Enterprising Insights, – Contact Center New Product News, Episode 27

Hello everyone. I'm Keith Kirkpatrick, research director with the FU Arm Group, and I'd like to welcome you back to Enterprising Insights. It's our weekly podcast that explores the latest developments in the enterprise software market and the technologies that underpin these platforms, applications, and tools.

This week I'm gonna address a couple of contact center focused product announcements that have come out recently, namely Microsoft Dynamics 365 Contact Center and Cisco's WebEx, AI powered, self-learning contact center. Then, of course, I will address my weekly rent or rave. So let's get right into it here.

So there are a couple of announcements that are being made this week, uh, around contact centers. And when we're talking about contact centers, we're talking about contact centers as a service. So essentially it's cloud-based.

And the idea here is that what these companies, what these vendors are trying to do is really enable some of the functionality from, uh, you know, ai basically enabling AI within these contact center things to make customer experiences more seamless, uh, less, you know, full of friction, and of course, hopefully helping out both the end customers as well as the agents who are serving them. So let's take a look at what Microsoft is doing. So Microsoft is announcing the Microsoft Dynamics 365 contact center.

They're turning it a co-pilot first solution. Their goal here is really to engage or help customers engage and deliver exceptional customer experiences across all of the service channels. So when we're talking about, uh, this Dynamics 365 contact center, uh, really what they're talking about is this comprehensive, comprehensive vision for delivering service.

So it's going to really, uh, encompass not only the contact center functionality, but also pulling in things like CRM, generative ai, uh, you know, CDP, all of these different solutions, uh, all within a common platform. And the goal here is, there's really a few different things here that they're trying to do. One is make it easy to integrate all of the data from across the organization onto a single platform that just makes things much easier for it.

And also, in terms of actual utilization of the services, you're not having to go out and grab data, uh, or processes from a, a bunch of different unrelated platforms. Uh, the other thing that they're really kind of leaning into, of course, is copilot. And as everyone is very much aware, uh, Microsoft has leaned in heavily to delivering copilot across their experiences.

Uh, so this is essentially, uh, what they're trying to do is make it easy for, uh, customers and agents to interact with data and processes, uh, within the workflow that they're going in that, that they're using at the time to really bring in that generative AI functionality. Uh, so that can be anything from self-service routing, uh, to agent assist services, uh, post-call, wrap up analytics, you name it. They're trying to incorporate ai, particularly generative ai, to make things work more smoothly.

So, a couple examples. So let's say I'm a customer and I have an inquiry inquiry and I, uh, interact with, um, you know, a self-service application saying, I need help with something. Well, in many cases, if it's an easier request, the idea is to let the AI take care of that request automatically.

Uh, but what they're also trying to do is intelligently assess what is the caller or this, this person coming in through an SMS text or an app really trying to do. Basically, they want to try to find out or use this technology to identify intent. And in some cases it means, well, the best case is not to actually have someone, uh, get shifted over to a, a full bot service, but actually get routed to a human agent who has the right experience, knowledge, and tools to handle their requests.

So what the goal here is, obviously is to reduce that friction of going through an entire process with a bot only to be told, hold on, we're going to connect you with an agent. Their goal is to make sure that you're able to get to that agent right away. 'cause that will speed resolution, it reduces friction, and it makes the experience for the customer so much better.

We all have this horror stories of going through this endless process only to wind up with an agent. Anyway, uh, some of the other things that copilot can do, uh, within a contact center, uh, framework, uh, you know, assisting agents, so serving up knowledge to agents as they're working on a case, because this system will be basically incorporating all of the, you know, customer data, relevant customer data. When was the last time they called, what do they call about?

Uh, what types of products have they purchased, uh, what service agreements do they have? And then kind of, you know, serving up that information to the agent so it's at their fingertips so they don't have to hunt for that information. Uh, using generative AI to generate emails or communications.

You know, essentially if, if a, an agent has to reach out to a customer, they can generate an email for them. Obviously the agent still has the final word, it has to look, or they have to look over this content before it ever goes out, but it really is sort of a starter, you know, so, you know, the hardest thing is to actually write from a blank page. Uh, this gives them the, the relevant information they need to actually initiate that communication.

And then of course, something like call wrap up. Uh, one of the most difficult things for a contact center agent, whether we're talking about someone who's dealing with someone on the phone or through a text or through an app or what have you, is when that interaction is over, they need to capture quite a bit of information. Uh, it's not what they do best.

Uh, these, a lot of times these people haven't been trained on that by using AI to actually listen in and capture all of the steps that we're taking during that interaction, number one. And also wrapping up all of the other, uh, you know, notes about the interaction. You know, was the customer upset?

Uh, did they take these steps? What actually happened on that call? By using generative AI to capture all of that information, uh, it saves a lot of time with that post-call wrap up.

Uh, and it also, um, improves accuracy a lot of the time. And, you know, certainly people try their hardest, but sometimes it's difficult to remember exactly what went on throughout a call, particularly if that interaction was, was quite long in duration. And then of course, the other thing that Microsoft is talking quite a bit about is scalability and reliability.

That's critical in today's world, particularly for, uh, services that are targeting large enterprises. Ones that may, you know, have sort of a fluctuating demand in terms of number of agents that you're using or, or volume of inquiries. Uh, you know, we look at something like retail where obviously they're gonna see a real bump up in traffic and inquiries around the holidays, both in the pre-holiday season, throughout the holiday season, and then afterwards for dealing things with returns and that sort of thing.

So that's one of the things that they're really, that Microsoft is really kind of trying to market in these services. And I think when we, we think about, um, what they're doing here, Microsoft is doing is they're trying to basically extend, uh, uh, their market footprint. Uh, obviously they've had a strong sort of, uh, hold in the marketplace when we're thinking about Dynamics 365, uh, you know, in terms of productivity, um, you know, certainly, you know, they've tried to make inroads in terms of being sort of the ERP, uh, of record for small to medium sized businesses.

And what this does is gives them another application that they can then in turn go out to customers with and say, okay, you know, we have all of these applications available for you. They're all on the same platform. They're all going to be working together very seamlessly.

Um, and of course, when you do that, the actual cost to implement should be lower. So that's one of the things that, uh, is really coming up quite a bit today, is this whole idea of a, you know, how can we maximize our investments, minimize our costs? And of course, you know, the biggest thing is it's time to value.

When you think about the whole implementation process of putting in a new system, or even putting in a piecemeal system, you wanna make sure that you're able to get up and running very, very quickly. And the reason for that is when you see things like generative AI come in, you don't wanna have this long deployment cycle, because by that point, the technology will have, uh, the technology cycles would've cycled through a couple of different times. So you're really behind in terms of certain functions.

So it's important to be able to quickly get value to implement and get value out of each investment that you make. Um, and the thing I, I think Microsoft, like a lot of these companies, has realized that, and that is why they're leaning heavily into, uh, this idea, this platform play of making it, uh, super, uh, a lot more simple to, to implement, uh, whether or not you use all of Microsoft's tools or you have to integrate with, with another, uh, solution, uh, they're still trying to do what they can to make sure that that process is as seamless as possible. Now, I'd like to talk about another announcement that came out this week.

Uh, and that is Cisco. They actually, uh, announced their, uh, AI powered contact center. Uh, obviously it's branded under WebEx, and they're talking a lot about their new AI assistant for contact center capabilities.

And you know, like Microsoft, they have, you know, sort of similar use cases for ai. So things like, uh, agent summaries, uh, call summaries, uh, suggested responses, call wrap up. Uh, they actually also include things like coaching highlights.

So if an agent is, you know, has an interaction, there's something that could have been handled differently or better, uh, they'll actually get coaching, uh, you know, through the application. And, um, another one is, uh, that's pretty interesting, is sort of an automatic CSAT score, which is, uh, for those who are not familiar, uh, that's a customer satisfaction score. Uh, that's pretty interesting because if you think about what organizations are trying to do is quickly identify when there's been a lapse in customer experience.

If a customer is not satisfied after an interaction, they wanna know and they wanna know quickly. And, and, and, and of course the most important thing is they wanna try to identify the root cause of that. And that's where they can kind of look back through the interaction.

What happened? Did it take too long to service, was an issue with the product, was an issue with the interaction that was going on? And being able to do that and identify that very quickly can be really powerful in terms of delivering, uh, a better customer experience.

Uh, one other thing that that's really interesting, and you know, WebEx is doing this, is they actually have this burnout detection feature. So that's really interesting because when you think about the life of a contact center agent, it is not an easy job. Uh, they have incredible volumes to deal with in terms of interactions, whether we're talking about phone interactions or text or, uh, app, you know, uh, web app application, uh, communications, all really, it's very high volume.

A lot of times they're asked to handle multiple interactions at once. And let's face it, a lot of times, particularly if we're talking support, you're not dealing with happy customers calling up to say how happy they are. Almost nobody does that.

You're dealing with angry customers who are frustrated, who are automatically gearing up to having a negative experience just because of their past history of calling up agents and not getting what they need. Uh, so what they're trying to do with this is identify, you know, what it is that, um, you know, if there are certain things going on in interactions that are indicative that an agent's performance might be slipping or they might be slipping into a bad habit, whether it's sentiment or, you know, sort of tone of voice, that sort of thing, they're able to identify that. And then you might, um, you know, and, and I think the goal with all of these things is to just assess when an agent is having an issue so they can be pulled out of a heavy rotation for difficult calls or, or whatnot.

The the idea really is to make sure that, uh, agents are taken care of because it is a very stressful job. And the, you know, you know, being a contact center agent isn't on the top of anybody's, uh, list, generally speaking in terms of, you know, jobs that, uh, you know, people are clamoring to do, uh, right now. So they are having a labor shortage.

So anything that companies can do to retain good agents and also keep good agents from becoming bad agents is, is certainly welcome in the industry. Uh, one of the things that I was, uh, you know, that I found pretty interesting as well is that, um, uh, Cisco actually released a few numbers here. I believe this was from a early, they're early beta users.

Uh, they actually surveyed them to identify what, um, you know, how well everything was working. And a few of the stats here, I think they said that, uh, in terms of AI customer feedback in the contact center, uh, they were able to generate, you know, using ai, um, they were able to generate, uh, a three x re uh, faster response rate to customers. That's really important.

Uh, again, we live in an instant, you know, instant gratification world where you want an answer right away, it can't wait, customers won't wait, whether it's fair or not, you know, speed is everything. So that's really interesting to see how AI can improve response time. Uh, we also, uh, the, the, the survey also found that they were response for 80% of the responses were, uh, or, or of agents actually will reply more accurately with suggested responses.

So that's really important when you think of an agent who is asked a question on the phone or through text, if they're not able to, you know, look up the correct information, a lot of times they may just respond with something that might not be correct. If AI is able to suggest a response that is correct, that is grounded in company data. And when I'm talking about grounding, I'm talking about the AI model will only use the data that has been specified as being this body of knowledge that they, you know, are, that it is allowed to grab from.

So that's a really important thing, particularly when we are looking at, you know, certain, certain support things where if we're talking about a customer who has a question about an insurance policy or, you know, something where, where there are real consequences to giving a wrong answer. So that's a really interesting stat. Um, another really interesting stat is that of these early customers, they also said that agents, 93% of the agents can get up to speed with customer history and context of the call, uh, faster with virtual agents and drop call summaries.

What does that mean? Well, that means that, you know, the, there's just much more information provided in context to these agents. You know, about the interaction with the customers, uh, with their history, which is really great to see.

So for example, if, if I call up a customer service agent and I don't get through whatever, and the call has dropped because either I drop it or, you know, something happened technically, well, in the past, an agent wouldn't know that. They wouldn't know that I tried to call three times and I was having a problem getting it through, or I had too long of a delay or whatever the issue might have been. Now these agents are actually provided with that information automatically so they can open the call with, hello Mr.

Kirkpatrick. I just wanna first say, I'm so sorry you've been having difficulty getting through to us. Please tell me what your problem is right there.

You've automatically knocked down one of the big barriers to a, a, a positive customer experience, and that is demonstrating empathy for that customer situation. You automatically acknowledge, Hey, I know you've been having issues getting in touch with us, how can I help? So that's a real game changer when you think about the, uh, the, the typical nature of customer experience and customer support where, you know, you don't know who you're gonna get and they don't know you and it seems like they don't care about you.

Um, and then I think the, the last one is really important here. You said that 80% of agents, they have clear noise free and distraction free conversations with this technology that WebEx has included. Uh, it's called noise removal and voice to optimization.

What's this, what is this doing? Well, it's essentially removing the static, the background noise, everything that gets in the way of being able to clearly understand what the speaker on the other end of the line is saying. Uh, again, it's amazing how simple that concept is that if you have a clear line, communication is easier.

Um, so it's, it's, it's absolutely, um, it imperative today when we do have voice conversations that people can understand each other. I think, you know, the other thing that, that comes up and, you know, um, sometimes contact center agents, they may, uh, not be speaking in their primary language, and sometimes when you have accents involved, it makes it more difficult for people to understand each other. If you add in background noise, you know, then it can become really, really difficult when you remove it.

It just clears the path, you know, to better understanding and communication to people, uh, between people. So I think that's a really interesting and, uh, you know, powerful stat, uh, that came out of this sort of early, uh, test run with the, with the service. So, um, you know, again, I I'm gonna be writing some more, um, writing some more about both of these services over the coming week.

Uh, but I just wanted to kind of highlight a a couple of things there because I do think that we're seeing AI now become a, a real catalyst for, for really improving customer interactions. And really the contact center is the first stop on this journey with, with interactions anymore. It's rare that you have face-to-face interactions.

Um, I don't know anybody who writes a letter to companies anymore. I assume that they, they, they complain, they tweet about it now. So, um, so this is a really, really good step for the industry for, for ev any company that use utilizes a contact center.

So with that, I wanna move to my rant or rave segment. Uh, this is again, is where I pick something in the market and I either champion it or I criticize it. And today I have a, uh, trying to be topical.

I do have a contact center rant. Um, this one is related to, uh, well, there, there's, I'll give you the situation. So I took my car into the dealership for service a couple of weeks ago.

I had a, actually had a very good interaction there. They took care of what needed to be taken care of. They said to me, do we have two open recalls?

Would you like us to take care of it? Yes, thank you very much. I would love you to acknowledged repairs were done.

All good. Then about, uh, that was about two or three weeks ago. Then about, uh, a day or two ago, I started getting multiple phone calls to my home phone, to my cell phone.

I got a text, actually a couple of texts and a couple of emails all asking me or letting me know that I had an open recall on my car. And I thought to myself, I don't know if that's true 'cause I was just at this service center and, um, I just thought that was strange. So then, uh, I finally picked up on one of the calls 'cause I was tired of it interrupting for me, and I talked with the, uh, young lady who called and said, oh, you have a service.

I'm sorry, you have a, an outstanding recall. And I said, well, can you check that? 'cause I was just in.

So she checked, it took a little while, and then she acknowledged and said, oh, oh, you're right, sir. Uh, I'm, I'm sorry. Thank you very much.

Goodbye. So, a couple of things here that I'm gonna rant a little bit about. Number one, they should know this information.

This should, should all be in their CRM or CDP or whatever they happen to be using to contact me. Uh, the fact is, it was acknowledged that they took care of those, you know, previously open, you know, uh, recalls. It, it shouldn't have even been a phone call.

Um, this is what these systems are for, is to keep track of all that so you're not wasting the time and effort and annoying customers with basically irrelevant calls. Second thing would be, uh, when this young lady, you know, did call me and I explained that no, I already had the recall taken care of, uh, there was a missed opportunity there. Um, not saying I want to be sold every time I hop on the phone, but I do feel like they could have said, okay, I'm sorry sir.

Um, but you know, did you know we're running a special on this? Or, you know, did you ever think about this? You know, there were, there were a number of different upsell opportunities.

Uh, and of course the other thing that was, was missing was, uh, the, um, you know, just the what would you like to schedule your next service appointment? Very, very basic, not hard to do. It's rare that you get people on the phone these days.

Uh, so again, I think we're looking here at two things, training issue and a data issue. And those are two things that AI probably isn't going to be the solution. I think it comes down to really making sure that people are trained and they're the right processes within the systems to handle those things.

And, and really this can make all the difference in the world, uh, in terms of customer satisfaction, making sure that customers feel like, you know, that, you know, in exchange for all the data that we give our, all of these companies, that they're actually listening and, and being active and being present and understanding who we are, we're how we've interacted with, with the companies in the past. So anyway, that is my, uh, rave for, or I'm sorry, my rant for the week. Uh, not terrible, but I do think it's, uh, you know, an interesting aspect in the market that, that we do have the technology to handle these things and yet in many cases, it's still not being done well.

With that, that's all the time I have today. So I want to thank everyone for joining me here on Enterprising Insights. I'll be back again, uh, in about a week with another episode focused in on the happenings within the enterprise application market.

So thanks everyone for tuning in and be sure to subscribe, rate and review this podcast on your preferred platform. Thanks, and see you next time.