Courtesy of Presidio's 'Mladen Milanovic', below is a transcript of his speaking session on 'Creating positive customer experiences with Chat and Voice Bots leveraging Intelligent Automation' to Build a Thriving Enterprise that took place at the Customer Experience Excellence Virtual Conference.

Session Information:

Creating positive customer experiences with Chat and Voice Bots leveraging Intelligent Automation

This session will cover the importance of voice and chat user interface bot design with contextual hand off to human in case of escalation.

We will describe what additional value can be added by leveraging Intelligent Automation technologies (RPA)

Session Transcript:

Welcome, Glenn.

Is the Vice President of Engineering Responsible for Presidios Global RPA Program.

Glenn has immense experience in customer service, as he was running engineering organizations for Presidios Contact Center Business Unit, working for large size customers.

Milan, it's all yours.

Thank you, Jim. Before I kick this off, what can you just confirm that you can see my screen?

Yep, we can see your screen.

Awesome, thank you very much.

So, glad to be here. And, I have to admit that the reason for the presentation today is the last time when I was here with, with jaws at Paris. So, we kinda talk about his personal experience with a chatbot and voice bots, and, which was not pleasant. So we decided to kind of create this session For today. We'll talk about a customer experience and how we really can create that positive customer experience with the chat and voice bots, bots and also leverage the intelligent automation. So before we kick this off, let's just kind of look at the brief bus schedule.

What are we going to do today? Well, what's the agenda. So I'm gonna give you the very high level overview of Presidio. and what we do.

We'll talk about what isn't the customer experience and how what are the numbers, what that customer experience, that experience dashboard, that we can really understand what our customers expect from us, from a brand itself in order to qualify that interact as a good customer experience.

We'll talk about bots and why did bots fail so far?

And, we will talk about how to design a bot, both a chat or voice bot, read the customer experience in mind. And, in order to really avoid those mistakes and avoid that situation, where are we going to stay that, bought the bots are failing, our overall customer experience.

As a disclaimer, we have around the 30 minutes, I don't think, that's going to be able to give you the comprehensive review how to design a voice and chatbots because we feel that we are going to be able to really give you the good guidelines. And then, with that guidance, you guys are going to be able to really research and implement and really understand how to move forward to be done with the bots.

We will talk about intelligent automation in a box and we will wrap up really to kind of explain what does make that customer experience positive or that interaction with the brand. So let's kick this off again. Let's talk about briefly about the Presidio.

We are a one of the largest IT solutions provider in the United States, and in the world. And as I like to see, if you live in the United States, there is a probably 99% of chance that you interacted with the brand.

And, or a company that leverages our services or our expertise.

From a customer experience perspective, or customer care and contact center, we have over a thousand customers.

And throughout our tenure of 20 years, the point contact centers, we deploy over half a million NEF agent.

Interesting thing is that the first, our first experience with a, at that time, we called that conversational self-service, interactive voice response, is we had that in the late 2014, where we kind of started deploying a conversational IVR for a job for a big good health health insurance company.

And that, over time, we the labor, and develop the expertise that one of the most powerful cities in the world trusted us to upgrade and innovate on, on their customer experience platform, or their natural language, understanding IVR.

So, what is the customer experience? This is definition, I'll kinda play read: That customer experience is the sum of Tata customers interaction with the brand.

And that can be really how customer interacted with person in a store or your online shopping experience or even your experience with your contact center and experience with, your, with your self-service IVR.

And definitely, customer experience is, uh, characterizes how day meaning customers are feeling about your brand. Do they trust you?

Do they like you, or do they feel satisfied giving you their their business?

And it's needless to say, but in today's very competitive environment, the customer experience is becoming more and more important. Because in order to differentiate, especially in the industries, that they're becoming a commodity commoditize, we need to have a strong customer experience because that's going to increase overall brand loyalty. And customer loyalty.

Select, Let's look at briefly the customer experience and the numbers.

So based on several big, big research is that we were able to find, and we're using on a daily basis, Here's the, here's the results, Here's a dashboard, 75% of the customers are expecting that they are going to receive how help, we didn't have five minutes if the problem with your online tool.

If the 25% of the customers that have a bad experience are going to deflect and probably look for some other brand or some other company to bring their business over there.

And 73% of the customers stated that, the customer experience is more important than the price when they are deciding to purchase products and, or service.

On the other hand, there is a couple of other adaptations that our customers have today.

First, customers want to interact with a brand on a channel, on a communication channel of their choice. So, multi channels is becoming the most, is becoming a standard, So, you, as a brand need to have a ability to communicate with your customers. Not over that, just traditional channels or over the channels that you feel are important.

You need to understand, what are the important channels for your clients and we need to be able to serve the customer inquiry over that channel without forcing a client or customer to change that channel.

The self-service adoption is that increasing every day and, today, what we are seeing that most customers wants to first try to resolve the issue or so, or make a purchase or do something.

We, the self-service applications, online tools, self-service IVR, um, a self help websites or something like that before they opt out and go to a, to a human or to a live agent. And, at the end, the personalized customer experience is very important. So, customers are expecting that, you know, why they are calling, that you already know who they are, and they already have a, that you already have at least a understanding how to help them without elongating that customer service call.

So, what are the bots, in fact?9088888889\\\\\chat and voice bots are computer programs that are leveraging Natural language capabilities and they can be configured or built to converse with human users.

So, when we're looking at a bot, we have an interface, which is the part that interface or interacts with the user.

We have intelligence, which does give a nice how bot is going to make a decision and serve the client, the backend systems that are impacting supporting that intelligence in supporting that and giving that agent or bought or chat or voice bot ability to serve the client.

The main characteristic of the bots, first, that they are providing easy personalization, because if we have a data about the customer, we can easily custom tailor those conversations for a, uh, for a specific user, they're very fast.

They can be built to support any channel.

There are available. 24, 7 and a cost of operating Vault bought is significantly lower than the cost of having a human being available 24, 7 being able to serve as terrible and every channel and and provide personalized therapy.

So that's the reason why, when 2016, in 20 15, when bought technology came, came about everybody work. That's a ultimate tool. That's deep thing, that tool that we need to use.

And that's the solution that these are going to help us really understand and address all those needs of our customers.

If we look a little bit deeper, and let's just look August, September of 2016, kick A platform had 20,000 bots that were exchanging one point eight billion messages, and Facebook had 330,000 bots and 40,000 developers that were leveraging Facebook, Facebook bought the environment, and providing a therapist.

So, overall, everybody jumped on up, bought chat bot and voice bot bandwagon, and they said, yes, That's the solution, That's, the, that's the technology that is going to help us deliver on our customer experience, But, 2018, we kind of hit the wall and understood that our customers are still prefer human agents to a chatbot.

And, we still see that at that time. That barth's kind of fail overall, to deliver on overall customer experience and customer customer success.

So, why that happens, in our opinion, there was, there was a 3, 3 major reasons why we saw, early on, failure of the, of the bots, bots, bots, voice, and chat bots, as well. The number one is the technology readiness and what they mean by technology readiness.

If we look at the Gartner hype cycle, all curve 20 18, we did see that, even in 20 18, the chatbot technology, from the curved perspective was really early in the development stage.

But there was the huge press and in the uterus, the technology and limitation of that technology.

We're not understood. Well.

An expectation of the customers were high, as I said, everybody expected that those bots are going to be able to deliver on all those four major points, and we have the best practice scenarios.

And, to be honest with you, early adopters will elaborate, that we all kind of learn, and, and, and, and, and try to understand how to deploy. We had a bad experience. I have to admit that, on a procedure side? The project, in our side was very successful, but we went to the significant amount of development, insignificant amount of trial and error in order to avoid impacting our customer and their clients.

So, today, if we look a little bit closer, varies, awareness Robotic, I'm sorry. Where is a chatbot or chatbots?

We can say that, today, according to Gartner and I completely agree with them, that chatbot technology is very well understood.

And we have better understanding of those capabilities and use cases.

We had those best practices then, if you look, chatbots are in a field of slope of enlightenment.

So, traditional service, these organizations, are beginning to build a more mature practices, and we are moving forward with implementation with traditional customers. So, definitely, if we compare where both technology was 2016 and where technology was, was now, or is there really is going to be. We see that chatbots went through the significant development phase.

And that today we can we can we can consider them as a prime time reading.

Initially expectations. For inflated, I mentioned that, because everybody we're expecting just putting the chatbot on your communication challenge is going to solve your problems.

The big thing that we are even seeing today, is that chatbot environments, voice bot environments, are built in a silo.

And what that means is that they don't have ability to escalate a conversation or escalate a communication contact, from the artificial intelligence power bot, to a human person. Because there is, and there will always be a limitation what technology can provide to a, in order to address the customer issue.

So, what did we learn in Alaska?

In the last probably, 10 years, of building the robots and building the chat and voice bot, there are, at least, in our opinion, sevin major, seven majors areas, where, how we should start in order, where we should start, in order to, to develop, and create, and design a bot, that is going to be able to deliver on, the problem is of good customer experience.

The first of all, understand the customer channel. Then, we have to talk about creating a system persona.

We need to very well understand our customers and identify your technical capabilities, both internal and external systems, in order to address those needs that customers have.

Designing the dialog is the core of the entire, entire design process.

And definitely, testing, testing, and testing easy, very important, in order to deliver on, on a very high customer, customer satisfaction and customer experience.

And in order to really get some hard data, we need to embed and provide a statistics on efficiencies and, or metrics that are going to really show how our bot chat or voice bot is performing in the real-world.

So, let's kind of look at each one of those, the design areas, know, a little bit more details.

First, what when we say, understand the communication channel? What does it mean?

First of all, we need to understand, that's very important, that goes to that first thing, that our customers are requesting the service on a channel of their choice.

It's very important to understand where that customer contact is coming from.

Today, we, our customers, have a lot of different applications on their phones.

They are using different social media or communication platforms, so it can be a chat, it can be SMS, it can be a call. It can be a social media platform. It can be your website.

The reason why that's important, because all those communication channels and the need to cover those, it's going to determine what type of platform you are going to select in order to build your chat and voice bot environment.

The piece of advice is we always need to strive to select a flexible, enough platform that's not going to satisfy today's needs, but being a being able to be expanded to satisfy needs of the future in swap.

When we understand where the communication channel, what communication channels we need to use, we also need to custom tailor communication for the specific communication channel.

The basic example, we cannot say, if we are having a chat bot, we don't want to send a message to a close to the customer, or to the user it say, please say your credit card number, We probably want to say, please type your credit card number, or your account number, or something like that.

And definitely most important thing is, do not force channel switching.

If you are not able to support specific communication channel, end to end, don't pretend that you can meaning, oh, let me initiate the contact via SMS, but if customers try to customers try to complete the transaction for SMS, we're going to send him a text message to complete the Eastern section, Please call us on this number.

The good example and we are seeing that every day, is when you get to, when you receive your appointment reminder from your, from your dentist, some platforms has no limitations. So what's happening? They say to confirm your appointment press yes or no, Yes.

Any ..., And you say no, you responded to, know, they come with a message, please call us to reschedule an appointment. That's the bad. That's us for single channel switching. That's a bad that's going to cause a bad customer experience for sure.

So, let's look at the next, the next point, and that's creating space for them, persona. So, what is the persona, that's your ... partner? That's what you want your customers to experience when human or your customer is interacting with your boss.

Ah.

Keep in mind that the goal of creating persona is not to trick the user into thinking that they did. They are communicating with a bit of human.

You better be up front and say, hey, my name is Alice, and I am automatic voice assistant or I am automatic chat system for this brand.

It's better for us to set the expectation that there might be some limitation of the platform that you're using.

Dan, try to convinced or tried to trick the user, that the user is talking to a human and then, when you cannot deliver on something, user is getting frustrated.

Keep in mind, this persona should be created with your brand and your customers in mind.

So, and change it. Choosing persona is, from my perspective, and for our perspective, how many different customers we had.

We usually work with the marketing departments and, you know, really, in order to understand what type of users we have and, Or usage of the bot, what is the your image that you want to project that specific chatbot? And, based on that, we're going to select the voice. There's going to select the types of conversation. We're going to take the dialog structure, Demographics of your users are also important in order to select that, to make a proper selections on all those attributes as well.

So, so, all of those things are important, where we are.

When we are creating, and we start to really building a chat or a voice bot, we need to understand our customers.

So, while I mentioned, I mentioned demographics.

Who are our users?

What are their needs in how they are coming in? How, and what tasks are they are completing today?

So, if you are working, or if you are planning to put a bot for a utility company, you need to understand what your users are calling your contact center about and understand what are those services that would be easily moved from the human handling to a self-service.

We need to understand the customer journeys.

From Google's perspective, what customer is trying to, to accomplish, and where they are coming from, their context.

Meaning, are they calling you because there is an outage or they are calling you because of, they cannot read your bill.

Uh, then, another reason why you want to make sure that you, understanding your customer. We need to avoid that developer bias.

You are not designing a bot for yourself. You're designing a bot for your customers and they need to be happy and satisfied with your specific specific, a bot.

From technical capabilities, excuse me, from a technical capabilities perspective, we need to make sure what systems are involved or going to be involved in order to provide a request to self service.

What are the limitations of those systems, and what are the integration points, what data we need to collect from the client, from the customer.

And what data we need to collect from those the internal systems or potentially external systems in order to complete the transaction.

And, I would say that that's the number one reason for a longer lead time and long deployment time when we are looking at the complex voice and chatbots solutions. Because sometimes we need to spend lots of time of preparing our backend systems to be able to interface with the bot framework's or chat or voice what, Kramer's. That's the reason why we are going to today also touch on the intelligent automation tools and intelligent automation.

Because definitely intelligent automation platforms like UI pack definitely can help us much faster bridge that gap between the bought the environment, check and voice bot environment. Which becomes an interface to communicate with the customer.

And a backend systems and that. And sources of records that we are going to use to complete the transaction.

So, so, let's look at the designing dialog, and, to be honest, this is the most difficult and most complex part of the, of the, of the board design into designing the dialog.

Number one thing is, you start with 80 20 rule, and then move with the design for a long tail.

What that means, that means that 80% of your users or your customers, are going to use 20% of the conversational paths.

So, what, why that's important, All those special cases are only going to be use roughly by 20% of the users.

So, bottom line, sit and understand what is the most likely path through the bot conversational path to the bot? That regular user is going to take. When you design that, you made this significant progress and then move on and start agile development for, for all those edge case.

Keep in mind, you are never going to be able to predict all edge cases. And that's the reason why I'm measuring.

And having that loop between measurement and development is very important and testing as well, in order to catch down the road that goes alternative conversational paths that some of the users will take. And that's going to give your bot more and more ability to handle those specific cases.

Um, there is a very interesting theory, how humans are informative. And, that's probably something that we start learning if you already learned talking to different voice assistance that we now have in, in our home, but usually, you need to make sure that you design your dialogs.

That with the, with, with them.

Kind of thought in mind that humans are going to be informative, something along the lines.

I want to book a travel from New York City to Jacksonville and I want to leave it new.

So, what that means is that I gave you a several information, and you should be design your dialog to be able to collect, from that sentence, my starting point, my destination, and when I want to leave this, and when I want only my departure, date, time or date or something like that, make sure that you predict some error handling. And error handling should be done in a very subtle way. If you don't want to announce, Oh, I was not able to collect this information. Please try again.

You just want to do something along the lines.

When do you want to leave?

If you are not able to capture that specific information, use Familiar Phrase this set of words. Don't design your dialog with a, with some idea that your bot is going to talk a real robot or something from a science fiction movies.

Ideally, your chat bot platform allows you to have A, for a samy, 10 different dialogs.

I call that Spice it up, makes sure that every conversation, while honoring, but at least a couple of conversation can provide a blueprint dialogs. But that's very important because it does give you some kind of spirit or, or some good, good approach to the dialog design.

And testing The dialog is very important, one of the great testing methodology is the so-called wizard pause, where you are going to design your dialog by just writing the dialog on a piece of paper.

And then, you will have a human who will ask questions, and on another hashtag, you've got, you're going to have another person.

It is going to just read a dialog back to a, to the human, just to make sure that there is that good understanding and good dialog between you and the one on the other side.

So, so definitely, again, in a, in a 20 minutes, we definitely cannot spend, We could spend hours on on, on talking how, how to design dialog. But I'm hoping that, through this couple of four or both tab on the rules, that we were able to put it there.

That you guys kind of see what you guys should be thinking all, or asking your implementation partner, or preparing yourself for when you decide to deploy a chat or or voice bot.

And, again, I just don't want to forget, but to mention, again, test, test, test, That's very important.

And put the ability to measure the performance of your bot, because that's a, the best way to do it.

So, we mentioned intelligent automation on a box, is, that's something that became or, or, it's a game changer in, a, in, a bringing bots to, to market faster.

Definitely gives us the ability to support new self-service scenario live.

Adding a, yeah, document, understanding capability, power chatbot, ability for, for a user or a customer to upload a document, and that we can easily grab that document. You can have a robot, or, or, in a backend to take that picture, analyze a picture, and provide some self service based off of that picture. We can fit, more efficiently, bring machine learning algorithms into the fulfillment process.

And, if you remember what they said regarding, based, A, gracious read the internal applications, or ..., definitely, leveraging low code, and no code, the environment, adding them, it's, it's increasing, the speed to market, or time to market, via faster development.

And all those things are very inter-connected connected and provide us higher inter operability and the lower T steel.

So bottom line is choosing a flexible and adequate chat or voice bot platform.

Together with A RPA or intelligent automation platform that has interfaces towards different, different chatbots systems and different be from backend systems, set you guys up for success, in order to really provide a very robust chat or voice bot with the capability of providing a lot of different information. Or what are some different self-service use cases to your customers?

So, let's wrap up with the, with a kind of, oh, point on a positive customer experience. Today, we did touch on what, what are those rules, or those guidelines, how to design the chat and voice bot, and what technologies to choose to in order to ensure positive customer experience.

But, let's make sure that we all understand that if we wanna really deliver on customer experience and a positive customer experience, we need to focus on an entire journey.

That total customer experience, We, the journey, is a, if you look from a journey perspective, that's what they meant, is, in fact, a multiplier of all the experiences that customer is going to have with the really individual points.

We the Contact Center agent, with a contact center itself, with your online tools and with support.

This kind of screenshot from McKinsey Digital Labs.

The paper is something that I always like to show at the end of the presentation, because if you look your customer experience in a style, from an agent perspective, you have 90% agent experience. Customer experience, from a contact center, 85%, web, 85%, support 90%. So you would say, say that.

Looking all those touch points individually, your customer journey, I'm sorry, your customer experience should be good now. But your end to end journey satisfaction is only 60%.

So that's a major, major problem.

We can not, and we should not look at the individual touch points.

We should strive and focused towards individual touch points from an improvement perspective.

But in order to assess a total satisfaction with a customer experience throughout the entire life of the customer, or through entire journey, we need to look at all those touchpoints. And what is the the way how we can improve each one of those touch points in the role.

I want to thank you for your time today. If you guys need any more information, please do not hesitate to contact me, there is my e-mail address. But definitely it was a pleasure spending some time with you.

And thank you very much, one more time.

Fantastic presentation, really informative.

Certainly uncovering some of the mysteries of bots and chatbots.

And the experience that I've had in many I've had is maybe the technology was moving too fast.

Maybe now it's caught up a bit.

We do have a couple of questions.

Uh, one of the first question here that we received is, are you're certain, are there certain industries where bots do not make sense, could negatively impact the customer experience?

And it would, would it be better to remain with human agents?

Yes, definitely. And that's.

I cannot talk about the different specific industry industries, but there are certain topics, or certain customer service issues that can not be handled by a, by a self-service or bots.

So, that goes to my Mike point, that we made during the presentation. You need to understand your client. You need to understand the need.

And, if you see that, that this specific, the fulfillment of that specific need is going to be more complex, or it's not going to provide a good feedback to your customers, just don't do it.

Put that to the human. And that's very important, Jim, what we are seeing, that some of the industries are seeing increase of pressure to the context and rage.

Because, what we're seeing now more and more, that those low hanging fruits from a self-service perspective are going to the bots, voice and chatbots and self service. And now, contact center agents and humans are receiving more complex inquiries.

So if you have, if your clients are going to pose specific complex inquiries, not put them on on on a bot side because bots are not able today to handle those complexity inquiries.

Just to follow up on, You mentioned that before, that there's no way to handle the handoff between a bot directly to a human.

Do you see that that will change over the next, ah next 2 or 3 years or will that continue being a limitation?

Thank you, Jim, for asking that. The, That's change, that change. I think that, unfortunately, a lot of designers, and, some of the platforms are not able to do that. Because, usually, what we are facing, when we are talking to the clients, they are more focused on that.

The ability of the boss to converse with the customer, Humpback, AI, that natural language, understanding a conversational interface is built, that's the very important part.

However, every bought environment needs to be built with the will be the idea in mind, that bot is not going to be able to handle the interaction. And it has to have ability to handle the conversation to the contact center with the full context. So, that's the reason why we usually like to choose the platform that has that integral ability to be the contact center.

So when you receive a contact, with human receives, the contact from the escalated content from from the customer agent can look, oh, OK. They tried this, this, and this bot told them that, and they couldn't do this.

OK, now I can continue, and now I can help them to solve the problem.

You're kind of following up on that train of thought is there's a few.

Is there are people using software to analyze the most frequent past, or the most longest pass to retrofit ...?

Are they process mining to help in that part?

How, what is the percentage of companies that are actually doing that, the, the time on the customer by using the bot?

This app done a lot, right.

It's not high percentage, the best in class from a customer experience aren't doing that. Religiously.

They are measuring they have a dedicated teams that are measuring the performance of their of their voice interaction and the check interaction platforms on a daily basis.

And, based on that, they are providing feedback to their Agile product teams, to improve their there, their systems, and their conversational interfaces. Unfortunately, what we are seeing, this is not a rule.

It's an exception for now. I would say, I would be very optimistic, 10 to 15% of the companies are going.

So, it is then linked to the journey mapping.

You see one day when we'll be able to do's intelligent process automation and do true journey mapping on both the the customer service agent as well as the customer coming in and their journey. And really map those out and see where the intersections are.

Is there anybody who's doing that very well today that you could share with us?

So, I will tell you from our perspective, so, collecting the pieces of data that are going to map that journey, that we're going to leverage to, map, that their journey is not an issue anymore. We have different abilities, even Twilio has the APIs to do that. They get that with a segment segment Acquisition.

But, what we are seeing, where intelligence automation, like UI Path, is doing great.

We tended automation.

on the Agent Desktop, we are able to help contact center Agent two in a real time, get the full journey map and that information.

Because don't forget, we do not have the contact center agent receive escalated conversation from the, from the human, right.

And that he or she didn't have enough time, but if we have attended automation, that he's gonna go and grab those pieces of data, run through the specific AI or ML ML platform and speak out.

Here's what happened, and here is what we need to fix.

That's something that we add, that we are seeing and, and, and, and we are seeing that all those components are available in UI path Platform.

So, the customer profile, past experiences from the sales, Like what James went through, you went through seven journey maps.

If, if, if you went through those seven different journey maps, do you see that to be available to the customer service agent?

Then that will not be the norm, and how many years will it take us.

Where that will be the norm?

Because that's still the customer expectation today, Is that when a customer calls, they expect that you can do that, but we can't do it yet. So, the technology is getting there. You're right. Technology is getting there. It's, those leaders. Are, you get to it today? It's definitely 2 to 5 years where we can see that become a standard Porsche.

All right. That's great. Great.

That was a fantastic presentation and very clear where bots are.

Certainly something I was wondering about, so thanks to Joe's for I'm pushing you to do this presentation.

Yeah, we've been using the box for over 20 years, As you know, they're not new.

But to really tie it all together into what we call intelligent process automation, is, is this easier said than done, right? Yeah.

I agree.

Any parting words before we sign off for today?

No. Thank you very much for having me. It was a pleasure, as always, so, you know. Thank you very much, you guys, man. You guys have a good rest of your day.

Thanks, thanks, Milan. And hope to catch up soon. Thanks so much, definitely. Thank you.

All right.

So that wraps up today.

And we look forward to tomorrow's presentations.

We hadn't really incredible presentations to get today from.

I'll just review a little bit.

Brandon Garrett, from Seattle, on and he provided us insights, quite a bit of insights on customer experience.

Then we had doctor Maples and Jennifer, and they gave us, I think the you might call it touchy feely, but it's it's what you really feel. And in tools that you can use right away to train your, your folks to understand how different folks are feeling.

And take that into account.

Then James, I have to say, I enjoyed his presentation.

Immensely shift happens.

Shift happens, You know, dating your customer.

I think that's an important concept, that we all need to look at, is, no, treat our customer like we were on that first day, and you gotta treat them that way every time.

And just having that with them in the seven customer journeys is, is very enlightening.

Then we had, again, the Bots, which was a great discussion on where we're on, on that intelligent process automation journey, when we're going to get there, and the bots will eventually perform what we were, what we expected, maybe sooner than later.

So tomorrow, we'll kick it off again at nine o'clock.

I'll be here, attend fill with a little bit of introduction for today presentations by Abby on gaining a new perspective on your processes by Richard Raven.

And then we'll go into at 10 o'clock Eastern Time.

Customers are the real stakeholders for customer excellence by another Jim James Seiner.

So a lot of gems here.

And then 11 o'clock, emotional intelligence and empathy, the key to Uber.

Uber, immense, immersive user experience by Jason Rudolph for Retiree Health.

Then, we'll wrap up tomorrow with leveraging data, analytical tools to identify valuable business opportunities, drive decisions and innovate products. And that comes from Stephen, me, on the other side of the world for me. And Singapore.

Stephen Yi is a Deputy Executive Director of as an ETF.

So again, thank you so much for joining us today. We look forward to seeing and hearing from you tomorrow, keep those questions flowing.

Fantastic dialog, fantastic questions, and have a great day.

About the Author

Mladen Milanovic,
Vice President of Engineering,
Presidio.

Mladen Milanovic is Vice President of Engineering responsible for Presidio’s Global RPA Program. Mladen has 20+ years of experience in contact center industry leading presales, post-sales, project management, and custom application development groups. In recent years Mladen is focused on workforce transformation and automation.