>> Announcer: Live from the Wigwam in Phoenix, Arizona it's the CUBE, covering Data Platforms 2017. Brought to you by Qubal. >> Hey, welcome back everybody, Jeff Frick here with the CUBE along with George Gilbert. We're at Data Platforms 2017 a the historic 99 years young Wigwam resort outside of Phoenix and we're excited to be joined by our next guest, Alex Sadovsky, he the director of data science for Oracle Data Cloud. Welcome. >> Thanks, thanks for having me. >> Absolutely, I know so I know we got a short time window, you're racing off to your next session. So, for the people that aren't here, what are you going to be talking about in your session here? >> So, the Oracle Data Cloud, what we do is online advertising and essentially we have lots and lots of data, customers comet to us and they have some sort of question in mind. They want to say, I want to figure out who's going to buy a mini-van in California next month, or who's going to get a hotel in Las Vegas, who's going to buy Kraft macaroni and cheese? All sorts of different questions. We have all of that data, we have to turn it into actionable insights, into audiences for them so they can advertise Facebook, Twitter, all over the web. And so, what this talk is really focusing on is how do we take all of this data and use it efficiently? And it's going to talk about the technologies that we've used specifically Hive, and then moving that technology over to Spark, just so that we can use more data, get quicker processing, and essentially make our clients have a better experience and give 'em a better product. >> And do the clients execute the results of this process inside their other Oracle apps, or is it something that they can use with any number of apps? >> So, a lot of the ways that we work, we actually are interfaced with companies like Facebook and Twitter directly. And so, essentially what we're doing is we're partnering with them so that the client, all they really need to do is kind of come to us either onboard some data through maybe other Oracle applications or onboard data directly through us and then push it out, we help push it all the way through the process, all the way into Facebook, etc. >> Yes, 'cause we were covering Oracle modern marketing, which is now Oracle modern customer experience, I'm sure you guys must be tightly integrated with all that. >> Yeah, and so for Oracle Data Cloud it's kind of interesting we're a collaboration of five recently acquired start-ups. And so it's everything from two to three years ago all of this coming together. So, for us, we're really excited because we're just at the tip of the iceberg of getting into the whole Oracle ecosystem and having that help build up our product even better. >> So, when you say partner with Facebook or Twitter, that would be for brand or direct response advertising that one of your B2B clients has signed up for? Or I should say, B2B, your B the client is B, and the end customer's C, so it's a B2B2C. And now okay, so you help them in a consultative way. You have the data, you have a consultative sales approach, are you building models for them? Or are you telling them, sort of running a model? >> Alex: Yeah. >> Sort of which is it? >> So, we will, we run models based upon data. So, a customer could come to us with, here are a thousand people that that customer knows bought their product last month, and they say, we want to expand our business, we want to advertise to 20 million people who might be similar to those thousand. And so that's where all of our data comes in. We can look at those thousand people and we can say, hey did you guys know that most of your customers are millennials? Did you know that most of them tend to live on the west coast or east coast populated cities? And we're not really consulting that in the sense of like there's people looking at the data, it's all machine learning. And so computers are looking at all of our data to help get insights from what the customers bringing to us. >> So, would it be fair to say then that the, let's say the thousand example that the customer brings in is the training data. >> Yes. >> And then you use your data in your databases, your consumer databases, to say, to generate essentially scores, since they were going to send out to these. >> That's 100% right. They come in with a thousand of their customers, we see how those customers rank up against every single household in the entire United States. >> I was going to say, we're going to be at Spark Summit in a couple weeks or a week, whenever it is. I can't keep track of all these shows. So, they can't do the whole thing wiHive to Spark, but in three minutes or less wiHive to Spark. >> So, number one reason for us, and number one reason I think a lot of people are moving to Spark is just speed. Without getting into a lot of technical details, there's just a lot better engine, a lot better flexible engine underneath Spark than kind of traditional Hive. >> And then machine learning models are, most of the libraries are built in, which Hive doesn't have. >> Yeah, machine learning is really built into Spark. There's, you know, whole projects within Spark built around that. And so, for us, we really, Spark considers machine learning kind of a first class citizen. And since that's essentially what our business is, we go 100% into Spark as well. >> So, let me ask you, what is the scope now and potentially in the future for these data based predictive models where customer comes to you with essentially some labeled data and then you'll come out with I guess that's the training data and then right now you have data in what categories? And then what categories would you like to have? >> So, we have data everything from what people are doing on the web, so what they're searching for, what websites they're going for. We have grocery store data. So, what people are buying in the grocery store. We have retail data. So, what people are buying in the malls. Because a lot of what happens is, even though consumers are spending a lot more time on the web, 80%-90% of purchases are still made in the store. So, we have all of this actual real world purchase data that we've partnered with different retail partners, including like automotive data, too. So that's really like the core of our data. So, really what we try to do is have data sets strategically placed all around and that's why the Oracle Data Cloud is made up of so many different start-ups, we're really getting expertise from different areas for different data sets to bring that together. >> Do you need to buy those sources of data? Or can you license? >> Data is everything from licensed to purchased outright to shared, revenue sharing with other companies. It's really, there's a huge data market right now. It's kind of the data gold rush and we're trying get in anywhere we can, figure out what's going to help us and what's going to help our customers make better models. >> What would you like to see in terms of a, if you look out a couple years, where would you like to see your data assets sort of augment all your Oracle applications? >> Yeah, so I think... SO, augmenting Oracle really we have so many different data assets that everything from like live streaming data, of what people are searching for on the web, to historically what someone has bought in the last three years and so, as we partner more and more with Oracle, Oracle has different things in healthcare, in retail, in all sorts of B2B applications. And our data really can fit almost everywhere. It's really like a data driven sort of product. And so, we've been partnering with Oracle left and right many different groups just trying to figure out where can this data help augment kind of your services. >> Alright, Alex, well, we got to leave it there. That was a good summary. I know you got to race off to your thing. I'll let you take a breath and get a glass of water. So thanks for squeezing us in your busy day. >> Alex: Thanks so much. >> Alright, he's Alex, he's George, I'm Jeff, you're watching the CUBE from Data Platforms 2017. We'll be right back after this short break. Thanks for watching.

>> Announcer: Live from Las Vegas, it's The Cube, covering Oracle Modern Customer Experience 2017, brought to you by Oracle. (dynamic music) >> John: Hey, welcome back everyone, we're here live. Day two coverage of Oracle's Modern CX Modern Customer Experience #ModernCX. Also check out all the great coverage here on The Cube, but also on the web, a lot of great stories and one of the people behind all that is Des Cahill, who's joining Peter Burris and myself. Kicking off day two, Des, great to see you, Head of Customer Experience Evangelist, involved in a lot of the formation and really the simplification of the messaging across Cloud, so it's really one story. >> Yeah, absolutely, so John, Peter, great to be here. You know, I think the real story is about our customers and businesses that are going through transformation. So everything that we're doing at Oracle, in our CX organizations, helping these organizations make their digital business transformation and the reason they're going through this transformative process is to meet the demands of their customers. I'd say it's the era of the empowered customer. They're empowered by social, mobile, Cloud technologies and all of us in our daily lives can relate to the fact that over the last five, 10 years, the way that we buy, our journey as we buy products, as we do research, is completely different, than it used to be, right. >> Talk about the evolution, talk about the evolution of what's happening this week, because I think this is kind of a mark in time, at least from our observation, covering Oracle, this is our eighth year and certainly second year with the modern marketing experience now, >> Des: Yeah. >> the modern customer experience, where the feedback in the floor, and this is noteworthy, is that the quality is great, people at the booth are highly qualified, but it's simple. It's one fabric of messaging, one fabric of product. It feels like a platform, >> Yeah. >> and is that by design (laughs) or is that kind of the next step in the evolution of, >> Des: Yeah, John. >> Marketing Cloud meets Real Cloud and? >> Yeah, yeah, so absolutely John. I mean that, that is by design and again, to support our customers and their needs on this digital business transformation journey, it starts obviously with fantastic marketing, we've just got fantastic capabilities within our Marketing Cloud, but then that extends to Sales Cloud. If you generate leads in marketing and you're not handing them over to sales effectively or of a good sales automation engine and that goes on to commerce, CPQ, social, and service. And all of this, if we bring this back down to again, this notion of the empowered customer, if you're not providing those customers with connected experiences across marketing, sales, service, commerce, you're not... you're going to, you might lose those customers. I mean, we expect connected experiences across our whole journey. If I'm calling my cell phone provider, 'cause I got a problem, I don't, and I don't want to call one person, get transferred to another person and then go to the website to chat with someone, have a disconnected experience. I want them to, when I call, I want them to understand my history, my status as a customer, I'm spending 500 dollars a month on them, the problems I've had before. I want them to have context and to know me in that moment and as Mark Hertz says, it's like a moment of truth with my cell phone provider. Are they going to delight me and turn me into a customer advocate, or am I going to leave and go to another cell phone provider? >> Well let's talk just for a second, and I want to get your comments on this and how it relates specifically to what we're saying here. Digital has two enormous impacts. One, as you said, that a customer can take their research activities with them, on their cell phone. >> Yeah. They have learned, because of commerce and electronic commerce, they've learn to expect and demand a certain style of engagement >> Des: Right. >> and that's not going to change, so if you are not doing those things-- >> We like to say Amazon is the new benchmark, either B to C or B to B, it doesn't matter, right. >> It is a benchmark, at least on the commerce side, so it's, so that's one change, is that customers are empowered. The second big change though, is that increasingly, digital allows people to render products more as services and that's in many respects, what the Cloud's all about. >> Des: Right. >> How do you take an asset, that is a machine and render it as a service to someone? Well now we can actually use digital technologies to render things more as services. The combination of those two things are incredibly powerful, because customers, who now have the power to evaluate and change decisions all the time are now constantly making decisions, because it's a pay-as-you-go service world now. >> Des: Right. >> So how do those two things come together and inform the role, that marketing is going to play inside a business, 'cause increasingly, it seems to us that marketing is going to have to own that continuous, ongoing engagement and deliver that consistent value, so a customer does not leave, 'cause you have more opportunities to leave now. >> Well, I, so I think that's a good observation, Peter. I do think that marketers can play, and do play, a leading role in being the advocate for the customer within the brand, within the company and as a marketer myself, I think about not just the marketing function, but I think about, well, what is the experience, that that lead or that prospect going to have when I hand over to sales? And what is the experience that they are going to have, when I hand them over to service? And in my past roles as a CMO, the challenge I always faced was that I couldn't get information out of the sales automation system or out of the service automation system, so as a marketer, I couldn't optimize my marketing mix and I didn't have visibility on which opportunities I passed, which leads I passed over turned into the best opportunities, turned into the best deals, turned into the customers, that were most loyal, that got cross-sold and up-sold and were the happiest. So I think, going back to Oracle's strategy in all of this, it's about having a connected, end-to-end suite of Cloud applications, so that there's a consistent set of data, that is enabling these consistent, personalized, and immediate experiences. >> I think that's interesting and I want to just validate that, because I think, that is to me, the big sign that I think you guys are on the right track and executing and by the way, some of the things you're talking about used to be the holy grail, they're actually real now. >> Des: Right. >> The dynamic is the silos are a symptom of a digital-analog relationship. >> Des: Right. >> So when you have all digital, the moment of truth starts here, it's all digital. So in that paradigm, end-to-end wins. And at Mobile World Congress this year, one of the main themes when they talk about 5G, and all these things, that were going on, was you know, autonomous vehicles, (laughs) media entertainment, smart cities, a smart home, you know, talk to things. To your point, that's an end-to-end, so the entire world wants-- >> Des: Throw IoT in there. >> Throw IoT, >> Right. >> So again, these digital connections are all connected, so therefore, it is essentially an end-to-end opportunity. So whoever can optimize that end-to-end, while being open, while having access to the data, >> Des: Right. >> will be the winning formula. >> Des: Right. >> And that is something that we see and you obviously have that. >> And then the other piece is how do you actualize that data? Right, and I know you spoke with Jack Berkowitz about adaptive intelligent apps, it's, we're taking approach to artificial intelligence of saying, how can we bring to bear the power of machine learning, dynamic decision science, so that all this data, that's being collected and enabled by all these digital touch points, these digital signals, how do you take that data and how do you actualize that, 'cause the reality is, 80% of data that's collected today is dark, it's untouched, it's just collected, right. >> Well, here is the hard question for you, you know I am going to ask this, so I am going to ask it, here's the hard question. >> Des: Yeah. >> It really comes down to the data, and if you don't, you, connected networks and all that good stuff is great fabric, end-to-end. >> Des: Absolutely, yeah. >> This is certainly the future, it's the new normal, it's coming fast. >> Right. >> But at the end of the day, the conversation we've been having here is about the data. >> Des: Yes. >> What is your position with Oracle on connecting that data, 'cause that ultimately is what needs to flow. >> Des: Right. >> How does that work? Can you just take a minute to >> Sure, sure. >> to address that, how the data flows? >> Yeah, I think it starts with our end-to-end connected applications, that are able, that are connected with each other natively and are sharing that same data set. We obviously recognize that customers have mixed environments, so in those cases, we can certainly use our technologies to connect to their existing data stores, to synchronize with their existing systems, so it all starts with the cleanliness and quality of that baseline customer data. The second piece I'd say, is that we've made a lot of investments over the last five years in Oracle Data Cloud and Oracle Data Cloud is a set of anonymized, third party data. We've got 5 billion consumer IDs, we've got a billion business IDs. We've got a tremendous amount of data sources. We just announced a recent acquisition of a company called Moat, last week at our Oracle Data Cloud Summit in New York City. So we've made a tremendous investment in third party data, that can augment anonymized third party data, that can augment first party data, to allow people to have not just a connected view of the customer, but more of a comprehensive view and understanding of their customers, so that they can better talk to them and get them better experiences. >> That's the key there, that we're hearing with this intelligent, adaptive intelligent app kind of environment, >> Yeah, yeah. >> where machine learning. The third party data integrating within the first party data, that seems to be the key. Is that right, >> Absolutely. >> did I get that right? >> Yeah, well I would say there's a number of points, so I would say that, that, you know, you can think of the Oracle Data Cloud combining with the BlueKai DMP and being a great ad-tech business for us and a great solution for digital marketers in and of itself. What we've done with adaptive intelligent apps is that we've combined that third party data with decision science machine learning AI and we've coupled that with the Oracle Cloud infrastructure and the scale and power of that. So we're able to deliver real-time, adaptive learning and dynamic offers and content at 130 millisecond clips. So this is real-time interaction, so we are getting signals every time someone clicks, it's not a batch mode, one-off kind of thing. The third piece is that we have designed these, designed these apps to just embed natively, to plug into our existing CX applications. So if you're a marketer, you're a service professional, you're a sales professional, you can get value out of this day one. You've got a tremendous data set. You've got real-time, adaptive artificial intelligence and it plugs right into your existing apps. It's a win-win. Take your first party data, take your third party data, combine it together, put some decision science on there, some high bandwidth, incredible scale infrastructure and you're getting, you're starting to get to one-to-one marketing. You're freeing your marketing teams from being data analysts and segmenting and trying to get insight and you're letting the machine do that work and you're freeing up, you're freeing up your human capital to be thinking about higher-level tasks, about offers and merchandising and creative and campaigns and channels. >> Well, the way we think about it, Des, and I'll test you on this, is we think ultimately the machines are going to offer options. So they're going to do triage on a lot of this data >> Des: Right, right. >> and offer options to human decision-makers. Some of the discretions, we see three levels of interaction, >> Des: Yeah. >> Automated interaction, which, quite frankly, we're doing a lot of that today in finance systems. >> Des: Yes. >> But then we get to autonomous vehicles, highly deterministic networks, highly deterministic behaviors, >> Des: Right. >> that's what's going to be required in autonomy. No uncertainty. Where we have environmental uncertainty, i.e. that temperature's going to change or I, some IoT things are going to change, that's where we see the idea of turning the data and actuating it in the context of that environmental uncertainty. >> Des: Right. >> We think that this is all going to have an impact on the human side, what we call systems of augmentation, >> Des: Right. >> where the system's going to provide options to a human decision-maker, the discretion stays with the human decision-maker, culpability stays with the human decision-maker, >> Des: Right. >> but the quality of the options determine the value of the systems. >> So the augmentation is-- >> The augmentation's great. >> So let me give you a great example of that with AIA. So, take for example, you're a pro photographer and you got a big shoot the next day and your camera, your main camera you bought three months ago, it breaks. And you buy all your stuff at photog.com and you call 'em up and what could happen today? "Hi, what's your account number? "Who are you? "Wait, let me look you up, OK. "I'm sorry, I'm not authorized to get you a return." You know, boom, and the person's like, "I'm never going to buy from them again." Right, it's that moment of truth. Contrast that with a, 'cause the person making that decision, if it was the CEO getting that call, the CEO would be like, "We're going to get you a camera immediately." But that person that they're talking to is five levels down in a call center, Bismarck, North Dakota. If that person had AI, adaptive intelligent apps helping them out, then the AI would do the work in the background of analyzing the customer's lifetime value, their social reach, so their indirect lifetime value. It would look at their customer health, how many other services issues, that they have. It would look at, are there any warranty issues or known service failure issues on that camera and then it would look at a list of stores, that were within a five mile radius of that customer, that had those cameras in stock. And it would authorize an immediate pickup and you're on your way. It would just inform that person and enable them to make that decision. >> Even more than that, and this is a crucially important point, that we think people don't get when they talk about a lot of this stuff. These systems have to deliver not only data, but also authority. >> Exactly. The authority has to flow with the data. >> Des: Right. >> That's one of the advantages-- >> On both sides, by the way, on the identity and-- >> On both sides. >> And I think that employee wants that empowerment. >> Absolutely. >> No one wants to take a call and not make the customer happy, right. >> Peter: Absolutely, >> Yeah. >> because that's a challenge with some of the bolt-on approaches to some of these big applications, is that, yeah, >> Exactly. >> you can deliver a result, but then how is the result >> How is it manifested? >> integrated into the process >> Right. >> that defines and affords authority to actually make the decision? >> OK, so let's see, where are we on the progress bar then. because we had a great interview yesterday with the CMO from Time Warner. >> Yeah. >> OK, Kristen O'Hara, she was amazing. But basically, there was no old way of doing data, they were Time Warner, (laughs) they're old school media and they set up a project, you guys came in, Oracle came in, and essentially got them up and running, and it's changed their business practice overnight. >> Des: Right, right. >> So, and the other thing we heard yesterday was a lot of the stuff that was holy grail-like capabilities is actually being delivered. So give us a slice-and-dice what's shipping today, that's, that's hot and where's the work area that's road-mapped for Oracle? >> Sure, well-- >> And were you guys helping customers? >> Sure, I'll talk about a couple of examples, where we're helping customers. So, Denon and Marantz, high end audio company, brand's been around 100 years. The way music is delivered, is consumed, has changed radically in the last 20 years, changed radically in the last 10 years, changed even more radically in the last five years, so they've had to change their business model to keep up with that. They are embedding Oracle IoT Cloud into every product they sell, except their headphones, so all their speakers, all their AV receivers and they are using IoT data and Oracle Service Cloud to inform, not only service issues, like for example, they are, they're detecting failures pro-actively and they're shipping out new speakers, before they fail or they're pushing firmware to fix the problem, before it happens. They're not only using it to inform their service, they're using it to inform their R&D and their sales and marketing. Great example, they ship wireless speakers, HEOS wireless speakers, highly recommend 'em, I bought 'em for my kids for Christmas, they're the bomb. But customers were starting to... They were getting a lot of failures in these wireless speakers. They looked up the customer data, then they looked up the IoT data. They found that 80% of the speaker failures, the products were labeled Bathroom as location in the configuration of their home network setup and what they realized was that customers were listening to music in the bathroom, which is a use case they never thought of and the speakers weren't made to be water or humidity-proof, so they went to the R&D department, 14 months later, they ship a line of waterproof HEOS speakers. The second thing is they found people, who were labeling their speakers, Patio, they were using it on the patio, they didn't even have a rechargeable battery on it, so they came out with a line with a rechargeable battery on it. So they're not only using IoT data, for a machine maintenance function, >> John: 'cause they were behaving-- >> they're using IoT data to inform, inform R&D and they're also doing incredible marketing and sales activities. We had Don Freeman, the CMO of Denon on the main stage yesterday, talking about this great, great stuff they're doing. >> And what's the coolest thing this week, that you're looking at, you're proud of or excited about? >> I'm excited about a lot of stuff, John. This week is realized, you alluded to this week has been really, really fun, really great, a lot of buzz, obviously a lot of buzz around adaptive, intelligent apps and we've talked about that. But I would say also beyond a doubt, that intelligent apps for CX, we've introduced some great things in our Service Cloud, the capability to have a video chat, so Pella Windows was also on one of our panels today and they were talking about the ability for, to solve a service issue, the ability to show a video of what's going on, just increases the speed with which something can be diagnosed so much faster. We're integrating on the Service Cloud, we're integrating with WeChat and we're integrating with Facebook Messenger. Now, why would you do that? Well again, it comes back to this era of the empowered consumer. It's not enough that a company just has a website or an 0800 number that you can go to for support. Consumers are spending more time in social messaging apps, than they are on social messaging sites, so if the consumer wants to be served on Facebook Messenger, 'cause they spend their time on it, the brand has to meet them there. >> John: Yeah. >> The third thing would be the ability for the Marketing Cloud and Service and Sales Cloud, we've got chat bots, voice-driven, text-driven, AI-driven, so mobile assistant for the sales professionals, so you can input data on the road, "Hey, open an account, here's the data "for the transaction here what's going on." >> John: Yeah. >> Incredible, incredible stuff going on all over the stack. >> I think the thing, that excites me, is I look at the videos from last year and the theme was, "Man, you guys have "all these awesome acquisitions," >> Des: Right. >> "But you have this opportunity with the data," and you guys knew that and you guys tightened that together and doubled down on the data >> Des: Yeah, with banking, yeah-- >> and so I thought that was a great job and I like the messenging's clean, I think but more importantly is that in any sea change, you know, we joke about this, as we're kind of like historians and we've seen a lot of waves, >> Des: Right, for sure. >> and all these major waves, when the user's expectations shift, that's the opportunity. I think what you guys nailed here is that, and Peter alluded to it as well, is that the users are expecting things differently, completely differently. >> Let me share a stat with you. 50% of the companies that were in the Fortune 500 in the year 2000, are either out of business, acquired, gone, 50% and those companies, >> Dab or die. >> Blockbuster, Borders, did they stay relevant? >> John: Yeah. I think changing business practice based on data is what's happening, it's awesome. Des Cahill, here on The Cube. More live coverage, day two of Modern CX, Modern Customer Experience, #ModernCX. This is The Cube, I'm John Furrier with Peter Burris, we'll be right back. (dynamic music)

>> Narrator: Live from Las Vegas, it's theCUBE, covering Oracle Modern Customer Experience 2017, brought to you by Oracle. (bright, lively music) >> Hello and welcome back to a CUBE coverage of Oracle's Modern Customer Conference here at the Mandalay Bay in Las Vegas. I'm John Furrier with SiliconANGLE, theCUBE, with my co-host this week, Peter Burris, head of research at Wikibon.com, part of SiliconANGLE Media, and our next guest is Austin Miller, Product Marketing Director for Oracle Marketing Cloud. Welcome to theCUBE conversation. >> Thank you very much for having me. >> This coveted post-launch spot. >> Yeah, we have a lunch coma kicking in, but no, seriously, you have a really tough job because you're seeing the growth of the Platform Play, right, really robust horizontal platform, but how you got here through some really smart acquisitions but handled well, and integrated, we covered that last year. You guys are seeing some nice tailwinds with some momentum certainly around the expectations of what the customers want. >> Yeah, I think that one of the best things when we start thinking about, to your point, product integration, it's also the way that we are talking to our customers about how they can use the products together. It's not really enough just to have maybe one talk to another, but unless we prove out the use cases, you don't get the utilization, and I think this year what we've really seen is getting those use cases to actually start getting some traction in the field. >> So this integrated marketing idea seems to be the reality that everyone wants. >> Where are we on that progress bar, because this seems to be pretty much unanimous with customers, the question is how to get there, the journey, and the heroes that are going to drive and the theme of the conference. But the reality is this digital transformation is being forced for business change. >> Austin: Absolutely. >> And marketing is part of that digital fabric. >> I think that one of the most interesting things about this is if you look at kind of the history of when did the stacks start becoming actually part of the story, it was at a point where we didn't really necessarily even have the capabilities to do it. As a result many marketers who thought they were maybe buying into a stack approach got a little bit burned. I think now we are actually at that place where that value is not only something that they can see inherently and say "oh, I'd like all these applications to talk together," but it's actually feasible, it's something that they're going to be able to use, and they can be optimistic about, frankly. >> Where are they getting burned, you mentioned that, from buying into a full stack of software for a point solution, is that kind of what you meant? >> No, I think that in the marketing realm, when you're talking to marketers, it is very easy to think about all the horrible things that they have to deal with on a daily basis, all these problems. And the reality is that oftentimes you've had to have this conversation with them that says, you know, there are not going to be easy answers to hard problems. There are usually hard answers to hard problems. We can help alleviate some of that friction, especially when we start talking about data silos or things about interoperability, so being able to not just have integration, but pre-built function within these particular platforms, but realistically, it just wasn't something that we necessarily in the market in general were able to deliver on until somewhat recently. >> So, I am very happy that I heard you use the word "use cases," especially at a launch, because that's been one of the biggest challenges of both marketing technology when we think about big data, there's been such a focus on the technology, getting the technology right, and then the use cases and how it changed the way the business or the function did things, kind of either did or didn't happen. Talk about how a focus in use case is actually getting people to emphasize the outcomes, and how Oracle is helping people then turn that into technology decisions. >> This may sound almost counterintuitive, but in reality the way that use cases we see helping us the most is that it really helps spur about the organizational changes that we need in order to actually have some of this happen, 'cause it's very easy to say, "we have all this technology marketer and you should be using it all," but if you don't actually prove it out and how that's going to impact let's say the way that they're creating their marketing messages, on even a kind of not exciting basis, like how are you creating your emails, how are you creating your mobile messaging, how are you doing your website, and then start talking about those in actual use cases, it's very hard for people to organize their organizations around this kind of transformation. They need something tangible to hold onto. >> And the old way with putting things in buckets, >> Austin: Exactly. >> Right, so so hey we got one covered, move on to the next one ... >> Peter: Or by channels even. We got an email solution, or we got a web solution and as the customer moves amongst these different mechanisms, or engages differently with these mechanisms, the data then becomes, we've talked a lot about this, becomes the integration point, and that as you said affects a significant change on how folks think about organizing, but what do you think are going to be some of the big use cases if people are going to be ... you're providing advice and counsel to folks on the 2017. >> Yeah, so I think that talking about marketing-specific use cases is really important, especially when we start thinking about how am I using my first-party data that I may have within a particular channel. And I'm using that to contextually change the way I'm communicating to somebody on another channel. But if we kind of take that theme, and we think about let's not just expand it to marketing but let's really talk about customer experience, because as a customer, I go in-store, I go on email, I go on your mobile app, I don't view those as different things. That's just my experience with your brand. And even as we start getting to maybe some of the service things, am I calling a call center? The way that we're really thinking about marketing is not only bringing all this information across our traditional marketing channels, but how are we helping marketers drive organizational change beyond the traditional bounds of even their own marketing department into service, into sales, into on-store, because in reality that's where kind of the next step is. It's not just about, to your point, promotional emails. It's about how are we bringing this experience across the full spectrum. >> So it's really how is first-person data going to drive the role of marketer differently, the tasks of marketing as a consequence, and therefore how we institutionalize that work. >> Absolutely, and I think that you can see this in the investments that we've made in the ODC, Oracle Data Cloud. It's first step, let's start thinking about how we can start moving around on first-party data, that'll be a nice starting point, but then afterwards, how are we taking third-party data let's say from offline purchases, starting to incorporate that and that store's third-party data, 'cause then we really start getting to that simultaneously good experience or at least consistent experience across digital, across in-store, we start piecing together, but we really need to start at that baseline. >> A lot of people have been talking about the convergence of adtech and martech for years, and we had a CUBE alumni on our CUBE many years ago, when the Big Data movement started to happen, and he was a visionary, revolutionary kind of guy, Jeff Hammerbacher, the founder of Cloudera, who's now doing some pioneering work in New York City around science. He's since left Cloudera. But he said on theCUBE what really bothered him was some of the brightest minds in the industry were working on using data and put an ad in the right place. And he was being kind of critical of, use it for cooler things, but we look at what's happening on martech side, when you have customer experience, that same kind of principle of predictive thinking around how to use an asset can be applied to the customer journey, so now you bring up the question of A.I. If you broaden the scope of adtech and martech to say all things consumer, in any context, at any given time, you got to have an A.I. or machine learning approach to put the right thing at the right place at the right time that benefits the user >> Austin: It's not scalable. That's the reality of it. To you point, if you're going to start thinking about this across all these different channels, including advertising as well, the idea of being able to do these on a one-off basis, from a manual perspective, it's completely untenable, you're completely correct, but to that point, where you're talking about the best minds in the industry maybe dedicated to figuring out, "if I put a little target here, am I going to get somebody to click on that ad one time, or how am I placing it," that is very much the way that we were at the very beginning parts of marketing technology, where it was bash and blast messaging, how can we just kind of get the clicks and the engagement, and how do we send out >> John: spray and pray >> Exactly. And now I think that we are getting to a much more nuanced understanding of the way that we advertise because it's much more reliant on context, it's not just how can I get my stuff in front of somebody's eyeballs, it's how am I placing it when they're actually showing some sort of intention for maybe the products I already have. >> Adaptive intelligence is interesting to me because what that speaks to is, one, being adapted to a real time, not batch, spray and pray and the old methodology of database-driven things, no offense to the main database cache at Oracle, but it's a system of record, but now new systems of data are available, and that seems to be the key message here, that the customer experience is changing, multiple channels, that's omnichannel, there needs to be ... everyone's looking for the silver bullet. They think it's A.I., augmented intelligence or artificial intelligence. How do you see that product roadmap looking, because you're going to need to automate, you're going to need to use software differently to handle literally real time. >> Completely. I think that this is a really important distinction about the way that we view A.I. and how it factors into marketing technology and the way that I think a lot of people in the industry do. I think that once again this theme of there aren't easy answers to hard problems, it is very pleasant to think that I'm just going to have one product that's going to solve everything, from when I should send my next email, to if there's clean water in this particular area in a third-world country, and that's just something that maybe sounds nice, but it's not necessarily something that's actually tangible. The way that we view A.I. is it's something that's going to be embedded and actually built into each of these different functions so that we can do the mission-critical things on the actual practical level, and kind of make it real for marketers, make it something that's isn't just "oh, buy this and it will solve all your problems." >> So I'm going to ask you the question, the old adage, "Use the right tool for the right job, and if you're a hammer everything looks like a nail." A lot of people use email marketing that way, they're using it for notifications when in reality that's not the expectation of the consumer, some are building in a notification engine separate from email. All that stuff's kind of under the covers, in the weeds, but the bigger question to you is, I want to get your insight on this because you're talking to customers all the time, is as customers as you said need to change organizationally, they're essentially operationalizing this modern era of CX, customer experience, so it's a platform-based concept which pretty much everyone agrees on, but we're in the early innings of operationalizing this >> Austin: Oh yeah. >> So how do you see that evolving and what do you want customers to do to be set up properly if they're coming in for the first inning of their journey, or even if they're midstream with legacy stuff? >> I think that that's a really good perspective, because you don't want to necessarily force people to go through excruciating organizational change in preparation if we're in maybe the first inning, but it is really just about setting up the organization to adjust as realistically we get into the middle innings and into the later innings. And really the kind of beginning foundation of this is understanding that these arbitrary almost like tribal distinctions between who owns what channel, who's the email marketer, or who's the mobile person, they need to be broken down, and start thinking about things instead of these promotional blasts to your point, or even maybe reactionary notifications. How is this contributing to the number of times your brand is touching me in a day, or the way that I'm actually communicating, so I think that it's an interesting kind of perspective of how we were organizationally set up for that, but the short answer is that A.I. is going to fundamentally change the way that marketers are operating. It's not going to fundamentally change maybe everything that they're doing or it's not going to be replacing it. It's going to be a complementary role that they need to be ready to adjust to. >> So you are, you're in product, product management. >> Austin: Product marketing >> Product marketing. So you are at that interface between product and marketing, both moving more towards agile. How are you starting to use data differently and how would you advise folks like you in other businesses not selling software that might not have the same digital component today but might have a comparable digital component in the future, what would you tell them to do differently? >> So, I think that the first step is to actually have an honest assessment of what we have and what we don't have. I think that there's a lot of people who like to kind of close their eyes or maybe plug their ears and just sort of continue down the path of least resistance. >> Peter: Give me ... >> Oh, an honest assessment of what kind of data we do have today, what kind of data we might actually need, and then most importantly, is that actually feasible data to get. Because you can't >> you can wish it but you can't get it >> You can wave a magic wand and say these are the numbers that I need on this particular maybe interest level of these particular ... >> John: The fatal flaw is hoping that you're going to get data that you never get, or is ungettable. >> Or, this is really something that I think a lot, would resonate more with marketers is that we have now set up all these different points of interaction that are firehoses of data spraying it at me, I may be able to retroactively look at it and maybe garner some kind of insight, but there's just no real way for me to take that and make it actionable right away. It is a complete mess of data in a lot of these organizations. >> And that's where A.I. comes in. >> Austin: Absolutely. It's able to automate that, reaction ... >> Peter: Triage at a bare minimum. >> Correct >> So the first starts with data. What would be the second thing? >> So it's data, presume that you're going to need help on the triage and organizing that data. Is there a third thing? >> I would say that you're going down the right path with the steps there, but once again, we're all talking about these concepts that do require a great deal of specialization and a lot of actual understanding of the way we're dealing with data. So honest assessment is definitely that first part, but then do I have the actual people that I need in order to actually take action on this? Because it is a specialized kind of role that really hasn't traditionally been within marketing organizations. >> I know you guys have a big account-based, focus-account-based marketing, you know, doing all kinds of things, but I'm a person, I'm not a company, so that's a database saying "hey, what company do you work for?" And all the people who work for that company and their target list. I'm a person. I'm walking around, I've got a wearable, I might be doing a retail transaction, so the persona base seems to be the rage and seems to be the center and we heard from Mark Hurd's keynote, that's obviously his perspective and others as well so it's not like a secret, but how do you take it to the next level? An account base could help there too, but you need to organize around the person, and that seems to open up the identity question of okay, how do I know it's John? >> I think that goes beyond just personal taste, but into what does this person actually do at this company, because I can go in and give a headspinning presentation to maybe a C-level executive and say, "look at all this crazy stuff you can do," and meanwhile the guy who might be making the buying decision at the end of the table's looking at that and being like, "there's no way we can do that, we don't have the personnel to do that, there's no chance," and you have already dissension from the innards of the actual people who are making the buying decisions. The vision can't be so big that it resonates with no one. And you need to understand on a persona level what is actually resonated with them. 'Cause feasibility is a very important thing to our end user, and we need to actually incorporate that into our messaging, so it's not just so pie-in-the-sky visioning. >> I did a piece of research, sorry John, I did a piece of research a number of years ago that looked at the impact of selling mainly to the CIO. And if you sell successfully to the CIO, you can probably guarantee nine months additional time before the sale closes. >> Austin: Yeah. Because the CIO says "this is a great idea," and then everybody in the organization who's now responsible for doing it says "hold on, don't put this in my KPIs while I take a look at it and what it really means and blah blah blah. Don't make me responsible for this stuff." You just added nine months. >> Absolutely. I even have a very minute example for something that we rolled out. This was a great learning opportunity. Because we rolled out a feature called multi-variant testing. It's not important what exactly it is for the purposes of this, but basically it's the idea of you can take one email and eight versions of it, test it, and then send out the best one. Sounds great, right? I'm an executive, I'm like boy, I'm going to get every last ounce of revenue from my emails, I'm only going to send out the best content. If you don't pitch that right, the end user, all they hear is wait, the thing that I do one of, I have to create eight of now? Am I going to get to see my kids ever again? That's just the way you have to adjust ... >> And seven of 'em are going to be thrown away. I'm going to be called a failure. >> Exactly. So it's just not something that you can take for granted because marketers have a variety of different roles and a variety of firm responsibilities. >> And compound that with everything's going digital. >> Exactly. >> So (mumbles) Austin, great to have you on theCUBE. Spend the last minute though, I'd like you just to share for the last minute, what's the most important thing happening here at #ModernCX besides the simplicity of the messaging of modern era of customer expectations, experiences, all that's really awesome, but what should people know about that aren't here, watching. >> I'd just say that the one thing that at least resonates most with me, and this is once again coming from a product and sort of edging on marketing, is that the things that we've been talking about with not only A.I. but even just simple things like having systems that are communicating to each other, they're actually real and we're seeing that as real. You can actually see them working together in products and serving up experiences to customers that we're even doing now as part of the sales process and saying "hey, this is how you would actually do this," as opposed to just "here's our Chinese menu of different options. Pick what you want and then we can just kind of serve it up." Because I think that there's something that's very heartening to maybe marketers who have a little bit of, I don't know, doubt about whether or not this is real. It is real, it's here today, and we're able to execute on it. >> And that's the integration of a multi-product and technology solution. >> I would almost say that it's slightly different from that though, in terms of, it's not just integration of these pieces, it's integration that's pre-built, so we actually have it pre-built together and then we also have these tremendous, new, innovative features and functionality that are coming with those integrations. It's not just portability, it's actual use cases. >> Would you say that it's as real as the data? >> It's as real as the data. I think that that's ... >> If you have the data, then you can do what you need to do. >> That's a very, a very good point. >> Austin Miller, Product Marketing Director at Oracle Marketing Cloud. Thanks for sharing the data here on theCUBE where we're agile, agile marketing is the focus. I'm John Furrier, Peter Burris. More coverage from day one at Mandalay Bay for Oracle Modern Customer Experience show. We'll be right back with more after this short break. (bright, lively music)