microsofts and things like that, who have got very senior buy-in that are saying, “Hey, look at these early access features. Come on board,” so they can look at things like the ROI calculations attributed to them as well.
Pete Wright:
Sure, sure. Well, it’s fascinating, Samantha. This is going to be a heck of a year, I think. A lot to look forward to. And thank you so much for coming and introducing us to 2024 and the trends to look out for. Any resources you want to point people to for learning more about some of the topics that we’ve talked about? Anything specific on your mind I need to link out?
Samantha Middlebrook:
Specific on my mind, I’m sure the marketing team will kill me, Pete, for not having them.
Pete Wright:
It’s okay. And in fact, the marketing team has already answered that question. I just want to make sure you have agency in the question.
Samantha Middlebrook:
[inaudible 00:27:53] probably 20 different things that we’ve written in the last-
Pete Wright:
Well, I’ll tell you, I’ve got three good ones that are going to be in the list for folks to check out. But thank you so much for hanging out and illuminating these topics. Samantha, as always, you’re great. And I’m sure this is not the last time we’re going to talk this year. Let’s keep hashing out these trends and watching AI grow and change our jobs for good.
Thank you, everybody, for downloading and listening to the show. We appreciate your time and attention. We’d love to hear what you think. Just swipe up in the show notes and look for that feedback link and you can send questions to us or any of our past guests, and we will do our best to get them answered. On behalf of Samantha Middlebrook, I’m Pete Wright, and we’ll see you right back here next time on Connected Knowledge.