 Live from Las Vegas, it's theCUBE, covering Adobe Summit 2019, brought to you by Adobe. Welcome back everyone, live CUBE coverage here in Las Vegas for Adobe Summit 2019. I'm John Furrier, Jeff Frick, our next guest is Jeff Allen, Senior Director, Product Marketing at Adobe. Jeff, welcome to theCUBE. Thank you for joining us. Nice to be here. So day one's kind of winding down, big great keynote, laid out the platform, products working together, a lot of data, a lot of data conversations. Yeah, exciting day. Excited to have Adobe Analytics in the mix with that, right? You saw the four clouds we talked about, Analytics Cloud is one of them, and really kind of core to everything we do at Adobe, right? In fact, even in the creative cloud side, document cloud side, our customers have to be able to measure what they're doing, and so data is obviously key to that. Tapping the data across the different applications and now clouds, it's interesting, it's a holy grail. This is what people have been trying to do for, how many years? Decade from the beginning. And it's always been that holy grail. Where is it? Now some visibility is starting to get the seeing into the benefits of horizontal scale, diverse data, contextual workloads, taking advantage of the scale. This is a big deal. It is a big deal. It's funny, our culture now expects data, right? We measure everything, right? Our kids are taught to measure things, even if something as simple as likes on, my kids, they argue about whether the picture mom posted of them or the other one got more likes, right? So we kind of have hardwired our society around measurement, and now, of course, marketing has always been a measurement-heavy discipline, and so it's just absolutely core to what we're doing. And we had a historic moment. We've been doing theCUBE, it's our 10th season, and we're going on a lot of events. Congratulations. And we had a guest come on here that we've never had before. The title was Marketing CIO, it was one of your customers that I met in life. But this brings the question of the confluence of the de-factions coming together, IT, creative, marketing, where the tech measurement, data. Yeah, totally. Data processing, information systems, kind of an IT concept now being driven and married in with the business side. This is really the fundamental thing. I started my career marketing the CIOs. In fact, spent most of my career marketing to the CIO organization, right? And about seven years ago, I came over to Adobe to market to marketing, right? And I used to say, you know, I kind of like marketing to this guy. I understand him better, right? Because I know how marketers think a lot better than CIOs. I had to go learn how they thought. But it's amazing the tech explosion that's happened in MarTech and AdTech, all these vendors here at this event. This is just a piece of our industry, right? There's thousands of companies serving marketing organizations, and so all of a sudden, the tech stack looks more crazy than even what many CIOs manage. And so it doesn't surprise me at all that organizations, you're talking to organizations that have a CIO, CMO, hybrid role. Jeff, I'm curious how the landscape's changing because all the talk here is about experiences, right? And the transaction is part of the experience, but it's not the end game. In fact, it's just a marker on a journey that hopefully lasts a long time. How has that changed kind of the way that you look at data, the way customers are looking at data, how the KPIs are changing and what they're measuring and the value of the different buckets of data as it's no longer just about getting that transaction, boom, ship their product and we're done. Yeah, yeah, so I look after Adobe Analytics. And Adobe Analytics was the first component we acquired in this business, right? Experience Cloud started with the acquisition of a company called Omniture back in 2009. It was an analytics company, primarily web and mobile app analytics. And it has grown since then to measure many more things. And we've seen our category with analytics that we've addressed. Move from web analytics to a broader view of digital analytics, right? The digital parts of marketing to all of marketing. The rest of marketing said, hey, we need measurement too. We need tools. And then it clicked out another broader click to this idea of experience, right? Because everybody has a stake in experience and experience is all wrapped around people and how people move through experiences with your brand. So that's kind of where we sit today is really helping organizations measure experiences and that spends every person in the organization. Talk about Jeff, talk about the dynamic between how the old way of thinking was shifting to this new way. And specifically the old way was, I'm a database guy. I got operational databases and analytical databases. And that was a relational unstructured kind of quadrants. Now it's kind of, it's not about databases, but data. So you have operational data, which is the analytical data now. So you have now new dynamic. It's not about the databases anymore. It's about the data itself. I would say it's not about the stores of data, right? It's about really getting the insights out of the data. And for the longest time in my career, you went to CIO, the CIO organization, and there was a BI team there. And you would ask them for data and they could go to the mainframe. They could go to these big IT systems. And in 30 days, they could email you back a CSV file or even before that, maybe they give you a zip drive or something, right? The CSV file on it. And then you got to go see if you could even get it to open on your laptop and get it into Excel and start to manipulate it. And those days don't work, right? And then you go get your root canal right after. Painful process. Today that data is trying to understand, hey, I got a guy who just checked in to the hotel. He's standing in front of me. I need to know if he had a bad experience last time he checked in with us. So I know if I need to give him an upgrade. And you can't go down to IT real quick, and ask him to take 30 days to get that data and then crunch the data, all to find out. Customers need to know in an experience business, immediately this person just walked into the hotel and we need to give them a good experience. We blew it last time for them. That's the experience business. You know, one of the questions we had with Anjul who runs engineering on the platform side was around the rise of prominence of streaming data. How is that impacting the analytics piece? Because if you want the flow, this is a key part of probably your bit side of the business. Can you comment and have a, what's your reaction to? We've been talking about streaming for a while, right? CIO, this isn't a new thing. We were streaming applications 10 years ago, 15 years ago. But really in the story I just shared, that idea of going down and waiting in this asynchronous process with data, the experience business can't handle that. So streaming data is really implying that as it's coming in, we're processing it and learning from it and getting that out into the systems and the people who can take action instantaneously. Talk about the dynamic that customers have around traditional silos within their organization. You know, that guy runs the database and data for that department. That person runs the data over there. And if this vision is to become true, you have to address all the data. You got to know what's out there. You got to have data about the data. You got to know in real time. And these are important concepts. How does a company get through that struggle to break down those kind of existing organizational structures? It's a cultural shift. I mean, who has a desktop publishing team anymore in their organization? Everyone does desktop publishing. That's how data is too. Everyone's got to be comfortable with data. They've got to be conversing around data and everyone needs access to data. So that's what's happening in our industry and the analytics industry is we're democratizing that data and getting it into everybody's hands. But it's not enough to just give them charts and graphs. They have to be able to manipulate that and make it apply to their part of the business so they can make a decision and go. And so that shift in how people think about data it's part of everyone's job as opposed to being a specialized siloed job. I'm just curious to get your take. A lot of conversations here about Adobe using their own products. Eating your own dog food, drinking your own champagne whatever now you like to use. And when you see the DDOM, right? The Data Driven Operating Model. On the screen in the keynote with the CEO and he says basically everyone in this company is now running their business off these dashboards. That's got to be pretty profound for a guy like you who's helping feed those things. It's cool, yeah. And so I like to talk about what I call the modern measurement team, right? And the modern measurement team is no longer that centralized data team, right? Or that centralized BI team. But every single function under CIO every one of the CEOs directs has their own data team. You go look around and you see that in every single function there's a sophisticated data team. They have the best tools in the industry. They have the smartest people they can find. They have PhDs on staff. And that's not enough. So these teams now have to get that out to every constituent in their organization. And that's what we're trying to do at Adobe. That's what we're seeing our best customers do as well. It's trying to inform every decision anybody makes. And that's when machine learning really shines. It is. You got high quality data on the front end with the semantic data pipeline and capability. Get that into the machine learning, help advance, automate. That seems to be the trend. Yeah, yeah, I mean, look the insights that you can get from the data, the ability to predict with rich data. It sounds, prediction sounds like invention used to sound like this novel thing, right? And then you realize we're inventing things all the time. That's not so, that's just creativity. Well, the same things happening with AI and ML is we're able to predict things with good statistical modeling with pretty strong reliability around those models. So- You know, the keynote had great content. I like how you guys did a lot of things really well. The architectural slides, platforms, the home run, how you guys evolved as a business CEO, laid that out nicely. But one of the things I liked was not that obvious and let you go to a lot of events like we do. Everyone says the journey of the customer. I mean, it's a cliche. It's become a cliche. You guys actually map specific things to the journey piece that fit directly into the Adobe set of product and technology in the platform. It was interesting. So the word journey has become like actually something you can actually look at, see some product, see some pathway to get some value. There's definitely risk that the word journey becomes like big data and all these other cliche terms, you know, that means everything. So it becomes, it comes to mean nothing. But for us journey and as marketers especially, journey is just naturally understanding. Where did I interact with this person? And what did that lead to along the way, right? And so customer journey is absolutely core of the way analytics. All the hype markets say we're cloud washing until Amazon showed them how it done and then the rest, everyone now kind of follow sweet. You guys are doing it here with journey. One of the things that came out was a journey IQ. I didn't really catch that. Can you take a minute and explain what this is? So we have a couple of things. We have something called segment IQ, attribution IQ, and now we've introduced journey IQ. And when you see that IQ moniker on one of kind of our super umbrella features, that means that we're applying AI and ML, right? And Sensei is involved. So we're using powerful data techniques and then we're also wrapping it with a really simple user experience. So journey IQ starts to break down the customer journey in terms that a normal person without a PhD, without knowing statistical methods or advanced mathematics can leverage those techniques to get really powerful insights. And this is specifically around the customer journey. So the IQ is a mark that you guys use as just indicate there's some extra intelligence coming out of the Adobe platform. We're going to democratize data, right? We have to democratize data science as well, right? And so a big part of what we're doing in Adobe Analytics, it's really simplifying the user experience, right? So I don't say, do you want to run a regression model against this to answer your question? We just say, click this button to analyze, right? And so it's a simple user experience behind the scenes. We can run these powerful models for the customer and give them back valuable insights. So journey IQ is specifically taking things like cohorts and introducing cohort analysis into the experience, making it simple to do powerful things with cohorts. What's the pitch to a customer when you go to and then talk about all this complicated tech and kind of new operationalized business models around the way you guys are rolling it out when they just want to ask you, hey Jeff, I care about customer experiences. So bottom line me, what's the pitch? How can you possibly address your customer's needs if you don't know what they think, right? What do they need? So at the end of the day, the great thing about working with customers like most businesses do is customers are happy to tell you where you're getting it right and where you're getting it wrong, right? And that's all over the data. So all you have to do is develop a culture of using data to make decisions and nine times out of 10, if you got the right data, people are using the data to make decisions, they're going to make the right calls and get it right for your customer. And when they don't, they're using opinions and they're going to get it wrong all the time. Or bad data, it could be hearsay. Or course correct, or that wasn't, you know, make an adjustment, right? Again, based on the data. Exactly, yeah. You're in product marketing, which is a unique position because you got to look back into the engineering organizations and look out to the customers. You're in a unique position. What's the customer trend look like right now? What are some of the things you're hearing from the market basket of customers that you talk to? Just generally their orientation towards data, where are they on the progress part? What's some of the state of the market on the landscape of the customers? What patterns are you seeing? Good question. There's a lot of anxiety around where do I have pockets of data that I'm not able to leverage? And how do I bring that together? So when we tell a platform story like you heard us tell today, customers are really excited about that because they know, they've known forever. I mean, this isn't a new problem. Like data silos have been around as long as data has. So the idea of being able to bring this data into a central place and do powerful things with it, that's a big point of stress for our customers. And they know like, hey, I have dark spots in my customer experience that I lose the customer. For example, if I'm heavily oriented around digital, let's say I'm a retailer and I see a customer, I acquire them through advertising channels. They come through an experience on my website and they buy the product, success. I ship the product to them and then they return it in the retail store. The digital team might not see that return. They think they were successful. So they think it was successful. So what do they do? They go take more money and spend it in the ad channel where that person originated. When in reality, if they could look at the data over time and incorporate this other channel data of in-store returns, the picture might look very different. So basically, it's those dark spots that customers are really- So getting more access to diverse data gives you better visibility into what's happened contextually to open up those blind spots. Exactly. Yep, it's just adding resolution to a photo. Love this conversation. We're obviously data driven as well on theCUBE. We're sharing the data out there, this interview's data as well. Fantastic. Jeff, final question for you. For the folks that couldn't make it here, what's the, how would you summarize the show this year? What's the vibe? What's the top story here? What's the big story that needs to be told? Yeah, good question. We're just a day in. There's a lot to do still, right? We still have two more solid days of this show. But you know the big themes are going to be around data. They're going to be about optimizing the experience for your customers. And what's really amazing is how many customers are here telling their stories. The thing I wish everybody in your audience could experience by coming here is there's 300 breakout sessions that feature our customers talking. All of our sessions on main stage, we bring customers out and we learn from them. That's the best part of my job is seeing how customers do that. It's also the best marketing. You let the customers do the talking and they're doing innovative things. Yes. They're not just your standard, typical testimonials. They're actually doing, you know, I mean Best Buy, what a great example that was. Yeah, what a cool brand. We work with some of the coolest brands in the world, so fascinating, brilliant people. Marketing, at scale, with data. Yep, good job. Jeff, thanks for coming on for your game. Thank you. All right, Jeff Allen here inside the Cube with Adobe. I'm John Furrier with Jeff Frick. Stay with us for more day one coverage after this short break. Stay with us.