Podcast appearances and mentions of mark stouse

This week, marketing and revenue operations expert Simon Daniels joins Ian after a two-year break working with Forrester to discuss how we define the discipline of revenue operations, how this sits with sales operations and marketing operations, and how we should implement this function.  In this discussion, they cover: Revenue operations, marketing, sales, and customer success operations. The organizational structure for RevOps varies by business context. Collaboration between sales and marketing  The death of the MQL Understanding the buying group and metrics for revenue and pipeline health The key technology and data platforms The role of AI in the analysis of revenue operations. As always, we welcome your feedback. If you have a suggestion for a topic that is hot for you, please get in touch using the links below.   Enjoy! — The Links The people: Ian Truscott on LinkedIn and Bluesky Simon Daniels on LinkedIn As mentioned this week and some further reading that Simon recommends: Blowing in the wind - Why I'm sticking with Revenue Operations (even if the rest of the world is not!) - LinkedIn post by Simon Why the MQL model is failing B2B marketing and what to use instead - Mark Stouse on Martech.org regarding ditching MQLs Beyond MQLs: Unlocking Revenue Growth by Embracing Buying Groups - B2B Marketing webinar on moving beyond the MQL Meet the new martech stack: systems of context and systems of truth – Chief Marketing Technologist RevOps And AI: The Cobbler's Children Need Shoes, Too – Simon co-wrote this on tech for Rev Ops ​​What's Broken in GTM and How to Fix It - Simon's podcast Rockstar CMO: The Beat Newsletter that we send every Monday Rockstar CMO on the web, Twitter, and LinkedIn Previous episodes and all the show notes: Rockstar CMO FM. Track List: We'll be right back by Stienski & Mass Media on YouTube You can listen to this on all good podcast platforms, like Apple, Amazon and Spotify. Learn more about your ad choices. Visit megaphone.fm/adchoices

Are your data science projects failing to deliver real business value?What if the problem isn't the technology or the organization, but your approach as a data scientist?With only 11% of data science models making it to deployment and close to 85% of big data projects failing, something clearly isn't working.In this episode, three globally recognised analytics leaders, Bill Schmarzo, Mark Stouse and John Thompson, join Dr Genevieve Hayes to deliver a tough love wake-up call on why data scientists struggle to create business impact, and more importantly, how to fix it.This episode reveals:Why focusing purely on technical metrics like accuracy and precision is sabotaging your success — and what metrics actually matter to business leaders. [04:18]The critical mindset shift needed to transform from a back-room technical specialist into a valued business partner. [30:33]How to present data science insights in ways that drive action — and why your fancy graphs might be hurting rather than helping. [25:08]Why “data driven” isn't enough, and how to adopt a “data informed” approach that delivers real business outcomes. [54:08]Guest BioBill Schmarzo, also known as “The Dean of Big Data,” is the AI and Data Customer Innovation Strategist for Dell Technologies' AI SPEAR team, and is the author of six books on blending data science, design thinking, and data economics from a value creation and delivery perspective. He is an avid blogger and is ranked as the #4 influencer worldwide in data science and big data by Onalytica and is also an adjunct professor at Iowa State University, where he teaches the “AI-Driven Innovation” class.Mark Stouse is the CEO of ProofAnalytics.ai, a causal AI company that helps companies understand and optimize their operational investments in light of their targeted objectives, time lag, and external factors. Known for his ability to bridge multiple business disciplines, he has successfully operationalized data science at scale across large enterprises, driven by his belief that data science's primary purpose is enabling better business decisions.John Thompson is EY's Global Head of AI and is the author of four books on AI, data and analytics teams. He was named one of dataIQ's 100 most influential people in data in 2023 and is also an Adjunct Professor at the University of Michigan, where he teaches a course based on his book “Building Analytics Teams”.LinksConnect with Bill on LinkedInConnect with Mark on LinkedInConnect with John on LinkedInConnect with Genevieve on LinkedInBe among the first to hear about the release of each new podcast episode by signing up HERE

Genevieve Hayes Consulting Episode 53: A Wake-Up Call from 3 Tech Leaders on Why You're Failing as a Data Scientist Are your data science projects failing to deliver real business value?What if the problem isn’t the technology or the organization, but your approach as a data scientist?With only 11% of data science models making it to deployment and close to 85% of big data projects failing, something clearly isn’t working.In this episode, three globally recognised analytics leaders, Bill Schmarzo, Mark Stouse and John Thompson, join Dr Genevieve Hayes to deliver a tough love wake-up call on why data scientists struggle to create business impact, and more importantly, how to fix it.This episode reveals:Why focusing purely on technical metrics like accuracy and precision is sabotaging your success — and what metrics actually matter to business leaders. [04:18]The critical mindset shift needed to transform from a back-room technical specialist into a valued business partner. [30:33]How to present data science insights in ways that drive action — and why your fancy graphs might be hurting rather than helping. [25:08]Why “data driven” isn’t enough, and how to adopt a “data informed” approach that delivers real business outcomes. [54:08] Guest Bio Bill Schmarzo, also known as “The Dean of Big Data,” is the AI and Data Customer Innovation Strategist for Dell Technologies' AI SPEAR team, and is the author of six books on blending data science, design thinking, and data economics from a value creation and delivery perspective. He is an avid blogger and is ranked as the #4 influencer worldwide in data science and big data by Onalytica and is also an adjunct professor at Iowa State University, where he teaches the “AI-Driven Innovation” class.Mark Stouse is the CEO of ProofAnalytics.ai, a causal AI company that helps companies understand and optimize their operational investments in light of their targeted objectives, time lag, and external factors. Known for his ability to bridge multiple business disciplines, he has successfully operationalized data science at scale across large enterprises, driven by his belief that data science’s primary purpose is enabling better business decisions.John Thompson is EY's Global Head of AI and is the author of four books on AI, data and analytics teams. He was named one of dataIQ's 100 most influential people in data in 2023 and is also an Adjunct Professor at the University of Michigan, where he teaches a course based on his book “Building Analytics Teams”. Links Connect with Bill on LinkedInConnect with Mark on LinkedInConnect with John on LinkedIn Connect with Genevieve on LinkedInBe among the first to hear about the release of each new podcast episode by signing up HERE Read Full Transcript [00:00:00] Dr Genevieve Hayes: Hello, and welcome to Value Driven Data Science, the podcast that helps data scientists transform their technical expertise into tangible business value, career autonomy, and financial reward. I’m Dr. Genevieve Hayes, and today I’m joined by three globally recognized innovators and leaders in AI, analytics, and data science.[00:00:24] Bill Schmarzo, Mark Stouse, and John Thompson. Bill? Also known as the Dean of Big Data, is the AI and Data Customer Innovation Strategist for Dell Technologies AI Spear Team, and is the author of six books on blending data science, design thinking, and data economics from a value creation and delivery perspective.[00:00:49] He is an avid blogger and is ranked as the number four influencer worldwide in data science and big data Analytica. And he’s also an adjunct professor at Iowa State University, where he teaches AI driven innovation. Mark is the CEO of proofanalytics. ai, a causal AI company that helps organizations understand and optimize their operational investments in light of their targeted objectives, time lag and external factors.[00:01:23] Known for his ability to bridge multiple business disciplines, he has successfully operationalized data science at scale across large enterprises. Driven by his belief that data science’s primary purpose is enabling better business decisions. And John is EY’s global head of AI and is the author of four books on AI data and analytics teams.[00:01:49] He was named one of DataIQ’s 100 most influential people in data in 2023. and is also an adjunct professor at the University of Michigan, where he teaches a course based on his book, Building Analytics Teams. Today’s episode will be a tough love wake up call for data scientists on why you are failing to deliver real business value and more importantly, what you can do about it.[00:02:17] So get ready to boost your impact. Earn what you’re worth and rewrite your career algorithm. Bill, Mark, John, welcome to the show.[00:02:25] Mark Stouse: Thank[00:02:26] Bill Schmarzo: Thanks for having us.[00:02:27] John Thompson: to be here.[00:02:28] Dr Genevieve Hayes: Only 11 percent of data scientists say their models always deploy. Only 10 percent of companies obtain significant financial benefits from AI technologies and close to 85 percent of big data projects fail. These statistics, taken from research conducted by Rexa Analytics, the Boston Consulting Group and Gartner respectively, paint a grim view of what it’s like working as a data scientist.[00:02:57] The reality is, you’re probably going to fail. And when that reality occurs, it’s not uncommon for data scientists to blame either the executive for not understanding the brilliance of their work, or the corporate culture for not being ready for data science. And maybe this is true for some organizations.[00:03:20] Particularly those relatively new to the AI adoption path. But it’s now been almost 25 years since William Cleveland first coined the term data science. And as the explosive uptake of generative AI tools, such as chat GPT demonstrate with the right use case. People are very willing to take on AI technologies.[00:03:42] So perhaps it’s finally time to look in the mirror and face the truth. Perhaps the problem is you, the data scientist. But if this is the case, then don’t despair. In many organizations, the leadership just don’t have the time to provide data scientists with the feedback necessary to improve. But today, I’m sitting here with three of the world’s best to provide that advice just for you.[00:04:09] So, let’s cut to the chase what are the biggest mistakes you see data scientists making when it comes to demonstrating their value?[00:04:18] Mark Stouse: I think that you have to start with the fact that they’re not demonstrating their value, right? I mean, if you’re a CEO, a CFO, head of sales really doesn’t matter if you’re trying to make better business decisions over and over and over again. As Bill talks about a lot, the whole idea here is economic,[00:04:39] and it is. About engaging, triggering the laws of compounding you’ve got to be able to do stuff that makes that happen. Data management, for example, even though we all agree that it’s really necessary, particularly if you’re launching, you know, big data solutions. You can’t do this sequentially and be successful.[00:05:04] You’re going to have to find some areas probably using, you know, old fashioned math around causal analytics, multivariable linear regression, things like that, to at least get the ball rolling. In terms of delivering better value, the kind of value that business leaders actually see as valuable[00:05:29] I mean, one of the things that I feel like I say a lot is, you have to have an understanding of your mission, the mission of data science. As somebody who, as a business leader champions it. Is to help people make those better and better and better decisions. And if you’re not doing that, you’re not creating value.[00:05:52] Full stop.[00:05:53] Bill Schmarzo: Totally agree with Mark. I think you’re going to find that all three of us are in violent agreement on a lot of this stuff. What I find interesting is it isn’t just a data scientist fault. Genevieve, you made a comment that leadership lacks the time to provide guidance to data scientists. So if leadership Is it treating data and analytics as an economics conversation if they think it’s a technology conversation is something that should be handled by the CIO, you’ve already lost, you’ve already failed, you already know you failed,[00:06:24] Mark mentioned the fact that this requires the blending of both sides of the aisle. It requires a data scientist to have the right mindset to ask questions like what it is that we’re trying to achieve. How do we create value? What are our desired outcomes? What are the KPIs metrics around which are going to make your success?[00:06:39] Who are our key stakeholders? There’s a series of questions that the data scientist must be empowered to ask and the business Leadership needs to provide the time and people and resources to understand what we’re trying to accomplish. It means we can go back old school with Stephen Covey, begin with an end in mind.[00:07:01] What is it we’re trying to do? Are we trying to improve customer retention? We try to do, you know, reduce unplanned operational downtime or improve patient outcomes. What is it we’re trying to accomplish? The conversation must, must start there. And it has to start with business leadership, setting the direction, setting the charter, putting the posts out where we want to go, and then the data science team collaborating with the stakeholders to unleash that organizational tribal knowledge to actually solve[00:07:32] Dr Genevieve Hayes: think a lot of the problem comes with the fact that many business leaders see data science as being like an IT project. So, if you’ve got your Windows upgrade, the leadership It gives the financing to IT, IT goes along and does it. And then one morning you’re told, when you come into work, your computer will magically upgrade to the latest version of Windows.[00:07:55] So no one really gets bothered by it. And I think many business leaders treat data science as just another IT project like that. They think they can just Give the funding, the data scientists will go away and then they’ll come in one morning and the data science will magically be on their computer.[00:08:15] Bill Schmarzo: Yeah, magic happens, right? No, no, magic doesn’t happen, it doesn’t happen. There has to be that leadership commitment to be at the forefront, not just on the boat, but at the front of the boat saying this is the direction we’re going to go.[00:08:29] John Thompson: That’s the whole reason this book was written. The whole point is that, analytics projects are not tech projects. Analytics projects are cultural transformation projects, is what they are. And if you’re expecting the CEO, CFO, CIO, COO, whoever it is, to go out there and set the vision.[00:08:50] That’s never going to happen because they don’t understand technology, and they don’t understand data. They’d rather be working on building the next factory or buying another company or something like that. What really has to happen is the analytics team has to provide leadership to the leadership for them to understand what they’re going to do.[00:09:12] So when I have a project that we’re trying to do, my team is trying to do, and if we’re working for, let’s say, marketing, I go to the CMO and I say, look, you have to dedicate and commit. that your subject matter experts are going to be in all the meetings. Not just the kickoff meetings, not just the quarterly business review, the weekly meetings.[00:09:36] Because when we go off as an analytics professionals and do things on our own, we have no idea what the business runs like. , we did analytics at one company that I work for. We brought it back and we showed it to the they said, the numbers are wildly wrong. And we said, well, why? And they said, well, you probably don’t understand that what we do is illegal in 10 US states.[00:10:00] So you probably have the data from all those 10 states in the analysis. And we did. So, we took it all out and they look down there and go, you got it right. It’s kind of surprising. You didn’t know what you were doing and you got it right. So, it has to be a marriage of the subject matter experts in the business.[00:10:17] And the data scientists, you can’t go to the leadership and say, tell us what you want. They don’t know what they want. They’d want another horse in Henry Ford’s time, or they glue a, a Walkman onto a radio or something in Steve Jobs time. They don’t know what they want. So you have to come together.[00:10:36] And define it together and you have to work through the entire project together.[00:10:42] Mark Stouse: Yeah, I would add to that, okay, that a lot of times the SMEs also have major holes in their knowledge that the analytics are going to challenge and give them new information. And so I totally agree. I mean, this is an iterative learning exchange. That has profound cultural implications.[00:11:11] One of the things that AI is doing right now is it is introducing a level of transparency and accountability into operations, corporate operations, my operations, your operations, that honestly, none of us are really prepared for. None of us are really prepared for the level of learning that we’re going to have to do.[00:11:36] And very few of us are aware of how polymathic. Most of our challenges, our problems, our objectives really are one of the things that I love to talk about in this regard is analytics made me a much better person. That I once was because it showed me the extent of my ignorance.[00:12:01] And when I kind of came to grips with that and I started to use really the modicum of knowledge that I have as a way of curating my ignorance. And I got humble about it made a big difference[00:12:16] John Thompson: Well, that’s the same when I was working shoulder to shoulder with Bill, I just realized how stupid I was. So, then I just, really had to, come back and, say, oh, God nowhere near the summit, I have a long way to go.[00:12:31] Bill Schmarzo: Hey, hey, Genevie. Let me throw something out there at you and it builds on what John has said and really takes off on what Mark is talking about is that there is a cultural preparation. It needs to take place across organizations in order to learn to master the economies of learning,[00:12:48] the economies of learning, because you could argue in knowledge based industries that what you are learning is more important than what you know. And so if what you know has declining value, and what you’re learning has increasing value, then what Mark talked about, and John as well, both city presenting data and people saying, I didn’t know that was going on, right?[00:13:09] They had a certain impression. And if they have the wrong cultural mindset. They’re going to fight that knowledge. They’re going to fight that learning, oh, I’m going to get fired. I’m going to get punished. No, we need to create cultures that says that we are trying to master the economies and learning and you can’t learn if you’re not willing to fail.[00:13:29] And that is what is powerful about what AI can do for us. And I like to talk about how I’m a big fan of design thinking. I integrate design thinking into all my workshops and all my training because it’s designed to. Cultivate that human learning aspect. AI models are great at cultivating algorithmic learning.[00:13:50] And when you bring those two things together around a learning culture that says you’re going to try things, you’re going to fail, you’re going to learn, those are the organizations that are going to win.[00:13:59] John Thompson: Yeah, you know, to tie together what Mark and Bill are saying there is that, you need people to understand that they’re working from an outmoded view of the business. Now, it’s hard for them to hear that. It’s hard for them to realize it. And what I ask data scientists to do that work for me is when we get a project and we have an operational area, sales, marketing, logistics, finance, manufacturing, whatever it is.[00:14:26] They agreed that they’re going to go on the journey with us. We do something really simple. We do an exploratory data analysis. We look at means and modes and distributions and things like that. And we come back and we say, this is what the business looks like today. And most of the time they go, I had no idea.[00:14:44] You know, I didn’t know that our customers were all, for the most part, between 70 and 50. I had no idea that our price point was really 299. I thought it was 3, 299. So you then end up coming together. You end up with a shared understanding of the business. Now one of two things is generally going to happen.[00:15:05] The business is going to freak out and leave the project and say, I don’t want anything to do with this, or they’re going to lean into it and say, I was working from something that was, as Bill said, declining value. Okay. Now, if they’re open, like a AI model that’s being trained, if they’re open to learning, they can learn what the business looks like today, and we can help them predict what the business should look like tomorrow.[00:15:31] So we have a real issue here that the three of us have talked about it from three different perspectives. We’ve all seen it. We’ve all experienced it. It’s a real issue, we know how people can come together. The question is, will they?[00:15:46] Dr Genevieve Hayes: think part of the issue is that, particularly in the area of data science, there’s a marked lack of leadership because I think a lot of people don’t understand how to lead these projects. So you’ve got Many data scientists who are trained heavily in the whole technical aspect of data science, and one thing I’ve come across is, you know, data scientists who’ll say to me, my job is to do the technical work, tell me what to do.[00:16:23] I’ll go away and do it. Give it to you. And then you manager can go and do whatever you like with it.[00:16:29] Mark Stouse: Model fitment.[00:16:31] Dr Genevieve Hayes: Yeah. And then one thing I’ve experienced is many managers in data science are, you know, It’s often the area that they find difficult to find managers for, so we’ll often get people who have no data science experience whatsoever[00:16:46] and so I think part of the solution is teaching the data scientists that they have to start managing up because they’re the ones who understand what they’re doing the best, but no one’s telling them that because the people above them often don’t know that they should be telling the data[00:17:08] John Thompson: Well, if that’s the situation, they should just fire everybody and save the money. Because it’s never going to go anywhere. But Bill, you were going to say something. Go ahead.[00:17:16] Bill Schmarzo: Yeah, I was going to say, what’s interesting about Genevieve, what you’re saying is that I see this a lot in not just data scientists, but in a lot of people who are scared to show their ignorance in new situations. I think Mark talked about this, is it because they’re, you think about if you’re a data scientist, you probably have a math background. And in math, there’s always a right answer. In data science, there isn’t. There’s all kinds of potential answers, depending on the situation and the circumstances. I see this all the time, by the way, with our sales folks. Who are afraid we’re selling technology. We’re afraid to talk to the line of business because I don’t understand their business Well, you don’t need to understand their business, but you do need to become like socrates and start asking questions What are you trying to accomplish?[00:18:04] What are your goals? What are your desired outcomes? How do you measure success? Who are your stakeholders ? You have to be genuinely interested In their success and ask those kind of questions if you’re doing it to just kind of check a box off Then just get chad gpt to rattle it off But if you’re genuinely trying to understand what they’re trying to accomplish And then thinking about all these marvelous different tools you have because they’re only tools And how you can weave them together to help solve that now you’ve got That collaboration that john’s book talks about about bringing these teams together Yeah[00:18:39] Mark Stouse: is, famously paraphrased probably did actually say something like this, . But he’s famously paraphrased as saying that he would rather have a really smart question than the best answer in the world. And. I actually experienced that two days ago,[00:18:57] in a conversation with a prospect where I literally, I mean, totally knew nothing about their business. Zero, but I asked evidently really good questions. And so his impression of me at the end of the meeting was, golly, you know, so much about our business. And I wanted to say, yeah, cause you just educated me.[00:19:21] Right. You know, I do now. And so I think there’s actually a pattern here that’s really worth elevating. So what we are seeing right now with regard to data science teams is scary similar to what happened with it after Y2K, the business turned around and looked at him and said, seriously, we spend all that money,[00:19:45] I mean, what the heck? And so what happened? The CIO got, demoted organizationally pretty far down in the company wasn’t a true C suite member anymore. Typically the whole thing reported up into finance. The issue was not. Finance, believing that they knew it better than the it people,[00:20:09] it was, we are going to transform this profession from being a technology first profession to a business outcomes. First profession, a money first profession, an economics organization, that has more oftentimes than not been the outcome in the last 25 years. But I think that that’s exactly what’s going on right now with a lot of data science teams.[00:20:39] You know, I used to sit in technology briefing rooms, listening to CIOs and other people talk about their problems. And. This one CIO said, you know, what I did is I asked every single person in my organization around the world to go take a finance for non financial managers course at their local university.[00:21:06] They want credit for it. We’ll pay the bill. If they just want to audit it, they can do that. And they started really cross pollinating. These teams to give them more perspective about the business. I totally ripped that off because it just struck me as a CMO as being like, so many of these problems, you could just do a search and replace and get to marketing.[00:21:32] And so I started doing the same thing and I’ve made that suggestion to different CDOs, some of whom have actually done it. So it’s just kind of one of those things where you have to say, I need to know more. So this whole culture of being a specialist is changing from.[00:21:53] This, which, this is enough, this is okay , I’m making a vertical sign with my hand, to a T shaped thing, where the T is all about context. It’s all about everything. That’s not part of your. Profession[00:22:09] John Thompson: Yeah, well, I’m going to say that here’s another book that you should have your hands on. This is Aristotle. We can forget about Socrates. Aristotle’s the name. But you know. But , Bill’s always talking about Socrates. I’m an Aristotle guy myself. So, you[00:22:23] Bill Schmarzo: Okay, well I Socrates had a better jump shot. I’m sorry. He could really nail that[00:22:28] John Thompson: true. It’s true. Absolutely. Well, getting back , to the theme of the discussion, in 1 of the teams that I had at CSL bearing, which is an Australian company there in Melbourne, I took my data science team and I brought in speech coaches.[00:22:45] Presentation coaches people who understand business, people who understood how to talk about different things. And I ran them through a battery of classes. And I told them, you’re going to be in front of the CEO, you’re going to be in front of the EVP of finance, you’re going to be in front of all these different people, and you need to have the confidence to speak their language.[00:23:07] Whenever we had meetings, we talk data science talk, we talk data and integration and vectors and, algorithms and all that kind of stuff. But when we were in the finance meeting, we talked finance. That’s all we talked. And whenever we talked to anybody, we denominated all our conversations in money.[00:23:25] Whether it was drachma, yen, euros, pounds, whatever it was, we never talked about speeds and feeds and accuracy and results. We always talked about money. And if it didn’t make money, we didn’t do it. So, the other thing that we did that really made a difference was that when the data scientists and data scientists hate this, When they went into a meeting, and I was there, and even if I wasn’t there, they were giving the end users and executives recommendations.[00:23:57] They weren’t going in and showing a model and a result and walking out the door and go, well, you’re smart enough to interpret it. No, they’re not smart enough to interpret it. They actually told the marketing people. These are the 3 things you should do. And if your data scientists are not being predictive and recommending actions, they’re not doing their job.[00:24:18] Dr Genevieve Hayes: What’s the, so what test At the end of everything, you have to be able to say, so what does this mean to whoever your audience is?[00:24:25] Mark Stouse: That’s right. I mean, you have to be able to say well, if the business team can’t look at your output, your data science output, and know what to do with it, and know how to make a better decision, it’s like everything else that you did didn’t happen. I mean it, early in proof, we were working on. UX, because it became really clear that what was good for a data scientist wasn’t working. For like everybody else. And so we did a lot of research into it. Would you believe that business teams are okay with charts? Most of them, if they see a graph, they just totally freeze and it’s not because they’re stupid.[00:25:08] It’s because so many people had a bad experience in school with math. This is a psychological, this is an intellectual and they freeze. So in causal analytics, one of the challenges is that, I mean, this is pretty much functioning most of the time anyway, on time series data, so there is a graph,[00:25:31] this is kind of like a non negotiable, but we had a customer that was feeding data so fast into proof that the automatic recalc of the model was happening like lickety split. And that graph all of a sudden looked exactly like a GPS. It worked like a GPS. In fact, it really is a GPS. And so as soon as we stylized.[00:26:01] That graph to look more like a GPS track, all of a sudden everybody went, Oh,[00:26:10] Dr Genevieve Hayes: So I got rid of all the PTSD from high school maths and made it something familiar.[00:26:16] Mark Stouse: right. And so it’s very interesting. Totally,[00:26:21] Bill Schmarzo: very much mirrors what mark talked about So when I was the new vice president of advertiser analytics at yahoo we were trying to solve a problem to help our advertisers optimize their spend across the yahoo ad network and because I didn’t know anything about that industry We went out and my team went out and interviewed all these advertisers and their agencies.[00:26:41] And I was given two UEX people and zero data. Well, I did have one data scientist. But I had mostly UX people on this project. My boss there said, you’re going to want UX people. I was like, no, no, I need analytics. He said, trust me in UX people and the process we went through and I could spend an hour talking about the grand failure of the start and the reclamation of how it was saved at a bar after too many drinks at the Waldorf there in New York.[00:27:07] But what we’ve realized is that. For us to be effective for our target audience was which was media planners and buyers and campaign managers. That was our stakeholders. It wasn’t the analysts, it was our stakeholders. Like Mark said, the last thing they wanted to see was a chart. And like John said, what they wanted the application to do was to tell them what to do.[00:27:27] So we designed this user interface that on one side, think of it as a newspaper, said, this is what’s going on with your campaign. This audience is responding. These sites are this, these keywords are doing this. And the right hand side gave recommendations. We think you should move spend from this to this.[00:27:42] We think you should do this. And it had three buttons on this thing. You could accept it and it would kick into our advertising network and kick in. And we’d measure how effective that was. They could reject it. They didn’t think I was confident and we’d measure effectiveness or they could change it. And we found through our research by putting that change button in there that they had control, that adoption went through the roof.[00:28:08] When it was either yes or no, adoption was really hard, they hardly ever used it. Give them a chance to actually change it. That adoption went through the roof of the technology. So what John was saying about, you have to be able to really deliver recommendations, but you can’t have the system feel like it’s your overlord.[00:28:27] You’ve got to be like it’s your Yoda on your shoulder whispering to your saying, Hey, I think you should do this. And you’re going, eh, I like that. No, I don’t like this. I want to do that instead. And when you give them control, then the adoption process happens much smoother. But for us to deliver those kinds of results, we had to know in detail, what decisions are they trying to make?[00:28:45] How are they going to measure success? We had to really understand their business. And then the data and the analytics stuff was really easy because we knew what we had to do, but we also knew what we didn’t have to do. We didn’t have to boil the ocean. We were trying to answer basically 21 questions.[00:29:01] The media planners and buyers and the campaign managers had 21 decisions to make and we built analytics and recommendations for each Of those 21[00:29:10] John Thompson: We did the same thing, you know, it blends the two stories from Mark and Bill, we were working at CSL and we were trying to give the people tools to find the best next location for plasma donation centers. And, like you said, there were 50, 60 different salient factors they had, and when we presented to them in charts and graphs, Information overload.[00:29:34] They melted down. You can just see their brains coming out of their ears. But once we put it on a map and hit it all and put little dials that they could fiddle with, they ran with it.[00:29:49] Bill Schmarzo: brilliant[00:29:50] Mark Stouse: totally, totally agree with that. 100% you have to know what to give people and you have to know how to give them, control over some of it, nobody wants to be an automaton. And yet also they will totally lock up if you just give them the keys to the kingdom. Yeah.[00:30:09] Dr Genevieve Hayes: on what you’ve been saying in the discussion so far, what I’m hearing is that the critical difference between what data scientists think their role is and what business leaders actually need is the data scientists is. Well, the ones who aren’t performing well think their role is to just sit there in a back room and do technical work like they would have done in their university assignments.[00:30:33] What the business leaders need is someone who can work with them, ask the right questions in order to understand the needs of the business. make recommendations that answer those questions. But in answering those questions, we’re taking a data informed approach rather than a data driven approach. So you need to deliver the answers to those questions in such a way that you’re informing the business leaders and you’re delivering it in a way that Delivers the right user experience for them, rather than the user experience that the data scientists might want, which would be your high school maths graphs.[00:31:17] Is that a good summary?[00:31:20] John Thompson: Yeah, I think that’s a really good summary. You know, one of the things that Bill and I, and I believe Mark understands is we’re all working to change, you know, Bill and I are teaching at universities in the United States. I’m on the advisory board of about five. Major universities. And whenever I go in and talk to these universities and they say, Oh, well, we teach them, these algorithms and these mathematical techniques and these data science and this statistics.[00:31:48] And I’m like, you are setting these people up for failure. You need to have them have presentation skills, communication skills, collaboration. You need to take about a third of these credits out and change them out for soft skills because you said it Genevieve, the way we train people, young people in undergraduate and graduate is that they have a belief that they’re going to go sit in a room and fiddle with numbers.[00:32:13] That’s not going to be successful.[00:32:16] Mark Stouse: I would give one more point of dimensionality to this, which is a little more human, in some respects, and that is that I think that a lot of data scientists love the fact that they are seen as Merlin’s as shamans. And the problem that I personally witnessed this about two years ago is when you let business leaders persist in seeing you in those terms.[00:32:46] And when all of a sudden there was a major meltdown of some kind, in this case, it was interest rates, and they turn around and they say, as this one CEO said in this meeting Hey, I know you’ve been doing all kinds of really cool stuff back there with AI and everything else. And now I need help.[00:33:08] Okay. And the clear expectation was. I need it now, I need some brilliant insight now. And the answer that he got was, we’re not ready yet. We’re still doing the data management piece. And this CEO dropped the loudest F bomb. That I think I have ever heard from anybody in almost any situation,[00:33:36] and that guy, that data science leader was gone the very next day. Now, was that fair? No. Was it stupid? For the data science leader to say what he said. Yeah, it was really dumb.[00:33:52] Bill Schmarzo: Don’t you call that the tyranny of perfection mark? Is that your term that you always use? is that There’s this idea that I gotta get the data all right first before I can start doing analysis And I think it’s you I hear you say the tyranny of perfection is what hurts You Progress over perfection, learning over absolutes, and that’s part of the challenge is it’s never going to be perfect.[00:34:13] Your data is never going to be perfect, you got to use good enough data[00:34:17] Mark Stouse: It’s like the ultimate negative version of the waterfall.[00:34:22] John Thompson: Yeah,[00:34:23] Mark Stouse: yet we’re all supposedly living in agile paradise. And yet very few people actually operate[00:34:30] John Thompson: that’s 1 thing. I want to make sure that we get in the recording is that I’ve been on record for years and I’ve gone in front of audiences and said this over and over again. Agile and analytics don’t mix that is. There’s no way that those 2 go together. Agile is a babysitting methodology. Data scientists don’t do well with it.[00:34:50] So, you know, I’ll get hate mail for that, but I will die on that hill. But, the 1 thing that, Mark, I agree with 100 percent of what you said, but the answer itself or the clue itself is in the title. We’ve been talking about. It’s data science. It’s not magic. I get people coming and asking me to do magical things all the time.[00:35:11] And I’m like. Well, have you chipped all the people? Do you have all their brain waves? If you have that data set, I can probably analyze it. But, given that you don’t understand what’s going on inside their cranium, that’s magic. I can’t do that. We had the same situation when COVID hit, people weren’t leaving their house.[00:35:29] So they’re not donating plasma. It’s kind of obvious, so, people came to us and said, Hey, the world’s gone to hell in a handbasket in the last two weeks. The models aren’t working and I’m like, yeah, the world’s changed, give us four weeks to get a little bit of data.[00:35:43] We’ll start to give you a glimmer of what this world’s going to look like two months later. We had the models working back in single digit error terms, but when the world goes haywire, you’re not going to have any data, and then when the executives are yelling at you, you just have to say, look, this is modeling.[00:36:01] This is analytics. We have no precedent here.[00:36:05] Bill Schmarzo: to build on what John was just saying that the challenge that I’ve always seen with data science organizations is if they’re led by somebody with a software development background, getting back to the agile analytics thing, the problem with software development. is that software development defines the requirements for success.[00:36:23] Data science discovers them. It’s hard to make that a linear process. And so, if you came to me and said, Hey, Schmarz, you got a big, giant data science team. I had a great data science team at Hitachi. Holy cow, they were great. You said, hey, we need to solve this problem. When can you have it done?[00:36:38] I would say, I need to look at the problem. I need to start exploring it. I can’t give you a hard date. And that drove software development folks nuts. I need a date for when I, I don’t know, cause I’ve got to explore. I’m going to try lots of things. I’m going to fail a lot.[00:36:51] I’m going to try things that I know are going to fail because I can learn when I fail. And so, when you have an organization that has a software development mindset, , like John was talking about, they don’t understand the discovery and learning process that the data science process has to go through to discover the criteria for success.[00:37:09] Mark Stouse: right. It’s the difference between science and engineering.[00:37:13] John Thompson: Yes, exactly. And 1 of the things, 1 of the things that I’ve created, it’s, you know, everybody does it, but I have a term for it. It’s a personal project portfolio for data scientists. And every time I’ve done this and every team. Every data scientist has come to me individually and said, this is too much work.[00:37:32] It’s too hard. I can’t[00:37:34] Bill Schmarzo: Ha, ha, ha,[00:37:35] John Thompson: three months later, they go, this is the only way I want to work. And what you do is you give them enough work so when they run into roadblocks, they can stop working on that project. They can go out and take a swim or work on something else or go walk their dog or whatever.[00:37:53] It’s not the end of the world because the only project they’re working on can’t go forward. if they’ve got a bunch of projects to time slice on. And this happens all the time. You’re in, team meetings and you’re talking and all of a sudden the data scientist isn’t talking about that forecasting problem.[00:38:09] It’s like they ran into a roadblock. They hit a wall. Then a week later, they come in and they’re like, Oh, my God, when I was in the shower, I figured it out. You have to make time for cogitation, introspection, and eureka moments. That has to happen in data science.[00:38:28] Bill Schmarzo: That is great, John. I love that. That is wonderful.[00:38:30] Mark Stouse: And of course the problem is. Yeah. Is that you can’t predict any of that, that’s the part of this. There’s so much we can predict. Can’t predict that.[00:38:42] Bill Schmarzo: you know what you could do though? You could do Mark, you could prescribe that your data science team takes multiple showers every day to have more of those shower moments. See, that’s the problem. I see a correlation. If showers drive eureka moments, dang it.[00:38:54] Let’s give him more showers.[00:38:56] John Thompson: Yep. Just like firemen cause fires[00:38:59] Mark Stouse: Yeah, that’s an interesting correlation there, man.[00:39:05] Dr Genevieve Hayes: So, if businesses need something different from what the data scientists are offering, why don’t they just articulate that in the data scientist’s role description?[00:39:16] John Thompson: because they don’t know they need it.[00:39:17] Mark Stouse: Yeah. And I think also you gotta really remember who you’re dealing with here. I mean, the background of the average C suite member is not highly intellectual. That’s not an insult, that’s just they’re not deep thinkers. They don’t think a lot. They don’t[00:39:37] John Thompson: that with tech phobia.[00:39:38] Mark Stouse: tech phobia and a short termism perspective.[00:39:43] That arguably is kind of the worst of all the pieces.[00:39:48] John Thompson: storm. It’s a[00:39:49] Mark Stouse: It is, it is a[00:39:50] John Thompson: know, I, I had, I’ve had CEOs come to me and say, we’re in a real crisis here and you guys aren’t helping. I was like, well, how do you know we’re not helping? You never talked to us. And, in this situation, we had to actually analyze the entire problem and we’re a week away from making recommendations.[00:40:08] And I said that I said, we have an answer in 7 days. He goes, I need an answer today. I said, well, then you should go talk to someone else because in 7 days, I’ll have it. But now I don’t. So, I met with him a week later. I showed them all the data, all the analytics, all the recommendations. And they said to me, we don’t really think you understand the business well enough.[00:40:27] We in the C suite have looked at it and we don’t think that this will solve it. And I’m like, okay, fine, cool. No problem. So I left, and 2 weeks later, they called me in and said, well, we don’t have a better idea. So, what was that you said? And I said, well, we’ve coded it all into the operational systems.[00:40:43] All you have to do is say yes. And we’ll turn it on and it was 1 of the 1st times and only times in my life when the chart was going like this, we made all the changes and it went like that. It was a perfect fit. It worked like a charm and then, a month later, I guess it was about 6 months later, the CEO came around and said, wow, you guys really knew your stuff.[00:41:07] You really were able to help us. Turn this around and make it a benefit and we turned it around faster than any of the competitors did. And then he said, well, what would you like to do next? And I said, well, I resigned last week. So, , I’m going to go do it somewhere else.[00:41:22] And he’s like, what? You just made a huge difference in the business. And I said, yeah, you didn’t pay me anymore. You didn’t recognize me. And I’ve been here for nearly 4 years, and I’ve had to fight you tooth and nail for everything. I’m tired of it.[00:41:34] Mark Stouse: Yeah. That’s what’s called knowing your value. One of the things that I think is so ironic about this entire conversation is that if any function has the skillsets necessary to forecast and demonstrate their value as multipliers. Of business decisions, decision quality, decision outcomes it’s data science.[00:42:05] And yet they just kind of. It’s like not there. And when you say that to them, they kind of look at you kind of like, did you really just say that, and so it is, one of the things that I’ve learned from analytics is that in the average corporation, you have linear functions that are by definition, linear value creators.[00:42:32] Sales would be a great example. And then you have others that are non linear multipliers. Marketing is one, data science is another, the list is long, it’s always the non linear multipliers that get into trouble because they don’t know how to show their value. In the same way that a linear creator can show it[00:42:55] John Thompson: And I think that’s absolutely true, Mark. And what I’ve been saying, and Bill’s heard this until he’s sick of it. Is that, , data science always has to be denominated in currency. Always, if you can’t tell them in 6 months, you’re going to double the sales or in 3 months, you’re going to cut cost or in, , 5 months, you’re going to have double the customers.[00:43:17] If you’re not denominating that in currency and whatever currency they care about, you’re wasting your time.[00:43:23] Dr Genevieve Hayes: The problem is, every single data science book tells you that the metrics to evaluate models by are, precision, recall, accuracy, et[00:43:31] John Thompson: Yeah, but that’s technology. That’s not business.[00:43:34] Dr Genevieve Hayes: exactly. I’ve only ever seen one textbook where they say, those are technical metrics, but the metrics that really count are the business metrics, which are basically dollars and cents.[00:43:44] John Thompson: well, here’s the second one that says it.[00:43:46] Dr Genevieve Hayes: I will read that. For the audience it’s Business Analytics Teams by John Thompson.[00:43:51] John Thompson: building analytics[00:43:52] Dr Genevieve Hayes: Oh, sorry, Building[00:43:54] Mark Stouse: But, but I got to tell you seriously, the book that John wrote that everybody needs to read in business. Okay. Not just data scientists, but pretty much everybody. Is about causal AI. And it’s because almost all of the questions. In business are about, why did that happen? How did it happen? How long did it take for that to happen?[00:44:20] It’s causal. And so, I mean, when you really look at it that way and you start to say, well, what effects am I causing? What effects is my function causing, all of a sudden the scales kind of have a way of falling away from your eyes and you see things. Differently.[00:44:43] John Thompson: of you to say that about that book. I appreciate that.[00:44:46] Mark Stouse: That kick ass book, kick[00:44:48] John Thompson: Well, thank you. But, most people don’t understand that we’ve had analytical or foundational AI for 70 years. We’ve had generative AI for two, and we’ve had causal for a while, but only people understand it are the people on this call and Judea Pearl and maybe 10 others in the world, but we’re moving in a direction where those 3 families of AI are going to be working together in what I’m calling composite AI, which is the path to artificial, or as Bill says, average general intelligence or AGI.[00:45:24] But there are lots of eight eyes people talk about it as if it’s one thing and it’s[00:45:29] Mark Stouse: Yeah, correct. That’s right.[00:45:31] Dr Genevieve Hayes: I think part of the problem with causal AI is it’s just not taught in data science courses.[00:45:37] John Thompson: it was not taught anywhere. The only place it’s taught is UCLA.[00:45:40] Mark Stouse: But the other problem, which I think is where you’re going with it Genevieve is even 10 years ago, they weren’t even teaching multivariable linear regression as a cornerstone element of a data science program. So , they basically over rotated and again, I’m not knocking it.[00:46:01] I’m not knocking machine learning or anything like that. Okay. But they over rotated it and they turned it into some sort of Omni tool, that could do it all. And it can’t do it all.[00:46:15] Dr Genevieve Hayes: think part of the problem is the technical side of data science is the amalgamation of statistics and computer science . But many data science university courses arose out of the computer science departments. So they focused on the machine learning courses whereas many of those things like.[00:46:34] multivariable linear analysis and hypothesis testing, which leads to things like causal AI. They’re taught in the statistics courses that just don’t pop up in the data science programs.[00:46:46] Mark Stouse: Well, that’s certainly my experience. I teach at USC in the grad school and that’s the problem in a nutshell right there. In fact, we’re getting ready to have kind of a little convocation in LA about this very thing in a couple of months because it’s not sustainable.[00:47:05] Bill Schmarzo: Well, if you don’t mind, I’m going to go back a second. We talked about, measuring success as currency. I’m going to challenge that a little bit. We certainly need to think about how we create value, and value isn’t just currency. John held up a book earlier, and I’m going to hold up one now, Wealth of Nations,[00:47:23] John Thompson: Oh yeah.[00:47:25] Bill Schmarzo: Page 28, Adam Smith talks about value he talks about value creation, and it isn’t just about ROI or net present value. Value is a broad category. You got customer value, employee value, a partner stakeholder. You have society value, community value of environmental value.[00:47:43] We have ethical value. And as we look at the models that we are building, that were guided or data science teams to build, we need to broaden the definition of value. It isn’t sufficient if we can drive ROI, if it’s destroying our environment and putting people out of work. We need to think more holistically.[00:48:04] Adam Smith talks about this. Yeah, 1776. Good year, by the way, it’s ultimate old school, but it’s important when we are As a data science team working with the business that we’re broadening their discussions, I’ve had conversations with hospitals and banks recently. We run these workshops and one of the things I always do, I end up pausing about halfway through the workshop and say, what are your desired outcomes from a community perspective?[00:48:27] You sit inside a community or hospital. You have a community around you, a bank, you have a community around you. What are your desired outcomes for that community? How are you going to measure success? What are those KPIs and metrics? And they look at me like I got lobsters crawling out of my ears.[00:48:40] The thing is is that it’s critical if we’re going to Be in champion data science, especially with these tools like these new ai tools causal predictive generative autonomous, these tools allow us to deliver a much broader range of what value is And so I really rail against when somebody says, you know, and not trying to really somebody here but You know, we gotta deliver a better ROI.[00:49:05] How do you codify environmental and community impact into an ROI? Because ROI and a lot of financial metrics tend to be lagging indicators. And if you’re going to build AI models, you want to build them on leading indicators.[00:49:22] Mark Stouse: It’s a lagging efficiency metric,[00:49:24] Bill Schmarzo: Yeah, exactly. And AI doesn’t do a very good job of optimizing what’s already happened.[00:49:29] That’s not what it does.[00:49:30] John Thompson: sure.[00:49:31] Bill Schmarzo: I think part of the challenge, you’re going to hear this from John and from Mark as well, is that we broaden this conversation. We open our eyes because AI doesn’t need to just deliver on what’s happened in the past, looks at the historical data and just replicates that going forward.[00:49:45] That leads to confirmation bias of other things. We have a chance in AI through the AI utility function to define what it is we want our AI models to do. from environmental, society, community, ethical perspective. That is the huge opportunity, and Adam Smith says that so.[00:50:03] John Thompson: There you go. Adam Smith. I love it. Socrates, Aristotle, Adam[00:50:08] Bill Schmarzo: By the way, Adam Smith motivated this book that I wrote called The Economics of Data Analytics and Digital Transformation I wrote this book because I got sick and tired of walking into a business conversation and saying, Data, that’s technology. No, data, that’s economics.[00:50:25] Mark Stouse: and I’ll tell you what, you know what, Genevieve, I’m so cognizant of the fact in this conversation that the summer can’t come fast enough when I too will have a book,[00:50:39] John Thompson: yay.[00:50:41] Mark Stouse: yeah, I will say this, One of the things that if you use proof, you’ll see this, is that there’s a place where you can monetize in and out of a model, but money itself is not causal. It’s what you spend it on. That’s either causal or in some cases, not[00:51:01] That’s a really, really important nuance. It’s not in conflict with what John was saying about monetizing it. And it’s also not in conflict with what. My friend Schmarrs was saying about, ROI is so misused as a term in business. It’s just kind of nuts.[00:51:25] It’s more like a shorthand way of conveying, did we get value[00:51:31] John Thompson: yeah. And the reason I say that we denominated everything in currency is that’s generally one of the only ways. to get executives interested. If you go in and say, Oh, we’re going to improve this. We’re going to improve that. They’re like, I don’t care. If I say this project is going to take 6 months and it’s going to give you 42 million and it’s going to cost you nothing, then they’re like, tell me more, and going back to what Bill had said earlier, we need to open our aperture on what we do with these projects when we were at Dell or Bill and I swapped our times at Dell, we actually did a project with a hospital system in the United States and over 2 years.[00:52:11] We knocked down the incidence of post surgical sepsis by 72%. We saved a number of lives. We saved a lot of money, too, but we saves people’s lives. So analytics can do a lot. Most of the people are focused on. Oh, how fast can we optimize the search engine algorithm? Or, how can we get the advertisers more yield or more money?[00:52:32] There’s a lot of things we can do to make this world better. We just have to do it.[00:52:36] Mark Stouse: The fastest way to be more efficient is to be more effective, right? I mean, and so when I hear. CEOs and CFOs, because those are the people who use this language a lot. Talk about efficiency. I say, whoa, whoa, hold on. You’re not really talking about efficiency. You’re talking about cost cutting.[00:52:58] Those two things are very different. And it’s not that you shouldn’t cut costs if you need to, but it’s not efficiency. And ultimately you’re not going to cut your way into better effectiveness. It’s just not the way things go.[00:53:14] John Thompson: Amen.[00:53:15] Mark Stouse: And so, this is kind of like the old statement about physicists,[00:53:18] if they’re physicists long enough, they turn into philosophers. I think all three of us, have that going on. Because we have seen reality through a analytical lens for so long that you do actually get a philosophy of things.[00:53:38] Dr Genevieve Hayes: So what I’m hearing from all of you is that for data scientists to create value for the businesses that they’re working for, they need to start shifting their approach to basically look at how can we make the businesses needs. And how can we do that in a way that can be expressed in the business’s language, which is dollars and cents, but also, as Bill pointed out value in terms of the community environment.[00:54:08] So less financially tangible points of view.[00:54:11] Bill Schmarzo: And if I could just slightly add to that, I would say first thing that they need to do is to understand how does our organization create value for our constituents and stakeholders.[00:54:22] Start there. Great conversation. What are our desired outcomes? What are the key decisions? How do we measure success? If we have that conversation, by the way, it isn’t unusual to have that conversation with the business stakeholders and they go I’m not exactly sure.[00:54:37] John Thompson: I don’t know how that works.[00:54:38] Bill Schmarzo: Yeah. So you need to find what are you trying to improve customer retention? You’re trying to increase market share. What are you trying to accomplish and why and how are you going to measure success? So the fact that the data science team is asking that question, because like John said, data science can solve a whole myriad of problems.[00:54:54] It isn’t that it can’t solve. It can solve all kinds. That’s kind of the challenge. So understanding what problems we want to solve starts by understanding how does your organization create value. If you’re a hospital, like John said, reducing hospital acquired infections, reducing long term stay, whatever it might be.[00:55:09] There are some clear goals. Processes initiatives around which organizations are trying to create value[00:55:18] Dr Genevieve Hayes: So on that note, what is the single most important change our listeners could make tomorrow to accelerate their data science impact and results?[00:55:28] John Thompson: I’ll go first. And it’s to take your data science teams and not merge them into operational teams, but to introduce the executives that are in charge of these areas and have them have an agreement that they’re going to work together. Start there.[00:55:46] Bill Schmarzo: Start with how do you how does the organization create value? I mean understand that fundamentally ask those questions and keep asking until you find somebody in the organization who can say we’re trying to do this[00:55:57] Mark Stouse: to which I would just only add, don’t forget the people are people and they all have egos and they all want to appear smarter and smarter and smarter. And so if you help them do that, you will be forever in there must have list, it’s a great truth that I have found if you want to kind of leverage bills construct, it’s the economies of ego.[00:56:24] Bill Schmarzo: I like[00:56:24] John Thompson: right, Mark, wrap this up. When’s your book coming out? What’s the title?[00:56:28] Mark Stouse: It’s in July and I’ll be shot at dawn. But if I tell you the title, but so I interviewed several hundred fortune, 2000 CEOs and CFOs about how they see go to market. The changes that need to be made in go to market. The accountability for it all that kind of stuff. And so the purpose of this book really in 150, 160 pages is to say, Hey, they’re not all correct, but this is why they’re talking to you the way that they’re talking to you, and this is why they’re firing.[00:57:05] People in go to market and particularly in B2B at an unprecedented rate. And you could, without too much deviation, do a search and replace on marketing and sales and replace it with data science and you’d get largely the same stuff. LinkedIn,[00:57:25] Dr Genevieve Hayes: for listeners who want to get in contact with each of you, what can they do?[00:57:29] John Thompson: LinkedIn. John Thompson. That’s where I’m at.[00:57:32] Mark Stouse: Mark Stouse,[00:57:34] Bill Schmarzo: And not only connect there, but we have conversations all the time. The three of us are part of an amazing community of people who have really bright by diverse perspectives. And we get into some really great conversations. So not only connect with us, but participate, jump in. Don’t be afraid.[00:57:51] Dr Genevieve Hayes: And there you have it, another value packed episode to help you turn your data skills into serious clout, cash, and career freedom. If you found today’s episode useful and think others could benefit, please leave us a rating and review on your podcast platform of choice. That way we’ll be able to reach more data scientists just like you.[00:58:11] Thanks for joining me today, Bill, Mark, and John.[00:58:16] Mark Stouse: Great being with[00:58:16] John Thompson: was fun.[00:58:18] Dr Genevieve Hayes: And for those in the audience, thanks for listening. I’m Dr. Genevieve Hayes, and this has been value driven data science. The post Episode 53: A Wake-Up Call from 3 Tech Leaders on Why You're Failing as a Data Scientist first appeared on Genevieve Hayes Consulting and is written by Dr Genevieve Hayes.

Crack the secret language of business to elevate your marketing game! This episode unpacks the meaning of "predictive" across industries, the CMO's unique challenges, and why timing is everything. Learn to position better, understand your market, and align strategies to drive top-line revenue.And don't forget! You can crush your marketing strategy with just a few minutes a week by signing up for the StrategyCast Newsletter. You'll receive weekly bursts of marketing tips, clips, resources, and a whole lot more. Visit https://strategycast.com/ for more details.==Let's Break It Down==04:58 Marketers gain respect through understanding business.07:51 B2B marketing benefits from consumer media strategies.12:41 Great products fail without proper market research.14:57 E Street Realty: Innovative, but market not ready.19:52 Positioning is crucial for product launch success.21:36 Founders assume expertise leads to successful positioning.24:34 Executives share issues across multiple departments.31:42 Established brands succeed faster than newer ones.36:05 Global consumer sentiment is extremely low currently.40:30 Marketers focus too much on efficiency metrics.46:12 Marketers must rethink outdated business strategies.==Where You Can Find Us==Website: https://strategycast.com/Instagram: https://www.instagram.com/strategy_cast/Facebook: https://www.facebook.com/strategycast==Leave a Review==Hey there, StrategyCast fans!If you've found our tips and tricks on marketing strategies helpful in growing your business, we'd be thrilled if you could take a moment to leave us a review on Apple Podcasts. Your feedback not only supports us but also helps others discover how they can elevate their business game!

Every marketing team  wants attribution. But weirdly, it's often not that satisfying when they actually get it. I led many multi-touch attribution projects as a consultant, and we got really good at implementing tools, creating taxonomies, and making sure that data was clean.But I found that when you actually showed these reports to a C-level executive, it was usually kind of underwhelming. The data didn't always pass the common sense test. Today's guest thinks there's a better way — Marketing Mix Modelling. It's basically the application of mathematical techniques to model relationships between different variables. However, technology now enables it to happen faster and more cost-effectively than ever before. Thanks to Our SponsorMany thanks to the sponsor of this episode - Knak. If you don't know them (you should), Knak is an amazing email and landing page builder that integrates directly with your marketing automation platform. You set the brand guidelines and then give your users a building experience that's slick, modern and beautiful. When they're done, everything goes to your MAP at the push of a button. What's more, it supports global teams, approval workflows, and it's got your integrations. Click the link below to get a special offer just for my listeners. Try Knak About Today's Guest Mark Stouse is CEO of ProofAnalytics.AI. With over 26 years of experience in marketing communications and strategy, he has a passion for transforming GTM performance with data-driven insights and agile decision making. Prior to founding Proof, Mark was CMO at Honeywell Aerospace, CCO at BMC Software, and a marketing leader at Hewlett Packard Enterprise. https://www.linkedin.com/in/markstouse/Key Topics[00:00] - Introduction[01:15] - Clarifying the acronym “MMM”[02:39] - Mark's background and how he founded Proof Analytics [07:57] - Limitations of multi-touch attribution (“MTA”)[14:16] - How MMM avoids the shortcomings of MTA[16:42] - The Fischer Price definition of MMM[19:56] - Demand vs. brand investments and their impact[24:09] - A/B vs. multivariate regression[25:21] - MMM is aggregate modelling, no reliance on PII[27:12] - Simple explanation of multi-variate regression[30:29] - Incorporating third-party data sources[31:48] - Historical ROI vs. forecasted ROI[32:52] - Is MMM just for enterprise?[34:51] - Marketing as a non-linear multiplier[38:02] - Getting started with MMM[41:18] - Updating models to include new data sources[42:07] - Competition in the marketing analytics space[44:41] - B2C marketing is more advanced in usage of multi-variate regressionResource LinksProof Analytics - Official SiteEconometrics // Lecture 1: Introduction Learn MoreVisit the RevOps FM Substack for our weekly newsletter: Newsletter

Correlation does not equal causation, as anyone who has studied statistics or data science would know. But understanding causality isn't just important when you're developing models.If you're working in business and want to be recognised for your work, it's essential to be able to demonstrate causality between what you do and the benefit flowing through to the business.In this episode, Mark Stouse joins Dr Genevieve Hayes to discuss how data science can be used to comprehend the underlying cause-and-effect relationships in business data.Guest BioMark Stouse is the CEO of Proof Analytics, an AI-driven marketing analytics platform. Prior to becoming an analytics software CEO, Mark had a successful career in B2B marketing and in 2014 was named Innovator of the Year at the Holmes Report In2 SABRE Awards for his work in tying marketing and communication investment to key business performance metrics.Talking PointsThe benefits to organisations of understanding causality.How such techniques can be applied to use cases and disciplines beyond marketing analytics.How data scientists can drive conversations about analytics at the C-suite level to maximise their impact.The potential future impact of generative AI on data science and the world in general.LinksConnect with Mark on LinkedInProof AnalyticsConnect with Genevieve on LinkedInBe among the first to hear about the release of each new podcast episode by signing up HERE

Genevieve Hayes Consulting Episode 30: Cause and Effect Data Science Correlation does not equal causation, as anyone who has studied statistics or data science would know. But understanding causality isn't just important when you're developing models.If you're working in business and want to be recognised for your work, it’s essential to be able to demonstrate causality between what you do and the benefit flowing through to the business.In this episode, Mark Stouse joins Dr Genevieve Hayes to discuss how data science can be used to comprehend the underlying cause-and-effect relationships in business data. Guest Bio Mark Stouse is the CEO of Proof Analytics, an AI-driven marketing analytics platform. Prior to becoming an analytics software CEO, Mark had a successful career in B2B marketing and in 2014 was named Innovator of the Year at the Holmes Report In2 SABRE Awards for his work in tying marketing and communication investment to key business performance metrics. Talking Points The benefits to organisations of understanding causality.How such techniques can be applied to use cases and disciplines beyond marketing analytics.How data scientists can drive conversations about analytics at the C-suite level to maximise their impact.The potential future impact of generative AI on data science and the world in general. Links Connect with Mark on LinkedInProof Analytics Connect with Genevieve on LinkedInBe among the first to hear about the release of each new podcast episode by signing up HERE The post Episode 30: Cause and Effect Data Science first appeared on Genevieve Hayes Consulting and is written by Dr Genevieve Hayes.

Mark Stouse is the Chairman and CEO of ProofAnalytics.ai, the only AI-native platform that enables GTM teams to plan, predict, prove, and pivot their investments in real time.In this interview, we discuss some of the hard truths about being a founder of a multi-million dollar company, and why he doesn't regret it for a second.https://proofanalytics.ai----#entrepreneurship #entrepreneur #psychology #business #startup #interview #podcast #welivetobuild Hosted on Acast. See acast.com/privacy for more information.

In this episode of Chasing the Insights, I talk to analytics guru Mark Stouse. Mark talks to us about utilizing marketing mix modeling (MMM). Mark Stouse is the CEO of Proof Analytics, a marketing analytics platform that helps CMOs and CFOs bridge the ROI gap by providing cause-and-effect analytics that shows marketing and sales true business impact and financial worth. The company's 'Proof Business GPS' guides through the whole marketing lifecycle, and provides a complete picture of a company's marketing efforts. Their solution enables planning, budgeting, and optimization of marketing in all channels. An award-winning B2B CMO and CCO, Mark is one of the first leaders to connect all types of marketing investment to revenue, margin, and cash flow impact in complex, long-cycle companies. In 2014, he was named Innovator of the Year for his pioneering work by U.S. marketing leaders.

Episode OverviewIn this 38th episode of the CDO Matters Podcast, Malcolm interviews Mark Stouse, the Founder and CEO of Proof Analytics. An accomplished business leader with decades of experience in leading data science initiatives, Mark shares his perspectives on the growing frustration that many organizations are experiencing because of an inability to realize significant benefits from investments in data management and data science.The risks of CDOs saying they aren't ‘ready' to provide business value from AI and data science are real and increasingly unwelcome from companies looking for more immediate returns from their data teams. This is producing an immediate need for CDOs to be unabashedly lean, with an unrelenting focus on a very limited number of specific business needs and outcomes.Episode Links and ResourcesFollow Malcolm Hawker on LinkedInFollow Mark Stouse on LinkedIn

IN CLEAR FOCUS: Seasoned marketing executive and serial entrepreneur Mark Stouse discusses the importance of analytics and having a single source of truth for informed business decision-making. Mark explains how his platform, ProofAnalytics.ai, aids businesses in tracking progress and making strategic decisions supported by artificial intelligence. Mark also reflects on the critical differences between being data-driven and analytics-led, sharing leadership insights from his forthcoming book.  

In this episode of Master Marketer Show, host Mike Grinberg sits down with Mark Stouse, founder and CEO of Proof Analytics, to delve into the often overlooked elements of time lag and opportunity cost in the B2B marketing landscape. Discover how understanding these factors can optimize your marketing efforts and drive revenue effectively. Gain actionable insights into leveraging data, analytics, and relationship-led growth strategies for business success. Don't miss out on this valuable conversation with two marketing trailblazers!

In this episode of Master Marketer Show, host Mike Grinberg sits down with Mark Stouse, founder and CEO of Proof Analytics, to delve into the often overlooked elements of time lag and opportunity cost in the B2B marketing landscape. Discover how understanding these factors can optimize your marketing efforts and drive revenue effectively. Gain actionable insights into leveraging data, analytics, and relationship-led growth strategies for business success. Don't miss out on this valuable conversation with two marketing trailblazers!

The most listened-to episode of Season 1 is still about how to go to market with Andrew Davis, and for this reason we are going to dive deeper into this same particular topic on How to plan, predict and prove your Go To Market plan. Our subject matter expert is Mark Stouse, CEO of Proof Analytics, an AI-powered platform for GTM.Mark's has 30 years in marketing, He was CMO for 10 years, now CEO at Proof Analytics.  Crafting a successful Go-To-Market (GTM) plan requires a strategic approach encompassing planning, prediction, and validation. Begin by meticulously planning each phase, outlining key objectives, target audience, and messaging. Leverage market research to predict trends and customer needs, ensuring your GTM plan remains adaptable to dynamic market landscapes. Implement analytics tools to measure and prove the plan's effectiveness, tracking key performance indicators (KPIs) such as customer acquisition cost, conversion rates, and revenue growth. Regularly reassess and refine your strategy based on data-driven insights to stay ahead in a competitive market. A well-structured GTM plan, grounded in foresight and substantiated by measurable results, is the cornerstone for achieving sustained market success. Key Timecodes (0:29) Show and guest intro (1:14 ) Why you should listen to Mark Stouse (3:28) What is Go to market?  (5:19) What kind of role does AI play in a go-to-market strategy? (6:44)  What is marketing mix modeling? (11:02)   Common mistakes companies make while building their go-to-market strategy (12:07) Mark's process for market strategy from scratch. (17:23) Things successful companies have in common in regards to to go-to-market strategies (18:39) What Common challenges are faced when taking your company or product code to the market? (21:18)  The right timing to pivot?  (22:54) Advice on how to grow to 10 K monthly recurring revenue. (25:44) How to grow towards 10 million ARR (30:42) What Mark wishes he knew 10yrs ago

Mark Stouse is the CEO of Proof Analytics, a sales and marketing analytics platform that helps CMOs and CFOs bridge the ROI gap by providing cause-and-effect analytics that shows true business impact and financial worth. The company's ‘Proof Business GPS' guides businesses through the whole marketing lifecycle, and provides a complete picture of a company's marketing efforts. Their solution enables planning, budgeting, and optimization of marketing in all channels. An award-winning B2B CMO and CCO, Mark is one of the first leaders to connect all types of marketing investment to revenue, margin, and cash flow impact in complex, long-cycle companies. In 2014, he was named Innovator of the Year for his pioneering work by U.S. marketing leaders. What you will learn Mark's journey in building his software platform Proof Analytics How to develop a good reputation in B2B marketing How Proof Analytics is implementing AI into their systems Mark shares the onboarding process for businesses interested in Proof Analytics How to decide whether your company should outsource analytics or manage it in-house Why it's critical to understand your own limitations and be open to learning throughout the entrepreneurial journey How detailed analytics can help you make confident business decisions Mark shares his key learnings as an entrepreneur Plus loads more!

Proof isn't just about data – it's about unlocking the potential within every decision. Harness the power of data-driven navigation and make your go-to-market journey a triumph of strategy and success. In this illuminating discussion, we sit down with Mark Stouse, the visionary founder of Proof Analytics, a groundbreaking analytics solution that's revolutionizing the way businesses approach marketing performance. Mark shares the trials and triumphs of building Proof, detailing the meticulous process of finding the right market fit and fine-tuning its offerings. He also highlights the power of iteration and feedback loops to the success of the product's direction. From identifying the Ideal Customer Profile (ICP), embracing the feedback wave, and predicting the future of analytics, Mark reveals plenty of wisdom and strategies in the episode. Tune in now to explore the wonders of Proof and understand how to navigate success!Love the show? Subscribe, rate, review, and share! http://stratyve.com/

Are you ready to unlock the secrets of successful B2B marketing and business growth? In this episode of Predictable B2B Success, host Vinay Koshy sits down with the renowned guest, Mark Stouse, an expert in marketing, data science, and collaboration. Prepare to be fascinated and intrigued as Mark takes us on a journey through the annals of history, discussing the contrasting approaches to innovation in 15th-century Italy and Germany. But this episode isn't just about history. Mark dives deep into the pressing issues facing Chief Data Officers (CDOs) and data science teams in today's rapidly changing business landscape. They discuss the challenges of providing timely and actionable insights, the subordination of data science teams to finance, and the evolving role of technology in decision-making.  Get ready to discover how Proof, Mark's groundbreaking analytics platform, is revolutionizing how businesses make predictions and optimize their choices to facilitate growth in a business. Learn about the importance of clean, accurate data in lean data applications, the impact of collaboration on problem-solving, and how aligning customer beliefs with data can drive success.  If you're ready to gain a fresh perspective on business growth and elevate your decision-making with analytics, then this episode is a must-listen. Join us as we unravel the mysteries of marketing, data science, and collaboration in this captivating episode with Mark Stouse. Some areas we explore in this episode include: The Historical Study of Innovation in 15th-century Italy and GermanyChallenges faced by CDO communities in providing data insights and analyticsSubordination of data science teams to finance teamsThe Proof platform and its capabilities in providing analytics and regression modelingThe need for better predictions and decision-making in the current era of change and volatilityThe role of Proof as a GPS-like platform for tracking and optimizing choices based on forecasts and real-time dataThe importance of collaboration between analysts and business users in utilizing analyticsThe limitations of traditional marketing mix modeling and the solutions provided by ProofThe shortcomings in forecasting accuracy in B2B companies and the lack of discipline in analytics knowledgeThe speaker's experience in collaborating with data scientists and the importance of perspective in utilizing analytics.And much, much more.

Mark is the CEO of Proof Analytics, a sales and marketing analytics platform that helps CMOs and CFOs bridge the ROI gap by providing cause-and-effect analytics that shows marketing and sales true business impact and financial worth.  In this episode, Mark shares his insights on the future of work and how individuals are becoming more entrepreneurial within a corporate setting. He also dives into the importance of having a strong foundation and skillset before jumping into a startup, and the value of self-assessment and acquiring necessary skills.  Mark offers advice on how to connect with him on LinkedIn and emphasizes his focus on business development and helping others. He also discusses his work in marketing analytics and the powerful automation platform he has built called Proof. Mark delves into the importance of innovation in sales and the ever-changing landscape of the market. He highlights the need to understand the real game being played in business and offers valuable tips for success. Lastly, Mark explores the concept of taking extreme ownership in sales, treating your work as your own franchise, and the benefits of having your own CRM system. Get ready for an enlightening and thought-provoking episode with Mark Stouse on the High Tech Freedom Sales Podcast! Contact Mark at https://www.linkedin.com/in/markstouse/  Enter our monthly drawing for an insulated High Tech Freedom tumbler - www.hightechfreedom.com/mug   Host Contact Information - Chris Freeman LinkedIn - http://linkedin.com/in/chrisfreeman Facebook - https://www.facebook.com/chris.freeman.9461

Mark Stouse is the CEO of Proof Analytics, a sales and marketing analytics platform that helps CMOs and CFOs bridge their ROI gap. He is an award-winning B2B CMO and CCO and has been a pioneer in connecting marketing investments to revenue, margin, and cash flow. In this episode of the Stronger Sales Teams podcast, host Ben Wright interviews Mark Stouse, the Managing Director and Founder of Proof Analytics. They discuss various topics related to sales leadership and performance, particularly in times of adversity. Mark shares his insights on learning hacks, the importance of continuous improvement, and the role of leaders in maintaining alignment within their teams. He emphasizes the need for leaders to take responsibility for their team's performance and to create a safe environment for learning and growth. Key Takeaways: Being on podcasts and engaging in conversations helps consolidate thoughts and generate new ideas. Continuous learning and building a broad knowledge base are essential for effective leadership. Leaders are responsible for maintaining alignment within their teams and clearly enunciating expectations. Leaders should not be too hard on themselves during tough times and should acknowledge and learn from their mistakes. 0:00 Intro 1:14 Recap 1:43 Top Learning Hacks 5:00 Learning Technology 8:17 Bringing Back a Member's Alignment 11:43 Apologizing 14:10 Outro About our guest: Mark is the CEO of Proof Analytics, a sales and marketing analytics platform that helps CMOs and CFOs bridge the ROI gap by providing cause-and-effect analytics to show marketing and sales true business impact and financial worth. The company's 'Proof Business GPS' guides through the whole marketing lifecycle, and provides a complete picture of a company's marketing efforts. Their solution enables planning, budgeting, and optimization of marketing in all channels. An award-winning B2B CMO and CCO, Mark is one of the first leaders to connect all types of marketing investment to revenue, margin, and cash flow impact in complex, long-cycle companies. In 2014, he was named Innovator of the Year for his pioneering work by U.S. marketing leaders. Rate, Review, & Follow If you're liking what you're hearing, make sure you ‘follow' the show wherever you listen to your podcasts…so you never miss an episode!I'd also love to hear what you think, so drop us a review after you close that next deal…tell me what you're liking, and what you want more of so I can look to cover it in a future episode.

Mark Stouse is the CEO of Proof Analytics, a sales and marketing analytics platform that helps CMOs and CFOs bridge their ROI gap. He is an award-winning B2B CMO and CCO and has been a pioneer in connecting marketing investments to revenue, margin and cash flow. In this episode of Stronger Sales Teams Podcast, Mark Stouse, CEO of Proof Analytics, discusses the challenges that CEOs and CFOs face in understanding the true business impact and financial worth of their marketing and sales efforts. He introduces Proof Business GPS, a platform that provides cause and effect analytics to optimize marketing and sales strategies. Stouse explains that in 2023 and beyond, go-to-market optimization will require a cohesive approach that considers the entire customer experience. He emphasizes the importance of experience and adversity in sales teams and offers advice on how sales leaders can prepare their teams for challenging times. Key Takeaways: CEOs and CFOs are increasingly seeking cause and effect analytics to understand the true business impact of marketing and sales efforts. Go-to-market optimization in 2023 and beyond will require a cohesive approach that considers the entire customer experience. Sales leaders should value experience and adversity in their teams to prepare for challenging times. Empathy and leading from the front are key to gaining alignment and engagement from sales teams in difficult times. 0:00 Intro 1:19 Guest Introduction 2:45 About Mark Stouse and Proof Analytics 7:38 What's Changed in the World of Go-to Market Optimization 11:34 Behaviors that A Sales Leaders Should Focus On 14:50 Preparing the Team for What's Ahead 17:35 Aligning Your Team 20:22 Outro About our guest: Mark is the CEO of Proof Analytics, a sales and marketing analytics platform that helps CMOs and CFOs bridge the ROI gap by providing cause-and-effect analytics to show marketing and sales true business impact and financial worth. The company's 'Proof Business GPS' guides through the whole marketing lifecycle, and provides a complete picture of a company's marketing efforts. Their solution enables planning, budgeting, and optimization of marketing in all channels. An award-winning B2B CMO and CCO, Mark is one of the first leaders to connect all types of marketing investment to revenue, margin, and cash flow impact in complex, long-cycle companies. In 2014, he was named Innovator of the Year for his pioneering work by U.S. marketing leaders. Rate, Review, & Follow If you're liking what you're hearing, make sure you ‘follow' the show wherever you listen to your podcasts…so you never miss an episode!I'd also love to hear what you think, so drop us a review after you close that next deal…tell me what you're liking, and what you want more of so I can look to cover it in a future episode.

There is a huge difference between being data-driven, which honestly is like saying, I make all my decisions based on the past, and being analytics led, which is, saying, I make my decision based on how things are actually operating now in a cause-and-effect relationship. In this episode, I sit down with Mark Stouse Founder & CEO of Proof Analytics. Mark shares his experience on the importance of data-driven decision-making in B2B marketing, his thoughts on the limitations of AI, and the importance of human intuition in data analysis. Chapters: (00:00) Intro (01:39) What is Proof Analytics? (03:14) Proof Analytics products (05:52) How does these models come to play? (11:04) The thin line between accurate data and semi-accurate data (13:34) Model overfitting (19:05) Ideal customer profile (24:55) The Background (33:43) Sales and Marketing in B2B (44:04) Lightning round Guest Contact Info: ⁠⁠⁠Website⁠⁠⁠ ⁠⁠linkedin.com/markstouse Sponsor: This podcast is brought to you by ⁠⁠⁠⁠⁠grwth.co⁠⁠⁠⁠⁠. Grwth offers fractional CMOs, paired with best-in-class digital marketing execution to support early-stage startup success. With a focus on seed and series A companies, Grwth has helped a number of SaaS, digital health, and e-commerce startups build their go-to-market function and scale up. To learn more and book a free consultation, go to ⁠⁠⁠⁠⁠grwth.co⁠⁠⁠⁠⁠. Get in touch with Mosheh: ⁠⁠⁠⁠⁠linkedin.com/in/moshehp⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠twitter.com/MoshehP⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠hello@pmfpod.com ⁠⁠⁠⁠⁠⁠www.pmfpod.com

In this special episode of SaaS Origin Stories, Phil brings you the season finale of the season. Dan Martell, Mark Stouse, Dani Grant, Brandon Metcalf, Ajay Goel, Geoff Roberts, Chris Frantz, Rand Fishkin, Jason Radisson, and Rex Kurzius share their experiences and insights on various topics in the startup world. They discuss their journeys as founders, the challenges they faced, and the strategies they used to build successful companies. They also touch on topics such as fundraising, product development, marketing strategies, and the importance of understanding the needs of your target audience. They provide valuable insights and advice for aspiring entrepreneurs.Guests at a Glance:Dan Martell on LinkedInMark Stouse on LinkedInDani Grant on LinkedInBrandon Metcalf on LinkedInAjay Goel on LinkedInGeoff Roberts on LinkedInChris Frantz on LinkedInRand Fishkin on LinkedInJason Radisson on LinkedInRex Kurzius on LinkedInLinks from the episode:SaaS AcademyBuy Back Your TimeProofMisbehavior of MarketsJam.devPlaceThe Hard Things About Hard Things by Ben HorowitzGMassOutsetaLoopsSparkToroRappi99 Uber TechnologiesAsset PandaLinks to full episodes:Building A Multimillion Dollar SaaS Company From Scratch with Dan Martell of SaaS Academy5 Things They Didn't Teach You About Leading a SaaS Business with Mark Stouse of ProofThe SaaS Product Market Fit Toolkit with Dani Grant of Jam.dev5 Things Every SaaS Founder Should Know About Navigating The World Of Startups with Brandon Metcalf of PlaceHow To Shoestring Your SaaS with Ajay Goel of GMassWhat SaaS Companies Need To Know About Content Marketing with Geoff Roberts of OutsetaHow to Refine your SaaS Product with Chris Frantz of LoopsThe End of VC with Rand Fishkin of SparkToroExploring the SaaS Impact of AI & ChatGPT with Jason Radisson from MovoHow This SaaS Founder Fixed an Outdated Business Model with Rex Kurzius of Asset PandaTopics we cover:[01:23] - From Coding to Reading: Dan Martell's Journey of Self-Driven Education[05:37] - Mark Stouse discusses the Origin, Development, and Unique Funding Approach of Proof Analytics[09:59] - Dani Grant's Insights: Transition from VC to Founder and Navigating Fundraising[14:40] - Brandon Metcalf's Journey: From Staffing to SaaS Funding and Mastering Salesforce[19:47] - Ajay Goel on Building GMass, and Navigating Operational Costs and Monetization[24:22] - Geoff Roberts on the Journey of Outseta: Part-time Beginnings, Bootstrapping Over VC Funding, and Leveraging Unique Marketing Strategies[29:50] - Chris Frantz discusses the Art of Software Craftsmanship, Early Fundraising, and Building Loops from Scratch to Simplicity[34:35] - Independent Pathways and Rigorous Research: Rand Fishkin's Journey to Build SparkToro[41:11] - Jason Radisson's Insights: Building a Tech-Enabled Business from Ground Up[47:40] - Identifying and Solving Market Problems: Rex Kurzius on Asset Management Evolution

Mark Stouse grew his startup, ProofAnalytics.ai, from $0 to $2 million in revenue in 18 months. Now they're one of the 100 partners for Salesforce and they're still growing. Their client roster includes mega brands like Bayer, Samsung, Johnson Controls, Oracle, and others. Show links, notes, and transcript: https://parisvega.com/mark-stouse-proof-analytics/ --- Send in a voice message: https://podcasters.spotify.com/pod/show/first-customers/message

Join Kevin and Mark Stouse to hear concrete ideas for aligning sales and marketing to drive corporate goals.Mark is the CEO of Proof Analytics, a marketing analytics platform that helps CMOs and CFOs bridge the ROI gap by providing cause-and-effect analytics that shows marketing and sales true business impact and financial worth. The company's 'Proof Business GPS' guides through the whole marketing lifecycle and provides a complete picture of a company's marketing efforts. Their solution enables planning, budgeting, and optimization of marketing in all channels. An award-winning B2B CMO and CCO, Mark is one of the first leaders to connect all types of marketing investment to revenue, margin, and cash flow impact in complex, long-cycle companies. In 2014, he was named Innovator of the Year for his pioneering work by U.S. marketing leaders.Connect with Mark: https://www.linkedin.com/in/markstouse/The podcast is brought to you by Sales Code, helping revenue leaders unlock added value in B2B SaaS sales teams.We welcome your views on our podcast and questions you might have for our podcast guests.Connect with the show host: Kevin Thiele:https://www.linkedin.com/in/kevinthiele/

Mark Stouse, CEO of Proof Analytics, talks about analytics and marketing mix modeling. While popular, ‘data-driven marketing' fails to account for a constantly changing reality. As such, campaigns based on historical and not future data, have limited success. Today, Mark discusses marketing mix modeling and marketing attribution. Show NotesConnect With: Mark Stouse: Website // LinkedInThe MarTech Podcast: Email // LinkedIn // TwitterBenjamin Shapiro: Website // LinkedIn // TwitterSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Mark Stouse, CEO of Proof Analytics, talks about analytics and marketing mix modeling. While popular, ‘data-driven marketing' fails to account for a constantly changing reality. As such, campaigns based on historical and not future data, have limited success. Today, Mark discusses marketing mix modeling and marketing attribution. Show NotesConnect With: Mark Stouse: Website // LinkedInThe MarTech Podcast: Email // LinkedIn // TwitterBenjamin Shapiro: Website // LinkedIn // TwitterSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Mark Stouse, CEO of Proof Analytics, talks about analytics and marketing mix modeling. We often get so caught up with operational KPIs that we lose sight of our revenue goals as marketers. Furthermore, to determine the impact of our marketing efforts, we must be able to measure our results. Today, Mark discusses tying marketing to measurable results. Show NotesConnect With: Mark Stouse: Website // LinkedInThe MarTech Podcast: Email // LinkedIn // TwitterBenjamin Shapiro: Website // LinkedIn // TwitterSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Mark Stouse, CEO of Proof Analytics, talks about analytics and marketing mix modeling. We often get so caught up with operational KPIs that we lose sight of our revenue goals as marketers. Furthermore, to determine the impact of our marketing efforts, we must be able to measure our results. Today, Mark discusses tying marketing to measurable results. Show NotesConnect With: Mark Stouse: Website // LinkedInThe MarTech Podcast: Email // LinkedIn // TwitterBenjamin Shapiro: Website // LinkedIn // TwitterSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Mark Stouse, CEO of Proof Analytics, talks about analytics and marketing mix modeling. Our world has changed considerably since 2020, and intuition-based marketing is a sure recipe for wasted time and resources. Marketers must take advantage of analytics and data to understand and thrive in our respective markets. Today, Mark discusses marketing innovation and rev ops. Show NotesConnect With: Mark Stouse: Website // LinkedInThe MarTech Podcast: Email // LinkedIn // TwitterBenjamin Shapiro: Website // LinkedIn // TwitterSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Mark Stouse, CEO of Proof Analytics, talks about analytics and marketing mix modeling. Our world has changed considerably since 2020, and intuition-based marketing is a sure recipe for wasted time and resources. Marketers must take advantage of analytics and data to understand and thrive in our respective markets. Today, Mark discusses marketing innovation and rev ops. Show NotesConnect With: Mark Stouse: Website // LinkedInThe MarTech Podcast: Email // LinkedIn // TwitterBenjamin Shapiro: Website // LinkedIn // TwitterSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Breaking Barriers: Reclaim Your Success in a Shifting Market In an era marked by volatility and mistrust, trust and empathy play a critical role in building mark.stouse@proofanalytics.ai Twitter: markstouse -- If you're looking for clear direction navigating the changing market, build a consistent pipeline of quality leads, close more profitable deals, more often, let's talk. Let's find 15 minutes, we can see if there's a fit. Click the link https://calendly.com/marcuscauchi.  

What's wrong with the CMO & and business? Today's modern marketing leaders are struggling to hold tenure and create confidence in the C-Suite. Why is that?Mark Stouse returns and expands on what he's seeing happen in the market as we face changing economic headwinds.Join us as we take an inside look at what it takes to drive change and create a true voice of marketing in the C-Suite.Support the show

Welcome to Eggs! the Podcast, featuring the best and brightest minds in business leadership, entrepreneurship, and technology. Today we have a special guest, Mark Stouse, CEO of Proof Analytics. Mark is an award-winning B2B CMO and CCO who connects all types of marketing investment to revenue, margin, and cash flow impact in complex, long-cycle companies. Today we'll chat with Mark about a number of topics, including marketing, innovation, and revenue optimization, as well as how to utilize marketing to deliver measurable business results. We'll also be discussing his company's marketing analytics platform and their powerful “Proof Business GPS,” which guides companies through the whole marketing lifecycle and provides a complete picture of their marketing efforts. So sit back, relax, and let's get cracking with Mark Stouse on Eggs!Our Guest:Mark StouseCEO at Proof AnalyticsProofAnalytics.ai----Credits:Hosted by Ryan Roghaar and Michael SmithTheme music: "Perfect Day" by OPMThe Carton:https://medium.com/the-carton-by-eggsThe Eggs Podcast Spotify playlist:bit.ly/eggstunesThe Plugs:The Showeggscast.com@eggshow on twitter and instagramOn iTunes: itun.es/i6dX3pCOn Stitcher: bit.ly/eggs_on_stitcherAlso available on Google Play Music!Mike "DJ Ontic" shows and infodjontic.com@djontic on twitterRyan Roghaarhttp://rogha.ar

Mark Stouse is the Chairman and CEO of Proof. With an extensive CMO background, Mark shares his career history as well as lessons learned as a CEO, including how to get out of your own way and keeping your ego in check. Learn more about Mark's career path to becoming a CEO, the roles of leaders, as well as the top challenges in B2B marketing.    Key Takeaways: [1:40] An introduction of Mark and his education background. [4:40] How a degree in the liberal arts prepared him well for a career in marketing [6:55] How Mark transitioned from CMO to CEO [9:55] How Mark overcame the challenge of being heavily involved in the day-to-day marketing operations once a CEO [11:15] Life is a series of numerator and denominator relationships. Mark explains what this means. [13:45] Although Mark has become a much better person and leader, being a CEO has been the most challenging role he's taken on to date [17:30] Mark has a policy that he doesn't sell on LinkedIn. Here's why. [22:45] Are CMOs well suited to be CEOs? [31:00] What are the six responsibilities of a CEO? [37:35] What does Proof Analytics do? [45:45] Marketing is the first one to get their budgets cut because they do not have the data to prove their ROI [47:50] No matter how good Mark's marketing team did, they simply weren't taken seriously. Mark got into analytics to fix that. [49:10] Mark answers the rapid-fire marketing questions.   Mentioned in This Episode: Demandspring.com Proofanalytics.ai Mark on LinkedIn  

Mark Stouse, CEO of data analytics platform Proof Analytics, discusses the difference between marketing mix modelling (MMM) and marketing resource management (MRM) and how they can demonstrate the impact of marketing activities on business bottom line. Mark also explains why it is vital to trust and use math when making marketing decisions and why pressure from the C-suite means this is increasingly important.

Proof Chairman and CEO Mark Stouse knows that true business transformation happens through relevant predictive analytics, not just collecting huge amounts of data. Learn how teams can transcend from just good enough to exceptional by becoming vibrant organisms that interpret change in making better decisions.

Episode Summary:In this episode of SaaS Origin Stories, Mark Stouse, Chairman and CEO of Proof, joins host Phil Alves. Proof offers an analytic tool used by sales, revenue, and analytics teams. The company is a five-year-old SaaS startup with a revenue pipeline of over four and a half million.Mark is a former CCO and CMO at multi-billion dollar enterprises like Honeywell and HP. He shares his perspective of an older founder and walks us through his journey from a unique funding concept to market fit, positioning, and pricing. Along the way, he shares his insights on leadership traits. Guest at a Glance:Name: Mark StouseWhat he does: Mark is the Founder, Chairman, and CEO of Proof, a SaaS company that offers an analytic tool used by sales, revenue, and analytics teams. He has been a CCO and CMO at multi-billion dollar enterprises like Honeywell and HP.Mark on LinkedInProof on LinkedInMark's Book Recommendation Misbehavior of MarketsTopics we cover:Things they don't teach you about leadershipA unique funding modelYou have way less than a one percent chance of founding a unicornA unique way of attracting customersKnow these facts before embarking on your startup journeyHighlights:Everything They Don't Teach, but You Should Know About LeadershipIt all starts with a shift in mindset. Trying to be indispensable at work is akin to slavery. They'll never promote you if you're indispensable, and you'll be stuck in a box. Leaders build teams that are collectively smarter than the leader, and sooner or later, the leader becomes dispensable—time to move on to bigger challenges. You need to be a leader before becoming a founder.“As a leader, it's my job to ask the best questions and not be the smartest person in the room”. Discovering Family Office Funding for a SaaS StartupMark made a conscious decision to avoid venture funding as VC expectations and benchmarks distort the nurturing phase of startups. Mark instead tapped into family office funding, a network of privately held companies that do wealth and asset management for high net-worth individuals. The family office is a tightly knit community, and the companies in a given niche talk to each other. Hence, if you can get one of them on board and have a successful proof of concept, the other family offices will knock on your door.  “We went with family offices that were in the software space and tied up funding rounds linked to performance gateways”.Set Realistic Goals; You're not Founding a Unicorn.Mark cautions founders, especially young founders, from setting unrealistic goals for their startups. Goals and performance gateways need to be realistic because no matter how unique and revolutionary your idea is, it's a brutal market out there. Also, there's a high chance that someone bigger than you and who has been around for longer is doing the same thing, maybe in just a slightly different way. “It's great if you build a unicorn and sell it for a billion dollars, just know that the real-world chances of that happening are way less than one percent”.A Unique Strategy for Building Trust and Attracting CustomersAt Proof, Mark uses conventional digital tools like ABM to achieve the marketing goal of converting leads into sales. However, much of his time to date is still devoted to posting on LinkedIn. He follows relevant conversations and offers free tips and advice. This helps build trust among his audience, and he counts on the audience to spread the word and create awareness. It also makes the audience more likely to convert when Mark recommends Proof as a solution. Mark is also a fan of the marketing mix modelling.“I participate below a relevant post and offer help to people; I'm like a free consultant. It helps build trust with the audience”.  One Person' Hindsight Is Another's ForesightKnow that being an entrepreneur will teach you things you can't learn anywhere else. Get ready to devote almost every waking moment to building and thinking about your SaaS. Get prepared to fail in front of an audience and know how to handle those situations. Be ready to pivot if your proof of concept proves that there are no takers for your exact idea but there is a crying need for something slightly different. Another must-have is the ability to talk in your audience's language. If you're qualifying your SaaS product in technical terms to a CMO, you will not make the sale. Instead, qualify your product in impact on marketing goals.   “We talk about product-market fit, but the real challenge is to qualify and sell your product in a language your audience understands”.

Confidence and trust are at the heart of great leadership. These two elements build great relationships with employees, employers, customers, partners, etc. whether the relationship is personal or professional in nature. While we see countless examples in the media where confidence and trust have been broken, there is always an opportunity to do the right thing and lead in a way that builds confidence and trust. In this episode of the B2B Leadership podcast, I spoke with Mark Stouse, Chairman and CEO at Proof Analytics. Mark has experienced the world that is possible when confidence and trust are at the center and when they are not (you have to hear the backstory on this). He and his team at Proof Analytics are champions of the truth with their clients, employees, and partners. The level of trust built has earned them incredible customer renewal and expansion rates. Podcast highlights: 0:20 - Mark's background - Mark explains his role at Proof Analytics. 1:39 - Proof Analytics' target audience - Mark explains the type of marketing organizations he works with. 3:58 - First leadership position - Mark considers his journey to be a very long and winding road. 7:05 - Good and bad leadership - What has Mark learned from experiencing varying qualities of leadership? 13:50 Exiting politics and finding a new role - Mark had an epiphany and decided he wanted a career change. 17:23 - Proof Analytics' culture - What kind of people did Mark want to surround himself with? 22:07 - Managing customer and team expectations - As a CEO, how does Mark toe the line of keeping both sides happy? 30:36 - Actions speak louder than words - Mark asks potential customers specific questions before working with them. 39:48 - Mark's advice to himself - What advice would Mark give his younger self? Learn more about Proof Analytics at https://www.proofanalytics.ai/ Learn more about your own leadership style at: https://www.b2bleadersacademy.com/ #Leadership #B2bleadership #BusinessLeader This episode is brought to you by the B2B Leaders Academy The cost of not consistently developing your leadership skills is enormous. At the B2B Leaders Academy you can gain access to monthly leadership training and live coaching. Being a great leader isn't hard, you just need a guide and the right set of tools. Head on over to b2bleadersacademy.com and become the leader you have always wanted to be.

The difference between good and bad marketing can be seen in sales results, right? Yes and no. Though marketing is important to all companies, most business leaders see marketing as a support for sales and don't appreciate the value it drives. Mark Stouse, Chairman and Chief Executive Officer of Proof Analytics, is on a mission to change that game through data analytics. So how can data analytics help marketing teams drive revenue optimization and growth? Mark joins us to answer that question and discuss marketing innovation, revenue optimization, and how marketing can lead the way to deliver measurable business results.

Sima is delighted to have Mark Stouse, the Chairman and CEO of Proof Analytics, joining her today to dive into his background, the years he spent building Proof Analytics, and the exciting work he is currently doing. Mark's story Even though Mark understands data science, he is not a data scientist. He is a business leader who got hooked and wanted more after discovering the power of analytics. So he began climbing the hill. Business problems It takes a lot of effort to get a small amount of data. So Mark started focusing on business problems associated with analytics. He decided to adopt the role of a whisperer figure and began building that role within all the different global organizations he ran. Building a team  He had to spend millions of dollars each year, mostly on salaries, to build a team that could provide the latency needed for the various businesses. But it worked! A valuable discovery The huge and intricate mega-models that Mark and his team created were time-consuming, and business leaders could never quite wrap their heads around them. That led Mark and his team to discover the value of what is now known as the Minimum Buyable Model. Code Mark and his team wrote some code early on to allow them to federate models in case they needed to make them bigger, more explanatory, or more inclusive. A better way It all took a lot of work. So, Mark looked for a better way of doing things. Something that had never been fully automated or aided before was multivariable linear and non-linear regression. Yet, that is a lean-data analytic that still answers most of the world's questions. Big data A problem many businesses are facing today is that they have tons of data, but very little of it is big data. The problem with time lags When looking at the impact of marketing on sales, almost everything marketing spends on increasing sales productivity has different time lags associated with each investment. Without knowing the normal time lag for each type of investment, you cannot know how to plan or find an ROI. Proof analytics At Proof Analytics, they used focused and targeted AI to assist and accelerate their modeling process. Once in production and linked to the necessary data sets, their models become mostly autonomous, so business owners need not be regularly involved with them. Their models get recalculated as new data gets presented, so people can see the historical reality, forecasts that get generated, and also, an updated reality as the future becomes the present. Mark's customers' favorite part of the tool Mark's customers like that they can load data into the libraries and then attach file-level security to that data. That makes it impossible for anyone to see the data in the file, yet the algorithm can still see it. Sessions Mark conducts sessions with his customers to help them triage. That is important because even with everything done with the Proof Analytics tool, it is still not fully democratized. So even though it does not require a data scientist to run it, a data analyst or someone switched onto the topic can help marketing teams have a much better experience with it. The ideal customer  The ideal customer for the tool is someone already doing all the work the old-fashioned way and looking for a way to do it more efficiently. Links: Email me your thoughts Sima@Infinity-2.com LinkedIn Twitter Infinity-2.com Proof Analytics Mark Stouse on Twitter Mark Stouse on LinkedIn

Sima is delighted to have Mark Stouse, the Chairman and CEO of Proof Analytics, joining her today to dive into his background, the years he spent building Proof Analytics, and the exciting work he is currently doing. Mark's story Even though Mark understands data science, he is not a data scientist. He is a business leader who got hooked and wanted more after discovering the power of analytics. So he began climbing the hill. Business problems It takes a lot of effort to get a small amount of data. So Mark started focusing on business problems associated with analytics. He decided to adopt the role of a whisperer figure and began building that role within all the different global organizations he ran. Building a team  He had to spend millions of dollars each year, mostly on salaries, to build a team that could provide the latency needed for the various businesses. But it worked! A valuable discovery The huge and intricate mega-models that Mark and his team created were time-consuming, and business leaders could never quite wrap their heads around them. That led Mark and his team to discover the value of what is now known as the Minimum Buyable Model. Code Mark and his team wrote some code early on to allow them to federate models in case they needed to make them bigger, more explanatory, or more inclusive. A better way It all took a lot of work. So, Mark looked for a better way of doing things. Something that had never been fully automated or aided before was multivariable linear and non-linear regression. Yet, that is a lean-data analytic that still answers most of the world's questions. Big data A problem many businesses are facing today is that they have tons of data, but very little of it is big data. The problem with time lags When looking at the impact of marketing on sales, almost everything marketing spends on increasing sales productivity has different time lags associated with each investment. Without knowing the normal time lag for each type of investment, you cannot know how to plan or find an ROI. Proof analytics At Proof Analytics, they used focused and targeted AI to assist and accelerate their modeling process. Once in production and linked to the necessary data sets, their models become mostly autonomous, so business owners need not be regularly involved with them. Their models get recalculated as new data gets presented, so people can see the historical reality, forecasts that get generated, and also, an updated reality as the future becomes the present. Mark's customers' favorite part of the tool Mark's customers like that they can load data into the libraries and then attach file-level security to that data. That makes it impossible for anyone to see the data in the file, yet the algorithm can still see it. Sessions Mark conducts sessions with his customers to help them triage. That is important because even with everything done with the Proof Analytics tool, it is still not fully democratized. So even though it does not require a data scientist to run it, a data analyst or someone switched onto the topic can help marketing teams have a much better experience with it. The ideal customer  The ideal customer for the tool is someone already doing all the work the old-fashioned way and looking for a way to do it more efficiently. Links: Email me your thoughts Sima@Infinity-2.com LinkedIn Twitter Infinity-2.com Proof Analytics Mark Stouse on Twitter Mark Stouse on LinkedIn

“Fun translates into good performance.” The four things every marketer should know before starting their career: Find a skill (channel) that is the most fun to do. Then specialize. Specialization brings money. Specialization solves hard problems that matter. You take this even further by also specializing in a specific industry (e.g. I specialize in marketing for fintech and insurance orgs at the moment). Understand the business you're marketing. Do your best to think like the CEO. Find an excuse to meet other experts. Personal branding is the easiest way to grow your network of mentors. Create a swipe file. This is not a new or novel suggestion, just one that works. There's a reason other marketing experts do this! Key moments from marketing experts: Mark Stouse, Episode #93 - https://kennysoto.com/podcast/mark-stouse-defining-a-recession-proof-career-things-to-know-as-a-new-cmo-ep-93/ Steve Toth, Episode #99 - https://kennysoto.com/podcast/steve-toth-understanding-in-seo-can-lead-to-exponential-growth-ep-99/ Jacob Warwick #91 - https://kennysoto.com/podcast/jacob-warwick-how-your-career-narrative-can-help-you-become-a-vp-ep-91/ Maya Grossman, Episode #84 - https://kennysoto.com/podcast/maya-grossman-the-career-advice-you-need-if-you-want-to-be-a-marketing-leader-ep-84/ Sara Pion, Episode #86 - https://kennysoto.com/podcast/sara-pion-navigating-the-startup-world-as-a-new-marketer-ep-86/ Lea Pica, Episode #81 - https://kennysoto.com/podcast/lea-pica-using-data-storytelling-to-spur-action-ep-81/ My “swipe file” of favorite marketing newsletters: Nik Sharma's DTC newsletter - https://www.nik.co/subscribe Why We Buy - https://customercamp.co/newsletter/ Dave Gerhardt's B2B Marketing Advice - https://dgmg.davegerhardt.com/email The Marketing Brew - morningbrew.com/marketing//r/?kid=9f1e7657 Stacked Marketer - https://www.stackedmarketer.com/friend-recommended/?utm_source=sparkloop&utm_medium=referral&utm_campaign=sm_daily&rh_ref=2b82a0e9 SEO-specific newsletters I use for work include: WTF is SEO? - https://wtfseo.substack.com SEONoteBook - https://seonotebook.com Jeremy Moser's newsletter -https://www.jermoser.com Other marketing podcasts to subscribe to: Exit Five - https://open.spotify.com/show/0OJJbQlcUlHiLSvNZoJTYf Marketing School - https://open.spotify.com/show/1NulSGKhstJuty8iYPBMo5 Marketing Against The Grain - https://open.spotify.com/show/3bMqKPfI45OmTK5hENtIOk *Quick editing note: I got the acronym for SCORE incorrect! It's actually the Service Corps of Retired Executives. I ended up clipping that audio out of this episode. --- This episode is sponsored by · Anchor: The easiest way to make a podcast. https://anchor.fm/app

Mark Stouse, CEO of Proof Analytics, talks about revenue-optimizing analytics solutions. Even before the pandemic hit, Johnson Controls' modeling predicted the economic decline and put them in the position to save a lot of money. Now, we've gotten to the point where marketing budgets are being slashed in half because of a lack of C-suite belief in marketers and the value they can bring to a company. Today, Mark discusses business data's underlying cause and effect relationships. Show NotesConnect With:Mark Stouse: Website // LinkedIn // TwitterThe Rev Gen Podcast: Email // LinkedIn // TwitterI Hear Everything: IHearEverything.com // LinkedIn // TwitterSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Mark Stouse, CEO of Proof Analytics, talks about revenue-optimizing analytics solutions. Marketing Mix Modeling or the MMM approach is based on a popular marketing theory known as the 4Ps of the marketing mix. The four elements of any successful business are product, price, place, and promotion, and marketers need to be able to measure the impact of their marketing and advertising campaigns. Today, Mark discusses marketing mix modeling. Show NotesConnect With:Mark Stouse: Website // LinkedIn // TwitterThe Rev Gen Podcast: Email // LinkedIn // TwitterI Hear Everything: IHearEverything.com // LinkedIn // TwitterSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

xWhat a fascinating conversation between our host Adam DeGraide and Mark Stouse from Proof Analytics. The concept that all data is in the past is educational, fun and actionable. A special shout out to our corporate sponsors https://automatemysocial.com and https://anthemsoftware.com who make this show possible. Mark's companies web address is https://www.proofanalytics.ai/ David Vs Goliath Podcast features some of the top small business CEO's stories of how they where able to leverage technology or other secrets to not only compete with their big competitors but actually win! In this fun and entertaining format your host Adam DeGraide will keep it interesting, educational and practical. This is a must view podcast for any existing or aspiring entrepreneur who has the desire to FIND, SERVE & KEEP more customers….PROFITABLY. --- Send in a voice message: https://anchor.fm/david-vs-goliath/message

xWhat a fascinating conversation between our host Adam DeGraide and Mark Stouse from Proof Analytics. The concept that all data is in the past is educational, fun and actionable. A special shout out to our corporate sponsors https://automatemysocial.com and https://anthemsoftware.com who make this show possible. Mark's companies web address is https://www.proofanalytics.ai/ David Vs Goliath Podcast features some of the top small business CEO's stories of how they where able to leverage technology or other secrets to not only compete with their big competitors but actually win! In this fun and entertaining format your host Adam DeGraide will keep it interesting, educational and practical. This is a must view podcast for any existing or aspiring entrepreneur who has the desire to FIND, SERVE & KEEP more customers….PROFITABLY. --- Send in a voice message: https://anchor.fm/david-vs-goliath/message

With the power of analytics, marketing campaigns can be fine-tuned for maximum impact and ROI. "Math and Analytics can make you a better person." Mark Stouse is the CEO of Proof Analytics and a former large company CCO and CMO. He has extensive experience in analytics and decision making, and is passionate about operationalizing analytics to empower business leaders. This is Mark Stouse's story... I am Mark Stouse, CEO of Proof Analytics. I have a long and varied background in analytics and decision making. I started out in a large company, HP, and my colleagues and I were constantly being cut, our budgets were being cut. I went on a quest to find a way to make better decisions with the data we had. I discovered mathematical models and got hooked. I've seen how challenging it is to operationalize analytics. The whole issue of latency In this episode, you will learn the following: 1. What is the OODA loop? 2. What is the difference between a cult of precision and a cult of pragmatism? 3. How can a data-driven approach help you win in business? What was mentioned: Multi Variable Regression - https://academic.oup.com/ejcts/article/55/2/179/5265263 Honeywell Aerospace - https://aerospace.honeywell.com/ OODA Loop - https://www.techtarget.com/searchcio/definition/OODA-loop#:~:text=The%20OODA%20loop%20(Observe%2C%20Orient,as%20more%20data%20becomes%20available. Procter and Gamble - https://www.linkedin.com/company/procter-and-gamble/ Johnson Controls - https://www.johnsoncontrols.com/ Connect with me: Mark Stouse Website: https://www.proofanalytics.ai/ LinkedIn: https://www.linkedin.com/in/markstouse/ Sam McKay Website: https://www.enterprisedna.co/ LinkedIn: https://www.linkedin.com/in/sammckayenterprisedna/ Loved this episode?Leave us a review and rating here: https://podcasts.apple.com/us/podcast/the-analytic-mind/id1541066997

Today's guest in the Expert Insight Interview is Mark Stouse. is the CEO of Proof Analytics. The proof combines seamless data management, automated, no-code modeling analytics, and world-class planning and budgeting capabilities. Their tools are all supplied as a simple, easy-to-use SaaS platform. In this expert insight interview, Mark and John discuss “Marketing Innovation and Revenue Optimization.”

Investing in marketing and analytics is critical to navigating your organization successfully. Mark Stouse, Chairman & CEO of Proof, and Jim Weiss, Founder & Chairman of Real Chemistry, join the show to discuss this and the current state of marketing.

In this episode of the Thoughtful Entrepreneur, your host Josh Elledge speaks with the CEO and Chairman of https://www.proofanalytics.ai/ (Proof Analytics), Mark Stouse. Proof Analytics is a marketing analytics platform that strives to help its clients make better decisions on a consistent efficient basis. In typical analytical formats, a business will see its statistics every quarter, half, and yearly basis. This does not help the business as they will always be looking backward while they are trying to move forwards which clouds the progression. Proof Analytics allows for consistent results to be provided so businesses can see where things need to change to promote growth. Mark explains that many teams are doing multiple variable regression analytics the old-fashioned way which does not promote efficiency for businesses. Proof Analytics changes this by providing the platform of speed for these consistent accurate results so businesses can get the results faster to make the changes faster.  Mark explains throughout Covid, video conferencing platforms soared in demand and the platforms were not built for this at the time. Revenues climbed as well as the stress on the technology that provided those services such as struggling bandwidth. Changes are happening at rapid pacing which changes the trajectory of investments and business strategies completely. Mark explains that self-aware automation is far from taking over because humans provide morality, ethics, and awareness of context that automation cannot. Mark explains that analytics gives context to data because without that context data cannot do much to aid a business. Analytics help businesses identify changes to patterns and make the appropriate responses to them so they can contribute to their growth and stability in the market.  Key Points from the Episode: What Proof Analytics is  How Proof Analytics tackles data differently Changes Mark has noticed throughout Covid  Automation  The importance of analytics  About Mark Stouse: Mark is the CEO of Proof Analytics, a marketing analytics platform that helps CMOs and CFOs bridge the ROI gap by providing cause-and-effect analytics that shows marketing and sales true business impact and financial worth. The company's 'Proof Business GPS' guides through the whole marketing lifecycle, and provides a complete picture of a company's marketing efforts. Their solution enables planning, budgeting, and optimization of marketing in all channels. An award-winning B2B CMO and CCO, Mark is one of the first leaders to connect all types of marketing investment to revenue, margin, and cash flow impact in complex, long-cycle companies. In 2014, he was named Innovator of the Year for his pioneering work by U.S. marketing leaders. Tweetable Moments: 06:04 "You've got to put the crude into a refinery and generate the gas that can power your car. It's the same thing with analytics. Analytics is the refinery, and we have automated very large portion of it." 12:09 "If you believe that tomorrow is going to be just like today, then go for it, right? But that's not happening. That's not the way life is. That's certainly not the way business is." Apply to be a Guest on The Thoughtful Entrepreneur: https://go.upmyinfluene.com/podcast-guest (https://go.upmyinfluene.com/podcast-guest) Links Mentioned in this Episode: Want to learn more? Check out the Proof Analytics website at https://www.proofanalytics.ai/ (https://www.proofanalytics.ai/) Check out Proof Analytics on LinkedIn at https://www.linkedin.com/company/proofanalytics/ (https://www.linkedin.com/company/proofanalytics/) Check out Mark Stouse on LinkedIn at https://www.linkedin.com/in/markstouse/ (https://www.linkedin.com/in/markstouse/) Check out the Accelerating Value podcast at https://acceleratingvalue.sounder.fm/ (https://acceleratingvalue.sounder.fm/) Check out Mark Stouse on Twitter at...

Mark Stouse was a CCO and CMO in large companies like Honeywell Aerospace. He claims that he is not a data scientist, but can play one on TV. He got to a high degree of organizational maturity, and could understand and speak to the needs of a data scientist. If he wasn't pursuing his current venture, he would likely be a history professor, as he is seriously passionate about 15th century innovation and the pre renaissance era. He is also a parent of 2 teenage boys, so outside of tech and history, he spends time doing what they want to do.As a communications and marketing leader, Mark was frustrated with the lack of recognition for his marketing teams to the bottom line. In addition, he solved major analytics problems at his prior companies, but had massive budgets to do so. He saw that software and automation was the way forward.This is the creation story of Proof Analytics.SponsorsAirbyteDopplerHost.ioIPInfomablLinksWebsite: https://www.proofanalytics.ai/LinkedIn: https://www.linkedin.com/in/markstouse/Support this podcast at — https://redcircle.com/code-story/donationsAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

“Just like you need to understand the business, you need to help them [the c-suite] understand the realities of marketing…” Mark is the CEO of Proof Analytics, a marketing analytics platform that helps CMOs and CFOs bridge the ROI gap by providing cause-and-effect analytics that shows marketing and sales true business impact and financial worth. The company's 'Proof Business GPS' guides through the whole marketing lifecycle, and provides a complete picture of a company's marketing efforts. Their solution enables planning, budgeting, and optimization of marketing in all channels. An award-winning B2B CMO and CCO, Mark is one of the first leaders to connect all types of marketing investments to revenue, margin, and cash flow impact in complex, long-cycle companies. Questions and topics we covered included: The story of how Mark built upon the Honeywell brand, in a sector within a slow sales-cycle industry (aerospace), How Mark approaches building marketing teams today (including how to pick out the right VP of Marketing/CMO), Why do investments in brand always get seen as wastes of money (by leadership) and how to fix that, How Mark defines the T-shaped marketer, What is the biggest enemy all CMOs will face in their career? Why forecasting is such an important skill for CMOs to know (so they can keep their jobs), Who should ultimately own attribution in a marketing team? How can marketers at all stages in their careers remain recession-proof? What is the OODA loop and why does it matter in data science? And more! You can say hello to Mark via LinkedIn: https://www.linkedin.com/in/markstouse Tweet to him at: https://twitter.com/markstouse --- This episode is sponsored by · Anchor: The easiest way to make a podcast. https://anchor.fm/app

LifeBlood: We talked about the characteristics of an entrepreneur, the desire to know the future and how to get better at doing it, the similarities between addicts and business owners, and how to make data usable, with Mark Stouse, CEO of Proof Analytics.  Listen to learn about the important intersection of intention and selfishness! You can learn more about Mark at ProofAnalytics.AI, Facebook, Twitter, Instagram, YouTube and LinkedIn. Thanks, as always for listening! If you got some value and enjoyed the show, please leave us a review here: ​​https://ratethispodcast.com/lifebloodpodcast You can learn more about us at LifeBlood.Live, Twitter, LinkedIn, Instagram, YouTube and Facebook or you'd like to be a guest on the show, contact us at contact@LifeBlood.Live.  Stay up to date by getting our monthly updates. Want to say “Thanks!” You can buy us a cup of coffee https://www.buymeacoffee.com/lifeblood

Mark Stouse is the CEO of Proof Analytics. The company's Proof BusinessGPS™ is the world's best and fastest automated Marketing and Revenue Optimization platform. Proof is integrating seamless data management and automated, no-code modeling analytics with top-class planning and budgeting capabilities. Their tools are all delivered as an easy-to-use, easy-to-understand SaaS platform. 00:00 - 00:17 “Data is all about the past, and only about the past.” — Mark Stouse 00:18 - 00:36 Welcome to Peppershock Media's Marketing Expedition Podcast 00:37 – 01:29 Mark' Bio 01:30 - 05:22 Marketing Essentials Moment: Provide Value to Others 05:23 - 07:08 Welcome to the show, Mark! 07:09 - 11:09 Extreme risk levels around decision making 11:10 - 15:01 How Mark started his company, Proof Analytics 15:02 - 22:53 The process of understanding data analytics 22:54 - 25:53 Predictive and prescriptive analytics software 25:54 -26:42 Explore the world of podcasting with Kitcaster! 26:43 - 28:43 Keeping up with the changes 28:44 - 34:55 The process of building an analytical model for the customer 34:56 - 37:33 Affordable and approachable tool for marketing 37:34 – 38:20 Combining data sets with analytics 38:21 - 40:29 Best way to reach Mark: Proof Analytics 40:30 - 41:15 Thank you so much, Mark! Enjoy your Marketing journey! 41:16 - 42:02 Join The Marketing Expedition today! #analytics #data #marketinganalytics #dataanalyst #software #marketingtools #marketingstrategies #digitalmarketing #business #businesstechnology #advertising #branding

Mark Stouse, CEO of Proof Analytics, talks about revenue-optimizing analytics solutions. Even before the pandemic hit, Johnson Controls' modeling predicted the economic decline and put them in the position to save a lot of money. Now, we've gotten to the point where marketing budgets are being slashed in half because of a lack of C-suite belief in marketers and the value they can bring to a company. Today, Mark discusses business data's underlying cause and effect relationships. Show NotesConnect With:Mark Stouse: Website // LinkedIn // TwitterThe Rev Gen Podcast: Email // LinkedIn // TwitterI Hear Everything: IHearEverything.com // LinkedIn // TwitterSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Mark Stouse, CEO of Proof Analytics, talks about revenue-optimizing analytics solutions. Marketing Mix Modeling or the MMM approach is based on a popular marketing theory known as the 4Ps of the marketing mix. The four elements of any successful business are product, price, place, and promotion, and marketers need to be able to measure the impact of their marketing and advertising campaigns. Today, Mark discusses marketing mix modeling. Show NotesConnect With:Mark Stouse: Website // LinkedIn // TwitterThe Rev Gen Podcast: Email // LinkedIn // TwitterI Hear Everything: IHearEverything.com // LinkedIn // TwitterSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Mark Stouse is the ceo and founder of Proof Analytics. He joins Ryan in this episode to focus on the customer-focused innovative pricing solution he and Proof Analytics created to cut their sales cycle, from 6-9 months to just 2 weeks! Mark also talks about the importance of taking your time with the hiring process, why Proof Analytics are renowned for mixed marketing and the evolution of the SAAS market. KEY TAKEAWAYS Proof Analytics is one of the world best and fastest automated revenue marketing and optimisation platform. Customers are generally having substantial trust issues with saas companies, so are moving away from annual contracts and looking at more shorter-term, flexible solutions. Proof Analytics allow customers to pay just $45 a month, this has resulted in them shortening their sales closing time from 6-9 months to just 2 weeks! Being one of the first to automate market-mix modelling, has allowed proof Analytics to really dominate the space. Hiring the right people is imperative to create a great company. Mark and Proof Analytics focus on getting the right people with the right values and don't compromise. They want to ensure the team are fully aligned with their values and act in accordance with these. You should hire slowly and take the time to get the right people. You can then fire quickly if needed, if they aren't right for the role, particularly in a start-up, then cut your losses. The brand work alongside the lower cost base of a monthly subscription has allowed Proof Analytics to grow substantially.   BEST MOMENTS  “Customers are moving away from annual contracts” “We're renowned in the area of market-mix modelling” “The natural human tendency is to be expedient” “You have to hire slow and terminate quickly”   Do You Want The Closing Secrets That Helped Close Over $125 Million in New Business for Free?"  Grab them HERE: https://www.whalesellingsystem.com/closingsecrets   Ryan Staley Founder and CEO Whale Boss 312-848-7443 ryan@whalesellingsystem.com www.ryanstaley.io    EPISODE RESOURCES www.proofanalytics.ai   ABOUT THE SHOW How do you grow like a VC backed company without taking on investors? Do you want to create a lifestyle business, a performance business or an empire? How do you scale to an exit without losing your freedom?Join the host Ryan Staley every Monday and Wednesday for conversations with the brightest and best Founders, CEO's and Entrepreneurs to crack the code on repeatable revenue growth, leadership, lifestyle freedom and mindset.This show has featured Startup and Billion Dollar Founders, Best Selling Authors, and the World's Top Sales and Marketing Experts like Terry Jones (Founder of Travelocity and Chairman of Kayak), Andrew Gazdecki (Founder of Micro Acquire), Harpaul Sambhi (Founder of Magical with a previous exit to Linkedin) and many more. This is where Scaling and Sales are made simple in 25 minutes or less.Saas, Saas growth, Scale, Business Growth, B2b Saas, Saas Sales, Enterprise Saas, Business growth strategy, founder, ceo: https://www.whalesellingsystem.com/closingsecretsSee omnystudio.com/listener for privacy information.

Today's marketing analytics are very complex, and the customer journey is more complicated than ever for B2B and B2C businesses. You need to have strong analytics to be more successful in your business. With the help of a great team, you can achieve easy-to-understand model visualizations that help both the marketer and the data analyst uncover the cause-and-effect relationships that drive meaningful business outcomes. In this episode, we have Mark Stouse, CEO of Proof Analytics, a marketing analytics platform that helps CMOs and CFOs bridge the ROI gap by providing cause-and-effect analytics that shows marketing and sales true business impact and financial worth. He is one of the first leaders to connect all types of marketing investment to revenue, margin, and cash flow impact in complex, long-cycle companies. Mark often gets so caught up with operational KPIs that we lose sight of our revenue goals as marketers. Resources: Proof Analytics SiteProof Analytics FacebookMark Stouse LinkedIn

If you own a P&L, Marketing Budget, or a Media Plan, this episode is for you. I speak with Mark Stouse, Chairman and CEO of Proof Analytics. Mark and I talk all about Marketing Mix. Specifically how you can make better decisions about it through Modeling and Predictive Analytics. Stick around till the end to hear about how you can take advantage of these concepts even if you have smaller marketing budgets. Enjoy! To make sure you never miss an episode of The High EQ Market podcast, subscribe on Apple Podcasts, Spotify, and the website. Listening on a desktop & can't see the links? Just search for The High EQ Marketer in your favorite podcast player.

A wide ranging conversation with Proof Analytics CEO, Mark Stouse, about marketing mix modeling, and all the ways data can leverage business and marketing performance. SHOWPAGE - www.ninjacat.io/blog/success-with-marketing-mix-modeling  © 2022, NinjaCat

Marketing as an AMPLIFIER to Sales productivity!!!The quote above was the primary focus of my discussion with Mark Stouse - the CEO of Proof Analytics.Mark self-identifies as a communicator turned marketer turned SaaS CEO. Over this journey, Mark has developed a strong perspective on how to prove ROI, especially for marketing investment.What are the metrics that matter to a Chief Marketing Officer? Mark says this is very straightforward: "Marketing's mission is to help Sales sell more product to more customers faster and more profitably than Sales could do by themselves". Simply stated, it is measured by more deals, bigger deals and faster deals - Deal Velocity! Calculating how marketing measures these should be the primary point of any metric that Marketing captures and reports.When pushed on the top three metrics, Mark responded that KPIs (data) by themselves are not enough. Data is the measurement of what happened in a particular time for a specific place - ALL in the past. Analytics, specifically regression analysis, enables a marketer to predict and forecast how future marketing investments will impact Sales productivity as measured by pipeline and revenue.The B2B SaaS industry is still young when measured against other industries such as manufacturing, retail, or consumer packaged goods. As such, the maturity of using sophisticated analytics to predict the future in the industry is still in its infancy - especially compared to larger, more data-intensive B2B online companies.An example of using data on a more granular level was Ideal Customer Profile (ICP) and Pipeline Coverage Ratio. By understanding how specific cohorts perform in top of funnel conversion, the marketing ROI can be increased materially through enhanced targeting.Next, we pivoted to Mark's concept of Marketing exponentially impacting Sales productivity. Mark has an interesting take on the concept: Marketing should invest more time helping Sales improve conversion rates in the middle and bottom of the opportunity funnel versus primarily being focused on top of funnel market engagement. Mark used a military analogy where the Air Force provides air cover to the ground troops. Why does Mark believe the above? Marketing has conditioned business leaders to think that Marketing is primarily a brand awareness and engagement function versus a selling process amplifier. Mark highlighted TRUST as a key ingredient to enhancing conversion rates and accelerating deal velocity. What drives a buyer's confidence - trust is a crucial ingredient to building buyer trust. The more confidence a buyer has that a company and their product will impact their buying process, measured by win rate and sales cycle time.As a marketer, a pivotal question is what are we doing to increase the buyer's confidence and trust, resulting in helping Sales close more deals faster!If you are interested in hearing thought-provoking ideas on how Marketing can use data and analytics to enable Marketing to become an exponential multiplier to Sales productivity - this conversation with Mark is fascinating.

In this fast-changing world, marketers need to act swiftly. The current situation (think inflation, economic uncertainties, and the likelihood of an economic downturn), asks for fast and data-driven decisions. This is where marketing mix modeling (MMM) comes in.  In this episode, Elias has a chat with Mark Stouse, the CEO of Proof Analytics.  Topics we discuss: The use of regression models in marketing How data can help you in making better decisions Examples of marketing mix modeling used in different industries LinkedIn Mark Stouse: https://www.linkedin.com/in/markstouse/  Website Proof Analytics: https://www.proofanalytics.ai/  The Marketing Technology Podcast is brought to you by Marketing Guys, the #1 Martech agency in Europe. If you want to be on this podcast or would like to know more about Marketing Technology, visit our website at marketingguys.com or contact Elias Crum at e.crum@marketingguys.nl

Mark Stouse, CEO of Proof Analytics, talks about analytics and marketing mix modeling. While popular, ‘data-driven marketing' fails to account for a constantly changing reality. As such, campaigns based on historical and not future data, have limited success. Today, Mark discusses marketing mix modeling and marketing attribution. Show NotesConnect With: Mark Stouse: Website // LinkedInThe MarTech Podcast: Email // Newsletter // TwitterBenjamin Shapiro: Website // LinkedIn // TwitterSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Mark Stouse, CEO of Proof Analytics, talks about analytics and marketing mix modeling. While popular, ‘data-driven marketing' fails to account for a constantly changing reality. As such, campaigns based on historical and not future data, have limited success. Today, Mark discusses marketing mix modeling and marketing attribution. Show NotesConnect With: Mark Stouse: Website // LinkedInThe MarTech Podcast: Email // Newsletter // TwitterBenjamin Shapiro: Website // LinkedIn // TwitterSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Mark Stouse, CEO of Proof Analytics, talks about analytics and marketing mix modeling. We often get so caught up with operational KPIs that we lose sight of our revenue goals as marketers. Furthermore, to determine the impact of our marketing efforts, we must be able to measure our results. Today, Mark discusses tying marketing to measurable results. Show NotesConnect With: Mark Stouse: Website // LinkedInThe MarTech Podcast: Email // Newsletter // TwitterBenjamin Shapiro: Website // LinkedIn // TwitterSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Mark Stouse, CEO of Proof Analytics, talks about analytics and marketing mix modeling. We often get so caught up with operational KPIs that we lose sight of our revenue goals as marketers. Furthermore, to determine the impact of our marketing efforts, we must be able to measure our results. Today, Mark discusses tying marketing to measurable results. Show NotesConnect With: Mark Stouse: Website // LinkedInThe MarTech Podcast: Email // Newsletter // TwitterBenjamin Shapiro: Website // LinkedIn // TwitterSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Mark Stouse, CEO of Proof Analytics, talks about analytics and marketing mix modeling. Our world has changed considerably since 2020, and intuition-based marketing is a sure recipe for wasted time and resources. Marketers must take advantage of analytics and data to understand and thrive in our respective markets. Today, Mark discusses marketing innovation and rev ops. Show NotesConnect With: Mark Stouse: Website // LinkedInThe MarTech Podcast: Email // Newsletter // TwitterBenjamin Shapiro: Website // LinkedIn // TwitterSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Mark Stouse, CEO of Proof Analytics, talks about analytics and marketing mix modeling. Our world has changed considerably since 2020, and intuition-based marketing is a sure recipe for wasted time and resources. Marketers must take advantage of analytics and data to understand and thrive in our respective markets. Today, Mark discusses marketing innovation and rev ops. Show NotesConnect With: Mark Stouse: Website // LinkedInThe MarTech Podcast: Email // Newsletter // TwitterBenjamin Shapiro: Website // LinkedIn // TwitterSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

We've all heard the line that 50% of our marketing is working, we just don't know which 50%! Our guest today has answers. Mark Stouse is the CEO of Proof Analytics, a marketing analytics platform that helps CMOs and CFOs bridge the ROI gap by providing cause-and-effect analytics that shows marketing and sales true business impact and financial worth. The company's 'Proof Business GPS' guides through the whole marketing lifecycle, and provides a complete picture of a company's marketing efforts. Their solution enables planning, budgeting, and optimization of marketing in all channels.An award-winning B2B CMO and CCO, Mark is one of the first leaders to connect all types of marketing investment to revenue, margin, and cash flow impact in complex, long-cycle companies. In 2014, he was named Innovator of the Year for his pioneering work by U.S. marketing leaders.If you have a sales team and you want to boost results, you need to get to know Selling From the Heart. What's great about Selling From the Heart is how it takes a different approach to driving sales. The goal is to build trust quickly with clients and prospects through authenticity. The result is more effective prospecting, higher close rates, and more referrals. Best of all, the Selling From the Heart methodology works with your existing sales model. To learn more, visit www.sellingfromtheheart.net and make sure to listen to me and my co-host Larry Levine each week on the Selling From the Heart Podcast!

Analytics has typically been too slow to be operationally relevant to making business decisions. In this conversation with Mark Stouse, CEO of Proof Data Corporation, we discuss the advancements in marketing analytics that make it possible to avoid the tyranny of intuition and cooked data, and establish analytics as an inseparable coach and bodyguard to helping achieve desired business outcomes. 

Mark Stouse (Chairman & CEO, Proof Analytics) on what he believes the greatest enemy of a CMO is. He also elaborates on why it's important for marketers to understand how their organization generates revenue and how their efforts should impact sales.

In this episode of the Marketing Analytics Show, Mark Stouse, CEO of Proof Analytics, discusses everything you need to know about marketing mix modeling. You'll learn: What marketing mix modeling is and when it's a more useful method compared to multi-touch attribution What groundwork teams should lay before implementing this model How to sell the idea of marketing mix modeling to the leadership team Links mentioned on the show: Follow Mark on LinkedIn. Start your free 14-day Supermetrics trial. Follow Supermetrics on Twitter. Follow Anna on Twitter.

Mark Stouse is the Chairman and CEO of Proof Analytics. He was 2020's Top 10 Most Influential Analytics Leaders. He was also CMO/CCO at Honeywell Aerospace, so he has tons of experience. Mark also hosts his own podcast called “Accelerating Value”, a weekly podcast aimed at guiding people in creating, defending, and proving value with the help of experts. In this episode, Mark discusses how analytics lead SaaS businesses to success as he shares insights most SaaS entrepreneurs need to know about the relationship between analytics and pricing.   Why you have to check out today's podcast: Discover how a different way of consulting like analytics can help SaaS businesses to become profitable nowadays; Know how much of a game changer analytics is in terms of keeping the relationship between customer loyalty and pricing intact; Find out how the scientific sense of inquiry helps pricing people reach greater heights in relation to sales and pricing with clients   “It isn't that you say, ‘Hey, what are you willing to pay for this?' That's not the question. You've got to say, ‘tell me about what you're really trying to solve for here and how big a problem is this to you. What would make you feel spectacular?' Then let's talk about the technical realities, and then let's talk about a price.” – Mark Stouse   Topics Covered: 02:02 – Getting exposed to pricing and learning things through failures with Mark's experience in Honeywell Aerospace and Proof Analytics 04:06 – Diving into the world of pricing with the help of advisors he trust 06:41 – Starting out in a SaaS company and initially doing consulting: a good way for one to be profitable 09:02 – A different consulting model – analytics – for a better, faster, and cheaper reality nowadays 13:16 – Business and the gap it has with data scientists due to the lack of contextual understanding in both concepts 18:23 – What does Proof Analytics charge for and why is that the right thing for them to charge for? 20:20 – Talking about the concept of 10 models equals 10 questions and how COVID affected the business industry in the past two years 26:05 – The differences in the opportunity costs of small and large companies 30:23 – A model as an indicator of customer success and people's obsession with margins 33:25 – What makes SaaS beautiful is that it concerns value at all times 35:30 – Mark's pricing advice for the listeners   Key Takeaways: “If you want to talk about a lesson in the reality of economics, start a SaaS company and you will learn more than you ever dreamed was out there.” – Mark Stouse “The problem has been not the math and not even the data. It has been the issue of how do we operationalize analytics so that everybody is able to make a better decision today than they were making before when they didn't have analytics. It really is taking the existing reality and making it better, faster, cheaper.” – Mark Stouse “Data scientists really don't typically have much subject matter expertise about any part of the business, so as the business person, you have to be very prescriptive with the data scientist in terms of laying out the non-mathematical equation.” – Mark Stouse “If you're a very large enterprise and you're spending $150-$200 million on marketing, what you are really after is maximizing the upside and minimizing the negative impact EPS from bad investments. That's what you're really after. If you are a much smaller company, you're really trying to avoid, among other things, being a two-time loser.” – Mark Stouse “The intersection of customer loyalty and pricing is also a piece that is usually ignored, because pricing is seen in a very short cycle sense rather than something that's a longer time.” – Mark Stouse “The human being has become key to the success of set which probably really and truly always was or should have been. There was just this unhealthy obsession with 90% profit margins.” – Mark Stouse   People / Resources Mentioned: Proof Analytics:https://www.proofanalytics.ai/ Honeywell Aerospace:https://aerospace.honeywell.com/   Connect with Mark Stouse: LinkedIn:https://www.linkedin.com/in/markstouse Email: stouse@proofanalytics.ai   Connect with Mark Stiving:    LinkedIn: https://www.linkedin.com/in/stiving/ Email: mark@impactpricing.com  

In a recent LinkedIn discussion, Mark Stouse (CEO of Proof Analytics) mentioned on LinkedIn that there is a near-total misunderstanding about the purpose and focus of a great ABM effort. In this podcast, Kristina Jaramillo and Mark discuss:1. How ABM is not synonymous with ABM tech like 6sense, Demandbase, and Terminus. You'll see that Mark describes ABM as an approach to reaching out to specific stakeholders within very specific, identified accounts and helping them understand their needs and the needs of their team.2. How ABM using 3rd party data is only DM on steroids - You'll see how your future and existing customers should not realize that you are using ABM on them.  3. How ABM measurement is off-target and how ABM should have a positive impact on stage progression, time to close, and deal value.4. How you can not retrofit ABM on top of existing marketing structures and why you should only be applying ABM to 10 - 20% of target accounts. 5.  How ABM programs are creating headwinds for sales and are slowing deal time and lowering deal sizes. 6.  Why alignment does not build the sales and marketing alignment that organizations want- and what marketing must do before alignment can be attained. 7.  How ABM should not be about the top of the funnel even though 60% of marketers focus on pipeline KPIs and marketing source revenue. You'll see how it should be about helping disparate stakeholders in the customer understand their needs better AND the needs of their peers better, thereby helping to create a consensus that drives purchase.If you liked this podcast with Mark Stouse, you'll want to listen to his interview:Rebooting GTM Planning and ExecutionYou'll also want to check out these additional resources that will help you clear up ABM misunderstandings:Our LinkedIn discussion around ABM misunderstandingsABM should not be synonymous with ABM techABM should impact more than your pipeline6 elements that are missing from most ABM programs

In this LinkedIn Live episode, our panel — including a CMO-turned-CEO, Mark Stouse — discuss what a CEO looks for in a CMO, why metrics and analytics are the backbone of any organization, and how to think about data. This is a #FlipMyFunnel podcast. Check us out on Apple Podcasts, Spotify, or here.And if a thriving community of growth-oriented marketers sounds like your kind of place, be sure to check out PEAK Community.

In this episode, we talk to Mark Stouse, Chairman & CEO of Proof Analytics & Host of Accelerating Value on Apple Podcasts.

Chris joined Mark Stouse on the Accelerating Value podcast to talk about the differences between B2C and B2B, specifically in regards to what B2B companies should unlearn from B2C marketing strategies. They talked about disrupting the “agency” world and why if a marketing agency can’t market themselves that should be a red flag. Chris also shared why churn is a business problem, not a customer success problem, and what the leading causes of churn are and how to correct them. Thanks to our friends at Hatch for producing this episode. Get unlimited podcast editing at usehatch.fm.

If the pandemic or climate change hasn't made it obvious yet… Math, sciences and analytics are how we save the world. And they're also how you save your marketing.  In today's episode, I'm joined by Mark Stouse, Chairman and CEO at Proof Analytics.  He has weathered several crises throughout his career — and through his move from a CMO to CEO — and each one has further bolstered his belief in the power of analytics.

Making the leap from CMO to CEO takes you from a position requiring deep, specific knowledge to one that needs a broad perspective. How can professionals position themselves to transition and grow throughout their careers? In this one Sangram interviews Mark Stouse, now CEO at Proof Analytics and former CMO at Honeywell. Mark is a marketer through and through, and notably, he's the first State Department speaker we've ever hosted on the podcast. Mark transitioned from his long-time career in marketing to become a CEO. He came on the show to talk about that change and the journey he's been on. Sangram asked him about the roles of CEO and CMO and about how to make a transition like this one happen.

Bulleit Group CEO Kyle Arteaga talks to the Holmes Report's Aarti Shah about the way companies — and the media — are rethinking how they position and talk about innovation. Later in the show, Proof Analytics founder Mark Stouse joins to talk about a recent survey that showed 96% C-suite respondents see their marketing and PR teams as “unwilling or unable” to prove ROI.