Interview
The Gist
- Digital shift redefines service. The transition to digital-first contact centers shapes future customer interactions.
- Technology bridges service gaps. Advanced technologies like AI and analytics enhance contact center effectiveness.
- Customer insights drive strategies. Understanding customer histories and preferences is crucial for tailored experiences.
In the latest episode of "Beyond the Call," hosted by Rich Hein, we delve into the transformative shifts occurring within the realm of customer service, specifically focusing on the evolving role of contact centers in a predominantly digital landscape. Joining the discussion is Sean Albertson, a seasoned expert in customer service and support and founder and CEO of CX4Rocks, who brings a wealth of knowledge from his extensive experience across various facets of customer experience management. This episode addresses crucial aspects such as the challenges and opportunities presented by digital transformation, the impact of technological advancements like generative AI and strategies for enhancing the customer service journey. In this conversation, Albertson, illuminates the path forward for contact centers adapting to meet contemporary customer expectations. This dialogue is essential for anyone interested in understanding and navigating the complex dynamics of customer service in today's digital-first environment.
Table of Contents
- Redefining Contact Centers in Digital Age (0:01)
- COVID Accelerates Shift to Digital Customer Service (2:49)
- Key Ways Smart Tech Affects Customer Expectations (4:14)
- Frustrating Customer Journeys in Digital Transition (4:14)
- Addressing Disconnect in Omnichannel Customer Service (8:30)
- Omnichannel Priorities: Enhancing Agent Awareness (10:35)
- Omnichannel Support: Seamless Integration Is Key (13:54)
- Bridging Data Silos for Enhanced Customer Service (15:03)
- Reducing Effort to Boost Customer Loyalty (19:03)
- Key Metrics for Contact Center Leadership (20:57)
- Predictive Analytics Enhancing Customer Experience (24:48)
- Overcoming Tech Implementation Challenges in Business (27:37)
- Practical Steps for Contact Center Tech Adoption (30:50)
Redefining Contact Centers in Digital Age
Rich Hein: Hello and welcome to “Beyond the Call,” where the go-to show for insight, trends, and actionable advice in the customer service and support industry. I'm Rich Hein, your host, and today we're diving into a topic that's actually reshaping the very fabric of customer service interactions, the evolving role of contact centers in a digital first customer service landscape. In this era where the majority of customer journeys begin online, the contact center isn't really the first touchpoint, but more often a critical second seat in the customer's quest for resolution. This shift has brought both challenges and opportunities, and it's fundamentally changing how we approach customer service in this digital age.
Joining me today is Sean Albertson. He's a seasoned expert in customer service and support, and he's going to shed light on this transformation. We're going to explore the challenges customer service and service agents face in this new reality, the disconnect that arises when contact centers are unprepared for their new role, and the innovative technologies that promise to help bridge this gap. You know, we've all been there from the frustrations of navigating phone trees and automated systems to the potential of generative AI and advanced analytics. We're going to cover it all today. So please stay tuned and we're going to unravel the complexities of all this modern customer service and discover how embracing this technology can actually turn these challenges into opportunities for connection and resolution.
So Sean, I want to say thank you for joining me today. I know I've had you on the CX Decoded podcast before and you've always had a lot of information to share with the audience. I know you've worked across multiple departments in customer experience in your different roles, but if you wouldn't mind sharing with the audience specifically how you got into the customer service and support industry.
Sean Albertson: Sure, well, I started on the phone back in the 19... And you know, that's where my first real jobs were on the phones answering service calls. And then I moved into supervisory roles, and I kind of had about every role in customer service at the time or contact centers or call centers that you could. I managed about every department from training and quality to operations to, you know, basically workforce management, just about everything. And so that's really what started my passion.
So I come from the heart of knowing how important the customer service organization is to companies. But since that time, I've been doing CX across marketing and product and pricing and even IT and digital. And so I bring that understanding of that, you know, the root of my core of being in that customer service and in the contact center to really all that other work and understanding how we in the contact centers can work better across our organizations.
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COVID Accelerates Shift to Digital Customer Service
Rich: I knew I was talking to the right person. So I'm so happy to have you here today. I think we can all agree that, I don't know, since maybe 2018, we've just seen some of the largest amount of change that we've seen in a long time and it all kind of happened at once. How have you seen the dynamics in customer service change over this time?
Sean: Well, we were already going to a digital environment prior to COVID. There was a lot of digital transformation exercises and a lot of companies were making those improvements. I mean, we've been doing that steadily in the early 2000s and through, but man, COVID just put it in high gear. And all of a sudden everything, you know, if they weren't, if a company wasn't thinking about going digital first, they were during COVID because that was the only way obviously that we, that they as an organization could survive. And so it's just put that much more pressure on the environment. Now the value to the consumer is they've gotten a lot more options. And now with, of course, the apps and the websites and chat bots, I mean, digital now has become the starting point for every interaction. And the challenge for most of us that have grown up in the contact center is now we're at, as you mentioned earlier, kind of that second seat. We come in after usually the initial work online has. And it's been an interesting migration, but that acceleration of that digital transformation, digital first activity, it's really put us in a position where we have to think differently about our role.
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Key Ways Smart Tech Affects Customer Expectations
Rich: Yeah, I mean, I definitely agree. I think gone are the days when you would call the 1 -800 number and that was the primary way you got customer support. I think those days are over. I mean, today, as a consumer myself, the first stop is often self-service. I'm looking in forums. I'm looking at FAQs. If there's a chatbot where I don't have to interact with somebody like right away, if I get through all those, then I'm — I get to the actual contact center. At that point, I feel like a lot of us just want to speak to a human being. So I think that this new perception from the consumer side is really challenging for the modern call center and customer service and support in particular. How do you see that impacting the day-to-day in the customer service industry?
Sean: Well, being that, you’re the second, third, or fourth, or fifth step that the client has taken, you know, ultimately in the contact center, we're already behind the eight ball in the consumer's mind, in the customer’s mind. You know, we of course don't know what they've tried necessarily and where they've been and how long they've already been working on it. The reality is though, from that seamless experience the customer expects, they expect us to know in many ways what they've done and the effort they've already put into resolving their issue. So by the time they talk to someone, they're usually at a level now of, well, I've done everything I know to do in an easy way, and now I've got to talk to you. And so that puts extra pressure.
Going back to your point, when the call center was the first stop, there wasn't that much expectation. But now there's kind of this expectation. You should know what I've already tried to do. And God forbid you should know if I tried to call you before, and this is my second or third call about a subject. And so we're already kind of starting off behind where the customer's expectations are in the contact center. And we have to think differently and ultimately act differently to really prepare ourselves for that new expectation.
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Frustrating Customer Journeys in Digital Transition
Rich: Yeah, I want to talk a little bit more about how organizations are getting some of that data of where the customer has been before. We're going to get to that in a little bit. But could you share real just briefly where you see like a typical customer journey that kind of highlights the frustrations we're talking about.
Sean: Well, we've all had it. I mean, I can even give my own example. I was working with a bank and, you know, I won't name them because it's not a good story, but I was working with this bank, and it got to the point that, you know, I tried online. I did about every research I could. I used the website, I used the app, the FAQs, anything I could find online, nothing. So I knew I had to talk to somebody. And so I picked up the phone and called for the first time and I got the front line and you know, the person I explained my situation. They answered my questions as best they could. It was a difficult situation already. And so that, you know, that expectation I had, they were not able to fulfill.
Well, the challenge for me was I ended up spending one to two calls per week for two months. So eight weeks in a row before I finally found someone who could actually help me resolve the issue. And I had plenty of promises between now and then. Oh, well, I know what you need. We'll get you taken care of. But this cycle of reactive response, if you will, from the call center and the contact center, it made my journey so much worse. I mean, I look at it and say, I always like to translate and kind of my books behind me. But I like to translate the customer journey is like a river. We like to think it's nice and straight and smooth. But the reality is it's fraught with rapids. It's winding around because we as customers are hitting rocks in the customer journey, and those rocks belong to the business. It's the way that they're established to create those pain points. So for me, I was bouncing off rocks literally multiple times a week, just not being able to move forward in my resolution. And it wasn't really that any one agent made a mistake or was problematic. It was a process issue. It was a fundamental flaw in the design of customer support for that organization.
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Addressing Disconnect in Omnichannel Customer Service
Rich: Eight weeks sounds egregious. I mean, honestly, just put that out there. That would definitely grind my gears a little bit as well. But I think you're highlighting what we're talking about here, which is the disconnect between customer expectations and traditional contact centers. And I think there's more to the disconnect. So if you could maybe talk a little bit about that, because there's a disconnect on both the customer experience side and how effective agents can be.
Sean: Oh, absolutely. And like I said, it's not really the fault of any one agent if the technology and the processes aren't conducive to creating a great experience. And honestly, the employee experience gets bad too, because then they know they're not doing what they need to do. And they know they're the ones kind of contributing to that bad experience. And that's not what they're there for. They're there to create great experiences. So that disconnect, again, most of us have gotten pretty good with channel and task. I go to the website, the product team develops tools for me to do certain things on the website. Great. Go to the chat. I've got processes with the chat team to do certain things. Great. I go to the call center. If I go directly, I can do certain things.
The problem isn't any of those one, it's the lack of connectivity between them that causes the most challenge and the inability really for those people ultimately responsible for the interactions further down the journey, further down the river, if you will. Not really being able to understand everything that's gone before. So they know where to start, how to help, and really how to step in at a certain level of maturity and success that the customers are expecting at this point. And that disconnection, you know, we're chasing a lot of silos. I know we'll get to kind of AI and stuff like that later, but a lot of people are chasing this idea of ChatGPT to get rid of, you know, the contact center. The reality is most of us can't do that yet. Our data is not in a position to do it, but… There's a lot of challenges with just standing up another piece of technology without really orchestrating the entire journey around it and including it in that journey that's already existing.
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Omnichannel Priorities: Enhancing Agent Awareness
Rich: I mean, I think you bring up another huge challenge that all organizations are facing, which is just the omnichannel experience. I mean, there are just constantly new channels coming online all the time. And now as an organization, you have to pay attention to this channel because your customers are there. So as a leader in the contact center and the customer service support industry, how do you, what am I trying to say here? Oh, what omnichannel capability should contact centers prioritize first? And what are the biggest experience gaps you see in this omnichannel journey?
Sean: Yeah, I think the key is understanding history at the point of new interaction. And so if you think about it, we've been using things like CTI, computer telephony integration, for screen pop, right? As an agent pops up, it says, here's who's on the phone with you, right? We've been using that for years and years and years. And the reality is now when we think about the opportunity, there's so much more that can go into that kind of example. So for instance, not only now do you have the who's calling, but there's no reason why a generative AI product can't be scanning the recent notes and activity from said client and popping that in a summary form, short form summary that says, here's what's been going on with this client recently. Especially in my case, if on my third call, someone had gotten a pop-up that says they've already called now twice this week, or maybe three times in the last two weeks, there's something going on that needs extra care. Now that would already put the agent now at more of an advantage. Take the disadvantage and turn it into an advantage.
So whether you're then using your generative AI or your tools, because we've been even using AI, not generative, but AI for personalization, and marketing in other ways for quite a while where we kind of predict what's necessary. Well, now we have the ability to really accelerate that value and share that information into the contact center. Not only in advance. I mean, that to me is the first step is put your employees at a position where they can take ownership faster instead of starting the call by, well, you know, tell me again for the 14th time what's going on on your account. Right? You know, they don't have time to read the entire notes, but if you can summarize it effectively using generative AI, they're already a step ahead.
Then of course, there's all the other use cases that can say, now bring in generative use cases to show me FAQs based on the conversation I'm having or other tools that will help me solve these things faster. Those are at least the starting points for creating better connectivity. Because that data is out there, whether it's web logs and what I've done online, whether it's, your recent chat transcripts, if you happen to do that first, that data is there. It's just about connecting that data and then presenting it using capabilities like CTI that have existed for a while, presenting that to the agent. So they're starting off on the right foot and creating more of that ownership. And ultimately for the employer, the client and customer, making sure they don't have to go again and again and again, re-explaining the same thing.
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Omnichannel Support: Seamless Integration Is Key
Rich: Yeah, I mean, we're entering the technology portion of this conversation. I'm happy we are because I think there's a lot here. You know, self-service, you know, does kind of rule the roost and customers definitely expect seamless support across whatever the channel is they're using. And so omnichannels here, you got to integrate all these channels like voice, chat, messaging and social media. And yeah, you use smart routing and unified agents and all these other things. And so you talked already about CTI. I know that that's been around for a long time. Can you talk a little bit about how that system has evolved?
Sean: Well, yeah, I mean, think about the IVR, the phone tree and phone system, you know, from touch tone in the past and now talking to it. Well, at that point, you know, they know which number you've called in on, you know, using your Annie or your actual phone number to find you, assuming you're calling on the number that which nowadays everybody calls from their cell phone because nobody really has home phones anymore. So, yeah, they know who you are. That integration then allows, you know, the IVR and that upfront system to kind of look into the CRM. And say, all right, I know this customer. I know their account. I know all sorts of good information about them. And that is being used and has been used then to present to the agent to say, hey, here's who's calling. But it's a tunnel, if you will, data upfront from an offline or a non-human interaction to then presenting to that human interaction within that integration. And that's the key behind it, for sure.
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Bridging Data Silos for Enhanced Customer Service
Rich: How is general or generative AI, how are you using this to kind of understand what the customer is doing before they actually get to the contact center? Because that always seems to me like where one of the gaps is currently. It's like, I could go on your FAQ or go on the forum or maybe send in a question to your technical support. And then I call in not having gotten a resolution. How does an organization like kind of, deliver that kind of data to the agent when you're calling in? Or is that one of the gaps that we don't have that ability yet?
Sean: We have the ability. One of the bigger challenges with that is the data is always in silos. And that's inevitably for most organizations that I work with in consulting or coaching. It's not that they don't have the data. The data is just not connected. Now, the key is you've got to have a tool that makes that connection for you. And there are tools out there, and there are vendors, CRM vendors especially. Salesforce is one and most of the others where they're doing their best to gather that data now and present it in a seamless front.
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There are other vendors that are now sitting on top on the outside. So for instance, I talked to a lot of vendors and folks about on the digital side, they're tracking customer usage through the website, literally tagging where that customer is going after they log in and they're signing in. So if that data were available, from one of those trackers. And there's plenty of vendors that kind of track that journey, that digital journey specifically, but it's connecting that then to the physical journey, the, or the human journey. And that's where a lot of these things break down.
Now there are some companies that are ahead of the game doing that. So I'll use an example. I got a bill from one of the companies I work with. And, you know, on the day of the bill, I'm looking at it. I'm like, this doesn't look right. Well, I pick up the phone and I call and the IVR recognizes that my bill date was today. And it actually said, so I see that today is your bill date. Is that why you're calling? Yes, it is. Let me get you to that department. So it knew, now this is not obviously the digital journey, but it knew something about me from the billing system. It knew that a bill was due today and that I was calling on that day. And it asked me, it didn't automatically force me, because what if I had called about something different? But it asked me, is this why you're calling? And by saying yes, it bypassed the pounding of numbers or all that sort of stuff and got me directly to the billing team.
That's the kind of opportunity that some of this new technology can do. And that's not even generative in nature. That's just kind of standard connectivity and understanding and looking up data in the right way. Now add to that the capability to summarize mass amounts of data in a more generative, pithy, if you will, summary. Now you can take key points out of certain other activity like online movement on the website or forums or whatever else and understand, hey, you just called yesterday. You're a repeat caller. You know, was your issue about what you talked about yesterday. And so there's some things now that you can do by summarizing that and understanding that at scale to basically help predict why they're calling and then show them a way and a solution before they even have to ask. I mean, customers don't want anything to go wrong, but when it goes wrong, they actually want you to kind of know about it ahead of time and help get to their resolution faster.
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Reducing Effort to Boost Customer Loyalty
Rich: Yeah, anything you can do to make that frictionless for them is going to make them. happier and increase retention and loyalty, I would imagine.
Sean: Oh yeah. Well, absolutely. And, you know, there's a big part of this. So I've measured customer experience in about every way possible. Obviously Net Promoter Score is big out there, overall satisfaction, customer satisfaction, but I really fall into this area of heavy, heavy focus on the customer effort score. Now it's not, it's pretty big. A lot of people know about it, but it's not No. 1 on the list, but what I've seen in my experience is that you don't want to measure for measurement's sake. So whatever you're measuring to measure loyalty or satisfaction, it's got to predict that actual behavior. If it doesn't, then you're maybe not measuring the right things.
So what I found, for instance, is that you can look at something, if a client says something is high effort, it's hard to do. It used to be, they're four times more likely to be disloyal. Now, several years later from when the book came out, and I'll talk about the book in a second, but when that book came out, it's now five times more likely. Hard effort equals disloyalty. So if something's hard to do, I'm gonna be disloyal. And it's the fault of the cell phone and everything being easy. And we're used to it. Our expectations now are, it's gotta be easy or else I'm gonna go to someone who makes it easy.
And this customer effort score was actually, I'll advise everybody, if you haven't read the book, “The Effortless Experience,” it came out back in 2013. Matt Dixon, Rick Toman, Rick DeLisi. I mean, great, great book. I still highly recommend it. It's not necessarily top on everyone's use case list, but I've seen more prediction using that metric than anything else to really predict the business impact of your experience with a call center or a website. Cause you can look at customer effort by a web measurement, a person measurement on chat or on phone. It really can be anything.
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Key Metrics for Contact Center Leadership
Rich: Well, that's interesting. And you bring up another question, which is when you're looking at being a leader or an operator or director in the call center and customer service and support, what are those metrics, like the high level metrics that leaders should be looking at? You mentioned customer effort score, but I'm sure that that's not the only one.
Sean: Yeah, customer effort score is kind of a hybrid score. So if you think about it, there's a lot of like Net Promoter Score, for instance, is primarily a relationship metric and really should not be tied to a transaction. It's really more just in general sense, you know, what you're likely to recommend. It's measuring loyalty to the brand and the organization. Everything goes into that. You've got things like overall satisfaction or customer satisfaction that are pretty commonly used in contact centers. And but they're aimed at how satisfied were you with the agent? Now, like I said, there's nothing wrong with that. And you can absolutely ask about how did the agent treat the customer or the client. The reality is I've never seen that or the results of that predict a customer behavior. It's more to grade the agent and you use it, a lot of companies use it to kind of grade the agent in their performance.
The effort score though is in between that. It's both transactional, but it's also loyalty predicting. So it allows you to look at the transaction and say, hey, again, high effort, more likely to be a detractor, more likely to be disloyal. But it also can look at and say, high effort, did the agent contribute to the high effort? Was it a process issue? What was it that made it high effort for the customer? And in many cases, the higher the effort or the more channels I have to use, the higher the effort. I mean, that makes sense, right? If I have to try three or four channels for resolution, my effort, it gets a lot harder. And so what we see is that impact. And then the understanding of that allows us to look more broadly, across the organization, but you don't have to stop there.
Contact centers have measured, I mean, we've been measuring so much for so long, handle time, hold time, talk time, after call work, service levels. I mean, we measure everything in the contact center. And what I'm now trying to say is use those measures for other purposes besides just administratively, I'm making sure we're doing what we need to do. Because again, when I look at high effort, there are other activities, you know, lack of first call resolution, huge predictor of high effort. A lot of call centers measure FCR, first contact resolution. Handle time could be a predictor. If it takes a long time to handle and take care of a certain call type, that can predict high effort. Hold time predicts high effort because maybe the agent doesn't know what to do, and they're putting the customers on hold too often because they're not trained very well on said call type. So, all the metrics that we've been measuring in the contact center that come from our phone system or any quality tools or anything else, the reality is there's multipurpose for those. It's just looking at that in a new way and saying, hey, I want to make sure, yes, I'm measuring the performance of the agent, but also heavily focused on the experience of the customers. And sometimes that has to do with the agent and a lot of times it doesn't. And that's where contact centers are the only group that can put really a heart and mind to the customer situation because they're in there with the customer talking to them about it. All the other channels are just technology.
So think about the power that that gives you to be able to go back to as a contact center leader, back to your business partners who run the web team or the mobile app team or whatever, and share with them all that data you have and the findings that are saying, here's what's making things hard. That's the kind of collaboration, the new generation organization and the lead that a contact center can take in a new organization instead of just cost center really switching over to being a value center because of all that knowledge and understanding of what's going on.
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Predictive Analytics Enhancing Customer Experience
Rich: So when you're saying like there's all these metrics that they have to measure, does predictive analytics play a role in having all these things and like delivering? How does that work? How do you get actionable results from all that data?
Sean: Yeah, absolutely. And that is, you know, that's a key, right? And, you know, again, predictive analytics isn't new either, but fundamentally it's, it's getting easier because a lot of us are putting our data in the cloud. Our data is now more joined. We can start to use it in that way. And so, yeah, using as an example. So what my rocks program, for instance, does, it basically looks at all of the relevant data associated with experience, you know, call center metrics, operational metrics, survey results and survey metrics. It looks at text analytics and journey analytics, the stitching together of the actual physical journey of the customer. And it uses AI to predict high effort, low effort across those scenarios.
So think of it this way, you can look at, for instance, your call transcripts and tie that to this post-call survey, because again, we all know. customers don't leave, most customers don't leave comments and most of the comments we get are kind of useless. But you merge together and use AI to study it, you can now look at the call transcript and say, what out of the calls is predicting high effort or lack of loyalty or sentiment or things of that nature? And then that predictive analytics, you train your models on the past data and now you can predict the same metrics, survey metrics if you wish on all the transactions that never took a survey. You literally can look across all your transactions and predict what their experience would have been or what their score would have been. And now you take proactive action to go after those clients and say, hey, we noticed this was occurring or even better, some of the tools and some of the vendors out there are getting even faster where you can almost do it in real time and you can interrupt the bad journey. And try to redirect it in a positive way.
And so those tools are becoming even more and more available using AI and using the power of data analytics, bringing those things together. And certain activities and certain metrics will predict certain results better. That's part of the predictive analytics you run. I mentioned earlier, lack of resolution, the No. 1 predictor of high effort. Not the only, but the No. 1, the highest correlation between lack of resolution and high effort.
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Overcoming Tech Implementation Challenges in Business
Rich: We've talked about a lot of different technologies here. We talked about CTI, IVR, generative AI, predictive analytics. So, you know, looking more holistically, what challenges do companies face when trying to actually implement these? Because I think a lot of people are behind the curve on some of this stuff.
Sean: Yeah. Well, I think... More often than not, in my mind, when I talk to folks, it's more about strategically, am I using what I have in the right way? A lot of companies, not all. Now there are some companies that are truly behind. They actually don't have call transcripts or things of that nature. But for the most part, today's modern organization, they're at least at a sampling level, they're transcribing calls, they're doing that sort of thing. And they're doing it because if someone calls in and complains, they can pull the data and things of that nature. But I'll use an example. I was talking to one company recently and I said, OK, do you record your calls? Yes, we record 100 % of our calls. Great. Do you transcribe those? Yes. What do you use that information for? Well, if someone calls in and complains, we go look up the call. And… that was it. They weren't thinking kind of more strategically about, oh, well, we're looking at the call transcripts and we're pulling out of those calls, the calls where the client says, hey, I had an issue with your website. And then we're summarizing that and analyzing it and we're handing it off to our digital partners. That's an opportunity, right?
So this idea that organizations, even if they're behind, they're probably not as far behind as they might think because they usually have a lot of this data and it's using it in the right way in this kind of new way of bringing the data together and aggregating and thinking more holistically and breaking silos down, you know, in the organization, it's just that step alone. But I do look at it and I'll just say, you know, I think the key is you got to get started. You got to take steps in that right direction and be able to really understand what's available to you. And most companies, I think, can catch up a lot faster because the technology is not as expensive anymore as it used to be. For sure. And I know text analytics for me, unstructured data, getting a hold of that and being able to pull in survey comments and the survey data, transcript data, I've already said it several times, CRM notes, and just study all of that content, that's a game changer for most organizations. And that's a great place to kind of think about starting if you haven't, if you're not there yet. More so than trying to do journey analytics or other things that get a little more complicated is just that unstructured data and bringing in, there's so many vendors out there that can help you make sense of that.
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Practical Steps for Contact Center Tech Adoption
Rich: So we are almost out of time here. Thinking about everything that we've talked about today, what advice would you give to leaders who are in contact center operations looking to adopt these technologies?
Sean: I'm actually going to carry on a little further what I just said. The biggest thing is getting started. And I translate that into steps associated with the letters of “started.” But the first being surveys. That is one of the best places to start. Most of you already have it. But not just surveys for like OSAT. Focus on and making sure you're asking about the experience, not just about the employee. Make sure that's part of your surveys. The “T” is “transactions.” You've got to know what the customers are doing. And again, we track that. We know how many people are doing certain transactions. It's data that's available. Surveys plus transaction, you start building on itself, right? The “A” is “associate notes.” Now you're starting to bring in the notes and the information from the customers. “R,” under “started,” “R” is now about “resolution metrics.” Again, a lot of us have that. We understand what the resolution is. “T” now starts to get “transcriptions.” Now it goes into it. Now it's halfway through the word, if you will, transcriptions, even though I said that's a great place to go. Because again, that may take for some organizations more to get to that point, but transcriptions. And then the “E” is “emotion,” emotion, sentiment, really understanding that. Again, it's something that comes out of that text analytics.
And the last is “digital.” That's sometimes the hardest and the most complex because if you've ever seen web logs for a customer interaction, making sense of that can be very, very difficult because there's so much data there. That's why I put it as the “D” is the last plus the word ends in “D.” But. The reality is that progression is exactly what leaders need to be thinking. How do I start to keep moving down into those next level of analytics and the power that they can give me? Because again, most organizations out there are focused on their silos. They've got their blinders on for what's important to them. The contact center can't afford to be that way. Because that contact center is the, in many cases, the last defense against customer churn, they have to be looking ahead, looking at the other channels, looking at all of that activity on behalf of the customer. And again, putting that heart and mind into that understanding because nobody else is talking to the customer except the contact center. So the power that that gives this new age contact center, the ability to change from just cost center to value center, that's where you start to win in the business. And it takes the contact center to be the lead in that.
Related Article: Building Winning Customer Satisfaction (CSAT) Surveys
Connect With CX Expert Sean Albertson
Rich: Sean, I just, I wanted to say thank you so much for sharing your insights with our audience today. We have about 30 seconds here. Can you share where our audience can follow you and catch up with what you're doing?
Sean: Absolutely. Well, you're always welcome to follow me on LinkedIn, Sean Albertson, but my website is CX4rocks.com.You can connect with me there. You've got some information and I'm a professional speaker now, a workshop facilitator trainer, and then a coach on all things CX. So happy to talk to anyone and love to connect with folks about this. Cause again, I'm passionate about the experience, but even more so I'm passionate about the role that the contact center can play in that experience.
Rich: Sean, thank you again. And thank you everybody for tuning in to “Beyond the Call.” This has been great and informative and I look forward to our next conversations.
