 From Las Vegas, it's theCUBE. Covering InterConnect 2017, brought to you by IBM. Okay, welcome back everyone here live in Las Vegas for IBM InterConnect 2017. This is Silicon Angles, theCUBE's coverage, three days. A lot of great interviews more in day two here. I'm John Furrier with my co-host Dave Vellante. Our next guest is Tanya CJ, founder and CEO of Arenda Software Solutions. Welcome to theCUBE. Thank you so much. So your company does a lot of cool things with data. One of the things, obviously in the news, you can't read a story these days without hearing something about Trump, Uber, bad behavior, fake news. There's always scandalous, it's the internet for crying out loud, everything's going on. But reputation now is measurable. And data is out there and companies now, as they go on to digital as a medium and to end for marketing and engaging customers, they got to be careful. What's your take, how does this, what's going on in this marketplace? There's a couple of things that are happening simultaneously. One is, we talked about this just briefly, the Edelman Trust Barometer. It's a global survey that's done every year. And it started, I believe, in 2010. In 2017, the findings were that we are in a trust crisis globally. And you would have heard that from Mark with Salesforce today. That's what he was referencing. At the same time, PricewaterhouseCoopers came out with another survey across North America. And it was that we are in the midst of a trust economy and trust is growing. So at one point we used to make our buying decisions on whether or not a product was convenient or a good sale price, those kinds of things. Now we want to know whether or not we trust the brand, whether or not we trust the CEO, and whether or not the companies have purpose. So our buying decisions are changing. So not only are we in the trust crisis, but we are also the trust economy. So measuring trust is exceptionally important and of value to all brands globally. This purpose thing is interesting. We've been seeing the same thing just at South by Southwest Intel. We were headlining an Intel AI lounge and they had this program, AI for Social Good. It's got a great program. It's on our YouTube channel, youtube.com, so it's still going to angle folks out watching. But there's a counterculture going on right now. We're seeing in the world. The younger audiences coming in, the new generation, the digital natives, they're living in a digital world 100%. So it seems to be a counterculture of anti what it was pre now, internet what it was before, trolling all this stuff could have been out for a while. But you're starting to see people really focus in on good and mission purpose. There's an element where there's a new generation saying we want to apply tech for good. And you're seeing it with equality. They mentioned a lot of things on the stage today, but beyond that, it's kind of this post 9-11 generation where like, hey, what are you, all you old people, just do social good. I mean, do you see that too? We're seeing a lot of it across the board. Can you share any stories in this area? Yeah, social good is really important in terms of giving back to your community. And in the communities where you do business, you want to have that connection. So when we were creating Aurendra, the software that measures trust, it also measures a few other things. We went back into about 30 years of research in social science and selected sick that there's six key factors to a healthy relationship. And what we were calling corporate social responsibility is now just more or less social good. So you want to do things that are good to the communities that you do business in. And there's also the exchange of benefits, you know, I do something for you, you do something for me, which brings in the more collaborative systems and partnership ecosystem. It's a community model too. We've been open to open source growing, connected internet, everyone's connected to each other. That's a community framework. That's right. And that's kind of the, seems to be the trend. It is a trend. And, you know, at one point, companies used to market to their customers. Now you see something quite different. Customers are empowered and they're engaging through content. So the exchange is continuous. One of the examples we have is with Apple. So every time your heart beats, someone is talking about Apple, right? It is so huge. The velocity, you mean the velocity? Yeah, just the velocity. There's so much of information coming out. We were following 25 different companies in December and we pulled in 5 million data points. So that's the amount of information that is coming at us and brands at any particular time. What we needed to do was turn that into insights in real time. If not, it's useless. It's interesting you mentioned Apple. So we have a data science group within SiliconANGLE theCUBE. We call it our cognitive beta program. We haven't released it yet. But we're looking at all the Twitter data and we can actually see all the tweets and then we can extrapolate the users. And obviously we get all the data which phone they're using, tweeting from. And that came out, you saw Trump was on Android and iPhone. And here at this show, based on the data that we have, 76% of this audience here and online is iPhone. Nice. Over Android. So you say, okay, big deal, ho hum. Actually, demographically it matters. Now some shows, the more geeky shows, you'll see Android over iPhone. Right. So it's a small little data point, but you can almost, like that movie, contact where you open up one door and you can get all this different insights. So a small data point like that could add to other data. It could. And it's unlocking it, like you said, that is the most important part. Like you can get all this data, you can get it continuously, but unlocking it and telling everybody what it means to them. And it could mean something different depending on what kind of solution or problem that you're trying to overcome. Yeah, and then the concepts we follow a lot of the big data world is data at rest and data in motion. And Dave and I were just at breakfast this morning talking about content in motion, brands in motion. So your company really is measuring the brand in motion. That's right. So this is kind of a cool new cutting edge coolness. It's really cool. Thank you. Explain what's going on there. What's the cutting edge tech? What are some stories? Good bad and the ugly, what's? One of the interesting things that we just did is we were following five of the biggest banks in Canada. And at the same time, CBC, which is the national broadcasting company, did this go public article and it was extremely negative. And we were tracking them. So we were able to show in real time the trust levels dropping and then correlation to that. We looked at the stock prices of those companies and they were also dropping. So to be able to demonstrate that the brand itself, the reputation, particularly trust was what the issue was and that makes a lot of sense. It's money, it's banks, it's trust. That's what's going to be impacted the most. But being able to correlate that is a piece of information that we haven't been able to use before. So that's insight. So now the actionable insight is, wow, we should send someone in there digitally, parachute into the virtual news cycle and provide content or perspective. You know what I'm saying, they can get in and stop the bleeding. Get in and stop the bleeding. And the other thing is that there were five national banks, but only one of them was taking the hit for it. They were the actual face of the issue. So to be able to say, we're all being hit by this particular news story, yes, but you're being hit the most. It's a classic public relations problem. They don't react and it gets settled in, it becomes a matter of fact. Yeah, so you need to be able to deal with that escalation in real time. So what do you guys do that's different than a lot of sentiment analysis and it's kind of an overcrowded space? It's a busy space, yeah. What's unique in what you guys? What's unique is the actual social science on top of that. So there is positive, negative, which gives you a little bit of information. What we did is just put on a whole other filter and we use social science to do that. So in order to show the brand momentum that needs to exist for a more resilient company, we said we need to know whether or not trust is increasing or decreasing commitment with the brand or loyalty to the brand is increasing or decreasing. This is really important information. Positive, negative just doesn't tell you enough. So when you are doing your messaging for a public relations point, you know to talk about integrity if there's a trust issue that you're dealing with. If it's satisfaction, then it's something that you wanna do better in terms of a particular product. So you get to focus on what the actual problem is. So that's how we're absolutely unique is that we're able to measure emotion in a very different way through social science and key factors that need to exist for a healthy brand. And the secret sauce behind the tech is what? Is it some cognitive, it's data science? We do a couple of things. So one of the reasons why we partnered with IBM and are using Watson, the APIs is that we built our own algorithms and we have it interact with a huge dictionary of words that we use. And we had to be able to customize that because the way we use language is always different. The way we talk about oil and gas is different than we would talk about Coca-Cola say. So we had to be able to customize the dictionary so that if we use the word recall with a car manufacturer, that's extremely negative. But recall within the healthcare system is probably neutral, right? So we had to be able to make those differences. So then we also use AI, we use the personality insights tool within Watson so we can take a whole customer buying group, look at them as an individual's huge amounts of data, millions and millions of data points and say this is what this particular customer group or stakeholder group, this is what they need as a group. This is what they value. These are the key personalities. So again, you just get that deeper insight into who's buying your product. And the data sources talk about where the data comes from? The data comes from social media and why that's really important is because within public relations and communications, there's always been focus groups, right? We try to pull out insights into our brand from focus groups, surveys. Weeks and weeks of research. Weeks and weeks of research. And you still have just a certain amount of data that you get to deal with. This, we treat social media as a huge focus group with tremendous amounts of data, tremendous amounts of insights and we can pull it out in real time. So if there's an issue that is escalating, we can say this is what your customer base is saying about you. This is how the impact is. We don't have to go through months of research to deal with an issue we need to deal with within 10 minutes usually. So Twitter's obviously a huge source of data. Is that correct? It's huge. Because it's so real time and there's so much of it. What other sources? I mean, is that the primary or a primary source? Facebook is interesting. You can get public information but you can't get private. Right. Instagram is another. Blogs are a great source of information as well. Almost any online information where there's engagement. So there's a conversation that's taking place. If it's static, it doesn't really have an impact on you. Is there a third party data sources that you use that other people use as well? Is it like the Twitter fire hose? Is it RSS feeds? I mean, is there like a syndicate of data sources? Yeah, we use Gidip. So that's all by Twitter. Yeah, that's what we use. For blogs, how do they get the blogs? Do you scrape them? So you scrape them? So RSS feeds? Yeah, and I really enjoy the fact that a lot of governments are going into open source data. So the more we get, the better it is. We have a couple of relationships, partnerships with national media sources as well. So we're able to use that and go back into time, thankfully, for their- Tell me, what's the coolest or weirdest discovery you've made with the data? Because as you get all this gesture data, I'm sure there's some things that have just, whoa! One of the funnest for me, I'm a bit of a political nerd, and so I really, really enjoy politics. And when we were building out a render, we used the federal election in Canada. And yes, we did do some with the US election too, but it was so much data. It was tsunami. Yeah, thanks a lot, Trump. It's not stopping, by the way, either. It's continuing to go on. Yeah, the funniest one with that one just as a side was the whole, would you rather have Trump or a monastic as president, which was really gained popularity. But for the federal election, what we did was follow the four federal candidates. And we were able to show when we stopped, as a nation, talking about Thomas Mulcaris, the next leader. And when we started talking about Justin Trudeau, and we were able to predict that Justin Trudeau's brand was building momentum weeks before the polls came out and said that they were, that, you know, that the- Seriously changed. All right. Well, Tanya, thanks so much for coming on theCUBE. Really appreciate it. I love what you guys do. I think that's, you're on the cutting edge of really compelling social science. And as the culture deals with autonomous driving cars and smart cities, I think this is going to be an ongoing field of study, of understanding the relationship between data and humans with respect to societal changes. So again, this is, I think, one small use case of really exploding areas. So thanks for sharing. It's theCUBE here live in Las Vegas for more interconnect coverage. After this short break, I'm John Furrier with Dave Vellante. We'll be right back. 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