Dynamics 365 AI | Accelerate Business Transformation with the Power of AI

Dynamics 365 AI | Accelerate Business Transformation with the Power of AI

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Introduce. Myself I'm John crass I, work. In the business applications, group and I focus on, Dynamics. 365. AI offerings, and, super. Excited today we're gonna talk about a couple different things we're gonna go, through where Dynamics, and AI intersect, and, as well we're gonna take. A walk through three of the products that are coming out this fall and I'll be joined during, the day by. A couple of my colleagues so you'll see people coming up and down. You. Heard in some of the other. Sessions. About how AI is changing, the nature of work but. We also believe it's it's going to be changing the way that people work and what their job roles are and it's interesting when you when you think about it your own perspectives, you see how this is already happening when, you have a question and you talk to a virtual agent online you. Don't realize that the, people who work in call centers their jobs are changing those, guys are not having, to answer some of the mundane tasks, they can now focus on some of the more complex but complicated ones and upskill. Their jobs at, the same time even in like very heavy. Document. Rich type, of occupations. Like law so lawyers and paralegals, their. Roles are also changing, they're now with, the, powers, of machine reading comprehension able, to spend, more time. Analyzing. And, writing and less on searching, and, organizing. So they're billable hours are actually, more productive than them going through lots of documents, and then even another, example. My wife belongs, to one of these online. Retailers. I would, ever lose a retailer but a stylist, and, what's, changed about her. Stylist, works, for a company and they get these AI patterns, of my wife's behavior, and, her preferences, and all the people who are like her and these. Patterns allow her to change and how she does her job and be more creative with a larger, tool set in terms of information and, even some of the product offerings so, it's already changing the way people's. Jobs work, some of whom are probably more obvious, like call, agents, or lawyers but even things like. I lost is. An example. But. Also what we've noticed is a lot of people want to do this from across the board there's lots of interest in terms of wanting. To do more around AI but, the but the truth is not, a lot of people are doing it right yeah so a lot of interest, not a lot of throughput and constantly. Some research did. A study with companies, that are normally early adopters and seventy seventy, percent said they already are doing something with AI but. The but the mere reality, is not put them through wide. Adoption and, wide production, yet and, so it says we're, still at the beginning and. They're not doing it but why isn't everyone doing this and it's it's some of these things are gonna be of course, very obvious, you can call me Captain Obvious on some of these things but, the a lot, of it's been overhyped and it's like the idea of these are magic, and it just it just happens, and it's not very hard you, see the commercials, where it you know we solve everything from you, know hunger. And cancer and it happens within 15 seconds it's really not the case it's actually quite difficult because, what happens is a lot of these AI you, have traditional ones and the original ones were built outside of normal applications. They're closed so they're not widely adopted at, the same time it's, taken very unique sets of skills of, data. Scientists. AI, devs, and people, who are really entrenched and those. Those occupations. Are kind of fewer and far between. At, the same time. Data, you heard in some of the other sessions how data is very siloed, which. Is a problem, not. Everyone has all her data in one place and. So it's, siloed, it's complicated. And data across the board is hard to be able to do something about that and, because, of all these things this stuff is very difficult. Expensive. So. We're, still at the beginning, phases of the way it's traditionally, been done, so. Then then you say well where does Microsoft think about this and now if you look at the slide you can almost draw a line through it like left, half right half left, half think of this as the platform and, Azure. There's like tons of sessions here in terms, of all these great tools. Services. For developers, to be able to build rich, AI. Applications, whether it's BOTS we have things with machine learning and all out. We're not gonna talk about that today if, that's what you're here for you're in the wrong room we're, going to talk about dynamics, 365, so we, have a couple of scenarios. About today but, think of these as the SAS out-of-the-box, offerings. Where, you can make, some of these things happen with, AI without. Having those, teams.

Of Data scientists, or AI devs you'll, see the word etc, you'll see, some examples but you can imagine this going across lots. Of different. Environments. And scenarios, things. That are also for, our dynamics customers, and you'll see a theme that we'll talk about is we'll, also have, options. For people who are not yet dynamics, customers. So. As we think about dynamics, and around, intelligence. Nai. There's. A couple main pillars. There's, insights, you've got some glimpse in some of the keynotes and what will go deeper on some of these things and think, of this is going, from what was traditionally analytics, to insights, to, really the word that really drives, out here is its, action, and you'll hear that a lot and all of these things are important, to be able to get to the to the next step function, and then mirror. That with conversational. Virtual agents, and this is where not, only do we help if you think about from a customer touch standpoint, improve the experience. But. Also employee, productivity and, then when you wrap these together and you'll see some examples later today, of. How we can put, these together all, of this stuff really drives better, business results by. The power, of AI. And. The, theme that I started, with of how it's gonna change different, jobs you could think about this as changing it from every every. Department, in every discipline, you, don't have to be an AI scientist. To be able to do this with with them SAS. Application, and we're. Gonna highlight these these are some of the big workloads, that you'll. See today but this is just an example of where, we're going and. The, important, thing is this is going to be. Solutions. That will fit within current infrastructure, and current. Talents, once again people who actually work in these departments, can actually get the benefits, out of AI and hopefully, by the time we leave here you'll. Get to see that. So. What does a company need and where does that really intersect, with, with Dynamics, I, a. Little, bit at, the beginning of us these have to be out-of-the-box, where you get immediate value right, away was without a multi. Month or a year set up to be able to start seeing some some. Advantages. With AI but, also have the ability for these things to grow as the the scenarios, get more complicated and we have, the power of asher, for. This to continue to grow and you heard James talk about the whole know cliffs, the. Idea that these are going to be infused we have a lot of customers on dynamics we're going to infuse some, of these AI capabilities, into their current workloads, but we're not stopping there we're, also going to have some and offerings, so if say you're a Salesforce customer, you're not using you're, not using Dynamics, there'll be some opportunities, to be able to utilize some. Of these offerings and take, advantage of AI, we. Talked about data being siloed. I mean think of three different buckets you have your your data and dynamics you, have your data and all these other systems, of record and then, we have a bunch of great Mart Microsoft, signals and we'll have an example then, I'll show you that how do you put these all in one place or a common data. Service where you can actually take advantage of, that and that's where the needs and what dynamics, can do will come together. And. Then the. The third bullet I just, want to focus on one word which is action, all these things have to lead on actually doing something that drives business results, not just for something that gives them more information but it has to lead to something that actually pays. Out we're going to talk about sales, sales managers. Customer. Support this will help dimensionalize, what the word action really means and then, from an evolved standpoint. We're. Gonna can this things are built to continue, to learn, and get better for.

The For the ones that we're already doing and, we're gonna continue to do these across other workloads, as. I said across every discipline in every department and. How. Do we think about this so we before, we even come to market with some of these things. Microsoft. Hate. The word dog food but we eat our own dog food in Las Vegas we take some of the technologies, that are built. Out of of, MSR. And other organizations. And we start utilizing these things and then we also do some early early. Pilots and early development, deployments. With some big partners a couple key things so, Microsoft we've done a couple different things with our sales group they've been using some of the sales technologies. With our inside sales and other sellers to, help improve the. Relationship, way of selling and have. Had great benefits, these technologies, then lead into products, also. Within Microsoft, if, anybody's been to support.microsoft.com. You'll. See a virtual agent Frank, will come up and talk about our broader customer support, offerings. But. It's already handling five million chats a, month. And being able to get smarter and answer more and more questions so we learn a ton from these very complicated ones, and a lot of times Microsoft. Scenarios, more complicated, than, our some of our customers so if we could solve it with ours then, it's, easier for us the abilities into products HP. Is another example, of where we are, working with a company too as we did some our initial virtual, agent and, Frank will talk more about that and then Infosys is an example who's. Using some of the technologies, in our in our a I for sales product, for a relationship, selling and once, again has really boost their sales productivity. So. Today we're gonna look at three things I figured, it's more important to look at demos than hear me talk about demos, so, we're, gonna start with AI for sales and this, will allow not. Only sellers, to, be more effective, with. Building, relationships and. Allow, their sales managers to be better coaches but overall drive better results, market, insights.

When. You think from a marketing person standpoint. They want to understand their. Brands, that, they represent, and. What are people saying. About them or do they searching about them and how do they feel about that we're going to talk about that and then, customer, service we're gonna go through the. Full. Product. Strategy, of how we're gonna once again try, to improve customer satisfaction. By. The tool sets that they have in there. So. Now I'm going to start with the first act which. Is AI. For sales. And. If. You think about what, should a seller be doing they should be selling and when, you look, at the time spent, and we have lots of different stats. There's. A lot of a lot of time spent on unproductive. Unproductive. Efforts of trying to figure, out what the next right best action, how do I get a hold of this person, how. Do I become more effective than my job and we believe that there's. An opportunity you'll see some of those and you've already seen some of those in some of the keynotes at, the same time sales, managers, need. To get a we've learned they have to have a better grasp of how do they not only coach, but, understand what's happening to be able to meet their goals and make, their overall. Org more productive, in terms of selling so we're gonna do is I'm gonna um, I'll. Do a little intro I'm gonna I'm gonna turn it over to Luca is going to come up here he's going to walk through the product and. Then we'll kind of walk through the, next couple of them and. We'll. Take it from there so Luca. We. Switch, you over. Use. Seven. Can. You hear me good. Morning everybody thank. You, John. So. As John was mentioning, today I'm gonna show you a couple of different, AI capabilities. Ready to the sales. World you. Know I'm Italian here, you might think that having, an Italian guy on stage talking about AI is just like having. Berlusconi. That talks about honesty, which. But. Bear with me. So. First. We're gonna start with the sales rep and. The sales rep world and we're gonna see how the AI. Infuse, capabilities. They're. Gonna help the sales rep. Understanding. A customer journey understanding, a customer, interaction, and. Extracting. Deducing, value, and insight for that for. All of these interactions, and then we're going to look at the how the sales manager. How. We can help, the sales manager, with AI capabilities. In, first. Coaching, his, team as, well, as helping. Him in, obtaining. His photo so. Let's jump to, the, sales. Rep world. Again. Here, I'm. Gonna show you the, infuse. AI capabilities. In there. Are 365. For. Sales or, application. That is going to be. Available. In, October so I'm, on, my dashboard and, as every, day I'm looking at my numbers, my opportunities. And I see this. Big. Red number here which, is not a very good one because what, is gonna tell, me is that we, I am, really, behind my quota for this quarter, so.

Here Let me pause for a moment because what. I really want to understand, is. First, what's going on why, I am well. Behind my quota and then if there is something, that I can do to just. Bridge. This gap so, let's. Let's now try to understand, a. Little. Bit more about my opportunities, here I can. Look at the estimated revenue, I can look at the data. Just like closed. State what. Is the account and so on and so forth but more importantly, here, I see. That they infused. AI capabilities. Have, been able to create and, calculate, this relationship. Health state. Value. Here and it's based on data on data coming from both the Nama 365, and office 365. So. What we can see here is that some. Of my opportunities, are in a good health state some of them are fair and poor it is very good for me to be able to understand, where. To focus and what I need. To do next but it's not just a picture, a static, picture of what's going on with, my opportunities. Because. If you see here, we have been able also, to understand, what is the trend. Applying. Predictive, model here will, be we are able to understand, where. My relationship is going on is going to be better. Soon, it's going to improve to the client, so, those two values. Here are very, good for me in order to be able to understand, what to do next, so. Let's now look at how. The. Relationship. Health. State and the trend are, gonna be calculate, is calculated. So. Here. We, look at all the interaction, the meeting requests, the, emails. And, the phone calls that we send to the customer, as well as, what, have, been their responses, back from the customer itself the time spent the email engagement, emails open attachment, viewed, links. Clickin and the response, rate and the response time, so. All of this information. Together. Calculates. And creates, and composes, the health, score so. What about the trend here as we. See here the interaction. History. Of the last couple of month. Web. What we have been doing around this specific opportunity, when it comes to all the interaction, the emails the, meetings, the phone calls have, been able to predict. And understand. What, is going to be the future for, this specific. Opportunity. When it comes to the health, state so. Now I have little bit more. Knowledge. About what's going on with my opportunity, so now let's see what, I can do in order for me to be able to improve this. This. The state of this relationship, so. Here, first. Of all I got a suggestion, which is hey there, has been no activity with, this account since more. Than a month, ago so I, can leverage the, power of the data within. LinkedIn to. Be able to understand, what are the icebreakers. What can I do what kind of connection, can, i leverage in order for me to be able to improve, my relationship, and. So. Now let's let's, switch gears and, let's. Move, to the, sales. Manager, world so. What. I'm going to show you here. Is the, dorama 365, AI for. Sales. Which, is gonna be public. Review this this October, so, here we are in the sales manager, world and first. Of all. What. I'm seeing here is that my team is well below the target and there, is just 11, days left so. The first thing I want understand, is why why. Is that why we are in this situation and. I'm. Not just having, numbers, as an, as an answer what, I'm gonna to have here, is real, suggestions. Really, insights so, things like so how are we doing versus. Historically. What are the in services industries. Are that we are winning Dell scene why. Are we losing deals where is our revenue, coming from how. Does our sales, funnel, look by stage how, are do, how do our want, versus loss deals correlate, to our and reread all. Of these information, comes. Both. From the nurse 365. End of, history 65, and we apply, statistical. Modeling. And machine. Learning in order to be able to have. This kind of insights but. Now it's. Not just that there is more than that because let's. Say that we want to understand, what to do so. It's again. Having. A clearer picture of what's going on it's good I, would. Love to understand, more I would love to understand, what to do let's. Have a look at couple of examples, here so, my team is having trouble, moving from qualification, to propose stage so, this is a clear. Insight. And, a clear way for, me to understand, where to take action what, where. To focus my nest back action. And then again here. We, can understand that we are losing most days from outsold again, all of these suggestions are really, precious for me. So. Now let's, move. On and let's see what what. The AI capabilities. Can do when it comes to, helping. Me coaching my team so. Here first of all I can see a couple, of highlights, so, one of my people Ryan just won a deal. So. This was a very important, deal so because, it was previously at risk of being lost and again. One of my person, here, Erik, Boocock is, quite. Behind the podium and. I. Can put together part, of different.

And Interesting information, here what first of all what's. Happening, with Herrick I can. Understand, that looking, at the sentiment, analysis, Harvey Scoles there. Is a significant. Drop in positives, and in positive sentiment, while talking to customer in the last month so. I need to understand with, him why and again. Here, what, I see that I have an upcoming one-to-one. To air with Erik in the next, 30 minutes, and since. He's achieved, 60, percent of his quota and, the. Health. Score. For, this opportunity is pretty low and, putting. Together the, data from linking, I can say, that since, I have a connection in, at contoso named, Paul cannon this. Guy might, help him on that with, the specific opportunity, so what I can do here I can just. Leave. A note for Eric and tell him that we can leverage this, kind of, information. So. Again what we have seen is that. The. Those. AI capabilities, will both, help me coaching. My team as well as reaching as reaching. The water, so. Now back, to you John. So. Don't go too far, you're gonna we're. Gonna change your role in a little bit, let. Me go back to. So. What you saw in, summary is a tool. Set that enables. Both sellers and sales managers to be more effective of closing their pipeline what did you next, especially. For sales, managers of how to coach and figure, out what what to do especially if something's not going well I also. Wanna clarify so, the first piece that Luca went through was the infused, into, the core application, that's going GA in October, the, second piece was a standalone, offering for sales managers that's going preview in October, so I just want to make sure you saw two different things and, both coming in October but slightly, slightly different. So. I want to jump to kind, of the next stage and when, you think about marketing and marketers. And there's like two. Sides of the same coin marketers. To be really, good at their job need to understand. Their. Customers, their, products, how people think about their products and at, the same time. You. Have customers who, increasingly. Gotten. Used to having things that are more personalized, not. To the level of creepiness but, personalized, of how they're communicated. To across, all different channels so, marketers, need to get better and customers, already expecting, it so what, are the tool sets that we could do to allow marketers, to have a better sense especially, if they're responsible, for a brand to be able to understand how people talk about that brand how. People search from their brand and then, even how they feel about that brand to help them have a competitive, advantage so let me I'm. Gonna switch back over we're. Gonna do a quicker walkthrough, on market. Insights. And. Then. I'm. Gonna stay up here I'm, not trying, to intimidate. You thanks. John so. So. As John was mentioning, I'm gonna show you a short presentation short. Demonstration of, the ramp, to 65 ai for market, insights and. So. Here the ability, is the. Main idea here is it's gonna be very interesting.

And Important for the marketers, because it's, going to give them the ability of understanding, what, the consumers, and the customers, are, thinking feeling. And doing both, in social, media world so we're talking about, Facebook. Twitter, Instagram and, so on as well, as the. Information. Coming from being, searched and, using. Statistical. Modeling, and, learning. We will be able to deduce in infer, some, very interesting insight, out of all those information, so. Now for. The purpose of this, this. Demonstration I use Microsoft ignite so, what we're gonna see. Now is, we're. Gonna try to have an understanding of what you guys think about us on stage and. So. First of all it's let's focus on, the on our ability, to understand, the content, of the. Social conversation. So, here we're looking at the, intention. Analysis, and auto-tagging. So the ability for the, for. Our AI capabilities, to understand. What, is the main content, of the conversation what. Are. What. What. Is the main level. Of and. In, the main tags that we have when, it comes to having a conversation be, in our social, world so, here. Thanks. To. Machine. Learning what, we see here is that this. There is this automatic, way to. Understanding. What are the intentions, just, like informational request support regrets, purchase complain. And so on and again, with the ability of auto tagging here but it is more than that because we, can also understand, what is the tone and the register, of the conversation. So if we look here at the sentiment, analysis, we can understand, if, a. Person. Is happy, with with. With, the comment that is living on the social media world is negative. And so on and again. We. Can also be. Able to deduce, and in, the, age group and, the gender of the, people, thanks to machine, learning model, so I'm able, to understand, what. Is the the. Group that the person belongs to and. So. Again I have a complete, vision not just about. The, content of the conversation, the tone of the conversation but I can also understand, a little bit more about, the demographics, here and back. To you John okay. Thanks. The we. Already had a head. Start on. Understanding. The social signals what, was what's, really new is being able to pull the thing the signals from Bing which is something that not a lot of there's, only a couple of companies in the planet, that can actually do these types of things which. We are one of them but. It allows our. Marketing. Audience to really understand, how, people, feel about brands, and ideally. Give them a competitive edge and seeing, how things are changing over time so. Now I'm going to go to the third act and we'll spend the remainder of the time on. That we're. Gonna discuss. Customer, service and this is an easy one I could throw lots of stats up here, there's. A room, to grow to have better customer, service no one likes calling, people no one likes being. Transferred, to someone who can answer the question they, just want to get their answer on the first time they, want to make sure that, from. A customer standpoint. They. Get, their get. What they need quicker and faster at. The same time it's, instant when you talk to like our VP, of customer support, she. Truly believes and I think this is pretty widespread the, customer service is the tip of the spear of how companies feel about our brand so, how you do that right how you answer their questions right not. Only from a live agent but how do you get it done before they even have to call someone is super important, so I'm gonna invite Frank Frankston Wiles the general manager, for. Our new customer service offerings. And he's gonna walk through our product strategy, as, well as go through some demos and. Look. At both sides of both be. Cool. Young. Insights. And virtual, agents thanks. For having me Joan so um, as. You heard I'm Frank Wagle I run the customer.

Care Telogen steam it's. One of these new, AI offerings, that you that you heard about him what. Gets. Me really excited about, this is. Customer. Services, John already mentioned, really is these. Days at the forefront, of our companies differentiate, themselves I'd. A lot. Of times the, experience, a customer will have with, your support, will be determining, whether their buy more product, what they say to their, friends their and colleagues about your company and so on now. At the same time everybody's. In a pressure to get the organization these support teams more and more efficient, at, the same time increasing cset. Right we all want happier customers, but we want to spend less on it and have, a lot, better support experience and for me this, is a great area where, a I really. Can shine because. If you look at what support, teams do that, typically is kind of from about. A large, volume of answers. That really the support agents can do in their sleep and they know but they do take. A lot of the time from the from the agents, and often impact, then the, time they can spend on the really complicated issues, and so, where, we are going and what we are really creating. Here at, Microsoft is the ability to. Holistically. Look at customer. Support together, with artificial intelligence. I'll show you pass how to do it better all the way to automating. The most common, topics to, offload the humans so the human agents can focus on the complex cases and your customers don't have to wait in queues in LA and so on until they get to speak with a representative now. We're, doing this already today so I think John referred to it we have it in production at large companies we ourselves if, you go to the, Microsoft support site, I have, a virtual agent their HP Macy's. As some other customers, who publicly can talk about and between all of them we're, doing millions of sessions, helping. Customers today, right now now. The big thing is that they're, today, this. Is something, that really, only very large companies, engage, with because, frankly. You start a very, large engagement. With a, services. Organization, and then we would use our technology to custom, create these. Virtual agents. And, the, thing, that we are very very proud to announce today is, that, we know bringing every. Thing we've learnt there to, ace a service, making, it possible, now to really, get, go and adopt this at its, scale. Meaning, any company, you, just sign up you try it out to create your own virtual, agent you, get a eye for insights. Into your support organization, without having. To have AI experts, data scientists. Start using your developers, and creating. A large-scale project and that, really for us is, so crucial because it now brings this power that we've developed. And, the years of experience we have come in creating, those as custom, bespoke systems, really, to enable any company, to take advantage, of it to take you to that next level and so. Where, we're heading for customer services we're going, to provide a range of these SAS offerings, that you can adopt individually, or you can use all together and I'm actually going to show you in the demo how, are some of the insights and the the, bots all come together, they're. Very easy to adopt and customize now, before I am ran, customer. Care I actually am used to run power apps and I, don't know whether anybody here has had a chance to try and build applications, with power apps it's all about, empowering. The individual, bringing, the, ability, to, empower.

Apps Case create applications. Here now to create customer, service, virtual, agents, to, the people who know the subject matter best, right. Because think, about it for support, you already have people in your company you know everything, about the product they know how they want a virtual agent to interact, to and, project the right voice the right manner of interacting, with customers, you. Have those people are ready today in your company I probably write call scripts for. Your father Union agents, um, but. What we're now for the first time enabling is that those audiences. Those experts, can actually go and take, their knowledge and expertise, and easily. Use it to create a bot because you do not need developers, AI experts, data scientists, anymore and that really that democratizing. Off of this AI technology, is something that I'm very passionate about because, I believe the, only way given. The digital transformation happening. So fast and the speed, with which companies, change it's the only way how, we can kind of keep up and make, sure that the fullest potential can be realized by all companies. Not just you know the. Top ten or 20, or 100 they, can spend very, large amounts of this and. We, also make sure that it works with your existing data and systems so, even. If you're not a dynamics customer, you'll, be able to adopt, both the virtual agents, as well as the customer, service insights it works against all. The standard systems, on. The standard data it integrates, with it of course if you are using dynamics, you'll. Be able to. Integrate it out of the box and some things it will show up and. So concretely there are two products, they. Want to talk about one. Is D. 365. Dynamis 265, ai for customer service insights, this. Is all about getting a, greater, understanding about how your support team is doing including, any virtual, agents you may have, it. Really lets you optimize this, using the power of AI and I'll. Talk, a little bit more about in what ways and, then the virtual agent which is really automating. Support. Topics, through. A bot and how you can build that, inside. Is going to go into preview next month so, you'll be able to try that hands-on yourself, very. Soon and the. Virtual, agents, product is going, to come out early next. Year. So. With that let. Me go and show you some of this in real, life. We're. Ready to go to D, once time. Logging. Back into my machine quick, show, of hands who, here whose. Company, here is using, chat. In customer, support today. Okay. If, you everybody, else what is is voice or the, primary Channel or email let's say raise your hands if it's voice. Okay. So mainly, email then I take it or all people don't don't, know so. See. Here is and the insights, product, the. Insides is like I said a single pane of glass where, you can see how your support team is doing including, any virtual, agents, and so, you. See yeah um you, know a lot of the standard metrics I can, I can go for example here and say let me show for the whole month and then, you, you. Know see for example here, in the case volumes. Right ice either I've got a big hole in the weekends which makes sense it's a business product. Really. Where. The AI part, is coming into this is, what. We have here on the left and we'll have this in a bunch of other places are I'll show you, the. Standard problem is that when cases come in. Your. Agents, you, don't see the similarities, between cases, easily, so if for your analysis, you normally see you know this. 500. Cases that are unresolved or something or here you know 5,000, cases that are new that's, easy any any bi system can, give you that stat the, problem is normally are you missing the context, of which, of those cases actually about the same topic, your.

Human, Agents will know this because you know that often will will have support. Articles, and other spiders but normally there's no way to automatically, figure this out and this is really where, the same natural. Language understanding technology. That we've developed for our BOTS comes, into play because what you see here as these case topics, was, not entered by a human, but, it's actually the result of, the. AI looking, at the case data and, deciding. Hey I think those you. Know. 568. Cases, actually, about the same topic, and the topic we believe is that when a user inputs, a coupon code the websites that promotion expired, but. It hadn't yet expired, it. Understands, that all those cases are about the same thing and it now groups them and once, you know which, cases, are about the same topic, fully automated, you, now get a whole new level of insight, that he, can do, so. In addition to you know the more traditional, KPIs, for, example. If I go to my incoming, cases I now. See you know what these topics are and I, see for example emerging. Topics I can. Do the analysis, where, we looking at well we think this is a cluster, offer, offer support. Topic, that's, coming up and we see how it changes, day, by day week by week and so we can actually identify, what. Are topics, that are suddenly growing. Those are on Sina for example here you've got once it has 84, cases you know it's nowhere near the the most. Popular, topics, you. Know even here 43, but, we know there's a meaningfully, change happening, it went, up by almost 20% versus, last period those are the ways how you can identify what. Are issues, that, may be really, important, and you can start addressing their before they have become. A big problem right, and this is exactly my view where AI really. Helps you because it can do things that as a otherwise. You will just lose in the data because. If you just see you know there's hundreds, of cases flying, by the. Support manager you can't really go and look at each case individually and, you would just lose completely, new you. Know the the at, breath the, the perspective, to realize what a new, topics, that you might want to be able to address you. Know and that can go. And I can drill in and I'll show you that morning in a second demo in a second but you know you can go and drill into these topic, Foster's and then, look specifically. You know here I can say Oh Vincent, seems to have you know a bunch of these cases I can really now go and work with individual. Agents, you. Know we've got something about the resolve. Impactors, for example, so, we can tell you we can break up and you know know. For example that, controls and nutrition ones have the biggest impact on cset.

Right, And the same for resolution, time I can go and start understanding, what. Which of these topic, clusters, has the biggest. Contribution. The biggest negative impact, right for example when, the user inputs a coupon code, the. One topic we talked about earlier, right the resolution, time and it's. Really quite high and there's a lot of volume so we know overall this is really impacting, 2 by 2 percent, of the overall case, resolution, time so you start to see how I can now go and specifically, target, my reaction. Based. On this inside and this is really where it's all about its cang outstanding, then being able to take an action on it and, then. The integration with virtual agent that's coming I can. Show. You here, a little bit this is the the KPI summary, that you already saw right, and so here see you cake incoming, cases is going up and. TEKT here's an emerging topic, that has quite a drastic change in volume, right, still, the total count isn't that high but I see there's a big change and actually the school buddy 1000 in this example let's say is something, a new product we just launched, so. I can go and now, go. And drill in, you. Look at the details, of this cluster the square showed you earlier now let me go down here to the Sankey chart with, this now lets you do is, neck. Tea shows you where, these, questions, originated, right across the different channels that support, and you, see a few things you see okay this virtual agent that this in this example cantos has deployed doesn't. Answer it so it's not a topic, that's already automated, and you see there's a whole bunch of unresolved. Basically. Meaning that this would be a new support topic your, support, team, doesn't yet have good answers to it so they're spending a bunch of time on this and, you just caught it and, you can go you know what I think we can totally your answer automate, answering, this topic and so, thanks to the integration will, have between the, insights product, and the virtual agent product now, without being, an area expert, I can go and say you know what I want to automate, this topic, and. I don't know who here has ever tried building a bot at the moment when you build a bot for, customer service it or. Any other thing it typically involves developers, use bot framework you, start coding and a, lot of things they're just you. Cannot do in, its support organization, here I just say I want to create this new topic. Then. You, know you help the AI, understand. What will people say, some. Of this we already prefilled, you can add more phrases but, then especially you. Can go and create the, conversation. Just. Like you would write a call script and tell you human agents, what, you want to do he can now tell the bot in a very very intuitive manner and, I can go and start, you know the virtual agent should say something. And. Then, if, I let me just skip forward to, a full kind, of tree here, you see a more complex, kind of conversation, and so. You can literally very intuitively, say you know which, model of school body do you have and if it's a thousand, this is what I want to tell this, way you can make sure the bot interacts, directly in, the tone of and, the style that your company wants to and you, can of course provide the right answer which is ultimately what our customers, care, most about right and now once I have deployed, this to, my website the, virtual agent now will, be able to, just go and answer this question, and, think.

About It it means now that all your support managers, have, the data to, understand, what are new topics that are impacting, what our topics may be where customers, are not happy about you. Can go and easily update the, response of the bot if you decide to automate, it and then, the, bot can provide the answers and, looking. At this is the data set you know a few weeks later, simulated. And then you'll see right that now my virtual agent can actually handle a lot of this volume, and so instead of having the, human agents either not know what to do or. Take time to explain how to reset the body they. Can spend time on more complex diagnostic. Troubleshooting all, the things that which humans are really great and an AI honestly, isn't there yet and this. Ease with which all this is possible, really, makes it now applicable to, the very broad audience any. Company, can go and start using it to, raise their. Customer. Service into this new era of. AI. Let. Me go back to five. No. 5 was the right one for the slides and, kind of just quickly, recap a, little, bit so the. First product, that you saw is customer service insights, it's, really all about the single player pane of glass across. Humans, and virtual, agents, we, do the automatic clustering. To really help you understand, what, are the topics that come in versus, just looking at case titles, and having thousands of those and you. Know today many of you might do this via an Excel spreadsheet. Which. Of course doesn't, happen all the time and then how do you know it's very difficult for humans to go through thousands, of cases and try to remember, which of those are common ones ai. Is very very good at identifying those, then, ultimately what it leads to is that, you can build much, improved satisfaction. And loyalty from, your customers, because they get relevant, answers very quickly very easily while. Still being able to escalate, to humans of course and then. Those, virtual agents, as, he said you can now just easily automate, them you. Don't need to have any of the expensive, AI. Experts. Data scientists, any of the things that are really hard to find these days, instead. Your, existing. Support. Managers, can, go and use this your IT staff can, do the integration through flow very, straight for straightforward. And all, of this is seamlessly. Integrated, you saw how you're able to go from insights directly. Into the agent to automate. You.

2018-10-10 21:40

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