(introductory upbeat music) >> Hello and welcome to this Cube conversation. I'm Natalie Ehrlich your host for theCube. Today we're going to speak with an AI enhancing data startup that recently raised $75 million in C-series funding. Now we're joined by the chief marketing officer of Exosporium Ajay Khanna. [Natalie] Thank you so much for being with us today. >> Thank you so much, Natalie. Thanks for inviting me in. >> So tell us what is Exosporium. >> Sure. So Exosporium, we provide external data platform and this platform helps you discover thousands of relevant data signals external data signals that you can then use in your analytics or in your machine learning models and all. So what we are offering here is this a unique end to end platform where you can have access to thousands and thousands of data signals. And then you can take those signals and match it with your internal data. You can enrich your internal data, do the transformations and then build pipelines that business analysts can use and take it to their, their tool of their choice. Or what data scientists can do is take that enriched data and improve their ML algorithms. So that is the end-to-end platform that we provide. >> That's really fascinating. So you're constantly improving on the data and providing better analytics. Can you tell us how specifically are you helping your customers? >> Ajay: Absolutely. So as we kind of jump into the customer use cases let's first discuss this challenge with the external data, right? So when we refer to external data with the increase in AI and ML adoption there has been increase in interest in external data like getting the company data from external sources whether it is formal graphics, technographic data, you want socio-economic data, you may want like foot traffic data. You may want to include like data about website visits and, and the tons of data out there website interaction that are not within your organization but you want to get that data to get better understanding of your customers. But the challenge is that getting external data is really hard. So, and what I mean by that is that it is hard to access. First of all you don't even know how many data sources out there. It could be thousands of data sources. If you just go to data.gov there are like 250,000 data sources out there. So that is the first problem to tackle is where do I get the data from? And how do I get? And even before that what is the data that is going to impact my business? So having that issue of like data access is, is big problem. Second thing is that once you know which data you want to get it is very hard to use within your systems, or it is hard to kind of like you're going to just directly use the data into your analytics or into machine learning. You have to clean it up. You have to evaluate the quality of the data. You have to do the proper alignment and matching and integration and so on and so forth. And by various estimates like data scientists and analysts spend 80% of their time doing just that job. And the third is around the, compliance issues. We want to make sure that data is compliant with the GDPR or CCPA kind of regulations. So what we are helping our customers do is have an easy access to all these relevant data sources and where the system can recommend that, okay this is the relevant data which is going to make an impact to your business. This is the relevant data, which is going to make your ML and analytics better, and then match that data with your internal data sources automatically so that you can focus on the business value that you want to generate and take that data... Once you understand the impact of the data take it to your actual business use cases of the models that you have created. So our customers are in like various kind of industries, right? They are in CPG, they are in retail. Our customers are coming from various FinTech organizations like payments and lending and insurance. And they are using us for like various use cases. Like whether it is lead gen or whether it is a lead enrichment fraud and risk kind of use cases understanding the loan risk loan application risks and the by having access to these additional data sources that helps them make better decisions about their customers, about their business. >> Natalie: Fascinating. Well tell us, how do you see this market evolving? >> Market is, is, is really dynamic. And we have seen this whole market changing the whole data market, kind of like changing in, last year and a half with the pandemic coming in, right? So the models that we were working on for credit risk for evaluating loan applications were not working anymore. The data that we had was not really usable to make those decisions. So many of our customers, they had to depend on external data to make those credit decisions, right? I mean, if I have to approve an application for a small or a medium business restaurant and the restaurant is closed for last to five months how do I do that? So they were looking for additional data sources like foot traffic data about the Yelp reviews or about the ratings around how they're signed up for various delivery services and use those alternative sources to make those decisions. I think with these kind of like, as the situation come in, companies will become much more agile to react to these kinds of either data losses or changes in the data that they need. And some of the things that we also see right now is where Google is stopping the third party cookies with Chrome, right? Or Apple saying that with iOS 14, there are new transparency requirements that you have to, you have to abide by. So if those signals are gone, then how do companies better understand their customers? How do the companies will redesign their information, that they are delivering to their customers or the products that they are presenting to their customers. So having that agility will be determining the competitive advantage for these companies. And once these data signal losses happen, you cannot start evaluating the alternate data at that point in time because it takes like six, seven months to going to find the data sources and negotiate for those data sources bring them on board and then integrate them to kind of start using them. Then it is already too late. So what we are seeing is that companies will be much more agile and looking for a lot of external data sources to bring them in seamlessly and be able to make their business decision by incorporating those data sources as well. So, so that's how we are seeing that the use of external data is going to, going to increase with the time. >> Fascinating. And also that you mentioned the pandemic and the company added new data signals to help organizations understand risk. >> Ajay: Absolutely. Can you explain how that actually works to our audience? >> Ajay: Sure. So let's take a couple of scenarios, right? So for example, there is a lending organization and then they are looking for approving a loan application for a small medium business. And they had like three years back revenues or three years previous employee data or their tax returns and everything. But that is irrelevant right now because the business is not running. So how can they use alternate data signals to make that loan decisions or credit decisions? So they will be relying on some of like foot traffic data. They may rely on ratings and reviews. They may rely on, on other delivery services subscription that they have subscribed to and helping their customers, and then use those additional signals to make those credit decisions. This is like one situation. Another situation that we came across was in, CPG where food and beverages, sellers, whether those are like convenience stores or whether those are like small restaurants they're going in and out of business. And now when they're coming back in or the new restaurants or convenience stores are emerging, how do this food and beverage provider find those new customers? What are the additional signals they can use to go to that customer right away and say that, okay we are there with you. We are here to kind of like support your business. What are the additional things that you need to kind of like bring everything back to business? What are the additional shelf spaces available to place your product out there? Because now you don't have data, there's a data lag now. So you need to kind of like provide that additional data to your field operations so that they can find the right businesses. They can find they can prioritize them and they can see that, okay these are the businesses which are going to kind of like come back and we need to proactively go and market to them. So that once we are out of this COVID which hopefully we are now and how to support the small businesses that come come right back on track. >> Very, very interesting. And recently your company Exosporium closed $75 million in seed series funding and not even a year before another $31 million. So what do you attribute to that success? >> I think it is, it is the whole idea of a increase in adoption of AI and ML that we are seeing in the last few years. And as this adoption increases there is an increase in appetite for external data. So companies do realize that just having ML algorithms is not enough. That is not a competitive advantage. Everybody has the same algorithms. The advantage is the data that you have, advantages the domain expertise that you have, and then having the wide variety of data that is really important. So what we are seeing is that there is an increase in trust and getting access to these external data sources as a competitive advantage and then having that access easily and being able to easily use that external data into your analytics, into your ML models. That's where the, the real kind of advantages where you can actually bring your big ideas to life and execute on those ideas, but are coming from your business analysts and from your data scientists. So I think that increased interest is what we are seeing here. >> Well, that's a fascinating point on how data is really the central point of analytics. Really appreciate your fantastic insights on this program for this conversation on theCUBE. I'm Natalie Ehrlich your host. And that was Ajay Khanna the chief marketing officer of Exosporium. Thanks so much for joining us today. 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>>Live from San Francisco. It's the cube covering micron insight 2019 brought to you by micron. >>We'll come back to San Francisco. Everybody wears pier 27. This is the queue. We're following micron insight 2019. Dave Volante with David flora. Theresa Kelly is here. She is the vice president of the CPG consumer products group at my country. So thanks for running over to the cube for a moment. >>Glad to be here. Thank you. So tell us about CPG. What's the, what's the scope? >> So CPG is a consumer products group. We have a crucial Grande that's been around for 23 years. Uh, we sell to you and you and me. And we provide SSD solutions and DRAM solutions. So it could be someone upgrading their computer, it can be someone that is trying to be a gamer because we have high performance DRAM. And today we announced we broke the world record. Yeah. So with a, an AMD platform and ASIS, uh, a team. So the three teams, partners, so pretty excited about that. Tell us about the hard news. What are the announcements that you made? So I just mentioned that we broke the record. So we were able to achieve a, a speed of 6,024 mega transfers with the AMD, um, partnership. And as soon as, so pretty excited about that because that just shows we are, you know, a vertically integrated company and we're great. We've got great product out there and we provide that to the gamers out there and are able to give a group a solution both at the mainstream and the high end performance. >> And then that's a major growth area. That game is, yes, it is a couple of these shows. Yes, yes. Different normal than number audiences they get in person and online. So you got it. >>So when we started the cube, we started on Justin TV, which became, >>which we used to get so much traffic. We're like, where's all this traffic coming from? You know, what it was, it was the gamers, so. Huh. What's the importance of gaming? Well, let's start, >> you mentioned Twitch. We've got one of the teams we sponsor that's a big Twitch, uh, following up there, the energy team. And so they're one of the, uh, both set better happening. So, you know, from a gaming perspective, it, it, it is a very, you know, one of the fastest growing, uh, consumer DRAM markets. And it is something that allows us to put both DRAM and SSD out there to the consumer. We sell to the consumer. We also partner with those that make those platforms. You know, it could be someone upgrading a computer or um, someone that's buying it in the store. So pretty excited about because we have both solutions and are, are both vertically integrated, which no one else has. >>Some gamers need. They need memory, they need need. Joe's about more about the, the crucial brand. You know, you guys are amplifying that know what's behind the brand and what's the brand promise. Yeah, crucial is um, having met with some friends yesterday, they said, you are a trusted brand. We know we're gonna get quality product from you. We ask what do we know now? And we do, we deliver on what we say. We don't make hype news. We very much are able to say we're going to deliver such a product and, and bring that back to you. And we're known for great customer support too. We've spent time over the past 12 months continuing to build out a portfolio for our consumers and they've, the response has been great. Both again on the SSD side and on the DRAM side. So it is, it's a brand that is worldwide. We're across the world. We sell places like Amazon but also a lot in Europe and in Asia. There's still a lot of retail, so we saw to retail too and or@crucial.com so we're provide solutions. >>Well it's good. Yeah. Consumer spending is powering our economy right now, so that's great. Last question is what should we expect going forward? You know, give us some guideposts. >>So you know, we have, as with the announcements today, I mentioned, I hadn't mentioned that the exit was announced today. It's our portable SSD almost twice as fast as any SSD portable SSD out there with that price point. So pretty excited for that. Again, giving great, you know, value for our money with our vertical integration. And we definitely have, um, insights into wine to build, uh, a broader portfolio in time for our consumers and we look to them and where the market's going to provide the solutions. And as mentioned, gaming is very important to us, so we intend to continue to have investments there too. >>Love, it sure is the gift that keeps on giving, right? We keep increasing capacities, lowering costs, and now increasing performance. Theresa, thanks very much for coming on the. Okay. Give right there. We be back shortly. Is this the cube from micron inside 2019.

>> Live from Las Vegas. It's the Cube covering Adobe Summit twenty nineteen. Brought to you by X Ensure Interactive. >> Welcome back, everyone. Cube Live coverage here in Las Vegas for Adobe Summit. Twenty nineteen. I'm John. For whichever Frick. My Coast. This week. Two days of wall to wall coverage. Our next guest is Janine Falcone. Is the marketing agency lead in North America for a center in Iraq? Thanks for joining us. >> Thank you. Thanks for having >> me love having the conversation just talking on before we came on camera around the role of the agencies. You guys are doing a lot of big work for big brands. B to C B to B. There's a big shift going on with Cloud computing. We've seen that movie is happening right now. Amazon, as you are all going on, but that what? The marketing world. It's not just about marketing. Cloud is a lot more going on there. The impact to the marketing world and the agency relationships are impacted. That's what's going on. Give us >> the state of >> the market, >> happy to sew an extension. Interactive. You know, a lot of clients come to us and they're living in this world. I talk with my hands. Sorry, living in this world of, like chaos, as I like to call it, because there's so many things going on the technology landscape that you described. It's crazy out there. Remember, the landscape used to be this big announces big. So there's all that sort of market buzz and chaos around. I should buy this technology in that technology, and marketers and CEOs they've all been out there doing, that's that's one piece. The second piece is the customer affectation, right? All that is evolving and changes a customer's always expect. I don't really carry our retailer bank whatever. They kind of have that uber experience that they all expect regardless of product or service or anything like that. So marketers have always tried to deal with that in the way they knew how. But then the third component is business climate and what's happening in their worlds with either shrinking budgets or aging workforce. I don't even mean age necessarily as much a skill set. Aging skill sets things that used to matter. Don't they've got that they've got organizational silos, they've got all these things. So those three things, plus I'm a marketer. I still have to deliver that old brand promise that they're told to dio, It's a crazy crazy time. >> All theaters air on massive change over chips happening. Marketers and CMOS also relied on agencies for help. Tell them they have domain expertise in certain areas, A and agencies and the other thing. But now that the value equations shifting in the economics underlying economics behind it are getting some visibility around its digital different new ballgame, you got a I and Machine Learning has caused that shift. So the question is, How should your customer how are your customers dealing with agency relation? Because in today's value exchange, >> totally and that's all >> don't often come ask us that so not only they have all those silos and all those things. They could have seventeen different agencies across multiple product lines that may have been doing a great job in their own silo. But who's bringing all that together? And then it's not even and my just not spending my money right with these agencies, like What are they delivering for that? So when they come to us, tow holistically, look across all of that and help them. We start with the customer in the center of all those siloed crazy areas. You've got to start with the customer, and what do they expect and how do you deliver to them? So, yes, we're seeing this crazy world in the agency space two of brandade disease desolate all the different kinds of agency >> toss another piece of fruit in the blender makes it all. So I was talking with the sea so that the chief information security officer at some chief security officer at Microsoft reports to the board in cybersecurity, going through the same transformation that it's happening, marking where now you have technology and AP eyes and and tools technical tools. So he's shrinking his supplier base down because he doesn't want his skills gas to get widened by having to learn new tools. So there's now a new forcing function on the tech side, and now we see that kind of creeping into the adobe conversation where it's like this techno involved. Yes, we now have toes, shrink suppliers even more so how do you get from seventeen to three years at the train? So there seems to be a discussion around the impact attack your thoughts. >> Yeah, well, absolutely. That was one of the areas I talked about. So what happens? There is they'LL need marketers to understand technology which today many do. Let's be honest, right? Like, ten, fifteen years ago. They didn't. Today they do. But it also requires you both internally and externally, tohave multiple skill sets. And sometimes they'LL say, Should I be bringing this in house shivering that in house? What do I do with this technology? And there's never one answer. There's never like you should enforce this or that. And so technology has had that massive impact on Oh, I could do this myself and then they realise that can and then back to the But do I have the right skill sets internally externally to be able to do that. And it's often seventeen different still skill sets to do one thing where it used to be. A lot >> of Jeff and I talked on the cue before about you know, the classic business school conversation around core competency should be in house Horak outsource your non core competencies. How did you see that evolved? Because at some point there has to be a core concert on data and things of that nature. So what's your thoughts? How do you advise clients on Okay, if you're going to go in house and start putting a toe in the water and building it out, it's an investment. And all I think about, what's the core competency? >> I mean core competence to me or anything related specifically to your industry that people have to continue to get skilled in an expert in. And they want to do just that. One thing. Sometimes people that are broader generalists in marketing and data, they might get bored doing that. But if someone is like, I want to be really good at this and I'm going to continue to hone my skills in that one thing Data Analytics, whatever, then that may be. And you live in the right market. You don't live in kind of a part of the country where it be hard to find those skills. Be honest. I mean some parts of the country, it's easier than others, so that is one way to look at it. But anything that requires generalist knowledge across industry knowledge or or things that are constantly evolving and you want someone else to pay for the training. >> What's the CMO conversation like for you in clients these days is actually lets a lot of stuff going on. We just illustrated the game is still the same. They gotta pride that brand promise. Now they got the text taxing always new things. Hopefully, Ball will move down the field faster. But what is the CMO conversation that you have? How they stay ahead of the curve? What's their edge? >> Yeah, >> how they posturing right now? >> I mean, I think it's an amazing time to be in marketing. So CM owes to me that are the pioneering. CMO is the ones that are really focusing back is in on the customer and developed, you know, delivering those relevant experiences. They're the ones that are being ex successful because they try toe, not certainly not. Ignore all of us chaos that's surrounding, but stay focused and then they don't worry about Oh, this isn't in my silo. I have to kind of reach across, and I have to make sure I get this first. They have to be the leaders. They have to lead the industry like knowledge and business would be the leader in the organization, whether or not they are and just be the pioneer to get that done, that makes them successful. The ones that are excited about that they're the future, writes >> funny. We interviewed a guy from Clorox while ago, and you think of CPG has been data driven forever right there coming out of there coming out of Cincinnati. They all got trained Teo G. But this is a whole different level of kind of, of data, of data driven execution's been than what they've been doing for years and years and years. That's >> right, because potentially they were product centric. So they dealt with their product in CPD, and I'm going to sell toilet paper. That's I'm going to be the best market or there is. But the customer expectations surrounding that have changed, and they expect you to know them in a relevant, non creepy way. And product marketing to customer marketing is a big shift, and potentially I know a lot. I know a little about a lot of industries. CPG has been very product focused, which is difficult when you now have to be customer centric, regardless of product right that your company is trying to >> send the >> changing rule of distribution, especially in cpt. Anywhere before they would. They would ship the the toilet paper, whatever they were doing, and it goes out the door and they don't know anything else about it to the next. Word comes in correct. Now they know how the products are being used. They got a direct connection to the to the customer, and they need to establish a relationship beyond just the actual execution of the purchase of a very different >> kind of a chance. Crazy. I love it. I think it's a crazy time >> to be able to do that. And again, the blurring between marketing and commerce and sales and service. There's all sorts of debates on where marketing ends commerce sales service begins because it's all clustered together now. Then there's creativity and technology and data and analytics all converging. So to me, people that understand all of those things at a high enough level and are good collaborators and orchestrators that know how to get things done, they will be successful. >> Do you take a lot of people tried to buy their way out of the problem because you know Martek technology has been around for a long time. Arguably, you know, kind of leading edge in a lot of the the things in terms of a web experience. But this, you know, so many of them. >> You can't buy your way out of the problem. Yeah, Yeah, except that. And >> buy it quickly, right? I'm going to buy it, and I'm gonna plug the sand. I mean, I feel like that might have happened years ago, and now you're right there seeing that. Oh, my God. Now, that, too, is like its own silo. Now they have a technology silo to, in addition to potentially some organizational silos that they have to break down. So But, you know, the good news is that everybody sort of sees this now and kind of gets it. And if people are just sort of focused on to do the right thing for the customer because if you don't, someone else will. And sometimes going back to what used to work works like Now, if I call a company, I have no expectation they're going to answer the phone. And when they do, you're like, Wow, that was a great experience. I scheduled a vacation. It was It ended up being non refundable. And I'm like, I'm just going to try to call. It was one of the online. It wasn't Airbnb was one of those like services I caught. They answer the phone. If seven o'Clock on a Thursday night, >> no problem. You can count. Like this is the greatest experience I've had. I'm going to use them again because I didn't expect >> that. So it's not like what used to work doesn't work anymore, but has to work on the right. >> Pleasant surprises. Exactly. Relevancy. That's healthy. And you got it. Yeah. And then they >> said I said, Okay, well, I mean, they're like, we don't need your information, you know, I have your cell phone, so I don't >> know. And I wasn't creeped out by that. I don't >> thank God. Now I don't have to fill out a form >> I need to do mother's maiden name, like, six different times. >> And then, you know what? I saw how you guys make >> money. Like I was so fascinated by this that I just had to sort of figure out the business model because I'm a marker there. And my point is that was. I don't know how much it costs them to do that, but that was a positive experience, >> President. People call in >> there, Bryan. Nobody call it. And I don't know how they got around the company for all I know. So I gotta ask you, I gotta ask >> you with all these new changes you mentioned in one of the great example of how the world's changing KP eyes also change around what's really what's relevant. Because these new things air going on where may or may not have KP I. So how does the CMO get out in front of that? How did they evolve their skill set to either either grok that understand all this new k p I potential? Yeah, and have that front and center and working through the marketing mix. >> Yeah, you can have KP I overload to write. So remember, old school still works. Brand matters. Brandt. No one worried about measuring that stuff years ago, and part of that is still relevant. I had a session earlier today and people talked about CP eyes like customer related influence and things like that, because that matters and some things you absolutely I know This is a Dobie a mike in trouble. You maybe can't necessarily measure. But, you know, it matters to your brand, and some of that matters to know how much you spend on that, how you sort of track that and maybe track I'm all about, like, mixing gray and mixing, you know, qualitative and quantitative stuff. That's part of the trick >> on these signals. Their market, their data signals totally put on the agency front. Go back to the agency for second because with sass, APS and these new things, people answer the phone, which has blended kind of channels. Is there a new agency model emerging around cloud and sass applications that that this doesn't feel like an agency but acts like an agency? Because if you're an agency you're providing a service, you have software service models out there. Self service is there in the evolution of change over and how ages new agencies looked like. And how does the CMO know if someone's a new agency is going to be relevant or not? >> I mean, it totally depends on the kind of agents, and I would tell C Motor not necessarily worry about that. I wouldn't worry about. Do I need a new kind of agency at all? It's like, What am I getting? What are they delivering for me? I would go back to the first question and what do I need to keep as a core competency? And inside versus outside I wouldn't worry about it. Might be the technology question. Right now, I'm gonna have even the others other crazy agencies in What I would worry about is what do I know? I need toe outsource and have people help me with that are going to come up with the best ideas. And I mean, agencies still do that because to come up with a creative idea, you need that expertise that is outside of your industry. So I don't see that ever changing >> don't ask in terms of because, he said, cause brand matters. And I always like a Harley Davidson is kind of the extreme brand loyalty where people tattoo it on their bodies and there's a whole ecosystem outside of the motorcycle. That's a really, you know, passionate group of people. Should everybody strive for that kid everybody. I mean they can't get quite where every tattoo and brands on their arm. But you know where we're kind of the limits And is it, you know, kind of appropriate based on what the product is, how people think about that. Specter. >> Yeah, I might be a little biased on that. I always think brand matters. I always think that when you think of something, if you don't in your head, know what that stands for, whether or not it's a positive or negative is not really relevant. It's yes, I think it does now. Should they strive to be that? No. But they have to be differentiated, and they have to have people know what they do quickly, because if you have to figure it out like mean, people struggle with that today in terms of knowing where to go for what, So without a clear value proposition, differentiation and a brand that matches that and a brand you can live up to with every experience, it's going to be rough. You might have some early success, but it won't. I don't know that it lasts their time and strong brands kind of carry through some tough times, too, You know, if sales are down on the market changes, >> we'LL keep doing our and our interviews on events and get smart people really smart people. And all the answers come out community. Thanks >> so much for coming on, sharing these awesome insights. Final question. What's going on? The show for you? What? Some of the hallway conversations here. You're speaking. What's the top story line for you here at this show? >> It's two things. It's what's going on. The market with our clients is as we just talked about. It's what's going on in our own industry. I mean, there's craziness in our own industry, which is kind of fun. You know what players do, what and who's going to do what and you know, where's this all going? And it's fun. I mean, it's it's really, really fun and exciting to be part of this industry. >> Well, thanks for coming on, Mr. Q. Where we're extracting the signal from the noise at this event. Adobe Summit twenty nineteen Talking the smartest people bringing it to you. Bring that data to you. We right back with more coverage after this short break

(upbeat music) >> Hey welcome back everybody, Jeff Frick here with theCUBE. We're in our Palo Alto studio this morning for a CUBE Conversation talking about content marketing, attention economy, a lot of really interesting topics that should be top of mind for marketers, that we're in very interesting times on the B2C side and even more, I think, on the B2B side. So we're excited to have Randy Wootton, he's the CEO of Percolate. Randy, great to see you. >> Thanks very much for having me. A real pleasure to be here. >> Absolutely, so for those who aren't familiar, give us kind of the quick and dirty on Percolate. >> Percolate has been around for about seven years. It started as a social media marketing platform. So helping people, helping brands, build their brands on the social landscape, and integrating campaigns to deploy across the different social channels. Over the last couple of years, it's been moving more into the space called content marketing, which is really an interesting new area that marketers are coming to terms with. How do you put together content and orchestrate it across all the different channels. >> And it's interesting, a lot of vocabulary on the website around experiences and content not a lot about products. So how should marketers think and how does experience and content ultimately map back to the products and services you're trying to sell. >> Well, I do think that's a great point. And the distinction between modern brands, who are trying to create relationships with their consumers, rather than pushing products, especially if you're B2B, or technology pushing speeds and feeds. Instead, you are trying to figure out what is going to enable you to create a brand that consumers pull through versus getting pushed at. And so I think the idea around content marketing is that in some ways advertising isn't working anymore. People aren't paying attention to display ads, they're not clicking, they aren't processing the information. But, they are still buying. So the idea for marketers is, how do you get the appropriate content at the right time, to the right person, in their purchase journey. >> Right, and there's so many different examples of people doing new things. There's more conversations kind of, of the persona of the company, of the purpose, purpose driven things, really trying to appeal to their younger employees as well as a younger customer. You have just crazy off the wall things, which never fail to entertain. Like Geico, who seems to break every rule of advertising by having a different theme every time you see a Geico ad. So people are trying humor, they're trying theater, they're trying a lot of things to get through because the tough thing today is getting people's attention. >> I think so, and they talk a lot about the attention economy. That we live in a world of exponential fragmentation. All the information that we are processing across all these different devices. And a brand trying to break through, there's a couple of challenges, one is you have to create a really authentic voice, one that resonates with who you are and how you show up. And then, I think the second point is you recognize that you are co-building the brand with the consumers. It's no longer you build the Super Bowl ad and transmit it on T.V., and people experience your brand. You have this whole unfolding experience in real time. You've seen some of the airlines, for example, that have struggled with the social media downside of brand building. And so how do control, not control, but engage with consumers in a way that feels very authentic and it continues to build a relationship with your consumers. >> Yeah, it's interesting, a lot of things have changed. The other thing that has changed now is that you can have a direct relationship with that consumer whether you want it or not, via social media touches, maybe you were before, that was hidden through your distribution, or you didn't have that, that direct connect. So, you know, being able to respond to this kind of micro-segmentation, it's one thing to talk about micro-segmentation on the marketing side, it's a whole different thing with that one individual, with the relatively loud voice, is screaming "Hey, I need help." >> That's right, and I think there are a couple of things on that point. One is, I've been in technology for 20 years. I've been at Microsoft, I was at Salesforce, I was at AdReady, Avenue A, and Quantive. And now, Rocket Fuel before I came to Percolate. And I've always been wrestling with two dimensions of the digital marketing challenge. One is around consumer identity, and really understanding who the consumer is, and where they've been and what they've done. The second piece is around the context. That is, where they are in the moment, and which device they're on. And so, those are two dimensions of the triangle. The third is the content, or in advertising it's the creative. And that's always been the constraint. You never have enough creative to be able to really deliver on the promise of personalization, of getting the right message to the right person at the right time. And that now is the blockade. That now is the bottleneck, and that now is what brands are really trying to come to terms with. Is how do we create enough content so that you can create a compelling experience for each person, and then if there's someone who is engaging in a very loud voice, how do you know, and how do you engage to sort of address that, but not loose connections with all your other consumers. >> Right, it's interesting, you bring up something, in some of the research, in micro-moments. And in the old days, I controlled all of the information, you had to come for me for the information, and it was a very different world. And now, as you said, the information is out there, there's too much information. Who's my trusted conduit for the information. So by the time they actually get to me, or I'm going to try to leverage these micro-moments, it's not about, necessarily direct information exchange. What are some of these kind of micro-moments, and how are they game changers? >> Well, I think the fact that we can make decisions in near real time. And when I was at Rocket Fuel, we were making decisions in less than 20 milliseconds, processing something like 200 billion bid transactions a day, and so I just think people are not yet aware of the amount, the volume and the velocity of data that is being processed each and every day. And, to make decisions about specific moments. So the two moments I give as examples are: One, I'm sitting at home watching the Oakland Raiders with my two boys, I'm back on the couch and we're watching the game, and Disney makes an advertisement. I'm probably open to a Disney advertisement with my boys next to me, who are probably getting an advertisement at the same time by Disney. I'm a very different person in that moment, or that micro-moment than when I'm commuting in from Oakland to San Francisco on BART, reading the New York Times. I'm not open to a Disney ad at that moment, because I'm concentrating on work, I'm concentrating on the commute. And I think the thing that brands are coming to terms with is, how much am I willing to pay to engage with me sitting on the couch versus me sitting on BART. And that is where the real value comes from, is understanding which moments are the valuable ones. >> So there's so much we can learn from Ad Tech. And I don't think Ad Tech gets enough kind of credit for operating these really large, really hyper speed, really sophisticated marketplaces that are serving up I don't even know how many billions of transactions per unit time. A lot of activity going on. So, you've been in that world for a while. As you've seen them shift from kind of people driving, and buyers driving to more automation, what are some of the lessons learned, and what should learn more from a B2B side from this automated marketplace. >> Well, a couple of things, one is the machines are not our enemies, they are there to enable or enhance our capabilities. Though I do think it's going to require people to re-think work, specifically at agencies, in terms of, you don't need people to do media mixed modeling on the front end in Excel files, instead, you need capacity on the back end after the data has come out, and to really understand the insights. So there is some re-training or re-skilling that's needed. But, the machines make us smarter. It's not artificial intelligence, it's augmented intelligence. I think for B2B in particular what you're finding is, all the research shows that B2B purchasers spend something like 70 or 80% of their time in making the purchase decision before they even engage with the sales rep. And as a B2B company ourselves, we know how expensive our field reps are. And so to make sure that they are engaging with people at the right time, understanding the information that they would have had, before our sales cycle starts, super important. And I think that goes back to the content orchestration, or content marketing revolution that we are seeing now. And, you know, I that there is, when you think about it, most marketers today, use PowerPoint and Excel to have their marketing calendar and run their campaigns. And we're the only function left where you don't have an automated system, like a sales force for marketers, or a service now for marketers. Where a chief of marketing or a SVP of marketing, has, on their phone the tool of record, they system of record that they want to be able to oversee the campaigns. >> Right, although on the other hand, you're using super sophisticated A/B testing across multiple, multiple data sets, rather than doing that purchase price, right. You can test for colors, and fonts, and locations. And it's so different than trying to figure out the answer, make the investment, blast the answer, than this kind of DevOps way, test, test, test, test, test, adjust, test, test, test, test, adjust. >> You're absolutely right, and that's what, at Rocket Fuel, and any real AI powered system, they're using artificial intelligence as the higher order, underneath that you have different categories, like neural networks, deep learning and machine learning. We were using a logistic regression analysis. And we were running algorithms 27 models a day, every single day, that would test multiple features. So it wasn't just A/B testing, it was multi variant analysis happening in real time. Again, the volume and velocity of data is beyond human comprehension, and you need the machine learning to help you make sense of all that data. Otherwise, you just get overwhelmed, and you drown in the data. >> Right, so I want to talk a little bit about PNG. >> I know they're close and dear to your heart. In the old days, but more recently, I just want to bring up, they obviously wield a ton of power in the advertising spin campaign. And they recently tried to bring a little bit more discipline and said, hey we want tighter controls, tighter reporting, more independent third party reporting. There's this interesting thing going now where before, you know, you went for a big in, 'causethen you timed it by some conversion rating you had customers at the end. But now people it seems like, are so focused on the in kind of forgetting necessarily about the conversion because you can drive promoted campaigns in the social media, that now there's the specter of hmm, are we really getting, where we're getting. So again, the PNG, and the consumer side, are really leading kind of this next revolution of audit control and really closer monitoring to what's happening in these automated ad marketplaces. >> Well, I think what you're finding is, there's digital transformation happening across all functions, all industries. And, I think that in the media space in particular, you're also having an agency business model transformation. And what they used to provide for brands has to change as you move forward. PNG has really been driving that. PNG because of how much money they spend on media, has the biggest stick in the fight, and they've brought a lot of accountability. Mark Pritchard, in particular, has laid down these gauntlets the last couple of years, in terms of saying, I want more accountability, more visibility. Part of the challenge with the digital ecosystem is the propensity for fraud and lack of transparency, 'cause things are moving so quickly. So, the fact, that on one side the machines are working really well for ya, on the other side it's hard to audit it. But PNG is really bringing that level of discipline there. I think the thing that PNG is also doing really well, is they're really starting to re-think about how CPG brands can create relationships with their consumers and customers, much like we were talking about before. Primarily, before, CPG brands would work through distributors and retailers, and not really have a relationship with the end consumer. But now as they've started to build up their first party profiles, through clubs and loyalty programs, they're starting to better understand, the soccer mom. But it's not just the soccer mom, it's the soccer mom in Oakland at 4 o'clock in the afternoon, as she goes to Starbucks, when she's picked up her kids from school. All of those are features that better help PNG understand who that person is, in that context, and what's the appropriate engagement to create a compelling experience. That's really hard to do at the individual level. And when you think about the myriad of brands, that PNG has, they have to coordinate their stories and conversations across all of those brands, to drive market share. >> Yeah, it's a really interesting transformation, as we were talking earlier, I used to joke always, that we should have the underground railroad, from Cincinnati to Silicone Valley to get good product managers, right. 'Cause back in the day you still were doing PRD's and MRD's and those companies have been data driven for a long time and work with massive shares and small shifts in market percentages. But, as you said, they now, they're having to transform still data driven, but it's a completely different set of data, and much more direct set of data from the people that actually consume our products. >> And it's been a long journey, I remember when I was at Microsoft, gosh this would have been back in 2004 or 2005, we were working with PNG and they brought their brands to Microsoft. And we did digital immersions for them, to help them understand how they could engage consumers across the entire Microsoft network, and that would include X-Box, Hotmail at the time, MSN, and the brands were just coming to terms with what their digital strategy was and how they would work with Portal versus how they would work with other digital touchpoints. And I think that has just continued to evolve, with the rise of Facebook, with the rise of Twitter, and how do brands maintain relationships in that context, is something that every brand manager of today is having to do. My father, I think we were chatting a little earlier, started his career in 1968 as a brand manager for PNG. And, I remember him telling the stories about how the disciplined approach to brand building, and the structure and the framework hasn't changed, the execution has, over the last 50 years. >> So, just to bring it full circle before we close out, there's always a segment of marketing that's driven to just get me leads, right, give me leads, I need barcode scans at the conference et cetera. And then there's always been kind of the category of kind of thought leadership. Which isn't necessarily tied directly back to some campaign, but we want to be upfront, and show that we're a leading brand. Content marketing is kind of in-between, so, how much content marketing lead towards kind of thought leadership, how much lead kind of towards, actually lead conversions that I can track, and how much of it is something completely different. >> That's a great question, I think this is where people are trying to come to terms, what is content, long form, short form video. I think of content as being applied across all three dimensions of marketing. One is thought leadership, number two is demand gen, and number three is actualization or enablement in a B2B for your sales folks. And how do you have the right set of content along each of those dimensions. And I don't think they're necessarily, I fundamentally think the marketing funnel is broken. It's not you jump in at the top, and you go all the way to the bottom and you buy. You have this sort of webbed touch of experiences. So the idea is, going back to our earlier conversation, is, who is that consumer, what do you know about him, what is the context, and what's the appropriate form of content for them, where they are in their own buyer journey. So, a UGC video on YouTube may be okay for one consumer in a specific moment, but a short form video may be better for someone else, and a white paper may be better. And I think that people don't necessarily go down the funnel and purchase because they click on a search ad, they instead may be looking at a white paper at the end of the purchase, and so the big challenge, is the attribution of value, and that's one of the things that we're looking at Percolate. Is almost around thinking about it as content insight. Which content is working for whom. 'Cause right now you don't know, and I think the really interesting thing is you have a lot of people producing a lot of content. And, they don't know if it's working. And I think when we talk to marketers, that we hear their teams are producing content, and they want to know, they don't want to create content that doesn't work. They just want a better understanding of what's working, and that's the last challenge in the digital marketing transformation to solve. >> And how do you measure it? >> How do you measure, how do you define it? And categorize it, so that's one of the challenges, we were chatting a little bit before, about what you guys are doing at CUBE, and your clipper technology and how you're able to dis-aggregate videos, to these component pieces, or what in an AI world, you'd call features, that then can be loaded as unstructured data, and you can apply AI against it and really come up with interesting insights. So I think there's, as much as I say, the transformation of the internet has been huge, AI is going to transform our world more than we even can conceive of today. And I think content eventually will be impacted materially by AI. >> I still can't help but think of the original marketing quote, I've wasted half of my marketing budget, I'm just not sure which half. But, really it's not so much the waste as we have to continue to find better ways to measure the impact of all these kind of disparate non-traditional funnel things. >> I think you're right, I think it was Wanamaker who said that. I think your point is spot on, it's something we've always wrestled with, and as you move more into the branding media, they struggle more with the accountability. That's one of the reasons why direct response in the internet has been such a great mechanism, is because it's data based, you can show results. The challenge there is the attribution. But I think as we get into video, and you can get to digital video assets, and you can break it down into its component pieces, and all the different dimensions, all of that's fair game for better understanding what's working. >> Randy, really enjoyed the conversation, and thanks for taking a minute out of your busy day. >> My pleasure, always enjoy it. >> Alright, he's Randy, I'm Jeff, you're watching theCUBE from Palo Alto Studios, thanks for watching. (digital music)

>>From the Mandalay convention center in Las Vegas, Nevada. It's the queue at IBM. Insight 2014 here is your host, Dave Vellante. >>Hi, welcome back to IBM insight everybody. This is Dave Volante with John furrier. We're here with the cube. The cube is our live mobile studio. We go out to the events, we extract the signal from the noise. Carla Gentry is here otherwise known as at data nerd. Carla, great to see you. Welcome to the cube. You are a data scientists. Do you have your own company? Um, we were just talking to, uh, to dr Ahmed Bouloud from a university in um, Istanbul and he said, well, it's data science. It really, really isn't a such thing as a data scientist. And so he and I are arguing a little about it. So I said, come back and see Carla, right? You're a data scientist, right? >>Well, you know, right out of college I started with a RJ criminal associates up in Chicago. And um, that that's what we all were a bunch of data nerds in there playing around with terabytes of data before anybody even knew what a terabyte one terabyte was really big. Right? Right back when the terabyte was big data, but a, you know, gleaning insight for a discover financial services. And then, you know, I've worked with consumer packaged goods, the education, I mean it's, it's been a wonderful, wonderful career. And what's so great about this is to be able to walk around and see how much data is a part of more people's lives now than it was 20 years ago. I mean, 20 years ago you couldn't have, you know, gotten thousands of people together talking about data analytics. Well, you know, the interesting thing about what you're saying without you, you CPG education, financial services, John and I talk about this a lot, how the data layer is becoming a transport mechanism to connect the dots across different industries and data scientists. >>You guys don't like to get locked into one little industry niche. Do you you'd like to gather data from all types of different sources? Talk about that. Well, that's the thing. Uh, unfortunately, uh, we get bored very easily because, you know, we like to have our fingers in a lot of different pies. But, you know, you wouldn't want to be necessarily siloed with just one kind of information because curiosity makes you think about everything. Education, risk, you know, I'm that way. I have no walls. You know, I can, I can glean insight from any type of data. If you've got a database, uh, we can jump in with both feet. Is data is data and why is the data more transformative today in this day and age, you know, circa 2014 versus say, when you came out of college, why is it that everybody's talking about data that data is able to, to change industries, transform industries. >>What's different? Well, now the, you know, data can actually give you, you know, an insight into your customer mean, you know, what is your customer buying, you know? Um, so when you go to, you know, run a campaign or something like that, you, you're not shooting in the dark. You know, you're actually, you have a face to your customer. So you know, you can make decisions and it's not just marketing, you know, which is what I started out in, you know, trying to do increase and lift, you know, sales. But now you know, you have risk, you have, you know, data breaches. You have, you know, what keeps CEOs up at night, you know, it's not only the cash flow, you know, it's the mitigated risk that's involved. And when you're looking at your, your data and you're collecting this information that gives you a view into what's really going on so you can sleep at night and have a little bit of comfort mostly, >>well not sleeping at night, it's a couple hours of sleep. The notification when I opened CEO's and CIO's, CFO's, chief data officer, you've seen much more formal roles around data where data is real key asset. And this is awesome because it brings to the forefront the role of data. And so I want to get your perspective on this. You brought into the kind of the, kind of the trajectory of where we've come from, um, and talking about the role of software because really what this highlights here at IBM insight is okay, it's not just data per se, you know, how software that's a key part of it. So it's now also an integral part of the platforms. You have a developer angle, you have the data asset, and now you've got this real time in the moment experience. And IBM is talking about engagement a ton here. And so what's your take on all that? I mean it's, it's exciting. Certainly if you're in the data business. >>Well definitely, I mean, real time data, of course it's very expensive. Um, but it's, it's more attainable now than it ever was. Um, the thing is now is you don't necessarily have to be a data scientist to be able to go and get at your data. I mean, thanks to software tools, you know, like IBM, they give you that benchmark, you know, the, these tools, uh, where you can use BI and things like that. To be able to get a view into your business. And you know, it's not just for, you know, your analytical department anymore. Um, so I think it's what it's done is it's actually made it more attainable now. You know, it was like people looked at data wagon back then, Oh, and it was so scary, you know, but now it's, it's bringing it to the forefront to where we can make decisions. We can want our bitter, our business better. And like I joined forces with a repo software years ago to look at the supply chain. Now when you talk about that, that's what keeps the lights on. But you're only as strong as your weakest link. So when you're working with third parties, you have to make sure that everything is going smoothly. So >>I want to get your take on a couple of things in. He chose SA was on earlier and she's an awesome guest. She's been on many times. She's dynamic and articulate and super smart, brilliant and beautiful. We love talking with her. She said, I asked her what are the top three customer issues? And kind of a double edged question. She said three things, customer experience, operational assets, AKA the supply chain, and then risk security and governance. And then we weaved in context computing and then cognitive. So let's break that down. So customer experience, internet of things is a data play, you know, probes and sensors and machines certainly get that >>analogies. People are things. Yeah, well you know, here's the thing that you think about. Data. Data is a person that record that you have in that database equates to a real live person and you want to, you know, you're not going to be friends with your, your customers, but you want to know more about them so that you can serve them better. Um, you know, for me the biggest thing is, you know, people will go out and spend millions of dollars on a database but not necessarily know what to do with it. So it comes down to what question are you trying to answer? >>Yeah. And the infrastructure piece is interesting because you want to have that agile flexibility, which is kind of a buzz word amongst vendors. Hey, be flexible. But there is meaning behind it. Right. So context computing is relationships across entities. The streaming stuff is very, very interesting to me because now you have streaming data coming off of devices and again brings up the real time piece. So making sense of all this means it puts it in the forefront. >>And what you can do with that data is if you do have a client or a customer and you let them link in socially, like log in through Twitter or LinkedIn or Google, Facebook, now you can append that social data. So now you, you've got an ideal, you know sediment and you know when you're positive you it's first party data. Yeah, exactly. The Holy grail of active data is first party data. Exactly. >>Cause we'd love the crowd chatting and love people. The logging in and, and thanks for, by the way, for hosting the crowd chat with Brian the other day. It was really fantastic conversation. My pleasure. Let's talk about cognitive because this brings a human element of it. And one of the things we've been teasing out of the past couple of shows we've been at around big data is the role of the developer where the developers in the old days from even going back to the mainframe days, cold ball, they were adding in these rooms, almost like almost an image of coders in the back room coding away. But now with the customer experience front and center with mobile infrastructure, the developers are getting closer to the customer experience. And so you're seeing more creativity on the developers side with the use of data. Could you share just observation, anecdotes, things you've been involved in that can tease out where this is going and how people should be thinking about it? >>Oh, do you know 20 years ago if he tried to show someone and graft with, you know, 16 different things at one time going on, they were like, that's messy. Now you can actually find the sweet spot or where everything interacts. So you know, when you're talking to an artist, a digital artist who's working with data and giving that picture, that's exciting for me. And going back when we were talking about cognitive computing, when you're talking about the Watson on ecology, that's exciting. Yeah, that's the highlight of it's almost magic. It's almost like black magic, this Watson stuff and people are really just now getting their arms around that and that is essentially making sense of the data, but that's the thing. See, it's no longer magic now. That's what they thought 20 years ago. Poof. People like me, they kept in a little closet, you know, and then our office and they only came to Moses when they needed something. >>Now we're an integral part and we actually are in the business development meetings and we're a liaison between the it department and the C suite. One of the, one of the things that it's interesting about your role as not only you out in the field doing some great work, you're also an influencer here at the IBM influencer program, so I want to get your take on this balance between organic data and kind of structural data. Organic data means free forming unstructured data and then existing data that comes in that's rigid and structured because of business processes. And I get that is data warehousing business has been around for years, right? It's intelligence, it's all fenced in, all structured. But now you have this new inbound data sources coming in, being ingested by these large systems, data changes the data. So you now have a new dynamic where latency, real time insights, these are the new verbs, right? >>So talk about that role, the balance being organic data and the structure data and what the opportunities are. Well, the wonderful thing about, you know, now that unstructured data was scary way back in the day. So now it's not so scary, you know, now we can actually take this data and make business decisions, but uh, you know, like social data and things like that. When you can add that in a pin that and get to, you know, what we all want is a better view of our customer and to be able to, you know, do better business with them. Like, um, like supply chain management and things like that. I mean you're, you're looking at open people, you know, collecting information from varying sources and this all has to be put together. So I think they mentioned earlier this morning how 80% of it is we're data janitors cleaning up this, that and the other. >>Whereas what we really want to do is, you know, glean the insight from it. But I think, uh, the tools these days are making that much more easier no matter what the source is that we can actually put it all together, what we used to call the merge Burj back in the old days. It takes weeks to do the merge purge and yeah, who all here knows what a DLT is trying to solve this problem for a while with traditional technology 17 years. So let's talk about, you know, the, the promise of BI and the traditional data warehouse 360 degree view of my customer, real time information. And that's what it's about. It's about drilling down predictive analytics, all these promises. Did the data warehouse live up to those promises in your view? Well, initially, maybe not, but you know, things are, it just seems in the last few years that people have had an epiphany of how this is really adding value to their company. >>Now back in the old days, they all knew that, you know, insight is wonderful, but now you can see it visibly showing signs actually making a difference in company so they can keep an eye on everything that's going on. Now, going back to what keeps CFOs, you know, up at night with the risk and stuff, there's still always the risk, but at least now you can get a little better handle on it. And thanks to the age of technology and the data that we have accessible to us today and the tools we have available to us today. It's, it's made a dramatic change. What are the technology catalyst? Is it do? Is it no sequel? Is it, what are the, what are the tools that are sort of the foundation of that change? Well, I think always the, you know, the new tools and making it so that you don't have to go out and learn SQL. >>You don't have to be a programmer, you don't have to, you know, go to college for four years and learn mathematics and engineering to actually be able to work with this data. So thanks to, you know, tools like had it been other tools. I mean you can really sit down and glean insight without having to write one single line of code. So the things we're getting some questions in the crowd chats, um, um, at furry, at data nerd, what are the key things that are messy, scary right now for CEOs and CFOs? So things are becoming less scary. What is the scary things right now? Oh, the scary thing is the breaches. You know, when you hear about target and these big names, you know, people getting access to your, your credit card data. That's, that's scary. So, you know, we've got to really try to lock down that risk, you know, and I know everybody's scrambling scratching their head, figuring out how we're going to keep these breaches from happening again. >>Yeah. Big data solves that. I mean you have big data technology, which is a combination of machine learning, streaming where you're getting massive surges of data coming in to these ingest systems where you can apply some reasoning to it, some cognitive, some insights to look for the patterns and that's where machine learning shines. Um, how do you see that aspect of machine learning and these new tools affecting that kind of analysis? Will I see it opening up a lot of different doors for a lot of different people and making a difference because, uh, you know, everybody knows that data is important, but not a lot of people know how to deal with it, especially when it gets into the zettabytes of data. When you have tools, you know, like the IBM tools that can handle this type of load and be able to, to give you, you know, instantaneous information. >>And, and like what we saw this morning where, uh, like risk, I mean an oil and gas industry, you know, you, you have to worry about, you know, as someone going to get injured on the job and they showed the the center, whereas she walked toward it, it went off. I mean the internet of things, being able to let us know in real time if there's a danger, you know, to personal life or to your database and then predictive to be able to say, well this is what we think is going to happen in the future and to be able to move and act on that. It's a very exciting time. You mentioned IBM, so obviously is a leader in here, >>Jeff Kelly's report shows IBM is the number one big data player. But big part of that is IBM. So big, right? >>Well and you guys were around a long, you've been around a long time. You guys were playing with big data way back before. Big data was big data. So yeah, we guys, us guys, yeah, well social, social data, >>those guys, right? So we're not all right, but so, but, but so you bring up IBM, a lot of people have a perception IBM big, hard to work with, but you're, >>but that's changing. So talk about that change. What I'm excited about is the Watson's analytics. I mean that in itself right there and made me sit up and, you know, get excited about the data world all over again. You know, to be able to excite you about Watson analytics platform? Well, I really like, uh, the, uh, the oncology, uh, Watson, um, they had the, the one for the, uh, not necessarily for the police, but for the, uh, the crimes. I mean, in real time, if you can see that a crime is about to happen and you can prevent it, or if you see someone's health is failing and you're able to step in. And that's why over there, earlier I was talking about IBM cognitive abilities can save lives, you know, so I mean, my, my mom passed away from cancer, so, you know, the, the, um, oncology Watson was very exciting to me, but it's gonna make a difference. And I think the thing is now is that how it's changed is to make them user friendly where you don't have to have a data scientist or an analyst to come in. You know, they talk about how expensive data scientists are. Now the reason I opened my business was to make it affordable to small businesses, you know, so although you know, people look at IBM and think it's scary, I think they're going to see now that the, the direction that they're moving is becoming more user friendly and more available. >>So Carla, I wonder if you could talk about how you engage with clients. So you mentioned small business, right? Cause you have a lot of, a lot of businesses, small midsize companies don't have the resources. Right? Um, so where did they start? Did they start with a call to you and, >>well, uh, most of the time it's a call where, you know, we spent all this money on this database and we still can't get what we want out of it. So it comes down to what question are you trying to answer? I think that's the most important thing because that directly deals with what data that you need. And if you don't have it internally, can we get it externally? You know, can we go through open source, can we get census data? Can we get, you know, work with hospitals and doctors and things like that and use this to be able to feed this information into them to make a difference. >>So what do you do? I mean, are you so CEO calls up small companies, is that got all this data? It's unstructured. I get some social data. I get my customer data trying to make sense out of. I'm trying to figure out, you know, who's >>ready to buy, where I should be, you know, focus my products. Uh, and I got all this, this, this date. I don't know what to do with it, but I know there's some gold in there. I know there's a signal in that data mining, right? So how do I get it? How can you help me? Well, it's gap analysis. First off, I would come in and I would sit down and first of all, I need to see what variables you're collecting. Uh, if you're telling me you you're collecting your name, address and phone number, but you want to do a predictive model, we can't get that. So, um, you know, the question that you want to answer is, is most important? Are you wanting to increase your sales? Are you wanting to get your, to know your customers better, to be able to service them better? >>Like in the healthcare industry, you know, you really want to know what's going on health wise, you know, so, uh, I sat down with them when we do a gap analysis, what are you missing? What do you have? How can we get it? What do you want? Where are you at? Yeah. And here's, here's what you have, here's what you're missing. How do we get at that? And that's oftentimes starts with data sources. Exactly. So then you go get the data sources and then more than what you do, well then we merge it back in. And here's the thing, you have to have that way to connect them. You know, the relational databases will always exist to where you have, you know, client information here and you've got other information over here and you have to always bring that back together. So, um, you know, it's a wonderful time. >>You're a data hacker in a sense, right? Is that fair data nerd in a complimentary way? I mean hacking is about exploration. Yeah, exactly right. So I mean, so you have the skillsets as a data scientist to pull all this data together, analyze it and well, you're going to bring in an external source and then when you bring it externally, you want to make sure that you can match it back up. And now that's the important and without a unique quantify or how do you do that? And that's why when you see databases with all these little arrows and everything pointing to where things belong, I mean we have to be able to pull that in to make decisions. >>Yeah. We were talking with frons yesterday to another influencer. We were talking about this particular point. He was ex P and G back in the day, which is very data-driven. Of course, they're well known for their brand work and certainly on the advertising side, but they're, they're quant jocks over there. They love data. Their data nerds over there, they're kicking out on data. And he used to say that the software would cut off data points that were skewing way outside the median. And so they would essentially throw away what are now exploratory points. So this kind of brings up this long tail distribution concept where, okay, you can get the meat of what you want in the head of the tail and distribution, but out into the long tail is all these skew data points that were once skew standard off the standard deviation that are now doorway. So, you know, we're old enough to know that that movie with Jodie foster with contact where they, they find that little white space, they open it up and there's a, a huge puzzle. That's the kind of things that's happening right now. So exactly >>the same thing. Well, yes, yes. I mean, you know, the thing is, uh, you know, a lot of people don't necessarily have the information that they need. So they're seeking it, you know, when they're going to what Avenue, where, where do I go to get this data? You know, and thanks to open source and things like that. You, you know, we've been able to get more information and bring it together than we've ever been able to do before. And I think people now are more open to analysis where it's not necessarily a dirty word. It doesn't necessarily mean you have to go out and spend $300,000 a year to hire a data scientist. You can sit down, you know, and look at what you have and uh, someone else mentioned that. Take the people that you have that know what's going on with your company. You know, they may not be data scientists, they may not be analytical, but they have insights they have. >>There's more of a cultural issue now around playing with data and an experimental sandbox way where you don't need to have the upfront prove the case. And then pre prefabricated systems you can say, I'm going to do some stuff in jest, for instance, bringing in data sources and play with the data. >>Well, and you mentioned, you know, outliners I mean everything when, when you look graphically at data, you expect everything to fall within this little bubble, this, you know, this thing. But when you see, you know, all these outliners going on for me, usually that means a mistake. Okay. So, and if it's not a mistake, it's something that calls attention. So it's definitely not something you just want to toss aside >>talking about creativity because creativity now becomes, you know, uh, uh, an aspect of the job where you gotta be creative, where it's not just being the math geek or being super analytical and you have to kind of think outside the box or outside the query, if you will, to do the exploration. What's the role of creativity in the new model? >>Well before, I think that we always thought of ourself as just being, you know, matter of fact, you know, just the facts please, you know, but now, you know, you can look at things visually and see, you know, and it is an art form to be able to find that sweet spot in the data. And um, you know, before, you know, years and years and years ago when you would take something like that to a CEO, he would say it was messy, you know, so now you get that creative side where you can actually make things visually attractive. And I think that's important to people too because it's not just data, it's the way you present it. >>It's also the mindset of understanding MSCI is a good start, start with messy and then versus getting the perfect answer. As we were saying, using it with pop-up Jana earlier about, don't try it at the home run right away. Hit a few singles. He's in the baseball metaphor given the world series going on. So totally awesome. Um, but I want to get your final thoughts as we wrap up the segment here on the practitioners out there. What's, what should they do? So there's an approach to the job now, right? So there is a shift and inflection point happening at the same time. What advice would you give to folks out there who say, Oh, I love Carla's interview. I want to do that. I just don't know where to start, what to do. How do I convince management I want to be, I want to get going. What do you, what would you share for advice? >>Well, I'm sure it's the platform. I mean, you know, think about the foundation of a house. Now if you have a strong data foundation, you can build on that. It's just like your house. If you have a weak foundation, your house is going to tumble down. So if you have a strong, you have a strong foundation or with your data and everything is built right now. When I say built right means, what are you trying to do? What are you trying to accomplish? You know, if it's risk, then you need to be, you know, looking at those, those factors. You know, how many people have been hurt? How many of you people been injured? You know, how many people died? You know, I mean, how many breaches do we have? You know, so it starts with the question, what is it that you're trying to accomplish? And then you go from there and collect the right variables. So don't wait, you know, a year later and call a data scientist and going, I've spent, you know, millions of dollars on this. I'm still not getting what I want. So think about an initially in the setup and you know, be involved, involved your analyst, involve your data scientists, make sure that they're in your business meetings because we're the liaisons between it and the Csuite. >>Yeah, and that's the key roles team as a team, that person really is collaborative. We heard from a med earlier pair programming pair, not pay eggs in an accent, pair programming, work in pairs, buddy system. This is really a true team effort. >>Well, I always said, you know, I am a team of data. Scientists can write programs, we can glean insight, but the team part has to come from working with it and working with your C suite. So very much agree. It's definitely a team sport. >>Carla Gentry, owner and data science analytical solutions influencer here at the IBM special presentation and second experience, second screen here in the social media lounge. Really doing a real innovative social business. Again, activated audience, you're an influencer, but also you're really a subject matter expert. Thanks for coming on the cube. Really appreciate and thanks for hosting the crowd. Chat with Brian Fonzo is really good content now. This is the cube. We are live here in Las Vegas. Extracting the ceiling from the noise, getting the data and sharing it with you. I'm John Frey with Dave a lot there. We'll be right back after this short break.