Ash Dhupar, Publishers Clearing House | IBM CDO Fall Summit 2018
>> 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 Gillin. We're joined by Ash Dhupar, he is the Chief Analytics Officer at Publishers Clearing House. Thank you so much for coming on theCUBE. >> Thank you Rebecca for calling me here. >> So Publishers Clearing House is a billion-dollar company. We think of it as the sweepstakes company, we think of the giant checks and be 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 amount 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 sell 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, you know the type of the customers. Some of our very heavily-engaged customers can spend as much as about two hours a day with us. (Rebecca and John laughs) >> Trying to win that, that either the big prize or there are small prizes like, if you go on our site, there's a winner everyday, like there could be 1,000 dollar winner everyday 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 though also still a large direct mail company. Still profitable and still growing. >> I'm sure the US Postal Service is grateful for your support. (laughs) They need all the help they can get. 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 you know personalized email? >> Sure, so I think using data is a core asset 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 we are 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, then 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 prior 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 with 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. >> Right. >> But what are some other ways beyond product recommendation engines, which are now sort of old hat. >> Right. >> What other ways are you enhancing the customers experience and personalizing it? >> Sure, sure. So, I'll give you a recent example of 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, after 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 you know 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 lotto 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 of, if you're going to buy something from us, are you likely to buy, you know 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 like more than that? Are you more likely to buy a magazine? So making it more relevant for the customer experience is where it is all about. We use a lot of this data to, to make that happen. >> So analytics is really core to your business. It's the, completely strategic. Where do you sit in the organization, organizational layout, 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, thing he started. He loves data first of all. (laughs) >> Lucky for you. (laughs) >> 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, I am part of that team. And work very closely with each of the business owners. That's the key, out here is like you know, it is, analytics is not in one corner but in the center of all the, 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. >> You're the Chief Analytics Officer and we're here at the Chief Data Summit here, of 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. >> Yes. >> 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 you know, we're all focused and we're all driving towards how can we drive growth? That's the bottom line, that is where the bucks stops for all of us in the companies. Are we building projects? Are we doing things that is going to grow the company or not? So the collaboration with the CTO is A, a critical piece. They own the infrastructure, as well as the data and when you own the data, which is, in a way, is slightly, I would say, data governance I would say is a thankless job (laughs) 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're going after a certain big project, whether it's putting things together in one place or 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 Adobe based? What do you use? >> All of the above. >> Oh. (laughter) No, so, what we have is because we are such an old company, you know we still have our legacy Db2 infrastructure. A lot of our backend databases, lot of our backend processes are all attached to that. We have a warehouse, a sequel 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 in 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 are a lot more in control with all the issues with data privacy. So it is. >> Which, I hope you don't mind my interrupting but we have to wrap here and I need to get that question in. (laughs) >> Yes. >> You have data on 100 million consumers. What are you doing with all of the attention being paid for privacy right now? What are you doing to ensure the. >> We have a very, very I would say integrated infrastructure, data governance, data. There's a whole slew of, I would say, people and process around that to make sure that our date is not exposed. Now luckily, it's it's not like PII to the level that it's a health care 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's 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 Gillin. We will have more from IBM CDO Summit just after this. (techno music)
SUMMARY :
Brought to you by IBM. Thank you so much for coming on theCUBE. and be the Prize Patrol surprising contestants, And we have, you can categorize or there are small prizes like, if you go on our site, that you have data on just in the US alone. we give you products that are relevant to you. if I were, I mean you said all these customers are united But what are some other ways and we could give you and direct you to those experiences how is that reflected in the way Sure, so, it is, I'm part of the C-Suite. Lucky for you. That's the key, out here is like you know, I mean you have a CTO How do you two collaborate and work together? and when you own the data, which is, in a way, That's where you collect a lot of data on a daily basis. and you are a lot more in control Which, I hope you don't mind my interrupting What are you doing to ensure the. So you are not really, you have information that is crazy thank you so much for coming on theCUBE, We will have more from IBM CDO Summit just after this.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Paul Gillin | PERSON | 0.99+ |
Rebecca | PERSON | 0.99+ |
Rebecca Knight | PERSON | 0.99+ |
Ash | PERSON | 0.99+ |
IBM | ORGANIZATION | 0.99+ |
Ash Dhupar | PERSON | 0.99+ |
1,000 dollar | QUANTITY | 0.99+ |
Publishers Clearing House | ORGANIZATION | 0.99+ |
John | PERSON | 0.99+ |
US | LOCATION | 0.99+ |
Adobe | ORGANIZATION | 0.99+ |
Boston, Massachusetts | LOCATION | 0.99+ |
One | QUANTITY | 0.99+ |
two buckets | QUANTITY | 0.99+ |
100 million consumers | QUANTITY | 0.99+ |
360 view | QUANTITY | 0.99+ |
two | QUANTITY | 0.99+ |
ORGANIZATION | 0.99+ | |
BigQuery | TITLE | 0.99+ |
15 products | QUANTITY | 0.99+ |
Boston | LOCATION | 0.99+ |
about 100 million customers | QUANTITY | 0.98+ |
each | QUANTITY | 0.98+ |
about 100 million people | QUANTITY | 0.98+ |
billion-dollar | QUANTITY | 0.98+ |
15 minutes | QUANTITY | 0.97+ |
10 | QUANTITY | 0.97+ |
IBM Chief Data Summit | EVENT | 0.97+ |
one place | QUANTITY | 0.97+ |
US Postal Service | ORGANIZATION | 0.96+ |
12 | QUANTITY | 0.95+ |
one corner | QUANTITY | 0.95+ |
two separate jobs | QUANTITY | 0.95+ |
about 400 million pieces | QUANTITY | 0.95+ |
about two hours a day | QUANTITY | 0.93+ |
about 15 million unique customers | QUANTITY | 0.9+ |
about 40% | QUANTITY | 0.9+ |
about two billion page views | QUANTITY | 0.87+ |
second | QUANTITY | 0.86+ |
IBM CDO Fall Summit 2018 | EVENT | 0.86+ |
theCUBE | ORGANIZATION | 0.84+ |
prem | ORGANIZATION | 0.83+ |
IBM CDO Summit | EVENT | 0.82+ |
Prize Patrol | TITLE | 0.81+ |
IBM Chief Data Officer Summit | EVENT | 0.8+ |
about three years ago | DATE | 0.74+ |
Data Summit | EVENT | 0.61+ |
-Suite | TITLE | 0.6+ |
almost | QUANTITY | 0.59+ |
Clearing House | ORGANIZATION | 0.59+ |
everyday | QUANTITY | 0.53+ |