>> 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. With Jeff Frick. Our next guest is Jeff Allen, Senior Director Product Marketing, Adobe. Jeff, welcome to theCUBE, thanks for joining us. >> Thank you. Nice to be here. >> So day one is kind of winding down, big, great keynote, laid out the platform product's working together, lot of data, lots of data conversations. >> Yeah, exciting day. Excited to have Adobe Analytics in the mix with that, 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 whole new grail, people have been trying to do for how many years? >> Forever, from the beginning. >> And it's always been that holy grail, where is it? Now some visibility is starting to get to see into the benefits of horizontal scale, diverse data, contextual workloads, >> Absolutely, yeah. >> This is a big deal. >> It is a big deal. >> Explain why it's impacting. >> It's funny. Our culture now expects data right? We measure everything. Our kids are taught to measure things, even 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, 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 at MetLife >> Interesting, yeah. >> But this brings the question of, of the confluence of you know, the 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. >> Absolutely. >> This is really the fundamental thing. >> I started my career marketing to CIOs, in fact, I've spent most of my career marketing to the CIO organization, right, and about 7 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 how the tech explosion has happened in MarTech and AdTech, all of 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 is 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 does that change kind of the way that you look at data, the way customers are looking at data, you know, how the KPIs are changing, and what they're measuring, and the value of the different buckets of data as it's no longer about getting to that transaction, boom, ship the product, and we're done. >> 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, 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 measurements 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 where we sit today, is really helping organizations measure experiences, and that spans every person in the organization. >> 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've got operational databases and analytical databases," you know, and that was it. You know, relational, unstructured, you know, kind of quadrants. Now, it's kind of, you have (laughs) it's not about databases, it's about data. So you have operational data, which is the analytical data now >> Yeah. >> So you have now, this new dynamic, it's not about the databases anymore >> Absolutely. >> It's about the data itself. >> It's not about, I would say, it's not about the stores of data, right? It's about really getting the insights out of the data, and you know, for the longest time, in my career, uh, 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 main frame, they could go to these big IT systems, and you know, in 30 days, they could email you back a .csv file, or even before that meeting, give you a .zip file or something with 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. >> And then you go get your root canal right after. It's a painful process. >> What if the data - today that data is trying to understand, "Hey I got a guy that just checked into the hotel. He's standing in front of me, I need to know if he had a bad experience the 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 I.T. real quick and ask them to take 30 days to get that data and then crunch the data all to find out. Customers need to know, and in the 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 what the experience business wants out of data. >> 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, you know, if you want the flow, this is a key part of probably your side of the business. Can you comment, what's your reaction to that - streaming trend? >> We've been talking about streaming for a while. CIO, this isn't a new thing, we were streaming applications, right, 10 years ago, 15 years ago, but really in the story I just shared, right? The 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 that 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 be, is to be, is to come 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, right? Everyone does desktop publishing, that is how data is too. Everyone's got to be comfortable with data, they have to be conversing around data, and everyone needs access to data. So, that's, you know, that's what is happening in our industry, the analytics industry, is that we're democratizing that data, and getting it everybody's hands, but it's not enough to 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, as it's not part of your - 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 you know, Adobe, using their own products, eating your own dog food, drinking your own champagne, whatever analogy (laughs) 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 at this company is running their business off of these dashboards, that's got to be pretty, pretty, uh, profound for a guy like you who is helping feed those things. >> It's cool. I like to talk about what I call the modern measurement team. The modern measurement team is no longer that centralized data team, right, or that centralized BI team, but every single function, right, under CIO. Every one of the CEO's directs, has their own data team. You go look around and you see that in every single function, there is 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, is trying to inform every decision anybody makes. >> And that's where machine learning really shines. You get high quality data on the front end, with the semantic data pipeline capability, get that into the machine learning, help advance, automate, that seems to be the trend. >> Yeah. Yeah, 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 thing is happening with AI and ML, is we're able to predict things with good statistical modeling, with pretty strong, uh, reliability around those models. >> The keynote had great content, I liked how you guys did a lot things really well, you had the architectural slides, platform was a home run, how you guys evolved as a business, see you laid that out nicely, but one of the things I liked, not that obvious, unless you go to a lot of events like we do, everyone says "The journey of the customer", I mean, it's a, it's become a cliche, you guys actually mapped specific things to the journey piece that fit directly into the Adobe set of products and technologies, and the platform. It's interesting, so the word journey has become, actually something you can look at, see some product, see some - a pathway to get some value. >> There's definitely a risk if the word journey, becomes like "Big Data" and all these cliche terms, you know, that means everything, so 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 to data analytics. >> All the hype markets, cloud washing, until Amazon shows them how it's done, everyone else kind of follows, 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 to explain? >> So we have a couple of things. We have something called Segment IQ, Attribution IQ, and now we have even introduced Journey IQ. And when you see that IQ moniker on one of our, 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 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 that's specifically around the customer journey. >> So the IQ is a marker that you guys use to indicate some extra intelligence coming out of the Adobe, from the platform. >> Yeah, yeah, if 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 at Adobe Analytics is 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? 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 one and 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 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 9 times out of 10, if you have the right data, and people are using the data to make decisions, they are 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, could be hearsay. >> Or you 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 have to look back into the engineering organization, and look out to the customers, so you're, 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? Generally, their orientation towards data? Where are they on the progress bar? What is the state of the market on the landscape of the customer, what patterns are you seeing? >> Good question. So there's a lot of - there's a lot of, um, 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, um, 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. >> So they might think it was successful. >> 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, basically. >> It's those dark spots that customers are really needing. >> So getting access to more diverse data, gives you better visibility into what's happening contextually, to open up those blind spots. >> Exactly. Yup. It's just that, adding resolution to a photo. >> Love this conversation, obviously we're data-driven as well on theCUBE, we're sharing the data out there. This interview is 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 from Adobe Summit? >> We're just a day in, there a lot, 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 are going to be optimizing the experience for your customers, and what's really amazing is how many customers are here, telling their stories. That's the thing, I wish everybody in your audience could experience by coming here, because there is 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. >> Some of the best marketing, you let the customers do the talking, and they're doing innovative things. They're not just your standard, typical, testimonials, they're actually doing - I mean, Best Buy, what a great example that was. >> Cool brand - we work with some of the coolest brands in the world, so, fascinating, brilliant people. >> Marketing, at scale, with data. Good job, Jeff, thanks for coming on, appreciate it. >> Thank you. >> Jeff Allen, here inside theCUBE with Adobe. I'm John Furrier with Jeff Frick. Stay with us for more Day 1 coverage after this short break. Stay with us.