Inside Analysis

Business Optimization for the Data-driven Reality

Eric: Ladies and gentlemen, hello and welcome back once again to Inside Analysis. My name is Eric Kavanagh, I’ll be your host for today’s conversation with David Thompson, chief marketing officer for a company called Domo. Folks, I got to tell you, we’re going to have a good talk today. I just chatted with him briefly. We had some interesting background, some shared experiences and we’re both big lovers of data and of marketing, so Dave, welcome to Inside Analysis.

Dave: Welcome, and not to mention red wine in Italy, but we won’t go there.

Eric: You’ve tipped my hand, you’ve tipped my hand. I’m going to keep focused, nonetheless, but yes I’m calling from Rome!

Dave: Oh, I’m so jealous, so jealous.

Eric: This place, talk about a marketing haven, right?

Dave: Yes, yes. For the last 3,000 years.

Eric: These guys knew what they were doing. Seriously, to this day.

Dave: I know, there’s nothing like a Corinthian column to draw you in.

Eric: I love that we’ve got alliteration going already. We just started talking. This is quality content, so yes here in Rome, doing as the Romans do. Of course Romans are very good at articulating things, and Italian is such a beautiful language; and the visual side of things too is just so fascinating and enriching and fun and interesting. You get to have cool conversations and I think that’s actually a really good metaphor to dig into what you guys are doing over at Domo, because the visual side of things is so important, but it needs to be connected to the business.

It needs to be connected to the processes and the workflows and you need to have that complete picture to really understand what’s going on; and when you hear these wonderful Italian people talk about their trials or their tribulations or their success stories, they have such a passion and such a flair for what they love that suddenly you’re just in their world and you’re having the conversation with them, and you understand. You see, then you get it and that’s really what business is all about and that’s really what tools like Domo can help companies achieve because you can tell that visual story and you can get right to the point with people who are working with you, either as collaborators or as employees or as directors or whatever the case may be. I’ve given this perspective on where I see you guys coming from but you tell me if I’m wrong. What do you think?

Dave: Well, going with the Rome metaphor for a second here, Eric, so obviously the conversations and the clarity that you reach, walking the streets of Rome in the cafe’s with coffee, that’s all great, but you stare down at the Tiber, the river, running through Rome and it’s flowing really fast. It’s kind of murky and I kind of see that as the data problem that the marketers face every day. With over 3,500 possible cloud systems they could choose from to generate data about the customers, understand what they’re doing in social media, how they’re responding to ads and then tying that all back together with, “How do we make money out of all that?” That becomes like a very murky river.

Getting clarity around marketing data, getting transparency and most importantly being able to tie it all together to business outcomes is what we like to talk about at Domo. What we really focus on with our business cloud platform can make it super-easy to cross-correlate whatever your source of clicks and interaction is, and response on your website, or your other digital properties, your apps — to actually turn it into revenue, and understand that dynamic and clarify that murky river of data.

Eric: That’s a really interesting set of comments you just made there and as I’m thinking about this, to turn the topic in my mind, brings in another language, another country, the lingua franca. I think that what you’re describing is, it’s almost like you’re offering this Rosetta Stone to help marketers bring together the concepts and the ideas and the business reality from the many different possibilities out there because it’s like a tower of Babel these days, right?

Dave: Totally, and the thing that is the number one priority of most digital marketers and marketers in general today is to be able to prove revenue impact and revenue ROI from the spend. In today’s data-driven world, there’s theoretically no excuse for that because everything is being followed by a cookie, everything is being tracked by a cookie. I like that they don’t lose track of your cookies. For heaven’s sake, that’s like the first piece of the recipe, but then it’s not enough just to eat your cookies, you also have to be able to understand the ingredients of those cookies and be able to mix it with the broader meal of the business which is, “I’m spending in order to produce revenue whether I’m a B2C marketer or I’m a B2B marketer.”

Here we are at Salesforce this week at Dreamforce with Salesforce and we’re talking about, “How do I take all this river of digital data that I have sending traffic to my website or my app or whatever it is and correlate that to actual deals?” Breaking down those silos between these different streams of data that track your customer are the ingredients, the cookies, that you need to create a profile of the customer you’re going after and then understand, “Okay. Well, these 3 touch points or these 30 touch points actually produced this deal and this ongoing customer relationship,” and that all sounds really hard, but that’s what we striven at Domo to make really easy, to make it easy to pull that data together, break down the silos, and understand something as important as revenue impact of your digital spend.

Eric: Yeah, that’s fantastic stuff because I’m actually a digital marketer at heart. I’ve been doing this stuff for, well in terms of email marketing, tracked email marketing, I’ve been doing that now, I’m afraid to admit, for 16 years, since 2000 because a guy that I did some work with actually built out a email marketing platform back in 1999 that I started using in 2000. Of course, if you look at iContact and ConstantContact, most of these companies came out like around 2007, 8, 9, 10, 11, etc. They all have their own proprietary way, their proprietary data model, their proprietary … Well, those who have APIs, that’s all coming around now, but the challenge for the marketer is as you have suggested, how do you reconcile and essentially normalize all that data to be able to capture all the detail and not strip out the context?

Dave: Correct.

Eric: You don’t want to lose the context these days. How do you normalize all that and reconcile it and deliver it in a fashion where a business person can look at some visualization and then drill down fairly quickly to get some details and within minutes, have a very deep understanding, a contextual awareness, about what has happened and how it happened, and then be able to translate that into action for a company? It seems to me like that’s what you guys have done better than most, if not all.

Dave: Absolutely. I could not have articulated the vision and now the reality of Domo and our platform that we call the business cloud better than what you just said. What I would just add to that is the starry reality for most marketers today is they’re kind of stuck in various forms of data hell. One level of hell is expressed by manual downloads of multiple sources of data into a Excel and then trying to pivot your way through rows and rows, hundreds of thousands of rows of Facebook data, LinkedIn data, Pinterest data, point of sales data, you name it, it just becomes a nightmare to try to do all that kind of locally on your PC or your Mac in Excel. That’s one form of hell.

Another form of hell is if you’re in a bigger company, the big enterprise version of what I just described is all of that data gets put into a data warehouse and you just can’t get to it. Most importantly, if you’re spending a lot of money on digital marketing, actually, I’ll just refer to my last job at, which is where I was working before I came here. I was spending millions of dollars on real estate ads and it would take me a month using things like Hadoop and those types of backend data warehouses to actually see the results in terms of traffic, in terms of conversions, in terms of purchases on the website and by then, it was too late to optimize the spend.

This vision that we have at Domo of being able to see your data in real-time and more importantly act on your data in real-time through the form factor of your choice, whether it’s mobile or desktop or web, to be able to see that data and then optimize your spend toward your goal, that’s the reality of Domo today and that’s kind of what makes our users like, I’ll give you an example, SAB Miller is a big, a brewery, a big producer of beer internationally, and they use Domo to check out what is the effect of their social media spend, both organic and paid media spend, on engagement with their prospective consumers.

With Domo pulling all of the data together in real time in the business cloud and presenting it back out to the marketers, they’ve been able to achieve significant increases in their efficiency.

Eric: Were you consciously or unconsciously channeling Dante there? I’m just curious.

Dave: It’s all coming back to me, Eric. I’m telling you.

Eric: Really, Paradisio Parduto, Paradise Lost!

Dave: Paradisio tutti!

Eric: You’re telling … I’m just having chills thinking about this because I have been to that layer of hell. I have been there and tried and you can do it yourself, man. You can hack out the java code to build yourself a Hadoop platform if you really want to, but do you really want to?

Dave: Why would you want to? Exactly.

Eric: Well, you’re doing your penance. You’re down there in the seventh level, the seventh layer of hell.

Dave: Here’s another interesting perspective on digital marketing. I think that too often when people think data and transparency and trying to work your way through to ROI on digital marketing spend, what they overlook are some of the deeper business issues that can impact revenue. This is where I start getting really excited about customers like Schneider Electric, big manufacturing firm, big Salesforce user. I’m sure they’re here at Dreamforce with us this week and what they were looking at in their data was ways to increase their sales forecasting accuracy and also obviously to increase topline production. What they could do with Domo is not only correlate actual sales data out of Salesforce with marketing data but with other data too.

In other words, if I sell your product A versus product B, which one are you more likely to buy more of in the future and maybe I can accelerate my forecasting accuracy by selling you more product B versus A. Those types of correlations, those types of deep insights from, in this case, product data and finance data and inventory SKU and order data correlated to pipeline data is producing strategic insights into how to drive your sales strategy for any given quarter, and therefore increase the accuracy of your forecast and ultimately increase the output of the sales force by getting them focused on the right types of deals with products the customers really want to buy from you.

Eric: That’s really interesting stuff because what you’re talking about now is being able to navigate the widely heterogeneous nature of information systems in the business world today and the fact that you have these disparate data models and processing engines and all these facets to the modern organization, the modern company, and trying to distill all of that down to some meaningful workflow and meaningful view or perspective of what’s happening in your business, that’s the big challenge, right?

Dave: Yeah, but it’s not just the challenge of breaking down those silos of data but it’s also about once you’ve broken down the silos of data and what’s so cool about what we’re doing with Domo and this whole notion of business optimization is the notion of an A/B test, that comes right out of the digital world. That comes right out of things like Omniture and Optimizely and all of those types of digital marketing platforms that say, “Okay, well did this offer on the website perform better than that offer and let’s make sure we put this content forward more often because it has a better response rate, etc.”

What’s so cool now with companies like Schneider Electric, producing light switches, is you can A/B test your hardware. You can A/B test your inventory sitting in a warehouse somewhere by the insights that you get through data, so in that sense it’s creating a digital revolution throughout the Internet of things and the Internet of everything that you can possibly collect data on.

Eric: Wow, that’s pretty interesting. I kind of walked into this with the marketer’s lens and was trying to figure out where you guys fit in that landscape and I do see it as the Rosetta Stone, as the prism through which you can better understand and segment, for example, but come up with some answers about what to do next; but as I’m talking to you, it sounds like you’re actually much more diverse than that in terms of how and where and why you apply the technology to business scenarios. When you talk about business optimization, to me that’s really the Holy Grail, because optimization of process using data can be applied to everything from operations to management decision-making, marketing, etc. Can you talk about how you guys have gotten there? What’s under the hood that enables all that?

Dave: Well, what it really is — just a common philosophy embodied in our platform — which is, if you can generate data on it, you can generate insights and hypotheses and action plans to improve your business based on that data. And whether that’s from our biggest of big enterprise customers like GE with their predict software layered on top of their turbine engines — as an example, those types of sales of both product and process through the sales force become very complex — my point with my earlier illustration of this is in a sales cycle, it’s not enough just to look at how many clicks got your customer to a website. You need to understand what is the entire lifecycle and relationship with that customer as it relates to sure, the click stream, but also the product stream and the consumption of the product.

Certainly, if you’re a digital property of any kind, if you’re a digital application of any time, the amount of data that you can generate on usage, on engagement, on purchases, becomes almost infinite, but then the need to drill into that and derive actionable insight on how to improve sales through better product mix, whether it’s a digital site, such as we have with some of our larger retail clients, or whether it’s through a hardware-based company and software-based company like GE. The problem set when it comes to the data and deriving the insights and the action plans that you want from that data are actually very similar.

Eric: Yeah, that’s really good stuff because again, you have the situation in every organization where you’ve got multiple applications. I think this is just getting even more complex by the day, at least at this point in the evolution of information systems, with all these cloud platforms, you mentioned, I think before the call, 3,500 different applications used for digital marketing in some way shape or form and they all have their…

Dave: Yes, and that’s up from 150 in 2011. It’s just crazy.

Eric: Which is insane. Really it’s like a Cambrian explosion of possibilities but you need to find some way to distill that down to really basic stuff, which is root cause analysis, understanding what could be done, what are your possibilities, what are your options and then business process optimization, really at the root level, it’s pretty simple stuff, but being able to distill all that information, all that data, in all its various forms into an understandable equation that you can explain to a business person, that’s the missing ingredient or at least it has been. It sounds to me like you guys have really focused on solving that riddle. Is that right?

Dave: Yeah. I think what you’re pointing at toward there, Eric, is for business people who are not necessarily analysts or BI experts or IT experts, the understanding and appreciation that data can really drive better business outcomes is there, but the patience with what has traditionally been a very cumbersome infrastructure for assembling your data, cleaning your data, preparing your data and getting it ready for analysis and then ultimately hypothesizing and creating action plans on top of that data, that has just been such a lugubrious process…

Eric: Oh, good word.

Dave: …a weighty, heavy process that your basic everyday decision-maker does not have the patience or expertise to do stuff like that and that’s exactly what the Domo business cloud is designed to take all that pain away, take all the pain of connecting to your data away, assembling it, cleaning it, governing integrity of the data, that’s all just kind of background noise and you get right to the fun part which is, “Hmm, I wonder if I told my salespeople to sell more product A than product B, what would the outcome be?”

In fact, a great story along those lines is we just signed a customer, a huge media, international media company. The have a brand-new revenue stream around programmatic advertising and they had no visibility about where the opportunities in that programmatic advertising was, vis-à-vis new markets, new potential advertisers, etc. They got Domo off and running and within two months, they were able to drive double-digit growth in their programmatic revenue by simply identifying, “Oh, look at all this unsold inventory internationally, mobile,” look mobile international sales force. Go sell that.

Low and behold, double-digit revenue growth and double-digit CPM price growth as a result of that increased demand for the supply that they’d identified through Domo, so it’s that rapidity of getting the system up and running, getting the data into it, and then being able to drive immediate business value, which is such a great advantage that you get with business cloud.

Eric: Well, I did another interview earlier today with Joe Propati from Aon. He’s the chief operating officer. Just amazing company. 40,000 clients in the United States, 40,000. Something like 50 offices all around the country. He’s in Chicago and what he told me was really quite compelling. He said with Domo he is able to see very quickly what’s happening at offices all around the country, find out which retail operations or which organizations are not performing as well as they should be and then getting some good insight into what’s happening there. He picks up the phone, he talks to someone in San Francisco, in New York, in LA, or wherever, and right off the bat he can ask the probing questions that get people clearing their throats and arching their backs a little bit and like telling him, “Okay. Well, you’re right. So, what’s happening is X, Y, and Z,” and the point there is, he can cut right through the noise, get to the signal, and have a meaningful conversation within the first 90 seconds of being on the phone with someone he may have never even talked to before.

You think about how that optimizes management of a business, not just business execution, but the management side of the equation, being able to talk without even doing 20, 30 minutes of research, maybe 18 minutes of research, being able to get right to a critical point with the person running that division all across the country, that’s a really, seriously big deal in terms of the immediacy of business, in terms of the efficacy of what people are doing, and in terms of helping your team stay on top of things and get their eyes on the ball.

Dave: Yeah, absolutely. I think what you just really pointed at there is the value of the data being available to you in real time and then being able to act on it almost immediately, and get real-time results from that action through, in this case, what you defined as kind of a tree, a spidering, of phone calls throughout his internal operations. I think that’s a really interesting observation you made there because what we’re seeing is that whole communication process of how is data insight shared, how is it socialized, how are hypotheses made about what should change as a result of the insights from the data, that there’s a lot of different channels that that communication and decision-making process can go through.

Phone is obvious. We’ve built a whole social network that we call Buzz into Domo that allows you to take any data visualization that you have in front of you, whether it’s an app or what we call “card” which is like a dashboard and share that out through a Facebook-like interface and increase that efficiency and also maintain the connection between the threaded conversation around the data-based decision and the original data because whether you email something or you phone call something, that connection is all too frequently lost and decisions will get made and fateful outcomes will occur and people won’t be able to track that. We think the number of channels, whether it’s this social network that we have, increasing to the point where eventually some of the stuff will just come automated through artificial intelligence engines, that process of optimization is going to get more and more interesting and more and more diversified in how it’s delivered.

Eric: Yeah, I think that’s exactly right. I think that in a very interesting way, what’s happening is we’re getting this convergence of channels. This is kind of ironic because what you were just referring to is this channel expansion. I remember the first time I heard that term, I was like, “Channel expansion? That doesn’t sound good. What are you talking about?” Then I realized-

Dave: Where data’s managed.

Eric: “Oh, goodness gracious. Now you’re talking about your direct message on Twitter or your Facebook message, your text message, you’re actually going to leave a message on my cell phone. Really? Are you sure?” There’s so many different channels out there but what’s, I think the straws in the wind tell me that the new convergence is coming and what I hear from you guys is you’ve really focused on setting up the catch basins and the funneling process to distill all of that stuff. I won’t call it noise because it all has value in a certain context. It’s not that it’s signal or noise, it’s a lot of material. It’s like grist for the mills as you used to say.

You’ve focused on A, the catch basins but B, the distillation process to get quality content, quality information and insight to the appropriate people at the appropriate time so that they can sort out the possibilities and make those business decisions very quickly so you don’t lose the opportunity, which these days happens faster and faster. Is that about right?

Dave: Yeah. No, that’s absolutely … I love the convergence idea and the fact of the matter is, every business and every decision-maker is really some form of a cyborg. At what point do you bring the human intelligence to bear on the data in order to derive the signal from the noise versus pointing the machine at it? That’s what we think is so powerful about a cloud-based solution like Domo and others, certainly, that you can have that mix. Insert human here, when key insights and decisions need to be made or not; if it becomes so repetitive, insert algorithm there and just optimize that process through an artificial intelligence or a neural network type of situation and either one of those types of optimization engines can be brought to bear as the technology develops and as the outcomes become more predictable.

Eric: Well, that’s just fantastic stuff and let’s just go ahead and tease your upcoming presentation here. You’re going to be talking at Dreamforce next week, next Thursday I believe it is, about using relevant marketing data to reveal strategic opportunity. Do you want to give a little insight as to where you’re going to go with that and maybe get some more people-

Dave: Yeah, actually we touched on a lot of the themes in our conversation today, but we’re going to get into some very specific examples. I think when you get all excited about data in the possibilities of shifting your culture in your business toward a data-driven decision-making process, it can become very heavy and very kind of almost too abstract, so what we’re going to get into is how do you crawl, how do you walk, and then how do you run to get that data in shape, to get that data at the table, in a form that you can actually start deriving the signal from the noise and then driving better decision-making? I think it’s really important to kind of keep it real and keep it relevant to kind of the everyday situations that people face in their businesses. That’s what we’re going to be doing.

Eric: Well, that is just fantastic stuff. Folks, I’ve been talking to David Thompson of Domo. You can check him out at Dreamforce next week on Thursday. I have to say, I’m really really psyched to have connected with you guys because I’ve been watching this conundrum form like a tempest, watching it come on shore from satellite for quite some time now and I’m a digital marketer at heart. I’m in the business of reaching out to people and having conversations and I’m seeing that … What would you call it? It’s the needle moving but really it’s more that a new crystallization is taking place. It’s still in fluid form right now, but it’s going to crystallize and the companies that understand the value of pulling in all the relevant data they possibly can to get to the insights to make better decisions, they’re the ones that are going to succeed. I don’t think there’s any doubt about that, so closing comments from you?

Dave: Absolutely. We see that over and over again — especially in segments, industries, that are straddling the divide between digital and your traditional, for example, retail big-box store format — and it’s only the folks who are able to use data to cater to the exact interest and the exact timing of interest; those micro moments is something that’s a big buzzword these days from Google on down; and be able to appeal in that real-time way, are going to be the ones that survive and cross the chasm.

Eric: I love it. Well folks, hope online to Check this stuff out, great great content. Thanks for your time today. We’ll catch up to you next time, folks.

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