 Hi everybody, this is Dave Vellante of Wikibon.org. This is theCUBE. We are cutting over from the keynotes at HP Discover. We're here live in Las Vegas at the Sands Convention Center. This is day two of our wall-to-wall coverage, Silicon Angles of theCUBE. We go out to the events. We extract the signal from the noise. We scour these events. We find the best guests and bring them to you. We package up the information to you, our audience. I'm Dave Vellante. I'm here with my co-host, Jeff Kelly. And Jeff and I are going to kick off the day today. We heard Dave Donatelli earlier today. I've known Dave Donatelli since 1987, and I'll tell you, he was relaxed, he was engaged, he was crisp, and he was even funny, which is unique for Dave Donatelli. He was uptelling jokes, which is quite good. We saw Robert Young-Johns talk about integration between autonomy and collaboration between autonomy and vertical, something that we've been calling for at Silicon Angle and Wikibon for quite some time. And so it was great to see that action going on. Colin Mahoney got up, he talked about Haven, which underscores that integration, a new big data platform. Thanks for watching, everybody. My name is Dave Vellante, and I'm here with... I'm Jeff Kelly with Wikibon.org. Dave, great to see you. Great to be at this event, kicking it off bright and early today. I've actually got the keynotes going on right behind us, but we're gonna start the day, as you mentioned, talking about autonomy. We're here with Rafiq Muhammadi, who's our first guest. He's the GM inside the marketing optimization group at HP Autonomy, Rafiq. Welcome to theCUBE. Thank you. So, obviously, we're hearing a lot about autonomy this week in relation to Haven. Why don't you tell us a little bit about kind of what's the vibe like inside autonomy these days, and how do you feel about the announcement? The announcement is exactly what it should be, bringing together all the technologies within HP, with the meeting-based computing, with the ability to process human-friendly information, combine it with Vertica, and deliver solutions that matter to our clients. Absolutely. I mean, I think we, you know, obviously there was the issues with autonomy on the financial side, but we've been saying autonomy's got some really solid software, really some great proof points among their customers. And HP's really got all the assets for a comprehensive big data platform, autonomy being one of those, and it's great to see now that they're actually, you are bringing that together in a framework, a platform that is Haven. What autonomy does is something extraordinarily interesting. It transforms the Haven big data platform into solutions that can be rapidly deployed by our customers, whether it be information governance, whether it be litigation management, or whether it be helping the chief marketing officer understand the trends within their business. Our applications are designed to promote customer conversions, increase revenues, manage risk within the enterprise, and increase customer loyalty. These are amazing applications with amazing customers. Right, so you mentioned the CMO, and I know, so you were in the marketing optimization group, so you really focus on that CMO role and how big data can help them do their jobs better. Can you talk to us a little bit about the changing role of the CMO as it relates to big data, and you know, we hear a lot in the press about kind of who's gonna be the bigger IT buyer, technology buyer, the CIO or the CMO in the future, and it's shifting to the CMO. What's your view on that? So the changes are pretty dramatic. It used to be, I started my career in 1982 when you actually had to use snail mail, get a IBM Selectric outright an email or an actual physical mail and get information. Consumers today are armed with extraordinarily interesting information. They have very low tolerance, they expect personalization. In other words, they expect companies to know a lot about their preferences. What our technology is essentially allows CMOs to do is to discover what these preferences are, to segment and learn about customer behavior, and then to monetize it all within the opportunity window. So we're talking about Haven as a real-time system that understands, detects preferences, and enables CMOs to put out offers and campaigns that make a material difference to the campaign. There's a big discussion going on in the industry around the individual's signature. The fingerprint, if you will, the digital fingerprint that somebody leaves behind when they go onto social or even through click streams, et cetera. There seems to be a movement among CMOs to go beyond the sort of, I want the demographic of 20 to 28 males, white disposable income of X to, I want to provide an offer to this individual at this precise moment that's specific to him or her. Do you see that in their client base and how are HP and autonomy supporting that? This is one of the most interesting questions. This is where I spend all my time. Let's talk about Mad Men, right? The Madison Avenue TV series that's going on. At that particular point in time, it was demographic segmentation. How old are you? What is your racial background? What are the kinds of things that you have done in the past? These things are very elementary in understanding human behavior. What we can do today, for instance, is that based on the web pages you're reading, I can immediately find out that Ruffique is a mountain bike enthusiast and his interest is in carbon fiber bikes with very special gears. That type of segmentation information is extraordinarily actionable because now you know the core interest of a person far beyond their age or their demographics or the neighborhood that they live in. And with this kind of human friendly segmentation, you can then begin to direct offers and campaigns that fundamentally change conversion or yield. One of the most interesting things about our industry today is that the yield rate is only two and a half percent. With the kind of human friendly information that autonomy is capable of understanding combined with the big data platform within Mordeka, we can actually take that yield rate and improve it pretty dramatically. Every half percent change in yield translates to 20% more in revenues and that's why the CMOs really like the economy HB combination. Right, I mean, marketing folks and particularly salespeople say they can't squeeze any more blood from the stone. I mean, they've hit the ceiling in terms of their yield rates. And so now you're able to increase those. Talk about why. It's presumably a combination of the source data and the tech behind it. And maybe there's some other processes I'm sure and people issues behind it, but talk about how you're able to increase those yield rates. So let's talk about the why, which is really what is material. Suppose you spend about a half hour on a website doing all kinds of searches, looking at products and things like that. And then you call the call center person saying, I'm interested in some products that your particular company has. Now, if the call center person or agent has absolutely zero information on your preferences and your last set of activities, that conversation has a very low IQ and in fact, will actually end up irritating you because you'll feel that this company has no knowledge about my preferences. It's by bringing together all of these behaviors together, understanding these behaviors, mining the behaviors to see what the next action or offer should be is how we can influence the interaction between companies and customers where both sides win. The customer feels that there's a highly personalized interaction going on and the company actually realizes more margin because the basis of that relationship is not commodity products, but customer intimacy, which consumers prize enormously. So do I buy this solution from HP Autonomy or do I as a Haven customer develop an application on top of this or is it both? It is indeed both. So on day one, we are able to offer you all of the packaged applications so that you can deploy it very quickly, get up and running and make a material impact to your business as quickly as possible. But one of the fundamental tenets at HP is that we don't lock you into anything. Our standards are open standards. So you also have the platform where as your knowledge about the application and the Haven platform grows, you can monetize it more by you or your partners developing additional applications around our platform. So I wonder, can we dig into one or two examples that you've come across in your customer base? Some of the more interesting things you're seeing and maybe use those examples to highlight some of the challenges they're facing and some of the ways that they're really succeeding as well in terms of leveraging all this data with your technology with Haven and some of the related technology with Vertica, et cetera. So let's talk about it again in real terms. Any complex company, for instance, will have tens of thousands if not hundreds of thousands of offers. You go on to a web application or you run a mobile application or you talk to a call center, where should that conversation essentially start? There is so much information that if you assume that everybody else is the same as everybody else, then that conversation gets meaningless. The information glut essentially makes it impossible to have a dialogue. What our technologies essentially do is that it learns about consumer preferences, it learns about how similar customers or consumers behave, and then it allows you to open the dialogue in a way where that relationship can be monetized both from the standpoint of selling products as well as increasing loyalty. So what we essentially do is that we can reduce large amounts of information and different kinds of behaviors into patterns that can actually be understand by the company and then can be used to shape the dialogue and the interaction. That's a simple example of what goes on. So sort of distill all the noise into a signal that says here's the next best action to take or perhaps some probabilities of perhaps next actions the customer might take or is that kind of how the end output is delivered? Exactly, I was really amused and excited when you started the question or started this session by saying that it's the signal that we extract. So essentially what is happening is that there's an enormous amount of data that's why we call it big data. There's petabytes of information, but then how do you turn that data into actionable information where the data is actually influencing decisions and interactions and that's what haven and that's what autonomy and that's what marketing optimization is. Don't steal our tagline. Don't steal our tag extracting the signal from the noise. Yes. So the example sounds like kind of a B to C example. Are you seeing a pickup in the B to B space? Does it have a play there in terms of marketing and what are the kind of other challenges different from one to the other? B to B is just as important as B to C. For instance, we might just say do a small joke or an anecdote in a few seconds. There's a major equipment provider that discovered within their B to B network with our software that people in Mongolia and people in Nebraska were buying exactly the same equipment. This kind of insight cannot be done without machine learning looking at big data. Now once they looked at the information they thought it was very obvious because the weather patterns and the population density between Mongolia and Nebraska is very common. So within B to B networks, they really can quickly position as to what the correlations are and again reduce this massive amount of information and data into interactions that make sense. B to C, we turned on a healthcare provider digital presence on recently where there are 70 million consumers on the other side, 70 million in literally every language that you can imagine. And what our technologies allow us to do or allows the customer to do is to first deliver messages or interactions in all of those different languages with the full HIPAA and security compliance, learn from the interactions and get progressively better in shaping those interactions and making sure that their consumers and customers are getting the best information at the right time. Excellent Rafiq, we are tight on time. Appreciate you putting up with the loud keynote in the background, HP $120 billion company, four billion of that comes from software. It must be bigger, it must grow faster. Autonomy and Vertica are two keys to the family jewels as to how HP is going to get there. Rafiq, thanks very much for coming on theCUBE. It was a pleasure hearing your insights. It's great being here. Thanks for watching everybody. Keep it right there. Tom Joyce is here. We'll be right back. Tom Joyce has a new role as the head of converged infrastructure within Dave Donatelli's group. We'll be right back with Tom Joyce right after this.