 Live from Boston, it's theCUBE. Covering IBM Chief Data Officer Summit. Brought to you by IBM. Welcome back everyone to theCUBE's live coverage of the IBM Chief Data Summit here in Boston, Massachusetts. I'm your host, Rebecca Knight, along with my co-host Paul Gillan. We're joined by Ash Dupur. He is the Chief Analytics Officer at Publishers Clearinghouse. Thank you so much for coming on theCUBE. Thank you, Rebecca, for calling me here. So, Publishers Clearinghouse is a billion dollar company. We think of it as the sweepstakes company. We think of the giant checks and being the prize patrol, surprising contestants. But it's a whole lot more than that. Tell our viewers a little bit. Just explain all the vast amounts of businesses that you're in. Sure. So, in a nutshell, we are a media and entertainment company with a large base of customers, about 100 million customers who are motivated with the chance to win. That's the sweepstakes angle to it. And we have, you can categorize the business into two buckets. One is our media and entertainment side, which is the publishing side. And then the other is our retail side, which is where we send a sale merchandise to our customers. Think of us as a catalog and an e-commerce company. On the media and entertainment side, we have a very good engagement with our customers. We get about two billion page views on a monthly basis on our website. We, about 15 million unique customers on a monthly basis are coming to the site. And they spend a considerable amount of time with us on an average anywhere between 12 to 15 minutes, depending on the type of the customer. Some of our very heavily engaged customers can spend as much as about two hours a day with us. Trying to win that either the big prize or there are small prizes. Like, if you go on our site, there is a winner every day. Like, there could be a thousand dollar winner every day playing a certain type of a game. So that's the media and the entertainment side of our business. That's completely ad supported. And then we are, the retail side of the business is, we are in direct mail. So the traditional, we would send someone a direct mail package and an e-commerce company as well. Just as a small nugget of information, we are, we send almost about 400 million pieces of physical mail, which is including our packages that are sent and so on and so forth and built. So still a large direct mail company. Still profitable and still growing. I'm sure the US Postal Service is grateful for your support. They need all the help they can get. The, you collect essentially the prize money is your cost of data acquisition and you have a huge database, you told us earlier before we started filming of about 100 million people that you have data on just in the US alone. Now, what are you doing at the upper limits of what you're able to do with this data? How are you using this strategically other than just personalized email? Sure, so I think using data is a core asset for us. For us, we are utilizing in giving our customers better experiences by utilizing the data we have on them, marrying it with other data sources as well, so that we can personalize the experience, so that we can make your experience when you come on the site better. Or if you're sending something to you in mail, we give you products that are relevant to you. So to bring it down to a little more tactical level in case of when you are on our site and on our e-commerce site, there's a product recommendation engine, right, which goes in and recommends products to you on what products to buy. Those product recommendation engines drive a significant amount of sales, almost about 40% of our sales are driven by the product recommendation engines. That is all understanding of the customer, what you're buying, what you're likely to buy, and the algorithms behind it are built through that. Can you give another example, though, of how, if I were, I mean, you said all these customers are united by a common desire to win and to play a game and to win. But what are some other ways beyond product recommendation engines, which are now sort of old hat, what other ways are you enhancing the customer experience and personalizing it? Sure, sure, so I'll give you a recent example where we are utilizing some of the data to give a more relevant experience to the customer. So when a customer comes on our website, right, when you're coming to register with us. So as you register, as you fill in the form of you, give your name address and your email address, and you hit submit, at that very second, there are some algorithms that are running behind the scenes to understand how are you likely to engage with us? How are you going to, let's say, because we have a diverse business, are you likely to buy something from us? Or are you not likely to buy something from us? And if you're not likely to buy something from us, which means I can get you to, and not waste your time in showing you merchandise, but I can give you an experience of free to play games, and you can, within free to play games, what type of games, like understanding the persona of the person, we could say, hey, you probably are a lot of player, or you are a word game puzzle player, and we could give you and direct you to those experiences that are more relevant to you. In case if you're going to buy something from us, are you likely to buy, highly likely to buy or less likely to buy? Depending on that, should I show you just 10 or 15 products, or should I show you more than that? Are you more likely to buy a magazine? And so making it more relevant for the customer experience is where it is all about. We use a lot of this data to make that happen. So analytics is really core to your business. It's completely strategic. Where do you sit in the organization, organizationally? How is that reflected in the way your job is integrated into the organization? Sure, so it is, I'm part of the C-suite, and I think our CEO, he had this vision. I think he started, he loves data, first of all. And- Lucky for you. Thank you. And he truly believes that data and analytics can drive growth and bring innovation from different areas if we utilize it in the best possible way. So A.M. part of that team, and work very closely with each of the business owners. That's the key out here is like it is, analytics is not in one corner, but in the center of all the business areas, giving them either insights or building algorithms for them so that we can make either better decisions or we can power growth, depending on which way we are looking at it. In term, you're the Chief Analytics Officer, and we're here at the Chief Data Summit here. How different are the roles in your mind, and do they work together? I mean, you have a CTO that is responsible for sort of Chief Data Officer responsibilities. How do you two collaborate and work together? It is a very tight collaboration. And they're two separate jobs, but it is a very tight collaboration. We work hand in hand with each other. And the best part I would say is that, we are all focused and we are all driving towards how can we drive growth? That's the bottom line. That is where the buck stops for all of us in the companies. Are we building projects? Are we doing things that are going to grow the company or not? So the collaboration with the CTO is a critical piece. They own the infrastructure as well as the data. And when you own the data, which is in a way slightly, I would say, data governance, I would say, is a thankless job, believe it or not. But it is a critical job. It is, if your data is not right, it is not going to work for whatever you're trying to do. It's the garbage in, garbage out. We all know about that. And we work very closely. If there are CAPEX proposals that needs to be put in place because we are going after a certain big project, whether it's putting things together in one place for a 360 view of the customer, all of that is worked hand in hand. We work together in working towards that. What is your big data infrastructure like? Is it on the cloud? Is it your own? Are you Hadoop-based? What do you use? All the above. All. Now, so what we have is because we are such an old company, we still have our legacy DB2 infrastructure, a lot of our back-end databases, a lot of our back-end processes are all attached to that. We have a warehouse, a SQL Server warehouse. We also, for our web analytics, we use Google's BigQuery. That's where you collect a lot of data on a daily basis. And recently, I think about three years ago, we went into the cloud environment. We have a map, our cluster, which was cloud-based. And now we have brought it on-prem very recently. Back from the cloud? Back from the cloud on-prem. And there was very good reasoning why we did that. I think, frankly, it's cheaper on a longer term to bring that on-prem, and you're a lot more in control with all the issues with data privacy, and so it is... I hope you don't mind my interrupting, but we have to wrap here, and I need to get that question. You have data on 100 million consumers. What are you doing, with all of the attention being paid to privacy right now, what are you doing to ensure the... We have a very, very, I would say, intricate infrastructure, data governance, data, there's a whole slew of, I would say, people and processes around that to make sure that our data is not exposed. Now, luckily, it is not like PII to the level that it's a healthcare data, so you are not really... You have information that is crazy, but you still have the PII, the name and address of these customers. And as an example, none of the PII data is actually available to even to the analytics folks. It's all stripped, the PII is stripped off, you give us an ID to the customer, and frankly, the analytics team don't need the PII information to build any algorithms as well. So, there is a whole process around keeping the data secure. Great. Well, Ash, thank you so much for coming on theCUBE, it was a pleasure having you. Thank you, and thank you for inviting me. I'm Rebecca Knight for Paul Gillan. We will have more from the IBM CDO Summit just after this.