How AI and Automation Are Changing Customer Service as We Know It

Summary

This webinar discusses the crucial role of AI and automation in customer service and how they are changing the landscape of customer contact. The focus is on practical examples and the real benefits of using AI to improve productivity, enhance customer experiences, and build lasting relationships. AI is utilized for automating level-one support, augmenting agent support, automating routine tasks, predicting outcomes, and automating complex business processes. It also addresses common fears associated with AI adoption, such as job displacement. The session emphasizes the importance of AI in delivering personalized and efficient customer interactions, making it a paramount component of future contact centers.

Key Takeaways

1. AI and automation play a crucial role in transforming customer service, leading to increased productivity and improved customer experiences.
Practical examples showcase how AI can automate level one support, assist agents, handle routine tasks, predict outcomes, and streamline complex business processes.
2. The fears of job displacement due to AI adoption are discussed, but the focus is on AI as a tool to enhance agent performance rather than replace them.
Personalization is key to building lasting customer relationships, and AI can assist agents in delivering personalized and efficient interactions by providing real-time information and context.
3. The future of customer service will involve AI-powered contact centers, where agents act as trusted partners, focusing on building brand equity and customer relationships, while AI handles repetitive tasks and provides valuable insights.

Transcript

We’re about to jump into one of the most paramount pivotal hot topics you can possibly discuss when it comes to the customer contact space. And that’s the role of AI and automation and how they’re forever changing customer service and how those changes are only gonna increase as we approach the contact center of twenty twenty five as we move into the future of customer contact. Now what’s so powerful and so important about this topic is it’s not one of those.
Let’s invent some really cool technology. Let’s explore an amazing solution and then try to figure out the use case. The reason AI and automation is such an important topic. The reason why it needed to be such a paramount component of this agenda is because it’s driven by realities in the customer contact space.
As we’ll share here, there are some clear challenges, some very obvious and powerful opportunities that directly tie to the benefits and the applications of AI and automation. They’re and as they create a necessity for it, This is purposeful technology. This is not random. Let’s sell something and hope it works with technology.
And that’s why I’m so thrilled to welcome our speakers right now. We have Gary from Paddle as well as Taylor from Kustomer. Gary, how’s everything going?
And, again, this is something that you and your organization focus on so intently. Now what’s so exciting about getting to share this with our audience when it comes to the contact center of 2020?
Yeah, absolutely. No, I’m super excited to be here. This is something that we have a large focus for the remainder of this year and then going into the next. So I’m excited to unpack this a little bit.
Cool. I’m thrilled to have both of you. Gonna jump into some statistics and just really create that context because, you know, I just promised the audience that there’s there’s meaning behind this. There’s a reason why we’re focusing on this area. And so some of these stats will really bring that to life. And then I’ll pass it back to you, gentlemen, to really walk through exactly what it’s going to take to make AI and automation work in your organization and what some of those amazing benefits can look like in practice.
So the key here is that it really is time for something new. It’s time to move forward when it comes to the world of customer contact.
Across our two thousand nine CTW digital reports, we’ve identified a few areas where there’s a real opportunity to do something better.
First of all, productivity is not what it needs to be. As of right now, only thirty two percent of contact centers fewer than one third believe that their agents are able to spend the majority of their day on meaningful work. High priority tasks, real engagement with customers. This is supposed to be the era of connecting with customers and making them feel valued and either agents in the majority of organizations are not able to commit to that the way they want to.
Additionally, technology, which is supposed to allow for that. It’s supposed to handle those simple tasks so that agents can start to focus on more complex interactions that’s not happening the way it needs to with only twenty percent saying that technology is creating that opportunity. And so, clearly, there’s a productivity challenge. But even if we were able to put agents in position to focus on meaningful tasks, even if we were able to have them spend their entire days connecting with customers, it turns out that they don’t have the context they need.
We’re seeing a lot of scenarios where customers have to repeat information when moving between channels or when escalating from self-service to live agents. In fact, in about twenty percent of cases, agents have no context whatsoever.
When a customer escalates. It’s as if the customer was not interacting with your brand, which is bad for the customer and bad for the agent because now The agent has to start from scratch. They’re gonna be slower, less productive, more frustrated, and that’s not the environment we wanna be creating. And then perhaps most importantly, that final experience for our customers is also suffering as a result of these challenges.
We identified the pain points in our consumer survey where we interviewed thousands of real life customers about what their experiences are like, and they’re still complaining about those same old things, long wait times, frequent transfer needing to repeat information.
Many of them don’t feel as if agents know them during interactions. And as organizations start to push them into self-service, they’re not really trusting these channels to get the job done.
So, yeah, to put it simply, we’re ready for a change. But the good news is organizations do understand the importance of moving forward. Ninety five percent of contact centers are recognizing that they need to start preparing their teams for the impact of AI and automation with eighty one percent saying they’re already getting started. Now not everyone’s taking the right path, and certainly we’re gonna share some recommendations for making a more meaningful transition moving forward.
But the idea is the intention is there. And customers are cool with it too. You know, from their perspective, the best kind of application of AI is going to be chatbots, and seventy two percent of customers are open to using them if they become more effective than they are right now. And so right now, we have a scenario where there’s a lot of productivity gaps, a lot of customer experience gaps, there’s an opportunity to really leverage automation technology to correct those.
And I’m gonna just pass it over to Taylor to walk through exactly what this landscape looks like and how we can use this technology to create a stronger more customer centric contact center of twenty twenty five.
Excellent. Yeah. Thanks so much. Yeah. So just to cover what we’re gonna discuss here today, I’d like to get into the rise and worries about artificial intelligence in the customer service space, how AI and automation are currently being used for customer service teams how AI can actually support building relationships with your customers and how AI is shaping a future of not only customer service but also the role of customer service agents of the future.
So lots to discuss here, and let’s begin. So in, It’s predicted that one hundred and forty three percent, of customer service teams, there’ll be an increase and the adoption of AI technology, meaning that this technology is something that can’t be ignored for both consumers and for businesses.
But the reality is that many people are still suspicious or nervous about AI and its implication for their business. And I think this quote from Anne Marie Stagg highlights that those fears, at least in a case of customer service, may be somewhat misunderstood.
Gary, I’d like to kind of understand what you’re seeing in terms of the fear of AI, in customer service.
Yeah. For sure. We kind of had several fears from our own teams when we started growing at AI.
A lot of the common fears, I guess, everyone’s probably heard before. So, you know, am I gonna be replaced by a robot?
There was also quite a lot of fear about whether or not they’d be allowed to kind of show their personality and actually be, like, like, more human.
And I guess for us as well, like, what kind of shone through more was a lot of our own staff.
They kinda own customers’ problems and want to make sure they actually deliver, like, really good interactions.
And they’re kind of afraid that kind of infant AI would stop them from actually doing that. And, of course, all these are kinda like their rational fears because, obviously, in the past, whenever you kinda had automation sorry. Whenever you’ve ever had automation, you tend to actually kind of have people’s jobs sometimes been at risk.
Got it.
Yeah. So I think that’s a really good point. And the reality that we see on our side is that AI does not mean that robots are taking over jobs of anybody or customer service agents are going to be displaced necessarily.
Instead, that customer service agents are actually handling more complex issues that AI can assist them with. While at the same time, it helps automate a low level and repetitive task.
Garry, I wonder what your perspective is on that?
Yeah. I mean, for us, we kind of have two kinds of customers at Peddle. We have some that we’re kind of trying to build relationships with, and we kind of want to deliver a much more personal service to those people. But then we also have customers where there’s actually quite a lot of volume and we’re trying to deliver, like, a one touch really good experience for those people. And that’s what we call transactional support. And so for us, like how we use AI, it’s a bit different in both of those cases.
But for both of them, we add on the side of doing what we call, providing agent assistance. So rather than having our AI at the forefront of our interactions, It’s behind the scenes really helping our agents deliver for us.
Awesome.
So let’s discuss how AI is actually being used today, by customer service teams.
Oh, according to Deloitte, eighty two percent of early AI adopters for customer service have reported a positive ROI.
And while AI’s penetration in the customer service industry is still relatively low, the results so far are obviously very promising.
As important, to discuss some use cases with AI, simply because it has such broad applications.
And there are really five that jump out, from my perspective. And the first is automating level one support.
Now this is more about self-service opportunities and information gathering. Think about things like chat bots which can instantly serve up basic information to customers. Things like auto populating useful data, like contact information or related incidents from multiple systems, or providing real time suggestions to requests based on issue type or location.
There’s also the case of augmenting agent support which is where we essentially improve agent performance through AI assistance. We could do something like making recommendations or suggesting the next best action to take for instance.
AI can also help automate routine tasks, things that may be manual or repetitive that don’t require human intervention. This can be things like tagging conversations, issuing refunds, prefilling fields, or creating invoices.
Also, predicting outcomes for management is another way that AI can help improve performance.
This helps address cases like keeping track of SLAs, managing the workforce depending on how busy a certain time of day or year it is, or even proactively engaging a subset of customers based on a recognized pattern.
And lastly, AI is also very good at automating complex business processes.
So, for example, at Kustomer, we have a system called queues and routing, where conversations can be classified and routed to the best and most appropriate agent for a speedy and personalized resolution.
Gary, do you wanna talk through a little bit about how Paddle is currently leveraging AI? On your side?
Yeah. No. Absolutely for sure.
It was quite interesting obviously at the start of the presentation and we talked about some of the common mistakes that we are still seeing, like, a lot of contact centers make. And for us, this was the kind of thing that we wanted to do with AI.
And so I’m sure you’ve all had those experiences where you get put on hold for a lot of time. And that’s kind of something that we know we’re quite guilty of ourselves.
And so behind the scenes, because we handle kind of taxes and, like, a VAT and a lot of other things for, like, all of our purchases, We actually have quite a few different systems that our agents actually have to go into in order to help some of our customers And so quite often we get an interaction where because, you know, the system’s door disparate, we’d actually have a problem that we’d have to put some on hold maybe for five, ten minutes while we try and dig down and find details to help them.
And so for us, we wanted to cure those kinds of problems.
So I guess that the best way to frame it, in my mind, is, kind of how the customer feels about an interaction. Is just as important as actually helping them as quickly as you can. And I’m sure we asked everyone on the call today to kind of describe the best customer support experience they’re probably gonna tell us that it was kinda fast and efficient, but there’s gonna be something else that kinda made it stand out in their mind as to why it was excellent.
And the chances are that excellence was actually driven by a human being, kind of, given a personal touch.
And so these three topics are kind of roughly on that kind of improvement.
The first one is kind of like real time information gathering. So this happens in all of our calls and it’s very, very seamless. So the customer doesn’t actually know what’s happening.
But in the background, when we take a call from our agents, the AI actually listens into that call, and it’s basically acting as like a friend to our agent And based on what the customer says to us, it then tries to dig down into all of our systems and starts putting together the story of that customer in real time. And one of the great things about doing this is it actually lets our agents have like a personal conversation with the customer And, obviously, they can show the empathy to the customer and try and, like, to talk them about what’s actually happening, but it kinda comes across very and there’s no pause to the customer saying, you know, I’m gonna have to go and check into these different systems.
I’ll get back to you in five minutes or so. It just kinda happens as an immediate kind of phone call. It kinda goes through from getting to the end with no real breaks in the background, the AI is what’s coming to leverage that power.
And then for automated workflows, this is more on our side where we’re trying to build relationships with some of our customers. And one of the key ways to do that is to actually bear with me, make sure we understand a lot of their policies. One thing that happens, especially in our customer automated workflows is as we get a new ticket that comes into our system, the workflow is actually going to look up all the details about that seller. So our sellers can actually do things like they can give us their kind of refund policy, they’re guaranteeing it.
And we can actually use that, within the workflow during the interaction. So as soon as the agent opens the ticket, all these details are actually at their fingertips, and it actually lets them craft a much more unique personalized variant to those customers.
And then lastly, we are also currently looking to try and help customers self-serve more. And we’re kind of doing that more in our transactional level simply because there’s actually, like, a really high volume.
So for, I guess, to put in context, this is where people are saying to us, you know, what have I actually ordered from you underneath my license fee. These are all pretty simple interactions where we think AI probably can have a real big impact to help those customers get a resolution much more quickly than actually waiting for a human agent. And one thing I would say is we all think it’s really important customers should be aware that they are actually dealing with an AI. And so for us, we always make sure that our AI, it kind of identifies itself as it’s there to help them, and it will try and help them while they’re waiting for a human. But we also give the option to update using AI and actually just wait for a human to come available because every customer is obviously different. Some customers like to use AI, and some customers don’t. And we also think it’s important to respect that choice.
I guess, for us as well, one of the biggest impacts that we’ve seen is because of freeing up all of the time for some of these basic interactions, it’s actually enabled our agents to kind of spend much more time on the complicated problems. So in the past, when things started getting complicated, our customers would typically have a much worse experience because the agents just feel that they couldn’t give the time to kind of give that a proper resolution. But now because we kind of freed that time, our agents can spend that time and make sure they really can deliver a personalized experience to those customers and really actually help them with those problems.
And so I guess, for me, Taylor, that’s really like how we’ve kind of deployed our AI.
That’s really insightful. Thanks, Gary. Thanks for helping, understand that context.
So I’d like to chat a little bit about how AI can also help support building lasting relationships with customers.
So the cost of human support is high. And as channels continue to expand, it will likely only get higher. This is definitely something that we deal with, at customer But AI, however, is a really good technology in helping CS organizations scale.
So setting up AI powered tools and processes the right way can definitely help deliver personalized human service. And really because the amount of data that AI technologies can work with is so vast. It’s a very good tool in assisting agents in keeping your customers at the center of your organization.
And additionally, connecting all of your customer’s history in one system and on a single screen, will make it easier for the technology and the agent to deliver personalized interactions.
Cool. So how can AI enable relationship building? And as Gary said, AI can be an agent’s personal assistant. It can listen in on conversations and run off to fetch the appropriate information for the moment you need it. It also frees up time for agents to work on more complex problems and provides proactive and personalized interactions.
Gary, how are you guys at paddle personalizing Outreach?
Yeah. For us, this was one of the big benefits that we actually got from using AI.
So one of the things that we actually do, is we kinda have a lot of deep information about our sellers milestones.
A basic example might be, for example, when they received their first payout. And so though we had all these details in our back end, it wasn’t very service to our agents when they’re doing with customers.
So we actually used AI to actually highlight those milestones to customers, and it doesn’t actually help them in resolving their problems. But it does actually kind of create a much more meaningful personalized relationship when, for example, you congratulate a seller for their first payout during the interaction.
So one of the great snacks that I’d like to highlight here that you can see on our slide is that we actually managed to save about four hundred and fifty hours with kind of automated workflows. So one of the things that we actually did is our sellers have their own policies for example, about their refunds and, like, other things they want us to follow. And quite often, you’re taking about one or two minutes to actually look up those details and we’re kinda doing that for every interaction that we’re having. Which doesn’t actually sound like much when you’re trying to say one minute in an interaction, but because we currently have twenty eight thousand tickets per month, that actually means that we’re saving about four hundred fifty hours just by servicing those details.
In that short manner, the funny thing that we always laugh at as well is that when we did this, it only took us about eight lines of code to actually deliver that change as well.
Thanks Gary. So I wanna talk a little bit about what the future of customer service and the future of CS agents looks like.
So the CS agent of the future will likely spend much more time in building brand equity and customer relationships than simply responding to inquiries and answering low level problems. Support will probably turn into more of an escalation channel when more complex problems need to be solved.
So in essence, the CS organizations will take much more of a role of a trusted partner from our perspective, where they understand the customers, they spend more time building relationships and reflecting the company’s values.
Gary, do you want to chime in a little bit about how you see the role of the CS agent developing in the future?
Yeah. Absolutely.
So for me, all the things we kind of chat about today they kind of saved you a lot of time. So you kind of got a lot of extra errors. And this is kind of where a company can decide, guess what their core values are and make sure you’re living by them. So at Pado, our mission is kind of, take the burden of selling and processing payments from our sellers. And the idea is they can then concentrate on making their products better and not worry about all those kind of legal sales tax problems.
But kind of alongside this, we also try to act as our trusted partner for our sellers. And we see it as our job to kind of see the opportunities for our sellers to kind of grow their market share and help them to kind of like grow and achieve those ambitions.
And so for us, with all the time we saved on our agents, they can now actually spend time actually delivering on that promise. And so because we actually have that spare time, They can go and analyze what’s happening with that seller. They can go and look at what kind of growth opportunity they might have had for them and provide that advice to the sellers.
And for us, you know, we’re actually in quite a lucky position where we have thousands of sellers. And so we do actually have a lot of unique data that can really help our sellers. And now we’re kinda in a position where we can start leveraging that to actually really kind of deliver meaningful changes to those sellers.
Awesome. Thanks, Gary.
So we’d like to thank you guys for joining us today. And to learn more about customer or paddle, feel free to visit our website and check out our resources.
And thanks again for spending some time learning about AI and the future of customer service.
And I do wanna thank Gary and Taylor for a tremendous presentation here. One of the things and if you’ve attended any CCW events, you know that I’m very passionate about moving beyond the typical let’s, oh, here’s what AI might be able to do or here’s how automation potentially can someday possibly impact the customer experience. What I hear at this point, our customers are demanding great experiences.
Our agents need to be more productive. So I really emphasize practical examples with real benefits and that’s what you just got for the past twenty or so minutes. So I really want to thank both of them for sharing some of those numbers, sharing some of those strong recommendations because whether we’re talking about the contact center of literally tomorrow or all the way in twenty twenty five, definitely gonna be one of thinking about giving every advantage you can to your team to best connect with customers.
Now we do have a few minutes of questions and we have received some. By the way, even if we don’t get to yours, I know that our speakers here will be more than happy to follow-up after email. So get them in. If you haven’t gotten them in, we’ll make sure to pass those along and provide those follow ups.
But we’ve already received a few, so I know that Gary and Taylor will be happy to answer what we have so far. So one of these concerns chatbots and this person is basically saying a lot of people talk about those kinds of internal use cases, but what about chatbots? You know, what have been some examples of how organizations are using chatbots right now? And are there any kind of successful use cases you can point to?
Yeah. I mean, I can start with this one here. This is something that we actually leverage quite a lot ourselves.
One of the things that we actually do is we actually use AI in our chat bots for all of our order transaction lookups. And so any customer, who you purchased something from Peddle, sometimes they’ve got requests, you know, what did I order? Sometimes they’re asked for, like, an invoice. Sometimes they might want, like, a license key etcetera.
And we actually use our chatbot to answer a lot of those queries. And so the idea is the customer can kind of come to the chatbot. They can give us some details about the transaction, the chatbot will walk things through that and hopefully match that for them. And they could do that with a human, but, obviously, we don’t actually have twenty four seven cover, and we don’t support every language on our team.
And the great thing about our chatbot is it understands all those things.
Another question we have here is concerning scaling the organization. So we started with a front end question. Here’s a great back end question. Really looking at how can AI be used to scale a customer success organization?
Yeah, I’ll take that. That’s actually really good and so, you know, I don’t wanna get too much into the technical details of it, but, you know, sophisticated as we can make an AI model or a program. It all does come down to the data. And if you wanna deploy AI in your organization, having to organize the data and get it sort of streamlined and consistent where one of these models can produce something useful for an agent is a bit of a force function for making sure that your data is formatted properly. It’s, like, decimal, and it all sort of streamlines into one, consistent view. And that can then be easily translated into something like a single page for agents to view where they and, you know, complete histories of a customer, all the interactions, order histories, things like that. And then that model can expand as you hire out and grow the team.
Now Taylor this question seems to be directed to something that you brought up earlier, but I’m sure either of you would have a great answer here and it concerns the human factors. So there’s someone here asking how can AI help with personalizing the experience which we all know is a priority for today’s customers and sure to continue to be one over the next few years.
Yeah. Maybe I can start with how we actually do that currently at Peddle.
For me, they were like that kind of personalized touch is more about knowing the context of those customers. And so, you know, what is it they’re doing on your platform? You know, any issues they recently had? And kinda understand that full context to kinda make a much more meaningful interaction with them.
And so what we do with the AI is we actually make it highlight those really important things that might actually help the agent in the conversation. And we just kind of display that there on the screen to them. Now, obviously, they can elect to use that if it’s relevant, but they can also, like, not do that. They don’t want to.
But for us, it’s kinda making sure that information is there in real time just as they need it is what makes it really, really powerful.
Thank you for that, Gary. And again, I wanna thank you and Taylor and your organizations for sharing with us today. This event is all about what it takes to start right now to create a customer experience that, yes, it’s gonna solve the problems that have been lingering. It’s gonna address some challenges that I’ve been referencing throughout the day and that I referenced at the start of your presentation.
But it’s also about getting ahead because it’s at that point where we can’t be playing catch up anymore because our customers aren’t gonna afford us the chance to play catch up. They’re gravitating toward the brands that are doing it right. The ones that know how to scale the organizations, the ones that know how to reduce effort and create more personal interactions with their customers and make agents better and more contextually aware and more engaged with the businesses that they’re representing. And so if you don’t leverage this kind of technology in the right way, If you don’t start looking toward twenty twenty five and beyond, you might as well be looking back at two thousand and five because that’s how your customers are going to perceive you.
Thank you so much for joining us. We will continue with CCW online. And again, any questions we didn’t get to right here, both Gary and Taylor will be more than happy to answer after the fact.