>> Live from Boston, Massachusetts, it's theCUBE, Covering IBM Chief Data Officer Summit. Brought to you by IBM. >> Welcome back to theCUBE's live coverage of IBM Chief Data Strategy Summit. My name is Rebecca Knight, and I'm here with my co-host Dave Vellante, we are joined by Christopher Penn, the VP of Marketing Technology at SHIFT Communications, here in Boston. >> Yes. >> Thanks so much for joining us. >> Thank you for having me. >> So we're going to talk about cognitive marketing. Tell our viewers: what is cognitive marketing, and what your approach to it is. >> Sure, so cognitive marketing essentially is applying machine learning and artificial intelligence strategies, tactics and technologies to the discipline of marketing. For a really long time marketing has been kind of known as the arts and crafts department, which was fine, and there's certainly, creativity is an essential part of the discipline, that's never going away. But we have been tasked with proving our value. What's the ROI of things, is a common question. Where's the data live? The chief data officer would be asking, like, who's responsible for this? And if we don't have good answers to those things, we kind of get shown the door. >> Well it sort of gets back to that old adage in advertising, I know half my marketing budget is wasted, I just don't know which half. >> Exactly. >> So now we're really able to know which half is working. >> Yeah, so I mean, one of the more interesting things that I've been working on recently is using what's called Markov chains, which is a type of very primitive machine learning, to do attribution analysis, to say what actually caused someone to become a new viewer of theCUBE, for example. And you would take all this data that you have from your analytics. Most of it that we have, we don't really do anything with. You might pull up your Google Analytics console, and go, "Okay, I got more visitors today than yesterday." but you don't really get a lot of insights from the stock software. But using a lot of tools, many of which are open source and free of financial cost, if you have technical skills you can get much deeper insights into your marketing. >> So I wonder, just if we can for our audience... When we talk about machine learning, and deep learning, and A.I., we're talking about math, right, largely? >> Well so let's actually go through this, because this is important. A.I. is a bucket category. It means teaching a machine to behave as though it had human intelligence. So if your viewers can see me, and disambiguate me from the background, they're using vision, right? If you're hearing sounds coming out of my mouth and interpreting them into words, that's natural language processing. Humans do this naturally. It is now trying to teach machines to do these things, and we've been trying to do this for centuries, in a lot of ways, right? You have the old Mechanical Turks and stuff like that. Machine learning is based on algorithms, and it is mostly math. And there's two broad categories, supervised and unsupervised. Supervised is you put a bunch of blocks on the table, kids blocks, and you hold the red one, and you show the machine over and over again this is red, this is red, and eventually you train it, that's red. Unsupervised is- >> Not a hot dog. (Laughter) >> This is an apple, not a banana. Sorry CNN. >> Silicon Valley fans. >> Unsupervised is there's a whole bunch of blocks on the table, "Machine, make as many different sequences as possible," some are big, some are small, some are red, some are blue, and so on, and so forth. You can sort, and then you figure out what's in there, and that's a lot of what we do. So if you were to take, for example, all of the comments on every episode of theCUBE, that's a lot, right? No humans going to be able to get through that, but you can take a machine and digest through, just say, what's in the bag? And then there's another category, beyond machine learning, called deep learning, and that's where you hear a lot of talk today. Deep learning, if you think of machine learning as a pancake, now deep learnings like a stack of pancakes, where the data gets passed from one layer to the next, until what you get at the bottom is a much better, more tuned out answer than any human can deliver, because it's like having a hundred humans all at once coming up with the answer. >> So when you hear about, like, rich neural networks, and deep neural networks, that's what we're talking about. >> Exactly, generative adversarial networks. All those things are ... Any kind of a lot of the neural network stuff is deep learning. It's tying all these piece together, so that in concert, they're greater than the sum of any one. >> And the math, I presume, is not new math, right? >> No. >> SVM and, it's stuff that's been around forever, it's just the application of that math. And why now? Cause there's so much data? Cause there's so much processing power? What are the factors that enable this? >> The main factor's cloud. There's a great shirt that says: "There's no cloud, it's just somebody else's computer." Well it's absolutely true, it's all somebody else's computer but because of the scale of this, all these tech companies have massive server farms that are kind of just waiting for something to do. And so they offer this as a service, so now you have computational power that is significantly greater than we've ever had in human history. You have the internet, which is a major contributor, the ability to connect machines and people. And you have all these devices. I mean, this little laptop right here, would have been a supercomputer twenty years ago, right? And the fact that you can go to a service like GitHub or Stack Exchange, and copy and paste some code that someone else has written that's open source, you can run machine learning stuff right on this machine, and get some incredible answers. So that's why now, because you've got this confluence of networks, and cloud, and technology, and processing power that we've never had before. >> Well with this emphasis on math and science in marketing, how does this change the composition of the marketing department at companies around the world? >> So, that's a really interesting question because it means very different skill sets for people. And a lot of people like to say, well there's the left brain and then there's a right brain. The right brains the creative, the left brains the quant, and you can't really do that anymore. You actually have to be both brained. You have to be just as creative as you've always been, but now you have to at least have an understanding of this technology and what to do with it. You may not necessarily have to write code, but you'd better know how to think like a coder, and say, how can I approach this problem systematically? This is kind of a popular culture joke: Is there an app for that, right? Well, think about that with every business problem you face. Is there an app for that? Is there an algorithm for that? Can I automate this? And once you go down that path of thinking, you're on the path towards being a true marketing technologist. >> Can you talk about earned, paid, and owned media? How those lines are blurring, or not, and the relationship between sort of those different forms of media, and results in PR or advertising. >> Yeah, there is no difference, media is media, because you can take a piece of content that this media, this interview that we're doing here on theCUBE is technically earned media. If I go and embed this on my website, is that owned media? Well it's still the same thing, and if I run some ads to it, is it technically now paid media? It's the thing, it's content that has value, and then what we do with it, how we distribute it, is up to us, and who our audience is. One of the things that a lot of veteran marketing and PR practitioners have to overcome is this idea that the PR folks sit over there, and they just smile and dial and get hits, go get another hit. And then the ad folks are over here... No, it's all the same thing. And if we don't, as an industry realize that those silos are artificially imposed, basically to keep people in certain jobs, we will eventually end up turning over all of it to the machines, because the machines will be able to cross those organizational barriers much faster. When you have the data, and whatever the data says that's what you do. So if the data says this channels going to be more effective, yes it's a CUBE interview, but actually it's better off as a paid YouTube video. So the machine will just go do that for us. >> I want to go back to something you were talking about at the very beginning of the conversation, which is really understanding, companies understanding, how their marketing campaigns and approaches are effectively working or not working. So without naming names of clients, can you talk about some specific examples of what you've seen, and how it's really changed the way companies are reaching customers? >> The number one thing that does not work, is for any business executive to have a pre-conceived idea of the way things should be, right? "Well we're the industry leader in this, we should have all the market share." Well no, the world doesn't work like that anymore. This lovely device that we all carry around in our pockets is literally a slot-machine for your attention. >> I like it, you've got to copyright that. A slot machine for your attention. >> And there's a million and a half different options, cause that's how many apps there are in the app store. There's a million and half different options that are more exciting than your white paper. (Laughter) Right, so for companies that are successful, they realize this, they realize they can't boil the ocean, that you are competing every single day with the Pope, the president, with Netflix, you know, all these things. So it's understanding: When is my audience interested in something? Then, what are they interested in? And then, how do I reach those people? There was a story on the news relatively recently, Facebook is saying, "Oh brand pages, we're not going to show "your stuff in the regular news feed anymore, "there will be a special feed over here "that no one will ever look at, unless you pay up." So understanding that if we don't understand our audiences, and recruit these influencers, these people who have the ability to reach these crowds, our ability to do so through the "free" social media continues to dwindle, and that's a major change. >> So the smart companies get this, where are we though, in terms of the journey? >> We're in still very early days. I was at major Fortune 50, not too long ago, who just installed Google Analytics on their website, and this is a company that if I named the name you would know it immediately. They make billions of dollars- >> It would embarrass them. >> They make billions of dollars, and it's like, "Yeah, we're just figuring out this whole internet thing." And I'm like, "Cool, we'd be happy to help you, but why, what took so long?" And it's a lot of organizational inertia. Like, "Well, this is the way we've always done it, and it's gotten us this far." But what they don't realize is the incredible amount of danger they're in, because their more agile competitors are going to eat them for lunch. >> Talking about organizational inertia, and this is a very big problem, we're here at a CDO summit to share best practices, and what to learn from each other, what's your advice for a viewer there who's part of an organization that isn't working fast enough on this topic? >> Update your LinkedIn profile. (Laughter) >> Move on, it's a lost cause. >> One of the things that you have to do an honest assessment of, is whether the organization you're in is capable of pivoting quickly enough to outrun its competition. And in some cases, you may be that laboratory inside, but if you don't have that executive buy in, you're going to be stymied, and your nearest competitor that does have that willingness to pivot, and bet big on a relatively proven change, like hey data is important, yeah, you make want to look for greener pastures. >> Great, well Chris thanks so much for joining us. >> Thank you for having me. >> I'm Rebecca Knight, for Dave Vellante, we will have more of theCUBE's coverage of the IBM Chief Data Strategy Officer Summit, after this.

>> Announcer: Live from Los Angeles. It's theCUBE covering Open Source Summit North America 2017. Brought to you by, the Linux Foundation and Red Hat. >> Hello everyone, welcome back. Our live coverage, theCUBE's live coverage, of the Open Source Summit in North America, it's a part of the Linux Foundation. I'm John Furrier your host, with Stu Miniman our co-host. Our next guest is Tanmay Bakshi, who is an IBM honorary cloud advisor, algorithmist, former CUBE alumni. Great to see you. >> Thank you very much! Glad to be here! >> You get taller every year. It was what, three years ago, two years ago? >> I believe yeah, two years ago, Interconnect 2016. >> IBM show... doing a lot of great stuff. You're an IBM VIP, you're doing a lot of work with them. IBM Champion. >> Thank you >> Congratulations. >> Thank you. >> What's new? You're pushing any code today? >> Definitely! Now today, getting ready for my BoF that I've got tonight, it's been absolutely great. I've been working on a lot of new projects that I'm going to be talking about today and tomorrow at my keynote. Like I've been working on AskTanmay, or course you know, Interconnect 2016, very first time I presented AskTanmay. Since then, a lot has changed, I've incorporated real, deep learning algorithms, custom, with tensorflow. Into AskTanmay, AskTanmay now thinks about what it's actually looking at, using Watson as well, it's really interesting. And of course, new projects that I'm working on, including DeepSPADE, which actually, basically helps online communities, to detect, and of course report and flag spam, from different websites. For example, Stack Overflow, which I'm working on right now. >> So you're doing some deep learning stuff >> Tanmay: Yes >> with IBM Watson, the team, everything else. >> Tanmay: Exactly, yes. >> What's the coolest thing you've worked on, since we last talked? (laughing) >> Well it would have to be a tie between AskTanmay, DeepSPADE, and advancement to the Cognitive Story. As you know, from last time, I've been working on lots of interesting projects, like with AskTanmay, some great new updates that you'll hear about today. DeepSPADE itself though, I'd like to get a little bit more into that. There's actually, I mean of course, everyone listening right now has used Stack Overflow or Stack Exchange at one point in their lives. And so, they've probably noticed that, a little bit, here and there, you'd see a spam message on Stack Overflow, on a comment or post. And of course there are methods to try and prevent spam on Stack Overflow, but they aren't very effective. And that's why a group of programmers, known as Charcoal SE, actually went ahead and started creating, basically this sweep to try and prevent spam on Stack Exchange. And they call it, SmokeDetector. And it helps them to find and remove spam on Stack Exchange. >> This is so good until it goes out, and the battery needs to be replaced, and you got to get on a chair. But this whole SmokeDetector, this is a real way they help create a good, healthy community. >> Yes, exactly. So, they try and basically find spam, report to moderators, and if enough alarms are set off, they try and report it, or flag it automatically, via other people's accounts. And so basically, what I'm trying to do is, I mean, a few weeks ago, when I found out about what they're doing, I found out that they use regular expressions to try and find spam. And so they have, you know, years of people gathering experience, they're experts in this field. And they keep, you know, adding more regular expressions to try and find spam. And since I, you know, am really really passionate about deep learning, I thought why not try and help them out, trying to augment this sort of SmokeDetector, with deep learning. And so, they graciously donated their data set to me, which has a good amount of training, training rows for me to actually train a deep learning system to classify a post between spam or non-spam. And you'll be hearing a lot more about the model architecture, the CNN plus GRU model, that I've got running in Keras, tonight during my BoF. >> Now, machine learning, could be a real benefit to spam detection, cause the patterns. >> Tanmay: Exactly. >> Spammers tend to have their own patterns, >> Tanmay: Exactly. >> as do bots. >> Tanmay: Yes, exactly, exactly. And eventually, you realize that hey, maybe we're not using the same words in every post, but there's a specific pattern of words, or specific type of word, that always appears in a spam message. And machine learning would help us combat against that. And of course, in this case, maybe we don't actually have a word, or a specific website, or a specific phone number, that would trigger a regular expression alarm. But in the context that this website appears, machine learning can tell us that, "hey, yeah, this is probably a spam post." There are lots of really interesting places where machine learning can tie in with this, and help out with the accuracy. In fact, I've been able to reach around 98% accuracy, and around 15 thousand testing rows. So, I'm very glad with the results so far, and of course, I'm continuing to do all this brand retuning and everything... >> Alright, so how old are you this year? I can't keep the numbers straight. Are you 13, 14? >> Well originally, Interconnect 2016, I was 12, but now I'm 13 years old, and I'm going to be 14 in October, October 16th. >> Okay, so you're knocking on 14? >> Tanmay: Uh, not just yet there, I'll be 14... >> So, Tanmay, you're 14, you're time's done, at this point. But, one of your missions, to be serious, is helping to inspire the next generation. Especially here, at the Open Source Summit, give us a preview of what we're going to see in your keynote. >> Sure, definitely. And now, as you mentioned, in fact, I actually have a goal. Which is really to reach out to and help 100 thousand aspiring coders along their journey, of learning to code, and of course then applying that code in lots of different fields. In fact I'm actually, already around 4,500 people there. Which, I'm very very excited about. But today, during my BoF, as I mentioned, I'm going to be talking a lot about the in-depth of the DeepSpade and AskTanmay projects I've been working on. But tomorrow, during my keynote, you'll be hearing a lot about generally all the projects that I've been working on, and how they're impacting lots of different fields. Like, healthcare, utility, security via artificial intelligence and machine learning. >> So, when you first talked to us about AskTanmay, it's been what almost 18 months, I think there. What's changed, what's accelerating? I hear you throw out things like Tensorflow, not something we were talking about two years ago. >> Tanmay: Yeah. >> What have been some of the key learnings you've had, as you've really dug into this? >> Sure, in fact, this actually something that I'm going to be covering tonight. And that is, that AskTanmay, you could say, that it's DNA, well, from AskMSR, that was made in 2002. And I took that, revived it, and basically made it into AskTanmay. In its DNA, there were specific elements, like for example, it really relies on data redundancy. If there's no data redundancy, then AskTanmay doesn't do well. If you were to ask it where it was, where's the Open Source Summit North America going to be held, it wouldn't answer correctly, because it's not redundant enough on the internet. It's mentioned once or twice, but not more than that. And so, I learned that it's currently very, I guess you could say naive how it actually understands the data that it's collecting. However, over the past, I'd say around six or seven months, I've been able to implement a BiDAF or Bi-Directional Attention Flow, that was created by Allen AI. It's completely open-source, and it uses something that's called a SQuAD data set, or Stanford Question and Answer Data Set. In order to actually take paragraphs and questions, and try to return answers as snippets from the paragraphs. And so again, integrating AskTanmay, this allows me to really reduce the data redundancy requirement, able to merge very similar answers to have, you know better answers on the top of the list, and of course I'm able to have it more smart, it's not as naive. It actually understands the content that it's gathering from search engines. For example, Google and Bing, which I've also added search support for. So again, a lot has changed, using deep learning but still, sort of the key-points of AskTanmay requires very little computational power, very very cross-platform, runs on any operating system, including iOS, Android, etc. And of course, from there, open-source completely. >> So how has your life changed, since all the, you've been really in the spotlight, and well-deserved I think. It's been great to have you On theCUBE multiple times, thanks for coming on. >> Thank you No, definitely of course. >> Dave Vallante was just calling. He wants to ask you a few questions himself. Dave, if you're watching, we'll get you on, just call right now. What's going on, what are you going to do when... Are you like happy right now? Are you cool with everything? Or is there a point where you say, "Hey I want to play a little bit with different tools", you want more freedom? What's going on? >> Well, you see, right now I'm very very excited, I'm very happy with what I'm doing. Because of course I mean, my life generally has changed quite a bit since last Interconnect, you could say. From Interconnect 2016 to 17, to now. Of course, since then, I've been able to go into lots of different fields. Not only am I working with general deep learning at IBM Watson, now I'm working with lots of different tools. And I'm working especially, in terms of like, for example Linux. What I've been doing with open-source and everything. I've been able to create, for example, AskTanmay now integrated Keras and tensorflow. DeepSpade is actually built entirely off of tensorflow and Keras. And now I've also been able to venture into lots of different APIs as well. Not just with IBM Watson. Also things like, we've got the Dandelion API. Which AskTanmay also relies off of Dandelion, providing text similarity services for semantic and syntactic text similarity. Which, again, we'll be talking about tonight as well. So, yeah, lot's has changed, and of course, with all this sort of, new stuff that I'm able to show, or new media for which I'm able to share my knowledge, for example, all these, you know CUBE, interviews I've been doing, and of course all these keynotes, I'm able to really spread my message about AI, why I believe it's not only our future, but also our present. Like, for example, I also mentioned this last time. If you were to just open up your phone right now, you already see that you're, half of your phone is powered by AI. It's detecting that hey you're at your home right now, you just drove back from work, and it's this time on this day, so you probably want to open up this application. It predicts that, and provides you with that. Apart from that, things like Siri, Google Now, these are all powered by AI, they're already an integral part of our lives. And of course, what they're going to be doing in our lives to come is just absolutely great. With like, healthcare, providing artificial communication ability for people who can't communicate naturally. I think it's going to be really really interesting. >> Tanmay, it's always great have you on theCUBE. Congratulations. >> Tanmay: Thank you very much. >> AskTanmay, good projects. Let's stay in touch, as we start to produce more collaboration, we'd love to keep promoting your work. Great job. And you're an inspiration to many. >> Tanmay: Thank you very much, glad to be here. >> Thanks for coming on theCUBE. Live coverage from the Open Source Summit's theCUBE, in Los Angeles. I'm John Furrer, Stu Miniman. We'll be back with more live coverage after short this break. (upbeat music)

>> Narrator: Las Vegas. Extracting the signal from the noise. It's theCUBE, covering InterConnect 2016. Brought to you by IBM. Now your hosts, John Furrier and Dave Vellante. >> Hey, welcome back, everyone. We are here live in Las Vegas for our exclusive coverage of IBM InterConnect 2016. This is theCUBE, SiliconAngle's flagship program. We go out to the events and extract the signal from the noise, I'm John Furrier, my co-host Dave Vellante, our next guest Kevin Eagan, general manager of IBM Digital. We're all digital right here all the time, real time, in a cognitive mode, Kevin, welcome to theCUBE. >> Hey, I really appreciate that, John, Dave, I love theCUBE. >> Oh, thanks for coming on. >> It's an honor to be here and look forward to going and watching myself on digital TV. >> Well, hopefully we get some CUBE gems out of this 'cause they'll be on Twitter immediately. Digital's obviously the big topic, digital transformation. We were talking yesterday about the slogan really should be digitize everything 'cause we are moving to a complete digitized world where data is the asset. And that kind of sounds easy to think about, but what does it mean to put it in practice because digital assets are shifting to be more interactive, less static, more dynamic, what's your thoughts on that? >> Well, first off, you're exactly right, the explosion of data has created the opportunity to create assets. Assets though are only a piece of it, until you unlock inside out of those assets towards the outcome of establishing trust with the client, solutions, helping to make decisions, you really haven't created a platform. So as we've seen the explosion of big data, one of the challenges that our clients have, and the customers, in fact, even inside of IBM we have this, how do you make sense of that so that you can construct thoughtful friction-free customer journeys. That as people are inspired by what they see, what they hear about at events, they can have a personalized journey that removes the roadblocks, brings in social content, brings in the best of industry expertise and unlocks the power and potential of doing digital in the transformative way no matter what your industry is. And so at IBM, we formed a digital unit across the company over the last year to help tie together this explosion of content that's happened, and I got to tell you, it's been a big year. A year ago at InterConnect, had you left the event and done a Google search to try to find what was announced a year ago, you would've seen the beginning of a narrative, but certainly not a journey that was leading towards a destination of transformation and great outcomes. This InterConnect, this is our first major event where work with companies like yours, working with our partners, you'll have a great experience whether you're here or you're at home or you're at work next week, bringing together the content, the insights, the social and a digital experience that frankly, behind it is a marketplace of content, ideas and solutions built on the IBM cloud that's going to accelerate our client's ability to make sense of all of this and get to the journey they want. >> Yeah, but you've seen the journey of digital from the Web 1.0 days or Web 0.5, however you want to look at it. You know, you're involved inside one of the first digital cities, community kind of things, evolving now. It's been a real interesting journey, but I want to get your thoughts on a concept called the user's preferred experience. That's the future experience that they want or hoping for, not what they get today. You mentioned Google, great example, you go to Google News, it's the same story, oh, VMware this and that, announcement, very news driven. There's no real discovery aspect of it. What is the mind of the consumer right now? From an experience standpoint, what are they looking for, and obviously, real time's a big part of it, what are your thoughts, you guys talk about this, you must have an opinion on this, I'm sure. >> Well, you know, what we're finding, we say users, we say clients, let's first talk about how, in our industry, in IT and in the big B2B spaces, the big change that's happened is we no longer think of the client as an organization. We've now made the full shift that our organizations that we serve are made up of individuals who are complex in their information needs. Different stages of mastery. They all have time compression, and they're so used to that digital experience that they're familiar with now from the consumer side of the world, as they've seen transportation being disrupted with Uber, as they've seen travel being disrupted by digital agencies. Every part of the consumer experience now informs those professionals at work to expect a seamless, user directed, instant and always available experience. So applying that consumerization of IT and the explosion of marketplaces that take the incumbents that have taken a vendor-centric approach and just absolutely disrupt them and almost make them obsolete, we see the opportunity to apply those best in class consumer experiences to give our customers, professionals in every industry, control of their journey, to inform that journey by their own profile, their preferences, their industry context and combine that with the world of social expertise and industry expertise that IBM's uniquely able to bring to the market, and use great platforms like IBM's own cloud, cognitive solutions and cognitive APIs from Watson, and you'll start to see this as an IBM client and be able to apply it in your own companies that you can simplify your own clients' journeys, your employees' journeys, and activate a new wave of productivity that I don't think we've seen for decades. We're really at the era of tremendous progress brought about by cloud platforms, cognitive solutions and marketplaces that bring industry expertise all together. >> Well, that narrative brings up so many thoughts, but I wanted to pick up, so IBM calls them clients, you use the terms users which sometimes is viewed as a pejorative, right. I like the terms digital doers, right, so we're seeing this new era of individuals who are trying to get digital content out to their customers, trying to build digital platforms. Who are these digital doers, obviously you got the digital natives, those have been untethered for life. But we got a big spectrum, how is IBM approaching the personas of digital doers? >> And so you're exactly right. We're in an era where professionals that have come out of technology and software engineering have become the modern builders of business process, the modern builders of customer experience. And so the word that I would use is we have to serve builders in industry. Builders as individuals and builders as organizations. To help them have the data, the tools, the platforms, the expertise so that they can build businesses, transform their business models, and frankly grow awareness of what the value is that they bring to the table. So this class of builders has a few things in common. First off, it's grown out of old school software engineering, and so increasingly in roles from marketing to IT, understanding the basics of software engineering is critical. And so at the heart of that IBM has a platform for builders. Whether you're a low level systems programmer or you're a high end frontend developer that brings the full spectrum of developer potential to life through Bluemix. Augment that with the communities that we've established through developer works, together with the ecosystem of partners who are bringing their components, their offerings, like the announcement of GitHub Enterprise, and you begin to get a critical mass of the solutions so that builders of modern business can come to IBM, experience and have a custom journey of content, learning and mastery, connected to a marketplace where the tools, the APIs, the datasets are there for them to fast forward from concept to outcome in a timeframe that, in the past, was measured by months or years, it's now hours, days and weeks for really fundamental outcomes. >> Talk about the community aspect, 'cause that's a really awesome vision, and the things that we talk about, we have free content, as well as paid subscription with Wikibon, but most to the point, we want to share as much content as possible. Spray it around the web, shoot it everywhere, but if you look at the developer, software developer, they have GitHub, they can store code, they have communities like Stack Exchange and these other sites for advocacy. Is that the model for content development? I mean, 'cause that open source ethos, if you make it so that everyone's connected, they're using open source tooling, this community contribution piece, how does that fit in, is this open marketplace, what's your vision on this 'cause the open piece might be a critical piece of that, how open, how IBM-centric is it, and vice versa? >> Well, I don't think that there's any sense in trying to put the genie back in the bottle of the open transformation that we're seeing. While some vendors would love to have virtual or digital walls that separate out the ability for content assets and learning to be unique to them, it's very clear that the technology has created an over the top transformation. That any attempt to lock up content that's a value to users is met with an over the top marketplace that aggregates, indexes, synthesizes. If a content creator in the old industry of television tried to lock up their content inside of their network website, we see the emergence of marketplaces that can over the top. Netflix, Amazon Video. And so applying that concept of marketplace aggregation of the content that has value, rich data personalization around what people are looking for, you begin today to be able to construct a marketplace that aggregates content from multiple sources. Now, even though there's content being sprayed, as you said, everywhere, it's frankly overwhelming when we listen to what our customers, what these builders tell us. That the ability to find information about blockchain, to find information that might be relevant in their industry, is so overwhelming that we go to the ultimate open source tool, the Internet, and we just go to search and we type in Google. But frankly, that experience has its limitations. And we think there is a better way than simply going to Google to find industry expertise and insight. And so our strategy for IBM's marketplace-centric strategy, for digital and for cognitive, is to aggregate together the catalogs of content, user profiles, industry expertise, and connect it to a marketplace of products, solutions, APIs and data sets, so that as I'm consuming content in that discovery and engagement stage, I'm always one click away from a trusted marketplace that can do key provisioning for APIs, give me access to tools, even connect me to human powered services in terms of being able to get me, get a physical buyer and a physical expert together. That kind of full wrapping of value around what businesses really need to drive digital and cognitive transformation, that's at the heart of what we're doing with IBM Digital. >> So I love the business impact discussion. We like to have that discourse. You talked about productivity. John's in Silicon Valley, we're bi-coastal, I'm on the East Coast. Silicon Valley's a little nervous right now, but we feel like we're on the cusp of a productivity boom, a renaissance in productivity, really two things going on there, one is productivity of individuals and the other is of assets, I mean, physical assets, whether it's parking meters or automobiles, they're becoming digitized. So talk a little bit about the business impacts of this digital transformation. >> First off, if you're not feeling the disruption of digital transformation in your business, then you should be worried, because this is where a case where the paranoid and the self-aware will survive. Every industry, every sector, from the biggest companies to the smallest companies, is having to fundamentally change the definition of who their customers are, how they reach them and how they create new business models and offerings to reach them. Now, for IT business, the way of building solutions is fundamentally changing, because small teams now with small starting budgets can rapidly prototype, compose, get proof of concepts. Use digital marketing tools to refine and pivot the value proposition through A/B testing. And so the world of engineering, the world of marketing are being collided together in an air of productivity that's powered by cloud-based digital platforms, connected to marketplaces and rich data that help create custom experiences for that professional. Now, productivity means that I no longer feel that, if I'm inside of a large company, that I'm beholden to a limited sandbox of what I can use, what I can experiment with, how I can explore. The top down model, which was command and control, is now being served by a model built on hybrid cloud with security that meets the needs of the strictest corporations, but unlocks personal productivity for this next generation of builders. So having an IBM account inside of an organization means that your employees have access to Bluemix, can connect to communities on developer works, have access to the content including, without sending all of your employees necessarily to this event next week, they can log on to IBM Go, experience the keynotes, see the workshops, connect that back to social networks on IBM, and enter into a marketplace-centric journey that leads to experimentation, higher productivity and faster pivoting as companies are trying to build next generation products and new business models. >> So obviously you're right on the edge there, you see the path, the vision and the future. Can I get your thoughts on the old way versus the new way? 'Cause this is an interesting topic, opt-in. If you have personalization, you have data and you have over the top aggregation now as a platform called the Internet, and you certainly have gated content, the notion of gated stuff. Google's organic search results, pay stuff, click, go to a forum, get access to content. That's an opt-in for the user. What is the new gated formula, what does opt-in mean now, because if you have access to all the data, the endgame is to get that user to what you just said, which is I just want to roll my own, get content, learn, connect to the others. But with personalization, there is no opt-in, you either know or you don't, so the goal should be no opt-in, I mean, I'm just trying to get your thoughts on this, 'cause it's one of those gray areas where a lot of people are working on stuff, and if you get it wrong, you lost. >> You're so right about that, because just a few years ago, it was considered digital acceptable practice that if you activated great content marketing and you were building rich assets, case studies, that you would tease those out on social media, you'd tease those in email. But before delivering any real value to the client, you used that bait to put right in their face that gate. Basically a DNA test of phone, address, date of birth. Frankly, in a world of immediate access-- >> And if you're from Canada. (laughter) >> I got to tell you, it created this, it created this expectation that the only purpose of digital marketing was to capture information to then hand off into the old school way of engagement. Which is offline human based followup, not on the buyer's terms, not on the client's terms, but when an agency decided or when a sales team decided that you were qualified. Now, that's a big, IBM fell into that camp a few years ago. But today I'm looking forward from 2016 on. IBM's philosophy around building value for clients is that content exists to help inform our client's journey, and the last thing we want to do is to gate content right at the moment when a customer is at that point of aha. Where the case study, where the CEO keynote, where the sample code is what they need to be inspired to take the commitment step. And so the concept of opt-in versus opt-out is being replaced with progressive profiling as a method that, at the point of value delivery, you have an identity system, you have anonymous and known data systems that come together. So that what required log in and authorization two years ago, today we can do a better job than that with anonymous validation of behaviors and patters. When you do get the customer identified, there's a new range of tools that require us to deliver even more value to the customer. So building value into your IBM Digital relationship means that by offering your identity, in addition to the highly optimized anonymous content we can serve you, we can now help you build a history across your devices, across time. In fact, just this last month on ibm.com, we've introduced My IBM. A service that, for the client who wants to log in and create an IBM account, ties together their experiences across over 150 IBM products so that you can manage entitlements, perform upgrades, look at time remaining in trials. And it beings to unlock the value of the silos of IBM's solutions, the silos of our partners' ecosystems and their products, and brings it together into a unified experience. >> This is so refreshing because you're right, the whole opt-in, fill out this form, basically says, I don't really, I don't know anything about you so just tell me 'cause I can't figure it out without that. And in reality, what's happening in consumers have all this information, there used to be an asymmetry of information, we knew, brands knew so much about the buyer, and now the buyer has the pricing power, so what are brands trying to do, they're trying to regain some of that knowledge, and so asking the customer, okay, fill out a form is just so, I don't know, 90s, 80s. >> That's an offline world too where, when you fill out a form, there's this expectation that you've just ceded control to someone else to decide, are you qualified? Now, while it's true that we do use advanced marketing automation systems, scoring platforms, lead management systems that flow into CRM, increasingly the customer-centric digital journey, instead of a form, it's a human being that's one click away to chat, to call, to even do video. So that the customer stays in control of the conversation. And as the value goes up-- >> You have a relationship with the customer, it's not like trap the user, to Dave's point, tell me so I can do something offline and maybe get a lead. It's like, okay, it's a historical relationship that has a series of value transfers. That's a social equation. >> It's social, it's on the buyer's terms and it's on demand. And so in the past, where registration forms played a key part of the customer qualification process for offline physical sales followup, the modern sales forces, the modern digital journey brings value without gating the content at the moment when a customer is needing assistance, increasingly chat, click to call, scheduled events, to keep the customer in control, are a much more powerful way to build trust and relationship and to deliver value. >> When you guys did IBM Go last year for the first time, one of the things that we were really hardcore on was ungate everything, let it all fly around, but use that all access gate as a context switch for value, if people want to go there, the value should be stacked up. That's IBM's opportunity, that's not the crowd. So gates are okay if the user goes there. In other words, if it's part of their journey, I mean, that's kind of the philosophy, right. I mean, you want to-- >> What's happening in just this year that this philosophy has accelerated is, by taking these principles of customer-centered experiences, content that comes from multiple sources and buyer journeys that lead to a unified marketplace, we've seen metrics that are the leading indicators of growth, of value, both for IBM and for our partners and clients. We saw the largest increase in unique visitor traffic from both a percentage and absolute number term we've ever seen beginning in Q4 of last year. >> IBM has got good brand value, people want to have a relationship with IBM. >> They do, but IBM also has the challenge of its business model being limited to the largest, the most substantial clients. As IBM brings a digital platform to go to market and works together with partners, IBM becomes accessible to a whole new range of business. Rather than being the largest enterprise, IBM becomes the platform company with cloud platform and cognitive solutions for businesses of every size, and while it may not always be the IBM Digital seller at the end of every conversation, it creates opportunities for our channel partners, for our ecosystem, and I think this is the productivity engine that we're all looking for-- >> So how are you going to do it then? >> What does that do for the 10? I mean, that just explodes the total market, right? >> You no longer need to have hundreds of thousands of face to face sales people in order to serve the largest clients, because digital takes you into every organization, and you're no longer limited to only large clients if you're a company like IBM because digital allows you to achieve reach and scale to clients of all sizes. >> Digital transformation, Kevin, thanks so much for spending the time to coming on theCUBE, really appreciate it. Give me the final word, what's the vibe of the show this year, obviously digital transformation. I mean, is it a new IBM, new spring in their step? What's the vibe of the show? >> I think the biggest exciting thing this year, and it started with customers actually telling the story of IBM, as we have a story now that might've been parts of the narrative a year ago, now it's crystal clear that IBM solutions that span from hybrid cloud to cognitive solutions are tangible, they're ready for the mainstream, and this is the first time that I've, I'm relatively new to IBM, as you know, only a year, that IBM now has a relevance and immediacy that works for clients of all sizes. So that energy is, I'm not just coming here to learn, I'm coming here to go back and do. >> And the cloud certainly going to be a big accelerator of that. Awesome, Kevin Eagan, digital manager at IBM Digital. Digital transformation from data to user experience all cutting in between great opportunities, thanks for sharing your thoughts and commentary on theCUBE. Be right back with more after this short break. And remember, March 15th is CUBE madness, that's when all of our guests stack up in the brackets and get voted on, we'll see who comes to the end, of course it turns into a hackathon because that's what people do, they stuff the ballots. We'll see who's got the best hacks, CUBE madness, go to siliconangle.tv, we'll be right back after this short break. (calm music)