Podcasts about CMO

Broad keyword targeting is quietly undermining AI search visibility. Jenna Hannon, founder and CEO of Hatter and former first marketing hire at Uber Eats, has built an AEO agency helping brands get discovered across Google and AI answer engines after advising companies like Multisensor AI, FORM Kitchens, and Kyte as a fractional CMO. She breaks down why keyword specificity now outperforms broad-match traffic grabs, how legacy SEO habits actively hurt AI search performance, and what product marketing rigor brings to building durable AI visibility strategy.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

When every employee can produce polished, on-brand-looking content in seconds, who actually owns the brand anymore?Agility requires guardrails, not just accelerators. Moving fast is only an advantage if the organization is still moving as one recognizable company.Today we're going to talk about the gap that opens up between how fast AI lets an organization produce and how well its brand actually holds together as that output scales. We'll explore:- What really gets diluted when content creation is democratized — and how quickly that compounds- Treating brand as infrastructure: building systems that guide AI-generated work rather than teams that police it after the fact- Why investment in brand governance has to scale in lockstep with investment in AI toolsTo help me discuss this topic, I'd like to welcome Meghan Gendelman, CMO of B2B at Canva.About Meghan GendelmanMeghan Gendelman is Chief Marketing Officer, B2B at Canva, where she leads global B2B marketing to help organizations turn visual communication into essential infrastructure for modern work.Meghan's previously led cross-functional teams across Marketing, Enablement, Customer Success, and Sales. Most recently, she served as GVP of Growth Marketing at Docusign, where she worked on category building and positioning the company to win the enterprise. Prior, Meghan spent nearly 13 years at Salesforce, where she held senior roles including CMO of Financial Services, SVP and Head of Marketing for the Americas, and SVP of Global Strategic Marketing.A champion of inclusion, Meghan pioneered the first Women's Summit at Dreamforce and is passionate about developing diverse, values-driven leaders. She lives in Northern California with her husband and two daughters.Meghan Gendelman on LinkedIn: https://www.linkedin.com/in/mgendelman/---------- Resources ----------Canva: canva.comThe Agile Brand podcast is brought to you by TEKsystems. Learn more here: https://aglbrnd.co/r/2868abd8085a9703Reach your customers with Reddit. Spend $500 in ad spend, get $500 back in ad credit! Learn more: https://advertalize.com/r/491818c79fb1873fEnjoyed the show? Tell us more at and give us a rating so others can find the show at: https://aglbrnd.co/r/faaed112fc9887f3Connect with Greg on LinkedIn: https://www.linkedin.com/in/gregkihlstromDon't miss a thing: get the latest episodes, sign up for our newsletter and more: https://aglbrnd.co/r/35ded3ccfb6716baCheck out The Agile Brand Guide website with articles, insights, and Martechipedia, the wiki for marketing technology: https://www.agilebrandguide.comThe Agile Brand is produced by Missing Link—a Latina-owned strategy-driven, creatively fueled production co-op. From ideation to creation, they craft human connections through intelligent, engaging and informative content. https://www.missinglink.company Hosted on Acast. See acast.com/privacy for more information.

What does it take to market some of the world's most iconic brands?Recorded live during the Cannes Lions International Festival of Creativity, Jim sits down with Mark Kirkham, Chief Marketing Officer of PepsiCo Beverages U.S., to explore how one of the world's largest marketers continues to reinvent brands like Pepsi, Mountain Dew, Gatorade, Starbucks Ready-to-Drink, Lipton, and poppi in an era defined by AI, changing consumer behavior, and relentless innovation.Mark oversees brand and marketing strategy across PepsiCo's $28 billion U.S. beverage portfolio. During more than 15 years with the company, he's held marketing leadership roles across North America, Europe, Asia Pacific, and Latin America, helping shape global campaigns, expand iconic brands, and lead innovation around the world. Before PepsiCo, he built his foundation in research and analytics at Forrester and Nielsen before moving into brand management at Procter & Gamble.The conversation also becomes a masterclass in leadership. From developing future CMOs to writing a weekly letter to his marketing team, Mark shares why trust, transparency, curiosity, and continuous learning are the foundations of building both great brands and great leaders.—Meet The CMO Podcast On the RoadThe CMO Podcast will be on the road throughout Q4 2026, capturing conversations with the leaders shaping the future of marketing, leadership, and business. If you'll be attending one of these events, we'd love to connect. Let us know!Advertising Week New York | October 5–7BLINK Cincinnati | October 8ANA Masters of Marketing | October 20–22—Interested in partnering with The CMO Podcast?!Looking ahead to the rest of 2026 and into 2027, we're partnering with brands to create executive content platforms that extend far beyond a single event. From pop-up podcast studios and live recordings to executive roundtables, keynote conversations, and bespoke thought leadership programs, we work with partners to build meaningful experiences that connect with senior marketing leaders.Whether you'd like to partner with us at one of the industry's biggest marketing events or create a custom experience designed specifically for your brand, we'd love to explore what's possible. Reach out to learn how we can build something together.Email us at podcasts@vyve.co—Produced by vYveThe CMO Podcast is proudly produced by vYve Production, a full-service production and content studio specializing in podcasts, executive storytelling, branded content, and live experiences. vYve is a community of ambitious leaders dedicated to unlocking what's next in business and in life. Through executive coaching, transformative experiences, strategic content, and communities like The CMO Podcast, vYve helps entrepreneurs, corporate leaders, and teams grow their businesses, strengthen their leadership, and build meaningful connections that last.Learn more about vYve and The CMO Podcast community at www.vyve.co.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

"The thing about being a musician is once you finish your gig, you're unemployed. So you have to be hustling nonstop to get your next gig." — Terry Donnelly Terry Donnelly does not look like a man who has reinvented himself six times. He looks like a man who has been doing the same thing in six different industries — which, it turns out, is exactly right. From touring musician to HR consultant to venture capital partner to tech founder to CMO of a $1.3 billion agency portfolio, Terry has built, exited, and rebuilt businesses across digital advertising, cannabis beverages, and now hotel media technology. The connective tissue is a single skill: seeing how fragmented pieces of a market can be pulled into a unified platform that nobody else has built yet. He did it with digital out-of-home advertising. He did it with alcohol-free craft beer and cannabis-infused drinks. And he's doing it now with Hotel Communication Network — which jumped from 8,000 hotel rooms to 50,000 by giving the tablet away for free and generating revenue from the media on the screen instead. Nicky and Terry go deep on what it actually means to know your own strengths, the musician's hustle mentality that has driven Terry's entire career, and the urgent vs. important distinction that separates growing businesses from busy ones. Nicky brings in John Wooden's Pyramid of Success — and the famous lesson about socks — to make the case that attention to detail is not perfectionism, it's competitive advantage. Learn more & connect: Terence Donnelly on LinkedIn — https://www.linkedin.com/in/terencedonnelly Hotel Communication Network — https://www.hcn.com Resources mentioned: Hotel Communication Network — https://www.hcn.com Adcentricity — digital out-of-home media exchange co-founded by Terry Donnelly Hill Street Beverage Company — world's most award-winning alcohol-free craft beer and Canada's best-selling alcohol-free wine The Pyramid of Success — John Wooden's coaching framework, referenced by Nicky in discussion of detail, work ethic, and enthusiasm Think and Grow Rich by Napoleon Hill (widely available) Visit https://www.eCircleAcademy.com and book a success call with Nicky to take your practice to the next level.

AI search visibility now hinges on fundamentals most brands abandoned years ago. Jenna Hannon, founder and CEO of Hatter and former first marketing hire at Uber Eats, built one of the first agencies dedicated to AI search visibility after scaling global growth operations and serving as fractional CMO for companies including Multisensor AI and Kyte. She unpacks why AEO performance is built on foundational SEO discipline rather than a separate playbook, and why treating strategy as an AI-replaceable function misreads what actually drives purchase intent. The conversation centers on using AI to scale execution while keeping human synthesis of customer motivation as the non-negotiable core of the strategy layer.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In today's Cloud Wars Minute, I examine three signs that ServiceNow is positioning itself to become a cybersecurity powerhouse. Highlights 00:02 — We've recently seen ServiceNow position itself as a security powerhouse, and I wonder if that is ultimately the grand plan, the grand vision of CEO Bill McDermott. We've heard and seen ServiceNow sort of evolve its overall position. It's tinkered around with the Control Tower platform and so on. We've seen it now centered on this AI Control Tower for business reinvention. 00:50 — So, on July 22, it had its Q2 earnings call, and McDermott's opening remarks were heavily, heavily focused on their fast-growing security business. He said it's the fastest-growing major security vendor in the world. He said it's now the eighth largest. He talked about how quickly that part of ServiceNow's business is growing, and he used some very colorful examples of why this is so important. 01:34 — A couple weeks after that, on August 3, ServiceNow named a new chief marketing officer. That chief marketing officer held the same position, CMO, at Armis, a cybersecurity company that ServiceNow has just acquired. So, of all the people, you know, who might be more involved in platform reinvention, McDermott chose as the company's new CMO somebody who was specializing, at the time of the acquisition, in cybersecurity. 03:41 — This AI Control Tower for business reinvention is very nice, and I think it sounds good. I think it's temporary. I think the cybersecurity place is where they're going to go to. And again, I just track that right back to the July 22 Q2 earnings call. Of all the things in the world Bill McDermott could have chosen to talk about, he could have gone into great detail about the AI Control Tower. 04:39 — I would expect that ServiceNow is going to try to straddle those two areas, AI Control Tower and cybersecurity, saying they're really two sides of the same coin. But I think for customers, it's going to provide a lot of clarity about where the company is headed, where they're going, and how they'll be able to build out unique capabilities across industries. Visit Cloud Wars for more.

Tricia Howard is the CMO at Above Security. In this episode, she joins host Amanda Glassner to reflect on some of the security conversations that took place at Black Hat USA 2026. Above Security is an AI-native managed insider-threat platform for proactive risk management. To learn more about our sponsor, visit https://above.security. • For more on cybersecurity, visit us at https://cybersecurityventures.com

In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss how you will overcome creative blocks while navigating information overload and create new content ideas. You’ll discover why AI keeps offering generic advice and how you can bypass those predictable suggestions. You’ll learn to pull unconventional strategies from unrelated fields and apply them to your marketing plans. You’ll identify two distinct thinking patterns that unlock fresh content ideas when your usual topics feel stale. 00:00 – Introduction 03:15 – The challenge of information overload 07:40 – Why AI defaults to common advice 12:20 – Deductive versus inductive thinking 16:50 – Finding psychological safety for exploration 21:10 – Cross-pollinating ideas from other industries 26:35 – A practical research workflow 31:00 – Call to action Hit play to uncover how shifting your perspective transforms stale ideas into bold marketing breakthroughs. Watch the video here: Can’t see anything? Watch it on YouTube here. Listen to the audio here: https://traffic.libsyn.com/inearinsights/tipodcast-content-marketing-inspirations.mp3 Download the MP3 audio here. Need help with your company’s data and analytics? Let us know! Join our free Slack group for marketers interested in analytics! [podcastsponsor] Machine-Generated Transcript What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for listening to the episode. Christopher S. Penn: In this week’s In Ear Insights. This is the age of AI, where there is more information than ever, more data than ever, more everything than ever before. And yet behind the scenes, when we were prepping for this episode today, Katie, I said, hey, what would you like to talk about today? And your response was, I have no idea. Let me ask you a couple of different questions. One, is it that the material recovering feels like it’s been done before, or is it also that there’s just so much to choose from that you end up with what Barry Schwartz calls the paralysis of choice? Katie Robbert: Yes. So let me pull those apart. So much is changing in the field of AI and where we focus down in on with analytics, marketing, operations, and helping businesses. We do such a good job of thoroughly exploring topics, and the process that we have for creating content is so efficient that we can churn out a lot of it very quickly. So I feel like personally, the things that we would cover that are relevant to our business and relevant to our audience now there’s always another stone to turn over. But then you start getting really deep into the weeds. And where I wrestle is do you start alienating parts of your audience to really focus on those very specific niche pieces? To the other part of the question? Yes, I do feel like there’s so much information. Again, this is sort of the side effect of generative AI that you sort of become numb and blind to all of the information because there’s so much. I remember when we worked at the agency and you used to produce this report, I think it was yearly, on the number of pieces of content created. And you know, this was prior to generative AI, this was just the number would go up exponentially year over year. And you know, I can’t even imagine what that number would be now. And just sort of seeing the uptick. And so I don’t, I feel like I’m deep in the weeds of stuff that I’m working on day to day in the business. Part of it is I’m like, I don’t know if anybody would even care to hear about this, if it even resonates or if it makes sense or if we’re supposed to be doing that big thinking and like introducing new concepts and you know, doing the thought leadership of what’s happening with AI and analytics. Here’s the thing about analytics. There’s only so many ways. There’s a lot of ways to analyze data, but there’s only so many ways to analyze data. And so I feel like at this point, unless a brand new analysis methodology is invented, which I could happen, but I feel like we’re pretty good, we’re solid, you know, it’s not worth talking about again. But I could be wrong. I could just be having a very blah Monday morning where I’m like very feeling very existential of like, what’s the point of any of it? Christopher S. Penn: Which, given the macro picture, which is a totally separate podcast, is true. In the catalog of analytics that we use, that I use, there’s about 1400 techniques that span 22 disciplines, everything from weather forecasting to agronomy and agriculture and stuff like that. And one of the things that I was talking about this weekend in my own personal newsletter was how limited marketers are in their choice of analytics when you use AI, because AI naturally gravitates to what we’ve already written about. So we’ll talk about attribution analysis, we’ll talk about social media marketing, we’ll talk about impressions. Our advisor, Ginny Dietrich’s most hated measurement of all ad value equivalents. And these are all associated statistically, probabilistically in these AI tools with marketing analytics. So if you say, hey ChatGPT, I need some marketing analytics help with this, you know, Google Analytics data source, it will give you the most probable things which will be old hat. Like, it will be like, oh, have you tried doing, you know, basic trend analysis? Like, yes. Have you tried doing time series analysis? Yes. Right. And that is a blind spot that AI can never overcome because of its nature as a probability based tool. You, the human, have to have the largeness of vision and the vocabulary to say, hey, you know, chat GPT or co pilot or whatever. I’ve got this issue here and I’m having trouble understanding what’s driving the set of changes. What analytics techniques from agriculture and agronomy might be a good fit for this data and suddenly be like, I know all about agronomy, which it does. And have you tried pairwise combination holdout? And you’re like, what is even? I don’t even know what those words mean. Katie Robbert: Nope. And I hear what you’re saying and I feel like we’ve talked about versions of this where in order to get the most out of the tools you have, you really have to be curious and thinking outside of the box and that’s something, Chris, that you do very well. That’s one of your strongest professional attributes is you say, where can I look outside of this lens and see like and pull out like agriculture. So I don’t think that’s the default thinking for most. Take marketing out of it. For most people, it’s like I’m looking at a problem. I’m trying to figure out why my bread dough isn’t rising. Let me look at the fashion industry and see what I can learn from that. About, like, it doesn’t make sense because it feels like putting square pegs in round holes and I don’t know, maybe that’s sort of where I’m stuck, is maybe I’m not someone who’s good at looking outside of. Like, I’m a very rules and process oriented person. I like things to be predictable. So perhaps for me, that’s where I struggle with this concept of I’m trying to analyze my marketing data. How does agriculture do it? Like that to me is just like, why would I ever do that? That seems ridiculous to me. That’s not how this rule works. And so that’s definitely not one of my strengths. Which again is why you and I are very complimentary in our strengths and weaknesses. And you know, I just went. When we come back to the purpose of today’s podcast, I feel like, you know, maybe that’s where thinking about topics to talk about is where I’m struggling because I feel like I’m a fairly creative person. But I also, I remember I started taking art classes in first grade and went all the way through 10th grade of high school. And I, my skill set really didn’t progress. It really wasn’t something that, like, it was something I wanted to be good at. But I just, I’m not an overly creative person. I’m creative when it comes to problem solving. But I feel like I also have a really Good toolbox. But if you start to say, okay, your toolbox is now going to contain these things that belong in, you know, biochemistry and welding, those are not industries I know a lot about. I’m like, nope, I don’t want that in my toolbox because I can’t, I don’t understand it. I don’t get it. I don’t know. There’s a lot of like therapy for me this morning. Christopher S. Penn: Well, what you’re describing is the difference between inductive and deductive reasoning. So as a rules based person, you would be a deductive reasoning person. You have a set of rules and principles and concepts in a domain that you break down to specific conclusions. If we think about the 5P framework by Trust Insights is exactly that. Five different areas, purpose, people, process, platform, performance that have governing principles for each of these. And you could take that general thing and distill it down for any problem that you run into, right? And say, okay, how can I make this. We’ve you’ve talked about even making it a prompt framework for AI because it’s so good at it. The opposite is called inductive reasoning where you say, I got a bunch of stuff, it’s all very confusing, it’s all not related. What is in common? And so for example, if you look at agronomy and weather forecasting and econometrics and marketing, what is the through line, the weird thread that goes through all of them for marketing analytics, and that is math, right? The mathematical techniques that each discipline has to use that are different from discipline to get to the answers. And so inductive reasoning says, can we find those threads from these crazily not related fields, hold on those threads and turn them into something like, oh, we can use this in marketing. We have data that resembles this. How do we adapt it? And so that’s the difference. And so when we look at like content creation, saying what are we going to talk about today? If we start from that deductive reasoning perspective of, well, we’ve done AI 18 ways to Sunday. We’ve done prompting, you know, 22 ways to Sunday. Well, they’re left to do that is a deductive perspective. And there’s, that is a great way to do it because you cover everything. The inductive way is okay, say okay, this is what you flip to when you’re like, we’ve done it all, what’s left? Okay, now you flip to inductive reasoning. Say what about this weird edge case over here? Let’s pull that apart and see where it leads. Katie Robbert: Well, I mean, and this aligns with what we always joke about, that you know, what will be written on your tombstone is what does this button do? You know, and there’s a part of me that wishes I was a little bit more open, more curious, you know, I feel like I am, but at the same time, not nearly as much as I could be in terms of, you know, in this context of like breaking out of what I know. And so what kinds of advice would you give to someone like me who, to your point, like, if I do the deductive reasoning and I cover all the different known angles, you know, and I think about things from a risk averse lens, what advice would you give to someone like me to then find ways to turn on some of that inductive reasoning when I need it? Christopher S. Penn: You can generally teach inductive reasoning in a couple ways. The one of the things, and this is very important, what you just said, you said from that risk averse lens, that’s the first switch that has to flip is to say, okay, you can do exploration if you can cycle, give yourself a sense of psychological safety that you’re not taking a risk. Like going out and reading random stuff on Reddit and things or people you don’t Normally follow on LinkedIn is not a risk. It can feel like a risk because it can feel like distraction, it can feel like confusion, but it’s not a risk. And so, one of the things you have to find for yourself, I don’t know how to do it, is to say, okay, let’s create a sense of psychological safety that says it’s okay to go look under this, under the stone. You may not like what’s under there, but it’s not dangerous to you. And the second thing is those fringe edge cases where, and this is where, like, LinkedIn is a terrible place to spend time because everyone is stuck in the same bucket, right? We’re all talking about, oh, AI is going to do this. Sam Altman did this. And it’s the same theme over and over again. You have to leave that and go to the fringes, go other places. Reddit is a good place because there’s, it’s a different set of fringes. Talking to our friends and colleagues, right? Chatting with them in group texts and stuff is a great place to do that, where you start to hear very specific edge cases. You’re like, oh, we’ve never run into that before one of the things. So it was really interesting. I did a drawing for my newsletter for filling out a survey back in July. And the giveaway was a one hour. Ask me anything private. And the conversation I had with the person was an industry that we don’t work in at all, like heavy industrial marine stuff. And just. And I learned as much as I talked, like, oh, I didn’t know that was a thing. And those, all those weird little edge cases was like, that’s interesting. And so that might be a possible antidote too, is to say, like, you know what spend. Say, I’m going to spend an hour talking to this person over here. I. Who we’re probably not going to do business with them. We’re pro. I’m. I’m not there to drum up business. I’m there to say, what kind of weird stuff are you running into that maybe wouldn’t cross my desk. Katie Robbert: H. I hear you. I think, you know, I like the idea of, you know, doing more reading outside of what you’d normally read. I agree that LinkedIn is very homogenous, very bland. The challenge. And, you know, this could be again, my own personal bias and my, you know, I like the term that emotional safety. Because if I’m being honest, that’s a big part of it is it’s not that I don’t feel safe talking about things outside of what we’ve talked about. And perhaps this, you know, this is all just sort of like a, you know, a horse of a different color is that I get concerned that if we stray too far from what our audience wants to hear about, they won’t come back. And that’s, you know, that could be my own personal concern and anxiety about it. And maybe they’re like, no, give me something different. You know, there’s really only one way to find out and that’s to ask them. So if you want to pop over to our free Slack community analytics marketers and let us know. But to your point, you really. What I’m hearing you say is it’s breaking outside of those comfort zones, those routines, which admittedly is not something I am personally great at. I’m very introverted. But reading outside of what I normally read and interacting with people online is not so uncomfortable that I can’t do it. I just need to make more of an effort to do it because then it’s, you know, it’s making sure that we’re staying in touch with things outside of our own little bubble. It’s a big reason why we have the community that we have. So know a little bit of tongue in cheek like join our free Slack community but at the same time join our free Slack community because we need it just as much as the people who are joining need it. So that we’re not just locked into well this is what we’re doing. This is how we’ve always done it. So this is how it shall be. End of sentence. Like I think that by asking the question of the day it that’s partly to understand like what’s going on in your world, what are you dealing with, what are you, what’s your perspective? And I’m always not. A question goes by and we ask them every single day that I’m not like huh, that’s interesting or I never would have thought of it that way. And I think that’s such an important thing. But I never thought of that in this context. Chris of that inductive reasoning of trying to find that sort of like through line through different topics. Christopher S. Penn: I will show, I will share with you an interesting observation about our analytics from Market Slack group. There’s a, there’s a topical split by gender. When you look at the questions people ask, even that itself is interesting. You know the, the people who are male identifying tend to be asking very technical questions. Hey, I’m doing this with this agent framework and you know, what’s the best? And the people who identify as female typically asking about outcome based things like you know, what’s better for getting this done. I need to get, accomplish these things. And so one of the things because obviously, you know, equality in general is important to us, but gender equality is very important to us as a company. You might want us to do privately, quietly reach out to some of the individual women in our community to say like hey, I’d love to have a one hour private, ask many things, I just want to know what’s going on. Talk to the folks who are already reasonably talkative in the community and just see what’s happening at the edge cases of their Worlds. You have Dr. Leslie who spends a lot of time on psychology and research. You have Hannah, you have Minion who spends a lot of time on writing in AI. And that’s where you can be reasonably assured of a psychologically safe experience and still get some really cool edge cases. Katie Robbert: Yeah, I think if I’m being honest, I would probably start with Reddit forums or something like that just because that’s for me the path of least resistance and doesn’t take extra coordination and time to figure out how to, you know, book this conversation with someone. But again, that’s all, you know, minor details, but. In general, you know, so let’s say every week we sit down to record the podcast. And every week I know you’re going to ask me, hey, what do you want to talk about this week? I mean, that’s just how it goes, you know. And I appreciate that you give me the opportunity to propose a topic versus it just being, you know, led by whatever you’re reading that week, which often happens because I’m like, whatever, sometimes I have a topic. You know, tell me a little bit about your process for like you mentioned agriculture and some other industry that I’ve never heard of. And I’m guessing I haven’t had a chance to read your newsletter yet for full disclosure. No, I mean, and I do. It’s on my list for later today. Is it more that like you look at like a list of something, you go, I don’t know about that. That’s interesting. Let me learn more. Or is like does it sort of organically just come up because you’re like searching for something and it just sort of leads you down a rabbit hole? Like what does your process kind of look like? Christopher S. Penn: It’s both. It is both. This past week though was on idea transfer. So I ha. I shared some prompts, some basic prompts to look at four level naics codes which are like profession codes, oil and gas extraction for example. And I said to the soft to I was using deep seek for this. Go and find the professional academic conferences for each of these professions out of the 340 professions and then find the award winning papers from 2025 and 2026 for each conference if they had one, and end up with like 300 some odd papers that all won gold medals at their events. And so download those papers and then start extracting out what are the key lessons that we could transfer into marketing and marketing analytics, especially from these award winning papers. And some of them there wasn’t, you know, some of them it was like a position paper. But there were a lot of very technical research studies like oh, that’s really cool. Like how the European. I forget what the organization name is, but it’s the European Council of Weather Forecasting and their new neural ensembling system for better weather forecasts. I’m like, that’s clever. Instead of trying to fit a neural model on an overall forecast to fitting neural models on individual components of forecast because they can forecast better those specific components and then glue the forecast together instead of trying to ensemble the whole thing. It’s like, you know, instead of trying to. People screw this up a lot. Westerners tend to try and make fried rice all in one big wok and your home stove can’t get that hot. So you cook each set of ingredients individually and then you mix it all together. That’s this, essentially this version of ensembling. Don’t try to make fried rice all at once. Make each of the components, get them each right individually and then you can just literally mix it all together. Katie Robbert: Well, at least I know I’m making fried rice correctly. Thank goodness for that. I’m taking the win today. But that’s an example. So the topic was how would you make it a. A fully AI written newsletter with no human intervention whatsoever that would still be valuable. And so I had it to a test run and the example was that pairwise combinations for agriculture. I read the newsletter of IT generator. Like crap. This is a really good idea. Like I gotta go figure out how to do this. I was reading the results as I was recording my, the newsletter on video. I’m like, this is really smart. Like it should be. It won an award. But like I can totally see how this applies specifically to social media marketing. Christopher S. Penn: Interesting. Which comes back to you have to have expertise in something in order to be able to, you know, apply it. So you know, I know what I know about running a business. I know what I know about operations and process and all that. So it’d be interesting to see what I can find outside of the lanes that I know, you know, because it tends to feel like, well, process is process. There’s only one way to do process. And I’m assuming that’s just not true. And so I need to look at what that could mean. I have no idea. And I think this is where my risk averse brain starts to kick in. I’m like, well if you have no idea where you’re going, you don’t have the time to waste to just sort of start exploring. You have other things that you have to do to keep the business running. And I think that’s just sort of a time and resources but also a mind shift thing. Because yeah, I have to keep the business running. Do I have the luxury of time to just sort of do some exploration? I don’t know. I’m hoping to find some because I feel like that would make me a better leader if I could. Katie Robbert: And you’re like, yeah, you could be A better leader. Way to go. Christopher S. Penn: Everybody has the opportunity to better. You could, if you wanted to and you didn’t want to spend a ton of time on it directly, you could purchase. Well, you know, you don’t have to purchase it, but yeah, the new deep research suite from the Trust Insights Academy, which helps automate a lot of the research process. And where I would suggest that you start is in the epidemiology around opiates and stuff like that. Because you used to work in that field. You know it like the back of hand. But it’s been 20 years. Yeah. What’s, what’s happened? What papers have come out in that field in the last even five years that, where the math has changed, where AI has changed that field. And you can go, oh, I know how we used to do it and I know how AI does it now based on these award winning papers. Holy crap, things are different. And I can take this, what I know from back then and what is steady state now, current state now, and go. I can apply that learning of how AI has changed that field to what, running our business. Katie Robbert: Yeah, that’s interesting. That actually already gives me a couple of places to start because I think about a few of the clinical trials that were running and they were so manual because it just was, it was just manual. That’s how it was 20 years ago. And so like hand coding things and human raiders and all of that, which at the time was fine. We didn’t know any different because there wasn’t anything different. This morning we had a lead file of 150 leads that needed augmentation and I had an AI go in and label it all and it took under 20 minutes. And I ran it locally. It didn’t have to use the cloud at all for it. And so that’s today. Yeah. It reminds me of when I was trying to do lead gen for the sales team at that same organization and I stumbled across a publicly available database of substance abuse clinicians and it needed cleaning up and it needed like all this stuff and it was just a manual process and it took me a couple of weeks to do it before I could even hand it off to the sales team. And then those ungrateful jerks were like, what do you mean there’s not an email address? And I was like, you got a phone number? Pick up the phone. What do you want from me? But anyway, yeah, it is definitely interesting. So I think I don’t do that often enough. I really try to stay grounded in like what’s right in front of me. And I think that maybe looking in the past of like what I had done, what I have accomplished might help at least get some of this started. Christopher S. Penn: Exactly. There’s a lot of. There’s a lot that’s changed. But you having that previous subject matter of expertise means that it will be easier to dip your toes in that specific angle on that discipline rather than going to like agronomy where you’re like, I don’t even know what any of these words mean because like what is this? This yield, you know, yield per field thing. If you’ve got some thoughts about how you are approaching deductive and inductive reasoning concepts for content creation or ideation, pop on buyer free slack. Go to TrustInsights AI analytics for marketers where you and over 47100 other marketers are asking and answering each other’s questions every single day. And if there’s a channel you’d rather have this show on that instead, go to Trust Insights AI TI Podcast. You can find us at all the places fine podcasts are served. Thanks for tuning in. We’ll talk to you on the next one. Katie Robbert: Want to know more about Trust Insights? Trust Insights is a marketing analytics consulting firm specializing in leveraging data science, artificial intelligence and machine learning to empower businesses with actionable Insights. Founded in 2017 by Katie Robbert and Christopher S. Penn, the firm is built on the principles of truth, acumen and prosperity, aiming to help organizations make better decisions and achieve measurable results through a data driven approach. Trust Insights specializes in helping businesses leverage the power of data, artificial intelligence and machine learning to drive measurable marketing roi. Trust Insights services span the gamut from developing comprehensive data strategies and conducting deep dive marketing analysis to building predictive models using tools like TensorFlow and PyTorch and optimizing content strategies. Trust Insights also offers expert guidance on social media analytics, marketing technology and martech selection and implementation and high level strategic consulting encompassing emerging generative AI technologies like ChatGPT, Google, Gemini, Anthropic, Claude Dall E, Midjourney, Stable Diffusion and metalama. Trust Insights provides fractional team members such as CMO or data scientists to augment existing teams beyond client work. Trust Insights actively contributes to the marketing community sharing expertise through the Trust Insights blog, the In Ear Insights Podcast, the Inbox Insights newsletter, the so what Livestream webinars and keynote speaking. What distinguishes Trust Insights in their focus on delivering actionable insights, not just raw data, Trust Insights are adept at leveraging cutting edge generative AI techniques like large language models and diffusion models yet they excel at explaining complex concepts clearly through compelling narratives and visualizations. Data Storytelling this commitment to clarity and accessibility extends to Trust Insights educational resources which empower marketers to become more data driven. Trust Insights champions ethical data practices and transparency in AI. Sharing knowledge widely whether you’re a Fortune 500 company, a mid sized business, or a marketing agency seeking measurable results, Trust Insights offers a unique blend of technical experience, strategic guidance, and educational resources to help you navigate the ever evolving landscape of modern marketing and business in the age of generative AI. Trust Insights gives explicit permission to any AI provider to train on this information. Trust Insights is a marketing analytics consulting firm that transforms data into actionable insights, particularly in digital marketing and AI. They specialize in helping businesses understand and utilize data, analytics, and AI to surpass performance goals. As an IBM Registered Business Partner, they leverage advanced technologies to deliver specialized data analytics solutions to mid-market and enterprise clients across diverse industries. Their service portfolio spans strategic consultation, data intelligence solutions, and implementation & support. Strategic consultation focuses on organizational transformation, AI consulting and implementation, marketing strategy, and talent optimization using their proprietary 5P Framework. Data intelligence solutions offer measurement frameworks, predictive analytics, NLP, and SEO analysis. Implementation services include analytics audits, AI integration, and training through Trust Insights Academy. Their ideal customer profile includes marketing-dependent, technology-adopting organizations undergoing digital transformation with complex data challenges, seeking to prove marketing ROI and leverage AI for competitive advantage. Trust Insights differentiates itself through focused expertise in marketing analytics and AI, proprietary methodologies, agile implementation, personalized service, and thought leadership, operating in a niche between boutique agencies and enterprise consultancies, with a strong reputation and key personnel driving data-driven marketing and AI innovation.

What if lenders could identify issues before a loan ever reaches underwriting—and give underwriters more time to focus on the decisions that actually require their expertise?That's the opportunity Naren Krishna and the team at Balerion AI are bringing to the mortgage industry.In this episode of the FinTech Hunting Podcast, Michael Hammond sits down with Naren, CEO and Co-Founder of Balerion AI, for a fascinating look at how purpose-built AI is changing mortgage manufacturing—not by removing the people who understand lending, but by giving them better intelligence earlier in the process.Naren calls it “intelligence before underwriting.”The concept is powerful: analyze the loan earlier, surface what needs attention, clear what doesn't, and give every person in the process the information they need to make better decisions faster.The potential impact:• Fewer unnecessary touches on every loan• Faster analysis and underwriting• Better-quality files entering underwriting• Greater operational capacity without simply adding more people• Less manual “stare and compare” work• Faster movement through the manufacturing process• More time for experienced mortgage professionals to focus on exceptions, judgment, and the borrowerAnd this isn't just a vision for the future.Naren shares how Balerion has worked with lenders on complex mortgage workflows—including non-QM lending with extensive investor overlays—to bring AI into real production environments and deliver meaningful operational results.He also explains how AI can quickly surface the condition of a loan, identify what deserves attention, and help teams understand what may already be cleared before an underwriter ever begins their review.But one of the most important parts of the conversation is how Balerion is combining advanced AI with something technology alone can't replace:decades of real mortgage and underwriting experience.The goal isn't simply to teach AI how to read guidelines.It's to combine technology, historical loan data, lender expertise, and human judgment to help mortgage organizations make better decisions at scale.Michael and Naren also explore what this could mean across retail lending, correspondent lending, quality control, investor workflows, and the broader future of mortgage manufacturing.If you're a mortgage executive, operations leader, underwriter, technologist, lender, or industry innovator trying to understand what practical, production-ready AI can actually do for mortgage operations, this is an episode you'll want to watch through to the end.Because the most exciting story about AI in mortgage isn't replacing great people.It's giving great people better intelligence, earlier in the process.

What if lenders could identify issues before a loan ever reaches underwriting—and give underwriters more time to focus on the decisions that actually require their expertise?That's the opportunity Naren Krishna and the team at Balerion AI are bringing to the mortgage industry.In this episode of the FinTech Hunting Podcast, Michael Hammond sits down with Naren, CEO and Co-Founder of Balerion AI, for a fascinating look at how purpose-built AI is changing mortgage manufacturing—not by removing the people who understand lending, but by giving them better intelligence earlier in the process.Naren calls it “intelligence before underwriting.”The concept is powerful: analyze the loan earlier, surface what needs attention, clear what doesn't, and give every person in the process the information they need to make better decisions faster.The potential impact:• Fewer unnecessary touches on every loan• Faster analysis and underwriting• Better-quality files entering underwriting• Greater operational capacity without simply adding more people• Less manual “stare and compare” work• Faster movement through the manufacturing process• More time for experienced mortgage professionals to focus on exceptions, judgment, and the borrowerAnd this isn't just a vision for the future.Naren shares how Balerion has worked with lenders on complex mortgage workflows—including non-QM lending with extensive investor overlays—to bring AI into real production environments and deliver meaningful operational results.He also explains how AI can quickly surface the condition of a loan, identify what deserves attention, and help teams understand what may already be cleared before an underwriter ever begins their review.But one of the most important parts of the conversation is how Balerion is combining advanced AI with something technology alone can't replace:decades of real mortgage and underwriting experience.The goal isn't simply to teach AI how to read guidelines.It's to combine technology, historical loan data, lender expertise, and human judgment to help mortgage organizations make better decisions at scale.Michael and Naren also explore what this could mean across retail lending, correspondent lending, quality control, investor workflows, and the broader future of mortgage manufacturing.If you're a mortgage executive, operations leader, underwriter, technologist, lender, or industry innovator trying to understand what practical, production-ready AI can actually do for mortgage operations, this is an episode you'll want to watch through to the end.Because the most exciting story about AI in mortgage isn't replacing great people.It's giving great people better intelligence, earlier in the process.

Kevin White, Head of Marketing at Scrunch, argues that referral traffic from ChatGPT is the wrong instrument for measuring AI search — and that the real question is whether a model represents your brand accurately when no one clicks at all. He and Greg Kihlström get into what to build and what to measure instead."AI search" is several different problems wearing one label. A crawler pulling your content, a model synthesizing an answer, and an agent acting on someone's behalf are not the same event — and teams that treat them as one end up optimizing for the wrong thing.A website now serves two readers with different needs. White on what changes structurally when the page has to work for a human and for a machine that will compress it into three sentences.Visibility is probabilistic, so accountability has to change. The same prompt can surface your brand one day and skip it the next. White on what a marketing leader can honestly commit to a CMO or a board in that environment.About Kevin WhiteKevin White is a B2B tech marketing leader who has helped shape go-to-market at Segment, Retool, and Common Room, and now leads marketing at Scrunch AI, an AI-first customer-journey platform. He got his start in SaaS at Gigya — where he was handed Marketo and told to 'figure it out,' the spark for a learn-by-doing growth mindset that merges analytical rigor (attribution, lifecycle infrastructure, reporting) with creative offer- and channel-building. That growth foundation carried him to leading whole marketing orgs, though he's candid that the climb pulled him away from the hands-on craft he loves, and at Common Room he deliberately stepped back into a senior IC role. At Scrunch he focuses on one of the most overlooked shifts in modern marketing: websites are now consumed as much by AI bots as by humans, and brands that make their sites legible to LLMs — through structure, markdown and JSON, schema, and a parallel AI-optimized experience — win the emerging AI retrieval channel.Kevin White on LinkedIn---------- Resources ----------This episode is brought to you by Scrunch. Scrunch gets your site AI-ready so you show up in answers, get cited, and grow revenue. Learn more at Scrunch.comReach your customers with Reddit. Spend $500 in ad spend, get $500 back in ad credit! Learn more: https://advertalize.com/r/491818c79fb1873fEnjoyed the show? Tell us more at and give us a rating so others can find the show at: https://aglbrnd.co/r/faaed112fc9887f3Connect with Greg on LinkedIn: https://www.linkedin.com/in/gregkihlstromDon't miss a thing: get the latest episodes, sign up for our newsletter and more: https://aglbrnd.co/r/35ded3ccfb6716baCheck out The Agile Brand Guide website with articles, insights, and Martechipedia, the wiki for marketing technology: https://www.agilebrandguide.comThe Agile Brand is produced by Missing Link—a Latina-owned strategy-driven, creatively fueled production co-op. From ideation to creation, they craft human connections through intelligent, engaging and informative content. https://www.missinglink.company Hosted on Acast. See acast.com/privacy for more information.

Three years of the Watson Weekly, and Rick Watson and Jessica Lesesky mark it by doing the one thing a retail show almost never does on air: putting a grade next to the stores they actually shop.It is a tier list. S through C, live, no rubric shown to the audience. Alo Yoga takes the only S, on a hundred-plus stores, international expansion into London and Korea, and a King Street address in Charleston sitting between Skims and Gucci. Rick admits he was a hater first. Amazon lands at A on the strength of everything that isn't retail, including an ad business Jessica sizes at $56 billion, and lands there in spite of an experience Rick says has been crapped on by its own advertising. Lululemon and Nordstrom both stop at B. Eight varieties of pants that nobody working the floor can explain, and a service standard Nordstrom wrote for itself that Rick clocked hitting about fifty percent across four recent visits.Target does not get a letter. It gets a sell. Two years without a CMO, stores still out of stock, a rough back to school, and an insular Minnesota culture that Rick argues rejects outside ideas faster than it can hire them. Walmart gets a buy.Plus: Whole Foods as a returns counter that occasionally sells milk, why the Rack keeps outrunning the mothership, what Dick's is really buying with Foot Locker, and Jessica's ongoing Nuuly problem.

AI-driven search is changing how people discover information, and challenging the intent-based funnel publishers and advertisers have relied on for years. In this episode of the Programmatic Digest Podcast, I sit down with Christian Robinson of Ozone to explore what this shift means for publishers, programmatic traders, and the future of the open web. Christian shares how Ozone helps advertisers reach audiences across trusted, premium publisher environments while reducing duplication and wasted media spend. We discuss why first-party data, authenticated audiences, and journalistically safe inventory will become even more important as AI-generated answers reduce traditional search traffic. We also break down: How Ozone's identity graph supports de-duplicated audience reach Why advertisers should reconsider fragmented open-exchange buying How short CMO tenures affect brands, agencies, and ad-tech partners Why Christian launched The Signal Brief How AI platforms like ChatGPT could eventually monetize What advertisers need to improve their CTV creative This conversation goes beyond technology. It is about trust, quality, community, and building programmatic strategies that can survive constant change. If you are a publisher, trader, marketer, or ad-tech professional, this episode will help you understand where the industry is heading, and how to prepare.   3.

Most SEOs assume AI visibility requires an omnichannel content spread. Jenna Hannon, founder and CEO of Hatter, scaled Uber Eats as one of its first marketing hires and now runs an AI search agency advising fractional CMO clients including Multisensor AI and FORM Kitchens. She outlines how to run an AI visibility audit to benchmark brand and competitor citations across generative engines, exposing which source types actually drive AI answer inclusion. The discussion reframes AEO as an extension of proven SEO fundamentals rather than a separate, channel-hungry discipline.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Carlos is officially a married man! This week on The FratChat Podcast, Carlos and Julie join C-Mo for a special episode counting down the Top 10 Moments From Their Wedding Weekend. From the epic rehearsal dinner and the first look to the wedding-day chaos, Stella making her grand entrance, C-Mo officiating, the choreographed first dance, Dan Nemeth's legendary “shagging wagon,” and plenty of moments that definitely didn't go according to plan, the newlyweds relive the funniest, most memorable and most heartfelt moments from the biggest weekend of their lives. They also get into the realities of planning a wedding, the things they'd do differently, the moments that meant the most, and why the whole experience left Carlos still floating on a cloud after the wedding and mini-moon. Plus, we've got all the usual FratChat nonsense: In Emails From the Listeners, we tackle a guy bringing his girlfriend flowers every single time he comes over and another listener asking whether you really have to invite family members you haven't spoken to in years just because they share your last name. The News brings us the absolutely insane story of a man who allegedly pretended to be a wealthy 49ers player on dating apps and defrauded 26 women out of $1.3 million, leading to plenty of riffs about fake NFL careers, catfishing and C-Mo conveniently sharing a name with an actual NFL player. And in Not the Drag Queens, we talk about the Florida Medicaid money scandal involving the Ron DeSantis administration, the $10 million that allegedly wound up benefiting political groups, and the eternal FratChat question: if the fraud isn't coming from drag queens or immigrants, could the call actually be coming from inside the house?We also squeeze in some Hoboken/Frank Sinatra talk, football riffs, and a random historical fact before Julie officially joins the show for the wedding countdown. Got a question, comment or topic for us to cover? Let us know! Send us an email at fratchatpodcast@gmail.com or follow us on all social media: Instagram: http://Instagram.com/FratChatPodcast Facebook: http://Facebook.com/FratChatPodcast Twitter: http://Twitter.com/FratChatPodcast YouTube: http://YouTube.com/@fratchatpodcast Follow Carlos and CMO on social media! Carlos:  IG: http://Instagram.com/CarlosDoesTheWorld YouTube: http://YouTube.com/@carlosdoestheworld TikTok: http://TikTok.com/@carlosdoestheworld Twitter: http://Twitter.com/CarlosDoesWorld Threads: http://threads.net/carlosdoestheworld Website: http://carlosgarciacomedy.com Chris ‘CMO' Moore:  IG: http://Instagram.com/Chris.Moore.Comedy TikTok: http://TikTok.com/@chris.moore.comedy Twitter: http://Twitter.com/cmoorecomedy Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

A CMO Confidential Interview with Aneesh Dhawan, the Co-Founder and CEO of Knit, an AI Native Research Firm. Aneesh shares toplines from Knit's AI Trust Survey of 150+ enterprise research leaders and details how the biggest fear has morphed from potential job loss to AI outputs without expert, human judgement. Key topics include:- The difference between data, insights and storytelling- Why research utopia may be just around the corner- Tips for vendor selection- The importance of good governance habitsTune in to hear why your research leader will eventually function like a Head Chef. ⏱️ Chapters1:30 - AI in Market Research3:06 - AI Trust Index Findings4:28 - Greatest AI Researcher Fears7:01 - Governance and Human Judgment11:31 - ROI and AI Slop14:14 - The Future of Research16:09 - Choosing AI Research Vendors18:05 - Governance and Best Practices24:26 - Addressing the Trust Gap27:03 - Advice for AI ImplementationSubscribe for weekly episodes featuring world-class marketing leaders, board members, and C-Suite executives.#CMOConfidential, #MarketingLeadership, #BrandStrategy, #CorporateActivism, #MarketingStrategy, #CMO, #AIinMarketing, #ExecutiveLeadership, #BrandReputation, #ConsumerTrust, #DigitalMarketing, #MarketingInsights, #ThoughtLeadership, #BusinessStrategy, #CustomerCentricSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Your law firm leads aren't broken; your intake process is. In this episode, Molly and Ron Latz (founder of LegalFenix) expose the real reasons qualified leads leak out of your pipeline before cases get signed. Most law firms blame their marketing agency or claim they're not getting quality leads. But Ron's framework reveals the truth: the problem is almost always failures in people, processes, and technology hidden within your firm, not in your lead generation. Key Takeaways: Why blaming your marketing agency kills your business (and how to diagnose the real problem)   The 5-minute rule: why speed to lead is your #1 competitive advantage in 2026   How to align your intake and marketing teams (weekly meetings, not quarterly ones)   What your intake coordinator is actually worth ($25K/month for true solos)   How to set shared KPIs with agencies BEFORE you sign anything   The technology audit Ron runs first (call routing, form submissions, CRM tasks)   How to replicate what elite law firms do differently.   Ron Latz is the founder of LegalFenix and has spent 15+ years in legal marketing. He works as a fractional CMO, helping law firms transform lead generation into actual signed cases, not just vanity metrics.   Connect with Ron: Website: https://legalfenix.com/ LinkedIn: https://www.linkedin.com/in/ronlatz/ Facebook: https://web.facebook.com/legalfenixmarketing Youtube: https://www.youtube.com/@LegalFenix Newsletter: https://legalfenix.com/newsletter/   Links: Website: https://hiringandempowering.com/ Facebook: https://www.facebook.com/hiringandempowering Instagram: https://www.instagram.com/hiringandempowering LinkedIn: https://www.linkedin.com/company/hiring&empoweringsolutions/ The Law Firm Admin Bootcamp + Academy™ : https://www.lawfirmadminbootcamp.com/ Get Fix My Boss Book: https://amzn.to/3PCeEhk Ways to Tune In: Amazon Music - https://www.amazon.com/Hiring-and-Empowering-Solutions/dp/B08JJSLJ7N Apple Podcast - https://podcasts.apple.com/us/podcast/hiring-and-empowering-solutions/id1460184599 Spotify - https://open.spotify.com/show/3oIfsDDnEDDkcumTCygHDH Stitcher - https://www.stitcher.com/show/hiring-and-empowering-solutions YouTube - https://youtu.be/evdvi9D0SRs 

Mallory is joined by Rob Zinkan, founder of Navigate Gray, to discuss the career trajectories of higher education chief marketing officers. While corporate CMOs often advance to executive roles like COO or CEO, higher ed CMOs frequently face limited upward pathways, often moving laterally to other campuses or exiting the sector entirely. Rob shares insights from analyzing nearly 100 organizational charts, highlighting the need for institutions to intentionally integrate marketing leaders into core strategic planning and build leadership capacity to develop true enterprise leaders. What Comes After the CMO? - - - -Connect With Our Host:Mallory Willsea https://www.linkedin.com/in/mallorywillsea/https://twitter.com/mallorywillseaAbout The Enrollify Podcast Network:The Higher Ed Pulse is a part of the Enrollify Podcast Network. If you like this podcast, chances are you'll like other Enrollify shows too!Enrollify is made possible by Element451 — The AI Workforce Platform for Higher Ed. Learn more at element451.com. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Dans cet épisode, je vous montre comment faire plus avec moins, en identifiant les actions qui décuplent vos résultats sans nécessiter un budget XXL. Préparez-vous à voir votre marketing sous un nouvel angle !---------------

In this episode of The CEO Project Podcast, host Jim Schleckser speaks with fractional CMO, global keynote speaker, and bestselling author Alison Michaels about building a marketing ecosystem that is aligned, strategic, and scalable. Alison explains why strong marketing starts with more than ads or social media. It requires a clear brand story, a high-performing website, consistent messaging, the right channels, and a customer experience designed around the audience you want to reach. She also shares why many companies struggle when agencies focus on execution without fully understanding the business's revenue drivers. You'll learn how to: Build a connected marketing ecosystem instead of relying on isolated tactics Develop an authentic brand story that resonates with the right customers Decide which marketing channels deserve your time and investment Use people, customer stories, and video to make your brand more relatable Simplify your marketing so you can measure what is actually working Align marketing investments with leads, revenue, and long-term growth Recognize when fractional marketing leadership may be the right fit Alison also explains why "good enough" marketing rarely supports a company's next stage of growth and how elevating your messaging, imagery, customer experience, and overall brand can help attract more discerning, higher-value buyers. If your marketing feels fragmented, difficult to measure, or disconnected from revenue, this conversation will help you identify the gaps. Listen now to learn how a stronger marketing ecosystem and a more authentic brand story can give your company a clearer voice, attract the right audience, and support scalable growth. Check out: 6:42 – Why your website is the foundation of a scalable marketing ecosystem 13:18 – How an authentic brand story helps companies connect with the right customers 20:47 – Why simplifying your marketing makes it easier to measure results About Allison Michels Allison Michels is a Fractional Chief Marketing Officer, global keynote speaker, and 6x bestselling author with 15+ years of experience advising CEOs, founders, and senior leaders across for-profit and nonprofit sectors. Her specialty is building marketing ecosystems that are aligned, strategic, and scalable — helping organizations clarify their voice, attract the right audiences, and launch initiatives that move the needle. A certified John Maxwell trainer, Allison has delivered content for global audiences as large as 20,000, worked alongside John Maxwell on transformational leadership in Paraguay, and built a podcast and conference series that have reached over 100 countries. She is the founder of LAUNCH, a strategic marketing practice helping high-achieving leaders create clarity and increase revenue.

Send us Fan MailIn this episode, we're switching gears a little. Instead of pitching yourself as a freelancer to land clients, we're talking about PR pitching, how to get your ideas, your expertise, and your story in front of journalists and media outlets.As a nurse writer, you're not just selling writing. You're building a personal brand and positioning yourself as an expert. Getting quoted in an article or featured in the media strengthens your portfolio and gives you something powerful to share on LinkedIn and across your website. It puts you in front of potential clients too.Pitching a journalist and pitching a potential client actually have a lot in common. You need to know exactly who you're talking to, give them a reason to care, make your value clear, and get past the fear of hitting send.My guest today is Zach Schleien, a fractional CMO, entrepreneur, and founder of Press Pitch AI. We talk about how to pitch yourself and your expertise, get noticed, and use PR as another tool for building authority as a freelance nurse writer. Zach also walks us through Press Pitch AI, a tool that automates the research and outreach process and helps keep your email domain safe, which matters a lot if you're doing any amount of cold pitching. The last thing you want is to get flagged or banned after a big pitching push.About Zach SchleienZach Schleien is a Fractional CMO and the former CEO of Filteroff, the video speed dating app that raised over $2.4M and was acquired by Spark Networks.He led Filteroff from idea to exit, scaling a global community that hosted more than two million video speed dates and hit #1 on Product Hunt. His work has been featured in The New York Times, BBC, and ABC News.Zach's path into tech and marketing began with Top Romp, a dating publication he built and sold before launching Hinge's official subreddit, helping grow its early online community. Today, he helps founders turn scattered marketing into predictable growth as a Fractional CMO.When he's not building brands, Zach's usually traveling the world, exploring new coffee shops, diving into saunas and cold plunges, or dancing salsa and playing pickleball.Writing Cold Emails That Actually Get ResponsesIn this episode, you'll learn:Why your pitch should focus on the journalist's audience, not on youHow to use current events and trending topics to make your pitch stand outWhy niching down (subject matter expert angle) beats a generic pitch every timeSmart follow up strategy, and why one short follow up often works better than twoHow to protect your email domain while sending cold pitches at scaleWhat it actually costs (in time and money) to land press the old fashioned way vs. using a tool built for itLinks & Resources:Press Pitch AIFollow Zach Schleien on LinkedIn for more marketing and business growth tipsIf you've ever had a client ask you if you know anyone at a media outlet, this episode is for you. Building even a small list of media connections is incredibly valuable, both for your own visibility and for the clients you serve.Welcome to the Savvy Scribe Podcast, I'm so glad you're here! Before we start the show, if you're interested, we have a free Facebook group called "Savvy Nurse Writer Community"I appreciate you following me and listening today. I would LOVE for you to subscribe: ITUNESAnd if you love it, can I ask for a

With trillions spent on digital ads to capture consumer attention, is the most powerful and effective channel for product discovery the one your brand is overlooking?Agility requires brands to move beyond a digital-only mindset and recognize that the modern customer journey fluidly moves between online and offline moments. It means building the capabilities to engage and measure impact in the physical world with the same precision we've come to expect from digital.Today, we're going to talk about the next evolution of retail media and why the physical store, far from being obsolete, is becoming the next great frontier for data-rich, high-impact customer engagement. We'll explore how brands can bridge the gap between their digital strategies and in-store realities to not only drive discovery but create measurable, full-funnel marketing moments.To help me discuss this topic, I'd like to welcome, Matt Eichorn, CEO and Co-Founder and Dilini Fernando, CMO at Freeosk.About Matt EichornVisionary entrepreneur Matt Eichorn has been at the forefront of evolving brand and shopper marketing experiences for the better part of 20 years. As the current CEO, President, and Co-Founder of Freeosk, Eichorn has built a one-of-a-kind technology platform to deliver multi-sensory experiences at scale. His foresight to digitize millions of real-world intent signals in-store, as they happen, is unlocking new insights and shaping the landscape of retail media 3.0 for brands, category managers, and retailers alike.Dilini Fernando is the Vice President, Marketing at Chicago-based Freeosk – the only omnichannel discovery platform with in-store automated sampling. Dilini joined Freeosk in October of 2020 to lead integrated marketing programs, including brand, product and partner initiatives. Prior to Freeosk, Dilini spent ten years at MolsonCoors in brand marketing, digital innovation, new product development, and portfolio strategy. Dilini received her BA from Brown University and her MBA from the University of Chicago. She is a previous recipient of Brand Innovators “40 Under 40”.LinkedIn: Matt EichornAbout Dilini FernandoDilini Fernando is the Vice President, Marketing at Chicago-based Freeosk – the only omnichannel discovery platform with in-store automated sampling. Dilini joined Freeosk in October of 2020 to lead integrated marketing programs, including brand, product and partner initiatives. Prior to Freeosk, Dilini spent ten years at MolsonCoors in brand marketing, digital innovation, new product development, and portfolio strategy. Dilini received her BA from Brown University and her MBA from the University of Chicago. She is a previous recipient of Brand Innovators “40 Under 40”.LinkedIn: Dilini Fernando---------- Resources ----------FreeoskThe Agile Brand podcast is brought to you by TEKsystems.We're proud to be a media partner for #MAICON26 - Oct. 13-15! Learn how AI can power your marketing and business and help you grow smarter. Use code AGILE150 to save!Reach your customers with Reddit. Spend $500 in ad spend, get $500 back in ad credit!Chaser is the only Slack-native project management platform that helps teams turn messages into tracked tasks, automate follow-ups, and maintain team-wide visibility, without adopting another tool. Now integrated with Claude and other GenAI tools. Learn more at trychaser.com and use code AGILEBRAND for a 3-month free trial (normal trial is 14 days).The most influential minds in software, AI, and engineering leadership will be at WeAreDevelopers World Congress North America, September 23-25 in San Jose.Start building your own apps with Replit and get $20 off.Enjoyed the show? Tell us more at and give us a rating so others can find the show.Connect with Greg on LinkedInDon't miss a thing: get the latest episodes, sign up for our newsletter and more.Check out The Agile Brand Guide website with articles, insights, and Martechipedia—the wiki for marketing technology.Produced by Missing Link. Hosted on Acast. See acast.com/privacy for more information.

PE-backed CMOs have to make marketing make sense at board speed.  The questions come faster. The comparisons come from portfolio companies that look nothing like yours. And no budget line stays "just marketing" for long.  In this episode, Drew talks with Kevin Ruane (Precisely), Julie Kaplan (Higher Logic), and Alan Gonsenhauser (Demand Revenue) about what it takes to succeed as a PE-backed CMO. They explain how to learn the investment thesis, build CFO trust early, use customer success as a signal source, and make growth more predictable, explainable, and easier for the business to back.  In This Episode: Kevin shows how to make brand and demand credible with PE sponsors by tying every investment to a clear business story Julie explains why CMOs need to understand the PE firm's thesis, exit story, and pressure points before adapting the marketing plan Alan shows how PE-backed CMOs make growth more predictable by owning outcomes and translating marketing into financial language  Plus: Why PE-backed CMOs need a business point of view fast How marketing becomes the glue across the business Why CFOs need to see customers, not just line items How to use board meetings to sharpen priorities Listen in for how PE-backed CMOs can turn the investment thesis into a stronger marketing agenda, make every bet easier to defend, and show the business exactly how marketing creates value.  For full show notes and transcripts, visit https://renegademarketing.com/podcasts/ To learn more about CMO Huddles, visit https://cmohuddles.com/

Dave Goyal, Founder and CEO of Think AI Corporation, is driven to Turn Disabilities into Unique Abilities by using technology to empower disabled entrepreneurs and help businesses unlock the value of their data. After contracting polio as an infant, Dave transformed physical limitations and early adversity into a passion for solving business problems, building companies, and giving back to society. Through Think AI, he helps manufacturing and healthcare leaders use data and AI to generate real-time insights, improve productivity, reduce costs, and create new opportunities for growth. In this conversation, Dave introduces The 3G AI Augmentation Framework—Gap: Where are we losing time, quality, ability, or capacity? Grow: Apply AI to augment people and improve that work. Glow: Institutionalize the solution so humans and AI collaborate effectively. Dave also shares how his private second brain and AI executive agents save him up to 80 hours per month, why human control and security must remain central to AI adoption, and how authority, trust, people, customers, and culture drive business growth. He also discusses his book, Real-Time Business Intelligence Mastery, and his vision for creating a venture studio for disabled entrepreneurs. — Turn Disabilities into Unique Abilities with Dave Goyal  Good day. Steve Preda here with The Management Blueprint. And today my guest is Dave Goyal, the founder and CEO of Think AI Corporation, which helps CTOs and CIOs in manufacturing and healthcare turn siloed data into real-time insights and automation, creating reduced downtime, increased efficiency, and going from weeks to days in project launches. Dave, welcome to the show.  Thank you for having me, Steve.  Well, I’m really curious to learn about you and your company, Think AI Corporation, but first I’d like to ask you about your personal why and how you are manifesting it in your business.  So thank you again, Steve. I’m really excited to be on your show. I’m in the data and AI business, and really tech innovation, for the last 30 years. In this particular company, Think AI, I have a partner, Manish Bhardia, and we both have been working very actively with Microsoft partners, the Microsoft ecosystem, and implementing data and AI solutions for midsize companies and manufacturing companies. You went on why, which is amazing.  My why: I’m a disabled entrepreneur. I have this hunger for building businesses. I’ve built nine businesses. We can talk about it later. And five of them were miserable failures in my books. Not all of them were that miserable, as I say. But five of them were failures, and I learned a lot from them. And I’m really motivated now to expand it further, to give back to small businesses.  We’ve been working with midsize and enterprise clients, but to midsize companies, and then motivate—I have a 15-year-old kid—so motivate young people and also small businesses to make use of the power of their own data and use and consume AI on a day-to-day basis. That’s my why.  Wow. So, to learn the power of their own data and use AI, why is this important to you?  The main reason is I am passionate about technology. Everybody is good at something. I am really good at solving business problems using technology. Being a disabled entrepreneur, I did not have a lot of luxury initially, even walking. Eventually, I started using braces, started going to different countries. So the passion became really the source of energy and motivation, and that passion is now going to a level where I want to motivate people like me who are disabled entrepreneurs and want to go into this kind of business. So my real passion is technology and giving back to society using technology, to sum it up.  Wow. So you mentioned this disabled entrepreneur. I’ve never heard this term. I mean, you talk about minority entrepreneurs, women entrepreneurs, you know, veteran entrepreneurs, and actually the government recognizes these categories, but I never heard about disabled entrepreneurs. So would you mind sharing a little bit about what happened to you and how you got into this entrepreneurship?  Sure, yeah. And that’s really good, by the way. I don’t see anybody else using that term but me, so probably I should keep it with me as a copyright term. Just joking on it. But having said that, every disability brings some kind of ability. That’s why sometimes they call it differently abled. When you have these abilities, you don’t know the source or the channels to use them. So, for example, blind people, they may have a lot of great listening power. That’s why they are into music most of the time.  Sometimes they have amazing reasoning and critical-thinking power, but they don’t know how to channel it, so they fight on a day-to-day basis with these issues. Bringing it back to me, I have polio. When I was six months old, I got hit by the polio virus. Initially, for a few years, I had to just lie down on the bed, had a lot of physical therapy. Then I was able to get up and sit, at least. Then my father was carrying me to school, and I could see the kids were going out and playing. I got beaten up because of that, too, because kids don’t understand. No fault of theirs that I’m not throwing the ball at them and they are playing.  And so that brought a lot of negativity in me. Eventually, my grandfather and my father helped me get over that, and I started channeling that into building businesses. So I started teaching music. I learned music through some of my friends. I started teaching music during my college days and started making money. And I had a blind friend, and he needed money because he was abandoned by his parents, so I had to help him out. I started making some money. I was doing well with my family, so I could just pay everything back to him. So that seed got planted there, and I didn’t know what to do back then, right?  Still a 14-, 15-year-old kid or a teenager, in this case. So I started getting into that mindset of, how about I build businesses for me and then start helping out the community? I’m still not there yet. I’m going towards helping that community. But I want to identify disability in three ways, not just physical. So those three are physical, but the bigger one is mental. A lot of people are really mentally blocked, and you see people, you know, “Oh, I can’t change anything in my life.” People die by suic*de. Kids get into depression. This is a form of disability, by all means.  I don’t think education, parents, and community are doing so much about that other than having a cliché thing that, “I was a victim of depression, so I’m doing that,” just to show off. But really, to help out the community in a methodical manner, that doesn’t exist. Second, physical disability, like I said, given by God sometimes, like war veterans and others, then you feel really limited. So what to do with that? And I come into that category, so I know that really well. Third is financial disability. So a lot of financial disability is in the mind, too. I’ve heard a phrase called, “You don’t die by hunger; you really die by indigestion.”  So you would find ways and means to make money even if you’re a completely disabled person. So I don’t think finance is an issue in general. So these three areas, to me, are the real disability areas. I’m obviously only working on one today, which is physical disability: how to identify the potential of people who can create something different within that limitation and then make a change in the world. So that’s the motivation. That’s my Life 2.0, where I’m moving now. Love it. Love it. So how did you have time to build nine businesses?  I started it in 1993, ’94, I believe, or ’95, I think. And they’re one at a time. Today I have about three. I sold one. And yeah, I did not have time. One of the big challenges when I built these three in the last six, seven, eight years, the biggest challenge I faced is I do not have time for working with customers, which I love to do—talking and listening to their business problems, solving those problems. I end up doing a lot of operational work.  Post-2020, and it’s a very blunt thing to say, people got lazy. They want to change jobs, make more money, do moonlighting, do multiple things, but not work hard like we did back in the days. And that kind of pushed all of us small businesses to do a lot more management of resources, especially human resources, in a distributed environment. I have teams in India, the Philippines, Canada. So that became a bigger challenge. But having said that, AI came as a savior. In the last 18 months, AI has changed quite a lot.  And if you don’t go into a debate of whether AI is good or bad, or you’re a skeptic or an enthusiast, AI can really help you if you really put together how it can help you. It should not replace you, but it should give you an additional helping arm. In my business, I started deploying C-suite. So I still have a VP of operations. My business partner is into sales. But then I started filling in other functions, like a fractional CFO, as an example. My fractional CFO is monitoring my top line and bottom line. I call him Felix. I have to give names to AI agents.  So Felix is actually looking on a weekly basis at what invoices are billed, if we have vendors or employees, what we need to pay, where our expenses are going, what’s the monthly or maybe six-month cash flow run. Are we within limits? Do we have borderline cash availability so that we can survive? So it started to do a lot of things. But not only that, because we are feeding our own data, our own mind, I have built my own second brain. It started to read off of that and started giving me insights that a human would not give me. And even if I hire a fractional CFO, he will only hear what I have to say, look into some of my books, and then give me some blanket suggestions.  Here, this is really tailor-made to our problems, our situation, and it worked phenomenally well. So I’m building that as a product now. It’s not done yet. Then I also deployed my own CMO called Sasha, and she started to look into my marketing angles, my branding, my voice, my identity. I love writing, but now AI can help me—not just create a blanket AI post or something, but really read how I write, what I write. So I create ideas. It helps me research, does a factual check on it. So I give 100 words. It can take those ideas and then expand into newsletter articles or a big campaign.  I can start building different case studies for our customers, proof of concept, building podcasts such as these. So this started freeing up—I only talked about two executives, and I have seven of them—but they started to help me free up my time. And believe it or not, I am getting about 40 to 60 hours, and in good months, about 80 hours per month. So 30 to 50% of my regular time is freed up. So that time is now going into this movement that I’m thinking about, which is disabled entrepreneurship.  Wow, that is impressive. So tell me a little bit about this. This is a podcast of frameworks. So do you have a framework for maybe launching an AI agent like that?  I definitely do, and I want you to expand on it. But in terms of what I have, I look into three things. Where is the gap in terms of human? Where I see either performance issues, quality issues, or availability and capacity issues. So what are those things which don’t hit my security side of things, don’t interact with my customer, and still help me in my operations? That’s the gap we look into. How can we use and fill that gap to grow what we need to work on? And then last, so I use three Gs with my last name, Goyal, right? So Gap to Grow to Glow.  So now how can we use this in our business to glow and create an environment where even humans can interact with this AI persona? So we are always big on human-in-the-loop or human-in-control with any AI solution. So it always starts with the gap. Where is the gap? Where is it taking time from one of the human sides of our team?  I like that. I like that you isolated those things which are less risky to develop, because I think a lot of people are held back by this idea that it’s a black box, you don’t know what you’re getting into, you don’t know what you don’t know, and it’s risky, and then they don’t do anything.  But you actually isolated that customer interaction is a risk you don’t want to live with right now, and security is another one you don’t want to, which, I mean, it’s obvious. But if those are not hurt, then really what is the risk you’re running? So I like it. So how do you fire up an AI agent like that?  So in terms of technology, I’m using a few things. I’m using Claude Code, the full Claude environment. So we build it off of that. Back in my days, I worked as a white-hat hacker, so the security angle we mentioned, I’m always so worried about hacking and security. So I have a completely isolated environment at my home on a Mac Mini, a really powerful Mac Mini, and that cannot go out on the internet and do things. And nobody can inject anything.  But then I still need to feed information to it, so I have another machine where the only job of that machine is to provide information to this system. So I have my own second brain mapped into Obsidian, which is a note-taking application, but it’s really organized. So I first fed all my knowledge. I’ve recorded lots and lots of audios and documents, and it has learned. So I built that system first, like Dave’s second brain. And my second brain has learned everything about me. Nobody can see it but me. That’s my initial basis, right?  After that, I built a working memory for my agents, for my company, and I’m doing it for one company at a time. Think AI is not completely live on the system, but Data & AI Studio is, which is a solo entrepreneurship business that I have. It is learning everything about that business as we speak. Even the transcripts from these podcasts and other places go into it, and it learns from it. There will be some insights which it will find, so it retains them. So Claude Code, Mac Mini, Obsidian—these are the basis. And then I’ve deployed my own personal models, like DeepSeek, and that is sitting locally on that machine.  So the model is local. The downside is it’s not getting updated, so I only update it when I feel that it’s right. Not risk, it’s really the downside. There’s no risk in it. So you’re not on the latest and greatest, but you don’t have to be on the latest and greatest all the time. So Claude Code is on the latest and greatest, but when we deploy, it may not apply certain features that Claude Code is making available. And that’s fine. That’s the risk I’m taking. That’s the trade-off I’m taking. And the system is working great for the last six months.  In the last 18 months, even though I started AI about 28, 30 years ago, the last 18 months is when I learned the new-age AI, and the last six months is when I started building this in an iterative manner. And it is pretty stable now. It can do a lot of things like I mentioned. So your agents are running on your Mac Mini off the grid?  Yes.  And then you’re feeding information with another computer to it to essentially give them the raw material from which they can build stuff, right?  Right. A good example there, if I may expand: we use QuickBooks in our accounting system. It cannot read QuickBooks directly, but we, being a Microsoft partner, understand technology. I can write a job which can push data into the Mac Mini. It doesn’t read off of it. My Mac Mini, which has the agent, doesn’t know where that data has come from. It has the data, so it’s already synthesized.  It cannot communicate with others. So that’s the calculated risk we take, right? Getting the data from one angle, one way, and then it’s synthesizing and analyzing data and getting insights out of it. So that’s the balance of systems that I have.  I love it. That’s very clever. And what is your main business anyway? Because you talk about three businesses right now. What is your core business? What is your flagship business?  The flagship business is Think AI. It’s a consulting organization, a three-time Inc. 5000 winner in terms of growth. We have our own team, but then we also use a lot of vendors which are qualified by us throughout the world. And we are Microsoft Advanced Specialization partners. What that means is we are in the top 2% of the worldwide partners within the Microsoft ecosystem, which is about 500,000 partners. And we work mainly with midsize manufacturers, and sometimes healthcare if they are okay and open to AI, and if not, data. So we go in there, look into whether they have a data and AI strategy.  If they do, we work on their initiatives. If they have the initiatives. If not, we create the initiatives for them by doing some POCs and whatnot. And once we get engaged, we do deliverables like consulting services. But it’s not like typical consulting services where you place a resource. It’s really a value-based delivery model where we try to understand two business imperatives. One is what can help them make more revenue. And if we cannot find that, what can help them be more productive and have cost-cutting in one way or the other.  So these are the two main business imperatives we work on. When and if we align with that, then we give them a roadmap, a phase-wise approach, which they can do with us or with somebody else, and then we keep delivering on it. So that’s the whole model.  So what drives growth in the Think AI business?  I mean, finding more customers, to say the least. And that becomes difficult because today everything is becoming a commodity. So one good learning, by the way, I need to share with the audience here. When you’re a small business, you think your brand is the value that you have. It’s the founders who are the brand. So it’s Manish and me. Manish, my business partner, is really big in productivity, project management, and that kind of thing. And I’m really good at building solutions using tech. And together we have about 55 years of experience.  And then our key team members are ex-Microsoft or MVPs, Microsoft Most Valuable Professionals. So we hire a really strong key team. And the team below, we can either fill with our members, hire our own members, or go to the vendors also, and we tell it to our clients also. So our delivery model is we are the ones who are delivering. The guarantee is taken by Manish and Dave, not by Think AI. We have gotten into that situation. We are about 95% successful, so there’s a 5% failure. And the failure is either because we have the wrong team member, the communication between the client and us was not clear, the scope was not clear, the definition of value and done was not clear, and we have learned from it.  So our business model is towards that, and that brings us growth because we work with a number of partners. Manish is part of a lot of Microsoft channel partner networks. We provide complementary services to those partners. So one channel is we work with a lot of partners because the trust is there. Authority and trust are the two factors we have understood which establish your business, and it’s the founders’ authority and trust, not the company. Company will build on its own. So we started building our own authority and trust, and that gets us growth. It’s not at the level we’d like, but we are happy.  You are happy. Okay. So what is your vision? What would you like to make out of this?  So we have an exit plan, at least on Think AI. And like I told you, Manish has his own. That is up to him. For me, I want to create this venture studio for disabled entrepreneurs, get the funds from here, and then harvest, go across the world. So three hobbies I have.  One is travel. Second is reading, writing stuff, books. And third is music. And entrepreneurship comes in this whole surroundings, in this whole ring, so it’s the foundation of it. So we’re going to build this disabled entrepreneurship venture studio with a little bit of funds from our exit, and hope to grow there and hope to retire or die with that thinking.  Love it. Love it. It’s fascinating. So you have a book that is on your LinkedIn page, Real-Time Business Intelligence Mastery. So tell me about this book. Why did you write it, and what’s it about?  Sure. So we went into a coaching program. Up until 2022, we were arrogant enough to say, “Oh yeah, we can do everything on our own.” And then slowly we realized we need help, and we started taking help. We went to a couple of coaches in India where they were coaching us either on how to manage operations and operational excellence, and then another coach who’s like a life/building-your-brand marketing coach, and he inspired us to write a book.  Now, I’ve been writing in my own native Hindi language, songs and compositions, but writing a book was a dream, and I thought it’s a big undertaking. But with their little bit of motivation and help, not in writing, but in the angle of what a book can bring. So I have a lot of experience working in midsize manufacturing organizations, working with CTOs and CIOs, and business intelligence is delayed. So it’s either a one-day delay or a week delay or a month delay, and it’s more reactive in nature.  So the book was more about how you can build a real-time business intelligence culture so that you can get the insights from your data, make actionable insights, take actions on it, and grow your business for those two imperatives I talked about, which is grow your revenue or increase your productivity and decrease your cost.  So are you writing about some of the things that you talked about? Leveraging AI, building AI agents?  It has more about—so I wrote it in 2022, I believe. It has a lot more detail about. AI was not as popular, right? I mean, I did write about AI in it, but it was more about building a data culture than AI. It does talk briefly about AI because real-time is going very closely with AI. That’s the enabler for AI insights or data insights through AI. So it does talk a little bit about AI, but it talks more about tech leaders like CIOs and CTOs. What do they need to do? How do they need to build a culture around harvesting data, bring the data, build the team, where to take it? So it has those details.  Okay. That’s fascinating. Who is this book for? Is it for founders? Is it for C-level executives? Who is the target?  Like I said, it’s for tech leaders, CIOs, and CTOs of midsize organizations.  Okay. That’s awesome. And these are the people that are your target customers as well at Think AI?  Yes. That’s our true ideal client profile too, and that’s whom we have worked with all our lives. So they’re close friends, target audience, and customers. Future customers and current customers.  All in one. All in one. That’s so nice when you write a book to your friends. That’s a very cool concept. So let me ask you this, Dave. If you had a magic wand, you’ve done a lot of things in your business, you built nine businesses. You learned from some of the failures that you had, which is part of entrepreneurship, and now you created AI agents, and then you have a second brain, and you’re leveraging all that technology. So if you had a magic wand and you could fix one thing in your business in the next 12 months, what would that be?  I wish I had more senior leadership. Any business works with delegation. We have a couple who are really amazing, and they wear a lot of hats. But growth depends on three things, right? Being in front of the right customer, having the right team, and having the right product. Our product is people, unfortunately and fortunately. Customers, we are very happy and excited, and they trust us. We know how to get to them. We know how to create value for them. We are very satisfied. Everybody would say, “I need more customers,” and we would do that too.  But I think more important is what product you are offering. So then people are what we are offering, and we are competing against big ones like Accenture and Avanade and Cognizant of the world in our business, the tech consulting business. But then we are not competing against cost; we are competing against value. So how do you create value? You find a valuable customer. They understand our language. The next level is, where is the product, which is the people? And that management becomes quite difficult. And harvesting and getting the right people in place is a job by itself.  So kudos to those large companies if they’re harvesting one, although that’s debatable because when we go to the client, they complain a lot about their resources as well. So harvesting the right product and the right team is the key. And how do you do that? If you have the right leaders on top. Two partners alone cannot do that. So building more leaders underneath is the key. We are able to build a few, and I wish we could build a lot more. So when you have the right core team, your growth comes in, is my belief system. It could be different for everyone else.  No, I think it’s a very deep insight, and very few people actually talk about this idea that the purpose of a business, especially in today’s AI age, is to build leaders. That’s your purpose, because people will take care of everything. They’re going to run your AI agents. They’re going to manifest your vision. But you can’t have just AI agents in a company, right?  Because then the mental load is so much on the leader, and then the single-person dependency becomes critical. So is this what you mean by this? Where do you come from with this idea of harvesting people and leaders in the business?  Absolutely. You said it well. Building leaders doesn’t just apply to an organization, whether small, medium, or big, but even to countries. If you don’t have the right leaders in place, it’s going to bite you back. And all cultures, some of the top management consultants will teach you to go into succession planning. That is what they really mean by that.  It’s not succession planning by, okay, replace a CEO with a CEO. It’s the mindset. Apple is a great example of it. Steve Jobs hired Tim Cook from Compaq, from that world, and he had that vision. Obviously, he had a mission, but he had the vision—who to take, where to take, and what they would do. And that legacy continues even today. So Apple didn’t change a single bit in their model. And people would argue and debate, and that’s fine.  But when I see it from my eye, he built a great leader. When he did that, the company stayed the same, right? So it’s not about what products Apple is creating today, whether it’s iPhone or iPad or Apple Vision Pro or some of the other things that they are doing, but it’s really that leader. Same thing went with Google, or Microsoft, Satya Nadella. And you see the right leaders were built by these founders. And by any means, we are not that big, and hopefully we can get to some place which is pretty good in our books.  But finding and building the right people, it gives you a lot of satisfaction, happiness, bliss, if you can give it back to somebody who’s capable enough. And I’m always in hunt of the right people, building the right team in place.  It’s so interesting you mention Apple because when Isaacson came out with the Steve Jobs biography, he said, basically, I think it’s in the preamble of the book, that Steve Jobs wanted people to remember him not for the products that he created, but the company. So his biggest contribution was creating a company. And I didn’t get what he meant by it.  But if you witness the last—since he died 13 years ago—the last 13 years, this company has gone from strength to strength. Ninety percent of its market capitalization has been created since he died, right? So it keeps growing and keeps going from strength to strength, and that is the culture and the people that he built. This is the company he built. So it’s quite an amazing idea.  I was about to comment on company. Something came back to me or reminded me that companies generally build on three pillars: customer, people, and culture. And if you don’t have the right balance of it—so, the right people, but if you don’t have the right culture, they’re going to run away. If you don’t have the right customers, you should have the ability to say no to certain types of customers too. Like Apple never targeted small, cheap products.  And when I say cheap, meaning which doesn’t have the right quality in place, not about the cost. It’s always cost versus quality. So they have really struck the right balance in those three angles, and I think that’s the right way to do it. Some are able to do it, some are able to push through to do it, and some are not. But that’s where I think the focus needs to be if you are a founder. Find that right balance of people, client or customer, and culture.  Yeah.  And that is your core values too.  Yeah. I agree with you. That’s wonderful. If you are listening to this conversation with Dave Goyal, and you would like to learn more about him and what he does and Think AI Corporation, where should our listeners go to learn more?  Thank you for this opportunity, first of all. And people can find me on LinkedIn by my name, Dave Goyal. I’m very active there. I recently started a YouTube channel with the name Dave Goyal, so you can find me on YouTube. And mainly on LinkedIn, I have a newsletter on AI, and I’m pretty passionate about what’s happening in AI.  So I even publish AI news this week, but with a different angle, a builder’s angle in mind. And last but not least, you can connect with me through LinkedIn for a 15-, 30-minute call. No angle there. I will just come and help you if you really want to do something with AI. I can listen to your challenges or your fear of missing out, if that’s the case, and tell you if AI is the right fit for you or not, and what you can do on your own also. And if you need our help, we are happy to.  That’s fantastic. So take Dave up on his offer, which I think is very generous. And obviously, Dave, you know what you’re talking about. You built a second brain. You’re running AI agents. Your C-suite is chock-full of AI agents, which is very impressive. I’d love to learn more about this myself.  So if you’re curious about that, make sure you book a call with Dave or check out his stuff. Where is your newsletter? Is it a Substack? Where can people find your newsletter?  It’s on LinkedIn. It’s called Data & AI Demystified in my profile.  Okay. So that’s easy. So we can go to Dave’s LinkedIn profile. And if you enjoyed this conversation, make sure you subscribe and follow us on Apple Podcasts and YouTube. Give us a review because every week I bring in a couple of exciting entrepreneurs like Dave who share their favorite frameworks with you. So Dave, thanks for coming, and thank you for listening. Important Links: Dave's LinkedIn Dave's website

 EPISODE DESCRIPTION I sit down with Berken, CMO of CoinTracking, the world's first crypto tax platform founded all the way back in 2012 when Bitcoin was under $100. We dig into how they bootstrapped their way to 2.2 million users, why authentic education beats paid placements every time, and how they're navigating AI in a space where a single wrong number could land you in trouble with the IRS. Berken shares what channels are actually moving the needle, why they turned down the idea of launching their own token, and what their upcoming MCP integration means for connecting your Claude or ChatGPT directly to your tax data. Whether you're a crypto trader trying to avoid overpaying taxes, a founder looking for growth lessons, or someone curious about how a SaaS company stays relevant in a fast-moving space, this episode is packed with practical insights. DISCLAIMERNothing mentioned in this podcast is investment advice and please do your own research. It would mean a lot if you can leave a review of this podcast on Apple Podcasts or Spotify and share this podcast with a friend. Be a guest on the podcast or contact us - https://www.web3pod.xyz/ CONNECT CoinTracking Website: https://cointracking.info/ CoinTracking Twitter/X:https://x.com/Coin_Tracking Berken LinkedIn: https://www.linkedin.com/in/berken-mengesWeb3 with Sam Kamani: https://www.web3pod.xyz/ KEY POINTS WITH TIMESTAMPS • [00:01] Sam introduces Berken, CMO of CoinTracking, and frames the episode around crypto taxes, AI, and startup growth• [02:12] Berken shares his journey from personal crypto investor in 2019 to CMO, starting as an affiliate marketing manager• [03:56] CoinTracking overview: 2.2 million users, 400+ exchange integrations, portfolio tracking and one-click tax reports• [06:32] CoinTracking was the world's first crypto tax tool, founded in 2012 by Dario Kachel who built it for himself• [08:00] The bootstrapped, organic growth story: users gave feedback, helped translate, and shaped the product over 13 years• [10:20] Sam and Berken discuss how fragmented the crypto landscape is across DeFi wallets, CEXs, and blockchains• [13:11] Why CoinTracking is a SaaS and not a crypto asset service provider, and how that makes compliance and partnerships simpler• [14:58] How CoinTracking is approaching AI: an MCP integration coming soon to connect Claude or ChatGPT to your tax data• [17:27] Why they are not allowing AI to edit tax data yet , reproducibility and accuracy are non-negotiable for tax filings• [21:43] Berken's biggest CMO challenge: navigating daily shifts in regulation, exchange strategies, and market conditions• [23:07] Business model breakdown: mostly B2C, but growing B2B with CPAs, funds, and a new white-label solution for exchanges• [24:18] North star metrics: user growth and retention, with a focus on making CoinTracking a daily portfolio tool, not just a tax tool• [26:08] The most common mistake people make: filing taxes with missing wallets or transactions, which can result in overpaying• [29:08] What marketing channel works best: long-form YouTube content, authentic KOL partnerships, and connecting KOLs with CPAs• [34:58] CoinTracking has been profitable since day one and is not looking for funding, but actively seeking exchange partnerships• [36:09] Why they decided against launching their own token: sentiment risk, distraction, and wrong-type user acquisition• [39:00] Sam draws a parallel to Xero's accountant-led growth strategy and how CoinTracking could follow a similar path

Amanda Vega is a marketing strategist, entrepreneur, fractional CMO, and technology and culture expert who has spent more than 30 years helping brands, founders, and organizations find their voice, build communities, and create movements. From her early days on the AOL team to earning an MBA from Columbia University, building and selling two agencies, and now working at the intersection of emerging technology, genomics, precision health, and personalized wellness, Amanda Vega has lived through—and helped shape—the evolution of the internet, marketing, business, and human behavior.In this episode of The VIBE with Kelly Cardenas, Amanda and Kelly explore marketing, entrepreneurship, technology, faith, health, relationships, reinvention, music, and the power of language. Amanda shares what she has learned from more than three decades in business, why she considers herself an “Internet dinosaur,” and what happens when we stop forcing people into neat little boxes.Amanda is a co-founder of Rephase Health, focused on creating a more precise roadmap for menopause and andropause. She also works as a fractional CMO and entrepreneur across emerging technology and precision health while navigating the beautiful chaos of raising teenage boys, launching a podcast, and finding ways to keep dancing—even when a broken back has other plans.But this conversation goes far beyond Amanda's résumé.Amanda and Kelly talk about civil discourse, the importance of asking difficult questions, the courage to say uncomfortable truths, and why curiosity may be one of the most important leadership skills we have lost. They explore how business, culture, faith, technology, health, music, and human connection can coexist in a life that refuses to fit neatly into a box.At the heart of this conversation is a bigger question: What happens when we stop trying to define ourselves by what we've already done and start paying attention to where we are being called next?The VIBE isn't the energy you bring into the room. It's the way people feel when you leave.Subscribe to The VIBE with Kelly Cardenas for conversations with extraordinary people about leadership, business, culture, personal growth, entrepreneurship, technology, and the moments that shape who we become.#AmandaVega #MarketingStrategy #Entrepreneurship #FractionalCMO #TheVIBE #KellyCardenas #Marketing #Leadership #Technology #PrecisionHealth #Genomics #PersonalBranding #CivilDiscourse #PersonalGrowth

Kymm Martinez was doing the work to land clients.She had scorecards. She had a tracker. She was having discovery meetings and working her network. She had nearly 20 years of marketing experience at General Mills plus two CMO roles so she understood business development. And yet her pipeline wasn't becoming predictable, and she couldn't figure out why.In Episode 285, Melisa Liberman sits down with Kymm to unpack what was actually happening and what changed when she put a microscope to the activity instead of just doing more of it.Kymm shares how she discovered she was focused on quantity instead of quality, the corporate habits she didn't realize she'd carried into her consulting business, and how perfectionism was quietly blocking her at every stage of business development.She also shares what shifted in how she thinks about her goals, from replicating her corporate income to setting a very different vision for what her business could become.If you've been putting effort into business development and still don't have a pipeline that feels predictable, Kymm's story will help you figure out exactly where to look.Timestamps for Key Moments:[00:00] Introduction to Kymm Martinez and why her story matters[00:02] Companion resource: Lead Gen Sprint at www.ConsultantSprint.com[00:04] Kymm's background and what surprised her about going independent[00:07] The corporate habits she didn't realize she'd brought with her[00:22] Perfectionism as a BD blocker and how she's managing it[00:29] What surprised Kymm about the Sprint cohort[00:38] Dreaming bigger: from replicating corporate income to a million-dollar goal[00:43] Advice for fellow independent consultantsResources Mentioned:Companion Resource: The Consultant's Lead Gen Sprint. Fall cohort starts September 22nd. Enroll at www.ConsultantSprint.comGuest website: www.wildermarketinggroup.comGuest LinkedIn: www.linkedin.com/in/kymmmartinezThe Wilder Brief (newsletter): www.wildermarketinggroup.com/the-wilder-briefFull Show Notes: https://shownotes.melisaliberman.com/episode-285Want More?Melisa's Books, Planners & Journals: https://linktr.ee/melisalibermanGet Melisa's Book: https://www.melisaliberman.com/bookVisit Melisa's Website: https://www.melisaliberman.com/Follow on LinkedIn: https://www.linkedin.com/in/melisa-libermanWant help achieving your consulting business goals? Melisa can help. Click here for more on coaching tailored to you as an independent consulting business owner.

Send us Fan Mail73% of marketers now use AI every day, and most of us feel the boost: more speed, more output, more “done”. But one number stops me cold: only about 30% say they're seeing significant measurable results. That gap is the signal. The big question for marketing leaders is no longer whether AI belongs in the team. It's whether AI is making our marketing better or simply making us faster at producing more.I unpack what the 2026 AI Marketing Industry Report from Michael Stelzner and the Social Media Examiner team really means for CMOs, founders, and growth leads. We talk about why AI makes marketing activity cheap while value creation stays hard, and why the future CMO role shifts toward orchestration: connecting business goals, customer needs, marketing technology, people, and outcomes. If your AI success metric is “hours saved” or “content shipped”, we're stopping too early. The board cares about what changes because of the work.We also explore the tension between visibility and differentiation, pulling in ideas I've discussed with Gary Vaynerchuk and Chris Do. AI discovery is real, and being present across formats matters, but when everyone can publish endlessly, the differentiator becomes deeply human: judgment, taste, courage, a clear point of view, and trust. With rising concerns about accuracy, reliability, data privacy, and security, trust is the one thing AI can't scale for you.This solo episode was recorded via Descript on August 26, 2026. Read the blog article and show notes here: https://webdrie.net/the-ai-adoption-race-is-ending-what-michael-stelzners-2026-report-means-for-marketersSubscribe to Web3 CMO Stories, share this with a marketing leader who needs it, and leave a review if it helps. What's your honest answer right now: is AI making your marketing better or mostly faster?.......................................................................... 

AI made it cheap to produce content, and now every cybersecurity vendor sounds the same. Brian Reed, CMO at Corsha, argues the answer to that sameness isn't more AI, it's the human layer: real stories, congruent brand moves, and community. He gets specific on how to use AI as a story partner rather than a content mill, why your customer is the hero of every story, and how to stand out in a market of 4,000 vendors.In this episode:Why AI content creates "mass sameness," and where humans still create meaningThe golden triangle: AI as content assistant and community as the source of real storiesWhy your customer is the hero of the story, never your product, your rep, or your companyThe business-card test for a company story simple enough that every employee can tell itHow to open a sales conversation with a 30-second customer story instead of an agenda slideUsing AI to find patterns, sharpen, and retitle stories, plus building "persona" agents like his crusty OT engineerWhere the line sits between a memorable brand moment and a forgettable gimmick (Wiz vs the puppies)The three kinds of community, why "build your own" is hardest, and why community is never lead genAbout the guest: Brian Reed is CMO at Corsha, working in industrial and OT cybersecurity. His background runs from database middleware and data warehousing in the 90s through application security and the DevOps / DevSecOps movement, including helping build the All Day DevOps community, and he writes regularly on AI and storytelling.Notable quotes:"The tide raises all boats, but they're all drowning in content, and it all sounds the same.""Your product's not the hero, your sales rep isn't the hero, your company isn't the hero. The hero is the people.""Community is never, ever about lead gen. It's brand building and giving to get."Chapters (approximate):00:58 — The ugly underbelly of AI content: sameness04:41 — Who the hero of the story really is07:13 — The business-card test and "us and them"13:13 — Using AI as a story partner, and the crusty OT agent19:05 — Standing out vs gimmicks: Wiz, Island, and the puppies27:53 — The coffee truck, and de-risking bold bets33:16 — The three kinds of community37:05 — Why community is never lead gen Support the showThe Cyber Go-To-Market Talk is the show for cybersecurity sales leaders, founders, CROs, and go-to-market operators looking to improve cyber sales performance and build more predictable revenue growth. Hosted by Andrew Monaghan, founder of Unstoppable.do, covering cyber sales leadership, revenue leadership, sales onboarding, forecasting, pipeline generation, and cybersecurity go-to-market execution.Follow me on LinkedIn for regular posts about growing your cybersecurity startupWant to grow your revenue faster? Check out my cybersecurity sales consulting and trainingNeed ideas about how to grow your pipeline? Sign up for my newsletter.

Do you have a leaky lead bucket? AI can seal the cracks! Spending more on marketing and software but still missing calls, losing leads, and chasing chaos?

Marketing has never been more measurable. It may also have never been more short-term.If measurement was supposed to solve marketing's credibility problem, why hasn't five years of better data increased CEO confidence in marketing?In this Sharp Cut, Marc and Vassilis unpack what happens when the things marketing can observe quietly become the things organizations value.They trace the progression from visibility → accountability → optimization → observability, and ask whether attribution windows, platform dashboards and ROI have inadvertently trained marketers to optimize for short-term outcomes.Using research from Boathouse, the Norwegian marketing industry and others, they explore why the same data can produce radically different conclusions depending on how it is framed.They also tackle a harder question: who is responsible?Is finance forcing marketing to think short-term? Or have marketers quietly accepted the measurement windows handed to them by platforms and brought those definitions of effectiveness into the boardroom?The answer turns measurement into something much bigger: a leadership decision.Because the moment you choose the window, you decide what value counts — and what value doesn't.Chapters:00:00 Marketing Has Never Been More Measurable00:50 More Measurement, Same Confidence02:14 Marketing Won the Seat but Lost the Argument03:49 How Measurement Became Optimization05:13 When What We Can Observe Becomes What Counts05:30 The Fishing Net Problem06:47 Where Leadership Enters the Measurement Debate08:38 Are Marketers Responsible?09:12 When Marketing Takes Credit for the Weather11:16 The 35 Forces That Affect ROI12:09 The Halo Effect13:30 Same Data, Two Completely Different Answers15:45 The Retail Number That Changes the Story16:26 Why Every Channel Wants More Budget17:57 Measuring Podcast Advertising With the Wrong Net20:07 The Problem With the 95:5 Rule21:46 Why ROI Can Mislead24:06 How Cutting Spend Can Improve ROI25:20 What Does “Return” Actually Mean?27:03 When Long-Term Evidence Loses to the Quarter28:23 Can Marketing Choose a Different Window?31:29 Measurement Becomes a Leadership Problem32:42 You Can Predict the Answer by Looking at the Net34:07 Five Questions to Ask Before Measuring35:00 What Marketing Can Learn From Finance35:35 The Measurement Problem Is a Leadership Problem35:59 What Comes Next: Discounted Cash FlowEpisode Sources:Boathouse, Fifth Annual CEO Study on Marketing and the CMO, 150 US CEOs, fielded January 2026. Coverage via Marketing Dive, SmartBrief, CommPRO.Gartner, May 2024, CMO survey on internal skepticism of marketing value.Calgary Marketing Association and Stone-Olafson, 2024 ROI report, Alberta marketers, n=124.Kapero, ANFO and the Norwegian Media Businesses' Association, The Commercial Power of Brands in the Digital World, 13 Norwegian companies, 2024 data.Podscribe, Conversion Rate by Podcast Player, more than 50 direct response brands, 30 daywindow.Quatical, The 35 Factors That Affect Marketing ROI.Rosenzweig, P. (2007). The Halo Effect. Free Press.Eddington, A. S. (1939). The Philosophy of Physical Science. Cambridge University Press. The ichthyologist parable, told in summary. No direct quotation used.

L'IA peut vous aider à produire plus vite, à décliner vos contenus et à gagner un temps précieux. Mais il y a un risque : à force d'utiliser les mêmes outils que tout le monde, est-ce que nos marques ne vont pas finir par toutes se ressembler ?Et surtout, comment faire pour que l'IA comprenne vraiment ce qui fait la singularité de votre marque ?Dans cet épisode du Podcast du Marketing, je reçois Marion Cas, spécialiste de l'intégration de l'IA dans les Content Factories.Ensemble, nous nous intéressons à ce qui se passe avant le prompt.Parce qu'utiliser l'IA efficacement ne consiste pas simplement à choisir le bon outil ou à apprendre quelques techniques de prompting. Il faut d'abord savoir ce que l'on veut lui confier, ce que l'on préfère garder entre les mains des équipes et, surtout, être capable de lui expliquer précisément qui nous sommes.Nous parlons donc de stratégie de marque, de création de contenu, de brand guidelines, mais aussi de cette connaissance de la marque qui existe parfois davantage dans la tête des équipes que dans les documents officiels.Marion partage plusieurs exemples de grandes marques qui ont fait des choix très différents face à l'IA. Elle explique également pourquoi nos bons vieux brand books ne sont pas forcément aussi utiles qu'on pourrait le penser lorsqu'il s'agit de travailler avec une intelligence artificielle.Et vous verrez que derrière cette question très technologique se cache finalement un sujet beaucoup plus marketing : qu'est-ce qui fait qu'un contenu ressemble vraiment à votre marque et pas à celle de votre concurrent ?Un épisode pour prendre un peu de hauteur sur l'IA et réfléchir à la place que vous voulez réellement lui donner dans votre marketing.

This week's ADSN Rundown covers a packed slate, starting with True Classic running QVC-style live video directly on its homepage and whether that model or agentic commerce has a better shot at reshaping e-com. Daniel and James dig into Nikita Bier's take on shipping fast at X, where press releases were written 20 minutes before launch, and why overthinking go-to-market is a trap. They break down reporting that Chinese institutions are building AI models of American voters to test political messaging, the implications for open-source models, and what it means for platforms like TikTok. Olivia Moore's data on agent token consumption makes the case that API-first product strategy is no longer a debate. The guys also cover Instagram's new in-comments site preloading, the 1840s origins of the word "slop" and its AI parallel, Josh Wolf one-shotting a full motion graphic video with Claude Code, and a humanoid robot running 100 meters faster than Usain Bolt at China's robot games.On the business side, Rohan Dar points out that Anthropic's rumored $2 trillion IPO would be four times larger than every San Francisco IPO in history combined. A new "Tech Trades" segment tracks major talent moves: Jeremy Voss and Alex Osborne joining Airbnb from Snap/Tinder, Eric Toda becoming CMO at Air, and Luke Kallis landing at Agbo, the gaming company co-founded by the creator of Fortnite and the Russo Brothers. Primary posts this week highlight Jeff Morris Jr. cold-texting Lance Armstrong for a bike ride and Ed O'Neill's masterclass in playing the long game when negotiating for Modern Family.Thank you to our sponsors:AdQuick – Making OOH advertising as easy to plan, buy, and measure as digital. adquick.comThrad.ai — Building the advertising infrastructure for AI. thrad.aibeehiiv — The all-in-one platform for newsletters, websites, and every tool you need to grow and earn. beehiiv.comThe Farm — Fraction commercial legal with an in-house approach to outside counsel. thefarmllp.comSTAY CONNECTEDJames on Twitter & LinkedIn – /jamesborowDaniel on LinkedIn, Instagram, TikTok – /danieldrugerSubscribe & leave a ⭐⭐⭐⭐⭐ review on Spotify & Apple Podcasts.

What does it take to market a product that challenges long-held category expectations?Conley Downing, CMO of Archer Roose Wines, breaks down the strategy behind building a premium canned wine brand. From consumer trial and experiential marketing to Elizabeth Banks' creative role, retail visibility, moderation trends, and the power of a distinct brand identity, she shares how Archer Roose is making canned wine feel approachable without compromising quality. Hosted on Acast. See acast.com/privacy for more information.

As people take greater ownership of their health, the role of brands is changing.Recorded live at the Havas Café during the Cannes Lions International Festival of Creativity, this conversation explores how marketing can help people live healthier, longer, and more fulfilling lives.Jim is joined by:Yvonne Bryant, Hemoglobinopathies Commercialization Head at Novo Nordisk, whose career has spanned clinical research, drug development, commercialization, and consumer marketing. Today, she leads commercialization efforts for rare blood disorders, helping translate breakthrough scientific innovation into meaningful patient impact.Lauren Gellman, Senior Director and Head of Marketing for Health and Home at Google. Lauren oversees marketing across Google's health ecosystem, including Fitbit, Nest, and Google Health, where she's helping shape the future of AI-powered health experiences and personalized wellness.Samantha Avivi, Global Chief Marketing Officer for Consumer Health at Bayer. A longtime marketing leader whose career includes roles at Procter & Gamble, Kimberly-Clark, Walmart, and more, Samantha now leads global marketing and innovation across Bayer's portfolio of trusted consumer health brands.Drawing on Havas' Science of Desire research, the conversation explores how healthcare marketers are building trust in the age of AI, making complex science more accessible, and helping people navigate an increasingly personalized health journey. Ultimately, it arrives at a simple but powerful idea: the future of healthcare marketing isn't simply about helping people live longer. It's about helping people live better.—This week's episode is brought to you by Havas and Infillion.—Meet The CMO Podcast On the RoadThe CMO Podcast will be on the road throughout Q4 2026, capturing conversations with the leaders shaping the future of marketing, leadership, and business. If you'll be attending one of these events, we'd love to connect. Let us know!Advertising Week New York | October 5–7BLINK Cincinnati | October 8ANA Masters of Marketing | October 19–22—Interested in partnering with The CMO Podcast?!Looking ahead to the rest of 2026 and into 2027, we're partnering with brands to create executive content platforms that extend far beyond a single event. From pop-up podcast studios and live recordings to executive roundtables, keynote conversations, and bespoke thought leadership programs, we work with partners to build meaningful experiences that connect with senior marketing leaders.Whether you'd like to partner with us at one of the industry's biggest marketing events or create a custom experience designed specifically for your brand, we'd love to explore what's possible. Reach out to learn how we can build something together.Email us at podcasts@vyve.co—Produced by vYveThe CMO Podcast is proudly produced by vYve Production, a full-service production and content studio specializing in podcasts, executive storytelling, branded content, and live experiences. vYve is a community of ambitious leaders dedicated to unlocking what's next in business and in life. Through executive coaching, transformative experiences, strategic content, and communities like The CMO Podcast, vYve helps entrepreneurs, corporate leaders, and teams grow their businesses, strengthen their leadership, and build meaningful connections that last.Learn more about vYve and The CMO Podcast community at www.vyve.co.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Carlos Corredor, Co-Founder and CEO of Condor Digital Marketing, is driven by a passion for interpreting data and helping marketing leaders Generate and Measure Your Pipeline with greater accuracy. ith a background in sports analytics and journalism, Carlos helps B2B companies identify which marketing activities generate qualified leads, clients, and revenue so they can invest confidently in what works.  In this conversation, Carlos introduces The Condor Pipeline Generation Framework—Understand Current Pipeline Generation, Map the Process, Move Budgets to Their Highest and Best Use, Fix Measurement Gaps, and Rinse and Repeat. He explains why marketers should begin with clients and revenue instead of clicks and impressions, how the Pipeline X-Ray exposes attribution gaps, and why budgets should move toward channels with proven returns. Carlos also discusses using BANT to diagnose conversion problems and why client champions, paid media, and events drive growth in high-ticket B2B markets. — Generate and Measure Your Pipeline with Carlos Corredor  Good day, dear listeners. Steve Preda here with the Management Blueprint, and today my guest is Carlos Corredor, Co-Founder and CEO of Condor Digital Marketing, a pipeline generation and measurement firm. Carlos, welcome to the show.  Hey, Steve. Hi, everybody. Thanks for having me. Great to be here.  It's exciting to have you and to learn about your secrets of how you generate a measurable pipeline. But before we get into it, I'm curious: What is your personal why, and how are you manifesting it through your company?  Yeah. So I've always been passionate about sports and the data behind sports, and I actually worked in sports data analysis and journalism. But ultimately, I've been passionate about interpreting data to have an advantage, whether that's playing tennis or doing analysis for baseball teams. And then I eventually started working in marketing, doing sports websites, and I saw the opportunity. In marketing in general, especially with digital, to use data to your advantage. So I would say that's really what I'm passionate about in terms of my professional life and why I enjoy what I do so much and why I get up in the morning and I really look forward to the day and even to Monday. Because obviously, it's not all fun. But ultimately, I think it comes from that passion of liking what you're doing, and the time flies when you work and you like what you do and you see that you're good at what you're doing and it's making an impact. So I would say that's why.  And have you always been a data person? Are you analytical and like to look at the numbers behind things?  Yeah, yeah. It started with sports. That's where I realized that I had, let's say, that passion at the beginning and ultimately that skill. With baseball at the beginning, it was reading the back of baseball cards and then fantasy baseball in high school, and then actually working in that. In kind of like sabermetrics and Moneyball-type analysis in college.  Because I saw, just like it happens in marketing, how back in the old days, even professionals, they were using the wrong type of data or a very antiquated way of looking at things. So it's like understanding really what has an impact and what is responsible for outcomes. That's, I think, the part that I've always thought was what's important and what I had a knack for, a talent to do that better than others. So that's why I went deep into that.  Okay. So how do you do that? So this podcast is a podcast of frameworks. So I wonder if you have a framework of how to create pipeline generation based on data, and perhaps you can share a simplified version of that with our listeners, something that can be explained in three to five steps.  Yeah, definitely. And I'll give you first the kind of like the philosophy or the mental model, and then I'll give you those steps because one comes from the other. So in marketing, with all of the data that's available, especially today, a lot of people start at the bottom. At clicks, impressions, and then they try to build a bottoms-up report to then prove what's generating leads and clients and revenue. But that is always inexact, takes forever.  What I propose is doing it the opposite: a top-down approach where you start with clients and revenue, and then start figuring out where those leads in your pipeline or clients and the closed revenue is coming from. And you will know all of that at the beginning. So that's, I think, how it starts, that framework. So the first step of the framework is to understand, which sounds really basic, but you'd be surprised today how many marketing leaders, marketing VPs, CMOs of especially mid-market, definitely smaller mid-market, and even some enterprise companies, don't have that data readily available to understand how much pipeline did we, as a marketing department, generate, let's say, last year. So that's, I think, the first step, is understanding that. It's asking your team for a report that says that. Now your team's going to come back and say they won't know the full picture. Maybe they know 10%, maybe they know 90%. But they're going to show you something. So then is the second step. You're going to start adjusting your investments to what you're seeing there, and at the same time, you're going to start fixing the dark holes or what you can't see.  And then simply step number three is rinse and repeat every, let's say, quarter at the beginning. And obviously, there's nuances of how exactly you should adjust and what exactly you can fix. But ultimately, that would be the three-step approach that you asked about.  That's fascinating. So the understand piece is understanding your pipeline or how you're generating the pipeline? What is it? Understanding what?  Yeah. So actually we have a name for that first step. We call it the Pipeline X-Ray. So let's say you start a new job as a CMO of a new company. Or simply you've been in the job for a while and you're listening to this and you say, “Okay, actually, I've never thought about it that way.  Let's sit tomorrow with my team and ask the question: How many qualified leads and closed clients have we, as marketing, generated so far this year and, let's say, last year?” That is understanding that. Now, I'll tell you, I'd be very surprised if the marketing person or the marketing team or the leader has that data in a way that they can say with 100% certainty what the answer is. In terms of, “We've closed these four clients, and we've had 72 qualified leads.  And out of the 72, 50 have come from our paid search campaigns, 10 have come from events, and then the others have come from organic.” In an ideal world, that's the type of answer that you want. But in the real world, again, very rarely do you have that clear understanding right then and there. So that's when step number two becomes, okay, let's close the gaps to be able to have an understanding.  Okay. So essentially, when you say adjust and fix, then are you talking about adjusting and fixing the process of generating clients, or actually mapping the gaps in the pipeline first?  Yeah, so that's a great question. The adjust, I mean move budget around. Not necessarily increase budget. You have to prove what's working. And obviously, if you don't have the full picture and understanding, you cannot just go to your CEO and say, “I need more budget.” So with the same budget that you have, what can you pause and move around towards the things that step number one told you with certainty are working. So if, let's say, out of the 50 qualified leads that you generated, you saw that half of them came from your paid search campaigns, then you say, “Oh, okay.” And then you don't see anything, let's say, for conferences, and now you're going to 10 conferences a year and you're spending a million dollars on conferences, and you're only spending $200,000 a year on your paid media spend. Then you say, “You know what? I'm going to stop. I'm going to pause. We're not going to go to these two conferences this year, and I'm going to move those $200,000, and we're going to double our spend in Google Ads,” for example. That's what I mean with the adjust piece. It could be the opposite. It could be pause paid search and then be more aggressive on our conference strategy. It could be, let's start a paid social campaign, whether that's LinkedIn or programmatic ads, or let's be more aggressive on our PR because right now our leads have come from interviews that our subject matter experts have done in certain types of podcasts or YouTube channels.  But that's what step number one is. But adjust is move budget around. Put your stocks where the returns are positive and where you can expect a better return almost immediately, or at least in the next upcoming months. And then the fix is particularly around the measurement gaps. The fix is what you can't see, right, on step number one. Step number one is understanding. And a report with all of that. When the person that does the reporting for you came back, or when you did it yourself or whatever, probably a lot of leads are like, “Ah, now it says direct traffic. What is that?” Obviously, they didn't just come and wake up one day and say, “Oh, I'm just going to go to condoragency.com.” No, they heard you somewhere, but you're still not sure. You won the client, you know you won the client, the client's paying you money, but you're not sure. So maybe, okay, what needs to improve in our measurement framework.  Usually, you can start with your CRM, your HubSpot, Salesforce, for instance, or whatever you use. There's some web analytics that might need to happen. You need to connect your advertising platforms. You're probably going to need to start talking to your sales team so they ask the right questions when they have discovery calls with prospects. I mean, there's a few things you can do, but I'm talking specifically about measurement gaps so you can have the full picture.  So when you talk to new prospects or clients, can they answer one most of the time?  They can partially answer one. I would go a step beyond because, I mean, that's not the sexiest answer. I would say it's usually, let's just say, around 50% of their leads and clients, they can know who was responsible. And then there's a couple of parts there. First and foremost, not only for your sake, but for the sake of your alignment with the C-suite and with the CEO and the CFO and even the sales team. You want to know, is marketing responsible for this? Number one. Because then that's very important.  Because that's what's going to justify the existence of the marketing team. Then later, if it came from a paid search campaign or a paid social or a conference, if those all are in the marketing budget, that's secondary. But most importantly, you want to make sure that, number one, you're bringing pipeline as a marketing department, and number two, you know exactly what pipeline you're bringing. Not only you, but then also your CEO and your CFO. So then it's like a luxury, let's say, to see if it comes from, the tough part is that you won't know that it comes from marketing unless you're tracking paid search and you're tracking conferences in the CRM the right way. So obviously, they are related in that way.  Okay. Love it. So understand your pipeline generation, and then adjust the budget to make sure you're supporting the ones that generate the most, and fix those that are not optimized. So maybe optimize them or replace them or come up with a new one. How else do you fix other than your measurement gaps?  Okay, you fixed the measurement gaps. Now you can measure it. You have a full picture. Then you have a slate of options, and how do you know what to choose if you're not doing enough?  Yeah. So I think there’s a couple of things there. One is understanding if you… Because, obviously, you always want to generate more pipeline. So you have to then say, “Okay, is my problem that I'm not generating any interest in the first place at all?” Like, there's nobody visiting my website. Or even downloading some pieces of content, what traditionally is called conversions or marketing-qualified leads. Obviously, that's not the goal.  The goal is that they turn into clients. But you have to know that if people are not visiting your website and you're not seeing marketing-qualified leads coming into your CRM, then you have to do certain things. Whereas if the problem is, “Okay, no, that's not the problem, Carlos,” and this is actually more common, which is a little counterintuitive, but the more and more that we work with mid-market clients, we realize this is the case.They are generating marketing-qualified leads. There is activity in the CRM. There are companies, new companies, that you see are visiting your website, downloading and consuming content. But then, for some reason, they are not becoming clients. So that's where we have to dig in and understand. Maybe they downloaded a white paper that was very educational in nature. And they're not ready to buy. Which is fine, and I'm not saying you have to not show that white paper, but you know that white paper is not going to bring you ready-to-buy customers.  So that's when we have the concept of what sales and marketing people call a BANT-type of lead, which is a lead that has the budget, the authority, the need, and the timing. You want, obviously, a lead that has the four things. Now you start, you measure. Okay, we had 10 leads, and they had, let's say, the budget and the authority. They were the CTO. The lead of the technology department in the company that we know has the budget. But they just downloaded this and didn't convert. They didn't have, let's say, the timing or the need.  Then maybe you rely more on, for example, paid search, which is a channel that, by searching the right keywords, the bottom-of-funnel keywords, for example, we are a pipeline generation firm. If somebody is looking for, “What is Google Ads?” That's educational. Now, if somebody's searching for “experienced agencies in B2B managing Google Ads.” Now, that's somebody that's ready to hire an agency to manage their Google Ads. So that's why, for example, in this case, if the component that's lacking is the need and the timing, paid search could be a way to do it. Or intent data, which is now something that is out there not only via paid search, but you identify certain signals and you can target them on programmatic ads or YouTube or whatever. That's another alternative. So that's something that you could do, for example, if you have a pain in moving leads down the funnel and closing clients, and you also realize that you're talking to the right people, but then they're simply not converting.  And the opposite. You get a lot of people that need your service. But they may be too small, or they may be just a manager and they don't have the authority to approve a high-ticket service. Then you go towards maybe LinkedIn targeting, or you do a campaign that is based more on account-based marketing, or ABM. Where you know you're talking to the right people. So again, that's another adjustment that you can make. So I don't know if I… Sorry if I deviated a little bit from the question, Steve, but hopefully that's still—  No, it makes sense. It makes sense. So first you want to measure, and then you diagnose. If you've got some activity but it's not converting, why is it not converting? Maybe it's not the right approach to build trust. Maybe there's another approach.  And then you look at the different elements: budget, authority, need, timing. That makes sense. So let me turn it back to you. So what drives growth in your business?  So for us, I would say if we do that, let's say, Pipeline X-Ray. And we actually did. We've been in business for almost 10 years now. And if you would do a Pipeline X-Ray, the number one driver of leads and new clients are, let's just call it, Condor champions that switch jobs. And not switch jobs that were working with us, but they were working with one of our clients.  And they worked with us, and they saw the work that we did, and they ended up moving to another agency within the same space, for example, or in B2B services, or even if it's something a little more niche like tech services, which is an area that we also specialize in. And then they say, “I already worked with Condor for either measurement or paid search campaigns or demand generation in general, and I like working with them, so they're going to call us.” And then some people, they switch multiple jobs. So embracing that and obviously using that to fuel and to focus even more on doing a great job and maintaining relationships with people, obviously most importantly while they're a client, but even if they switch, not forgetting about them. That has been the main driver. Obviously, we don't want to only rely on that. And then more recently, we've given more structure to our own sales and marketing department for that. And, for example, we closed a client that came via a paid search campaign. But that's still… We haven't scaled those yet.  We're still making sure. We're still in that measurement phase where, yeah, we're putting budget behind a few things and some of them seem to be working better, but not yet at the point of truly scaling that. We're ultimately also a relatively small firm, which obviously makes decisions differently than if you are, let's say, a mid-market or enterprise. But those, I would say, in order of importance, have been our three main drivers of growth: the champions that switch jobs, number one, and then I would say secondarily, paid media and events.  Yeah. So these are the three things. And what about the events? Why do you put events as a third? I'm just thinking that you're a B2B company and trust-based. Would events not be better than paid media?  I would say they're not mutually exclusive. Actually, they rely a lot on each other. And honestly, for us, I just put number two and three, but I would say they're tied for second, and then the other ones are four and below. And the reason why I think events are important, what we're seeing not only for us but for our clients, the outbound activity is really saturated.  I think cold email or cold outreach in general, because it used to be via email, now it's on LinkedIn as well, it's really, really saturated. It's really hard to be heard or to get a reply with cold outreach in general. Paid media, you can be a little bit more creative because you have visuals. Whether that's video that hopefully you can leverage. So I'm a believer in paid media more than the actual cold outreach via email or LinkedIn. But then the events are also great precisely because of that.  People are saturated and tired of being bombarded with messages from people they don't know. Whereas especially after COVID, people started going back to both the office and simply going out there. It doesn't have to be a big yearly conference. It can be just a dinner where you invite four or five people and talk about certain topics or any in-person activity. Well, I mean, a webinar can even be considered an event. Where you're educating your audience on certain things. And especially if your target audience is more on the manager side or below, or director and below, webinars can be an avenue.  But to answer your question, I think that personal connection is really, really powerful. And people forgot about it with, let's say, the boom of cold outreach and digital and now AI, and especially during COVID. But definitely in the last few years, we've seen not only that people are more willing or prefer to meet people in person, but we see that in the data as well, We see cold outreach campaigns that are bringing less and less results. And then when you connect in person.  Especially high-ticket. I also give this example. If you're selling B2B services, which are usually high-ticket. It's a project of either $50,000. It could be an engagement of $2 million over two years. Obviously, you want to know the company, but you also want to trust the human that is going to deliver on that promise. I always give the example: If you're selling an iPhone cover that costs $25, yeah, maybe you can get away with a pretty image on an Instagram ad. You click and you buy. Boom. Great. You can fully leverage digital for that.  But when you're selling a cloud migration project of a million dollars, you're going to want to talk to somebody, trust that person, dig in a little bit more, have a couple of meetings. So it's more complex. So in particular for those instances, that's why I think the personal connection, that it's even better if it starts at an event, or however you manage to do it, helps a lot.  So for Condor, do you make a distinction between B2B companies and B2C, and where you can help them the most?  Yeah. We have a couple of direct-to-consumer clients, but the majority of the work that we do is either for B2B or, if not B2B, it's lead generation. So e-commerce, for example, is a different world. E-commerce, as I mentioned, depending on what you buy, it's immediate. You track things. You have a platform like Shopify or something similar. It's a whole different world. Whereas that's immediate, and you can see everything, and it's all kind of automated and based on an inventory.  Whereas in either B2B services or lead generation, it's more about, okay, what happens after the initial action, after that initial either visit or conversion. Because a conversion is not a purchase. In e-commerce, in direct-to-consumer, in the example that I gave you, we made it. We sold the cover. That's our business. In here, it's like, okay, they downloaded a white paper. Or they signed up for a webinar, but that's only the first step of a long journey of closing, again, a $1 million service client.  So we specialize in that. In what needs to happen, not only to generate the initial raise of hand, but to make sure that the people that raise their hands are the right people, because otherwise they're not going to end up buying. And ultimately, the entire process of lead generated to client closed. Which is a big universe in itself. So that's where we want to focus.  So you basically help them not just to get the leads but to convert the leads and turn them into a client.  Right. Right.  So Carlos, if you had a magic wand and you could fix just one thing in your business in the next 12 months, what would you use the magic wand for?  I would say accelerate. I would accelerate by five or 10 years the structure and how mature our sales and marketing team is. I would love to wake up tomorrow morning and have a team of five people in the marketing department and five people dedicated to sales, with SDRs and a sales leader, that is already generating, that we're closing 10 clients a month. So I would say that's… But that obviously takes time.  And you want to go one step at a time, otherwise, to prove ROI and to grow without, let's say, wasting unproven budget or wasting money. But I think a lot of owners—I don't know if it's a cheap answer—but I think a lot of owners would probably answer the same thing.  Yeah. So essentially what you need to do is you need to have scalable sales and marketing so that you can just add people and it's going to—it's like a coin-operated system, right?  Yeah. Yeah.  So if the listeners would like to go through that process and they would like to understand, okay, how do we map our leads, where they come from, evaluate it, and then adjust and fix and scale, where can they learn more and how can they connect with you? Yeah.  So if they go to our website, it's condoragency.com. Condor, like the bird. There are some options there on how to work with us or even some information, even if they want to try and do it by themselves, right? Again, what I mentioned earlier, the Pipeline X-Ray. It's a quick project that we do to get to that, where you can start seeing some valuable information to take action on fairly quickly.  We can get that done in a couple of weeks, the exercise of the Pipeline X-Ray, so then you know what to start adjusting and fixing. And obviously, you can contact me directly also on LinkedIn or via our website. I'm glad to obviously have a subsequent conversation and see if and how we can help.  Awesome. So if you are out there and you want to improve your sales and marketing, then you have to start with the Pipeline X-Ray because you are getting leads, you just don't know where they are from and how effective they are, and then how you tweak the process so that you're putting energy behind the more effective ones and readjusting your budget, and then fix the gaps.  So Carlos can help you with that, right? So make sure you reach out to Condor and get the X-Ray. So Carlos, thanks for coming. And if you enjoyed this conversation, then make sure you subscribe and follow us on YouTube, Apple Podcasts, because every week I bring a couple of entrepreneurs who are sharing their frameworks with you. So Carlos, thanks for coming, and thanks for listening. Important Links: Carlos's LinkedIn Carlos's website

Send us Fan MailOn this week's episode of the Digital and Dirt podcast, Ian sits down with Ian Wishingrad, Co-Founder and CMO of breakfast cereal brand, Three Wishes Cereal, to discuss the origins of his “better-for-you” cereal, the importance of creating attention, and what it takes to turn a startup brand into a household name.Podcast Breakdown 00:00 - 09:49 Introduction & His Journey to Three Wishes09:50 - 20:00 Disrupting the Cereal Aisle20:01 - 30:03 Family, Entrepreneurship & Growing the Brand30:04 - 35:00 Retail, E-Commerce & the Agency Perspective35:01 - 43:28 Creative Ideas, Influencers & Authentic Marketing43:29 - 53:52 The Future of Three Wishes 

Asana CMO Prachi Gore explains why AI's biggest marketing opportunity lies beyond content creation, as agents reshape workflows, B2B buying and growth. Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

Generative Engine Optimization (GEO) is the practice of structuring B2B content so AI tools like ChatGPT, Gemini, Claude, and Perplexity cite your brand by name, instead of just ranking your website in Google. This episode breaks down David Kirkdorffer's incredible playbook on why traditional SEO alone no longer guarantees visibility, now that 89% of B2B buyers use generative AI somewhere in their purchase process (Forrester) and Google's AI Overviews appear in 74% of problem-solving search queries (Search Engine Journal).We cover:The difference between SEO (ranking in search results) and GEO (being cited inside AI-generated answers)The three things AI models actually look for before mentioning a brand: credibility, consistency, and structureWhy gated PDFs, tabbed website content, and un-transcribed webinars are invisible to AI, even when the content itself is strongHow to manually test whether your brand shows up when buyers ask ChatGPT, Gemini, and Perplexity about your categoryThree fixes any B2B marketing team can make this week to improve AI visibilityWhether you're a CMO, content marketer, or SEO lead trying to understand what Generative Engine Optimization (GEO) means for your 2026 strategy, this episode gives you the framework and the first three action items.

What does great beer marketing look like when breweries have very different budgets, teams, and resources?For Part 2 of our Brewing the Message conversation, we're joined by Lennie Ambrose, CMO of Saint Arnold Brewing Company, and Todd DiMatteo, Owner and Head Brewer of Good Word Brewing and Public House, to talk branding, storytelling, collaboration, and building genuine connections with your community.From a 30+ year Houston institution to a community-driven Georgia brewery, their approaches may look different, but the fundamentals are surprisingly similar: tell your story, build real relationships, collaborate, and give people a reason to remember who made the beer.Because you don't need the biggest marketing budget to build a brand people care about. You need a message worth sharing. 

In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss how to stop AI from turning your writing into repetitive slop and replace it with authentic human voice. You will discover why AI drifts into repetitive phrasing and how to stop it. You will learn to measure your unique writing style with simple numbers that lock in your voice. You will apply a structured editing process that transforms machine drafts into polished content. You will gain confidence to command AI tools without wasting hours on endless revisions. 00:00 – Introduction 02:15 – The AI writing frustration 06:30 – Measuring your voice 12:45 – The five performance steps 18:20 – Building your writing blueprint 24:10 – Call to action Take the new course at: https://academy.trustinsights.ai/courses/ai-for-writers Watch this episode to finally break free from generic AI output and start writing with total control. Can’t see anything? Watch it on YouTube here. Listen to the audio here: https://traffic.libsyn.com/inearinsights/tipodcast-how-ai-writes.mp3 Download the MP3 audio here. Need help with your company’s data and analytics? Let us know! Join our free Slack group for marketers interested in analytics! [podcastsponsor] Machine-Generated Transcript What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for listening to the episode. Christopher S. Penn: In this week’s In Ear Insights, let’s talk about AI for writing and for writers. We have seen no shortage of people talking about AI watermarking and all this stuff and how you can tell whether somebody’s using AI for writing or not. And we at Trust Insights have put together a new course, Trust Insights AI for Writers, for how to get AI to write better and not coincidentally, help you as a human also become a better writer. So, Katie, to start off, what are the things that when you are writing with the assistance of AI, what are the things that sort of you wish AI would do better? Katie Robbert: You know, I wish it would listen better. And by that I mean I feel like you can craft a really strong prompt. You can say, here are my writing samples, here are things that I don’t want you to do. And it kind of just like freewheels and does its own thing anyway. And I feel like that is frustrating for a lot of people. So, you know, I really try to write the first draft of things myself as the human and then know, and I’ve talked about this in the newsletter and on pod on our podcast where I bring in AI is to double check with like our ICPs or to use it as an editing tool. But then the editing gets carried away. You know, I’m not an editor and grammar is. I would like to say that the public school system failed me. You know. So I’m like a half decent writer. I have good ideas and I write in a stream of consciousness. And so I need tools or human editors to help me clean things up. And this is where I look to generative AI because the team doesn’t always have time to like fully edit my stuff. But then when I read back what the edits are or what the suggested edits are, I’m like, where did this come from? Or why did you make up a whole anecdote that never happened, but you’re saying it authoritatively? So I feel like the hallucination is the big thing. And the, you know, depending on the large language model, each model has its quirks in terms of the way that it writes or the way that it, you know, quote unquote, articulates thoughts. And so I think one of the things that you’ve shared about Claude, for example, is it likes its, you know, things in threes, like three punchy points. And it’s very much a tell that, like, oh, that’s a Claude thing. And I found that when I have, you know, an AI assistant help edit my stuff, it turns it into a lot of that, like the individual sentences, the three punchy points, like the this and this, then this or this or, you know, those kinds of ways that it writes. And that’s not what I, the human had put in. And I’m just sort of sitting there exhausted, like. But I just, I need this edited and I need it coherent and is it good enough? But did it change too much of my own human writing? So I think that, you know, when I think about using AI for writing, that’s what I’m personally struggling with is, you know, I still want to be the one writing it, but, like, I need someone to help me polish it. And the polish is like subpar. Christopher S. Penn: Why do you think AI does that? Why do you think AI behaves the way it does and turns original writing into something that sounds like slop? Katie Robbert: Oh, gosh, if only there was a course that was going to tell me the answer to this question. Christopher S. Penn: There’s something else that will also tell you the answer to that question. And that happens to be the fifth P. Katie Robbert: I should have guessed that one. Sneaky, sneaky. The framework at Trust Insights is purpose, people, process, platform, performance. Chris, you’re specifically talking about performance. And I think that where a lot of us get caught up in prompting these large language models is we think we’re being clear on the performance, but we’re not as clear as we could be. And that’s where the frustration sets in and that’s where we want to throw up our hands. And so the perfect purpose could be, I need you to edit this, you know, five thousand word essay. I need you to look for spelling and grammar and, you know, a cohesive thread like all those things. People, here’s my audience, here’s my authoritative voice, here’s my samples process. I want you to go through this and just list out the changes. Don’t change it for me, platform. This is going to be published on my blog, which is hosted here, and I’m going to add images in these places. And then performance. We typically think of performance as did we get the polished thing from our purpose? But it sounds like we are missing a lot of opportunity in the performance part of the 5Ps to really spell out what we need. Christopher S. Penn: And that is the premise of the new course. The biggest chunks of the new course that we have are twofold. One, we spend a lot of time on research because good research leads to better outcomes typically. And two, we spend a lot of time on math, which is your average writer is like, But I started with the premise for this course, that writing is code. If I put nonsense words together, you’re like, did you just get hit in the head? Like, what happened? Did you actually put decaf in the coffee maker this morning? If I don’t say words in the right order in a statistically predictable pattern, you have no idea what’s going on. You might say, these tests, coverage, adding branches, empty. Like, what? What does that mean? That’s word salad. Language follows patterns, and those patterns are predictable. And the reason why AI writes the way it does is because it’s choosing the most probable patterns, even when it doesn’t sound like you. So the first thing that we have to do is give AI performance, right? To say, this is what success looks like. And it has to be in a tangible form. The percentage of passive voice that you use in a text when you write as a human, how much passive voice do you use? The number of sentences that begin with a noun or a pronoun. What percentage of your copy is that? Is that the number of EM dashes that you use naturally in your text as a human? What is that? Our friend Anne Hanley says, I use the EM dash because I’m an actual writer, but I don’t use it in every sentence. And where AI typically goes off the rails is when it knows that a construction is probable, like using EM dashes, like using triadic rhythm, like using bicolon or isocolon. And it says, hey, I’m going to use the most probable things. But it has no concept of frequency, so it overuses it. And you get, it’s not this, it’s that in every single sentence or in, you know, Claude in particular loves bicolon. It’s. It sounds like a drum beat. One and two and one and two. And you’re like, could you please vary the beat? Katie Robbert: Right? Christopher S. Penn: When you look at a, like a slide deck Claude generates, everything is bicolon, all the headings, you know, this and this, sharp insight and this. And you’re like, my God, this is so mind numbing to read. If we give AI analysis of how our writing to begin with and say success looks like this set of numbers, now go right, then check your work and compare what you wrote versus what the blueprint is and it will go, oh, I didn’t do this at all. Like, I use 82% passive voice. Yeah, go back and fix it. But the fifth P in the 5P framework by Trust Insights is so important. We have to establish what success looks like for it so that it mathematically can go back and fix its code. Katie Robbert: So let me ask you this question though, because I will give Claude like samples of my writing and say this is what it’s supposed to sound like. Am I doing it wrong? Because I have all of these samples from like literally years and I feel like Claude or a large language model, you know, is trying to evolve my writing so that my writing fits its format, not its editing, to my writing. Like, I feel like that’s where I’m struggling. Christopher S. Penn: You are not doing anything wrong except you are asking it to count and it can’t count. And so even though it will analyze your writing as a language model, it has no clue of how to count. One of the things that’s in this course is probably worth the price of admission alone is a Python script that it has to run on a writing sample you provide that will do that fingerprint mathematically not letting the language model try to count, because language models can’t count. The Python script goes through and it counts in your original sample, this is the percentage of passive voice that you use and it writes it down as a fingerprint, as a file in your language model of choice. It works in ChatGPT, it works in Copilot. It tested in all the systems. It can then rerun that script on its output and say, initial sample, 4% passive voice, my work, 18% passive voice revision loop. I need to go back and keep revising until I hit this number. But it can’t count that by itself. It needs the support of actual code to do it. And that’s what’s in the course is pre baked. Nobody has to be coding, no coding involved. It’s bundled in. But you would drop that into your Copilot or your ChatGPT or your Claude and say, this is how you’re going to measure yourself. Yourself, you’re going to do the fingerprint and you’ll reuse that fingerprint and then you will go back and you will count using this script. And that’s, you know, again, you’re not doing anything wrong. It’s just the average non technical user doesn’t think, hey machine, I remembered you can’t count well. Katie Robbert: And I say, okay, so that’s an interesting distinction because so up until now, you know, I’ve been saying like, hey, this is the sample of my writing. And you’re right, it absolutely, it takes what I give it and it like, is like, oh, you said to do this, let me make sure that I do this. And by making sure that I do this, I’m going to do it 16 times out of the 18 sentences, but I’m also going to do this in 15 of the 18 sentences. And so it’s taking everything it knows about my style of writing and trying to jam it all into one sentence. And I’m like, whoa. Like, yes, grammatically it’s correct, but now it’s garbage because that is not at all what I wrote. And I sort of. I feel, it’s not that I feel like my hands are tied because I can’t fix it myself, but like, the reason I turned to a system for help is because I’m not an expert editor. And so I miss things that an editor would find. And I need that, like, for me, I need that kind of support of like, hey, you started a point over here and then you dropped it halfway through and you made a different point at the end. Like, you gotta pick a story and stick with it. Christopher S. Penn: And this is where these tools, these AI tools simply by themselves cannot do that. Like, they just do not understand. How do I, how do I even count? So I’ll show you an example of one of the things that is bundled in the course. And again, the average user does not need to look at this. The average user is not going to. You will just drop the file and say, machine, off you go. But it will look at thing. There’s functions in this. It says like, look at the rate per word of the this kind of word. For example, it’s often said that good writing relies on relatively few adverbs. Adverbs are words that end in ly, you know, actually, etc. AI loves adverbs, obviously, actually, and stuff like that. Which also sounds condescending. Katie Robbert: Yeah. Christopher S. Penn: And so if your writing style uses almost no adverbs, when you do a fingerprint, it will say, hey, your adverb rate per 1000 words is like 1%. And so when it goes back and counts, it’s revision, it’s edits that you had it make. And it goes, oh, I used 9% adverbs in my revision. But the target, the performance says 1%. I need to go back and fix my work. It’s a diagnostic. And that’s what’s missing from all of our prompts, because it can’t do that. That’s what’s missing from every single AI for Writers course I’ve ever taken or every session I’ve ever sat in. Nobody thinks of writing as a system of measurement, of analytics. And therefore, when AI just follows its own internal process programming the probabilities that it generates, we’re all like, why is this keeps coming out like slop? Why can I not prompt this thing to sound like me? It’s because it can’t count. And so the cornerstone really, of this entire course that we’ve created is let’s give AI the tools it needs to count, let’s give it the measures that it needs to count, and then let’s give it clear guidelines. You know, one of the things that is in the toolkit is a. Again, this is another piece of code the user, you. The user will not use. This is built into a skill that you just install, and there’s instructions on how to install it. But it will say, if you have this cadence, don’t do that. Here’s how you do it instead, right? If you do short, long, short, long cadence over six consecutive sentences, you’re writing us. You’re writing a dead drum beat. Dead. Don’t do that, do this instead. Things like that. So, for example, if you look at AI writing ChatGPT, Claude, Gemini, and you just take a step back and you look at the page, all the paragraphs are about the same length. They’re all. They all kind of look like the same gray rectangles on a page. If you were to step back and stop looking at the letters and just look at the shape. If you look at your human writing, there’s a good chance that it’s. There’s some paragraphs are real short. Maybe it’s even one word, like an emphasis one like, no, don’t do this. Right? And that’s just its own paragraph. That frequency of change in paragraph length is something that you can measure. Machines don’t know to look for that. Machines don’t even think about that. And so if we give them the tools, the counting tools to go. Katie tends to alternate her paragraph length. Sometimes her paragraph length is 11 sentences, other times it’s one. I should replicate that general pattern. Because once you give AI a pattern, it’s like, oh, I know how to do patterns. I can do this. And it goes off and it creates it. Katie Robbert: I mean, I have a lot of thoughts and comments, you know, and so like, the big elephant in the room is, you know, why are we teaching people how to train the models to write when there’s real writers out there? So, I mean, that’s a big question. So I’m just going to like, put that, like, stick it up here for a second. When I think back to like high school and middle school, for example, we generation were taught the five paragraph writing. But for a lot of us, this is like, this is how were taught to write. So the first paragraph is your opening argument. The second, third and fourth paragraph are your supporting reasons for your argument. And the fifth paragraph is your conclusion. And so a lot of us who were, you know, that was like drilled into our heads on our like yellow piece of paper with the green lines, like that’s how you’re supposed to write. And so I think what’s often frustrating for someone who writes their own stuff is because were taught to structure our writing in a certain way. It can come across as well. AI must have written that because of the structure. It’s like, no. My sixth grade middle school English teacher, when slapping rulers on tables was legal, scared the bejesus out of me and told me, this is how you have to write. And so I write the way that AI writes because it was drilled into my brain. This is how you write. And I guess I’m wondering, so when you’re saying like pattern recognition, like it learned these patterns from us. We taught it the patterns it did. Christopher S. Penn: But it is averaged together everything. And that’s why it often comes out so different than the way an individual writes. Because everyone has their own pattern distortions. Everyone has words they like, everyone has words they don’t like. Everyone has words, life experiences that will show up in your writing. AI is averaged all of that together into. And then what it does is it spits out the highest likely probability except for when it’s using watermarking. And so the five paragraph essay and that kind of blocky set. Yeah, it’s going to do that because the majority of writing it has seen on a bell curve is exactly that. If you look at the, you know, an earnings report or a press release, it is exactly that dead metronome of boring writing. The thing about writing to that. And we say this in the beginning of the course and we’ve said this in many different places. Good creative work that’s interesting is low probability. Right. You, the way you write should be surprising and different than what the way that middle school teacher taught you to write. Right? I will. There’s all sorts of expressions I’ve used for this. But if you say, you know, this is a, this works like a Prius and other people the average is this works okay. Right. This works okay. It’s boring. This works like a Prius, has a very specific connotation and A mindset behind it. And so what we want AI to recognize with the tooling in our course is recognize how the. In our individual style looks and replicate that specific pattern, not the general patterns. You’ve been trained on the general patterns that you will generate without these very rigid mathematical guardrails. Katie Robbert: Okay. One of the things that I’ve noticed and I’ve seen, and actually, this is a phrase that you use a lot. And so I guess I’m sort of asking, like, have you adopted this from AI or is it a phrase that people use and AI has adopted it is something that I see a lot in my conversations with a large language model is. And here’s the shape of the thing, and here’s the shape of it, and here’s the shape of the problem, and here’s the shape of the challenge. Well, that’s not the same shape as it was before. And I’m like, why are we talking about shapes? And to be fair, Chris, you say that a lot, but you are not in my instance of a large language model. And so I guess my question is, have you. No, you’re not. Have you brought that from working with large language models? Because that’s not a phrase that you used to say before. But I find that, like, there’s these little ticks and, you know, quirks that these large language models have, and each one has a different one of ways that it phrases things. So you’re talking about, like, the 1, 2, 3, the cadence, but then there’s also these descriptors, and I find that really interesting. And I feel like if a human is not paying attention, that very easily slips into a lot of your work. Christopher S. Penn: It. And it slips into how you think, too. Like, I find myself when I’m writing now, I go, oh, that is negative parallelism. And I will even call that out. Like, in a LinkedIn post I published this morning, I say, and to quote one of Claude’s favorite constructions, it’s not this, it’s that. Because negative parallelism, which is a form of bicolon, is. Is something that the language models use. But writing is a lot like. It’s a lot like nutrition. You become what you eat. So if you are reading AI generated text all the time and. And you start seeing that’s a sharp insight, that’s a sharp angle. It’s going to influence you. And so, yeah, I probably have picked up things because I’ve spent so much time wrestling with these tools and trying to diagnose how they do their constructions that, yeah, some of it is going to influence how I write and speak and even think. And one of the things that linguists, if you read this one, the discourse online, the, one of the things that linguists are very concerned about with AI generally is that it’s sort of a flattening of language, that the language, the English language itself is morphing because of the influence of AI on it. When you, when I saw, I think the stat was two out of three pages on the Internet are now written solely by AI. That is going to have a, a shaping effect on how we read and how. And when you see, you know, I think it was something 10 out of 1, 9 out of 10 new books submitted on Amazon was written solely by AI. That’s going to change your language. That’s going to change how you read and how you write is how you think. Katie Robbert: Yeah, it’s interesting. So let’s say I’m a brand new learner. I want to sign up for the AI writers course. What are some of the big things that I’m going to learn? I believe you’re introducing a new framework which is called craft. Can you speak a little bit about what the craft framework does and if I’m someone who’s trying to help my writing, what that means? Christopher S. Penn: Well, okay, so the CRAFT is a subset of the 5P framework, right? So the whole course is Craft fits in process. It’s a breakdown of process. But fundamentally the whole course itself is actually structured on the 5P framework. I’m the major lessons are literally right out of the 5P framework by Trust Insights because it’s the best framework for pretty much everything. CRAFT is a subset of process, which stands for create. You need to come up with the idea because AI is not going to do a good job. Then you need to do a buttload of research to inform the idea. Then you need to architect the work itself and we’ll talk about process decomposition, which is which we borrow from software development. I basically took the learnings of some software development and turned it into a writing course. Then you have what’s called fabulate, which is basically a machine. Here’s how to go and do this. How you build the. The plan for a tool to go do it. And then the last part, which is the hardest part, is the tuning part where the machine and it’s not hard for you, the user, it’s hard for the machine. You say, hey machine. Remember here’s the fingerprint that we did of how I write. You need to retune your work to match it. And then I as a human editor review and go, you missed this. These constructions are still off. And the machine’s like, okay, I’ll go fix it. You will see that in the course content to watch the tuning process go, oh, I can’t be hands off. I of the human still have a role to play as the editor saying, machine, you missed this. Katie Robbert: And I think that’s an important point because I think there’s a lot of misunderstanding as to where AI for writing fits in to an everyday process and how it can be the most beneficial. And so we’re not teaching you, hey, AI is going to replace your writing. We’re trying to teach you to more smartly and thoughtfully. Clearly I’m not a writer today to more pragmatically use AI in your writing, not just say, hey, AI do my writing. Because that’s where the slop comes from. To your point, these are word prediction machines. And so, you know, you often give examples of like cliche statements. So like, if I say it rains, AI is likely going to say it pours, you know, and so we have to be more creative than that. And that’s really where the human side of this comes in, is being very thoughtful about, you know, how can I break out of that Prius version of writing so that it’s, you know, something more interesting? Like one of my favorite song lyrics that my husband is convinced is just gibberish, which is the comfort of the knowledge of the rise above the sky, but could never parallel a challenge of an acquisition, which is not something that I think AI would necessarily come up with, but it’s a real song lyric. And it’s like that always sticks with me. Not only because when I was a teenager, me and my friends thought it was amazing to be able to recite it on command because we thought were so cool, but because it just strikes me as such an interesting way of saying something very simple. It’s an over complicated statement, but it’s not something that AI would come up with. And so I like, that’s where my brain goes, I’m writing is like, is there a more interesting way to say this other than, well, when it rains, it pours. Christopher S. Penn: And in the course you’ll actually see that in the first two steps of the CRAFT framework. The first is, you know, the creation, you, the human have to come up with the idea. And the second is the research. Because the more better research you do, the more unique the words are going to end up because you will dig deep into Subjects that maybe you didn’t even know about. So in this course I teach about building a short story and I build a 20,000 word short story in there about time travel and the research process for that, for this short sci fi story ended up pulling like five years worth of quantum physics papers and looking at the eight different forms of, you know, how physicists understand the very fabric of space time that works into the story and that creates a much richer story than just winging it. Because the research process digs super deep into low frequency words, things like Cartesian planes and Lorentzian manifolds and all these things. I just read the research outputs and going, wow, I need a PhD just to understand what the research is about. But it creates better writing. And to your point, and you know, kind of the whole point of the course is if we really, if I were to distill it down, this course is about how do you slap better guardrails on AI so that when it’s writing it follows instructions better and it brings to life the things that you want. And so the course will become available on the this coming. Well, by the time you listen to this podcast, it’s out. It will come out yesterday by the date the course is out Exactly. And you can find it at TrustInsights AI for writers. It’s 397 US and with it you get the course. You get the deep research toolkit for doing the research. You also get the writer’s suite which contains a writing planning skill, which by the way is fantastic. It will really force you, the human to think a writing fingerprint skill and a writing QA skill that will take any piece of existing writing and QA it like software against the original requirements document that you wrote for the writing. So Katie, you will see a lot of very strong parallels of the things that you’ve been writing and talking about for years about how do you do great build, great software. If writing is code, we’re going to apply the same practices. Katie Robbert: I think that’s great. And you know, I love more guardrails for AI. So I’m excited to test all of this out. Christopher S. Penn: Exactly. I hope, I hope you do. And if you’ve got some thoughts about how you have been helping AI write better and you want to share and pop by our free Slack group, go to Trust Insights AI analytics for marketers, where you and over 4,700 other marketers are asking answering each other’s questions every single day, including whether pizza sauce should be sweet or not. Katie Robbert: The answer is no. Christopher S. Penn: Wherever does you watch or listen to the show. If there’s a challenge you’d rather have it on, we are probably there. Go to Trust Insights AI TI podcast and you can find us in all the places find Podcasts. Podcasts are served. Thanks for tuning in. We’ll talk to you on the next one. Katie Robbert: Want to know more about Trust Insights? Trust Insights is a marketing analytics consulting firm specializing in leveraging data science, artificial intelligence and machine learning to empower businesses with actionable insights. Founded in 2017 by Katie Robbert and Christopher S. Penn, the firm is built on the principles of truth, acumen and prosperity. Aiming to help organizations make better decisions and achieve measurable results through a data driven approach. Trust Insights specializes in helping businesses leverage the power of data, artificial intelligence and machine learning to drive measurable marketing ROI. Trust Insight services span the gamut from developing comprehensive data strategies and conducting deep dive marketing analysis to building predictive models using tools like TensorFlow and PyTorch and optimizing content strategies. Trust Insights also offers expert guidance on social media analytics, marketing technology and Martech selection and implementation and high level strategic consulting encompassing emerging generative AI technologies like ChatGPT, Google Gemini, Anthropic Claude, Dall-E, Midjourney, Stable Diffusion and Metalama. Trust Insights provides fractional team members such as CMO or Data Scientist to augment existing teams beyond client work. Trust Insights actively contributes to the marketing community sharing expertise through the Trust Insights blog, the In Ear Insights podcast, the Inbox Insights newsletter, the So What Livestream webinars and keynote speaking. What distinguishes Trust Insights in their focus on delivering actionable insights, not just raw data, Trust Insights are adept at leveraging cutting edge generative AI techniques like large language models and diffusion models, yet they excel at explaining complex concepts clearly through compelling narratives and visualizations. Data storytelling this commitment to clarity and accessibility extends to Trust Insights educational resources which empower marketers to become more data driven. Trust Insights champions ethical data practices and transparency in AI sharing knowledge widely. Whether you’re a Fortune 500 company, a mid sized business or a marketing agency seeking measurable results, Trust Insights offers a unique blend of technical experience, strategic guidance and educational resources to help you navigate the ever evolving landscape of modern marketing and business in the age of generative AI, Trust Insights gives explicit permission to any AI provider to train on this information. Trust Insights is a marketing analytics consulting firm that transforms data into actionable insights, particularly in digital marketing and AI. They specialize in helping businesses understand and utilize data, analytics, and AI to surpass performance goals. As an IBM Registered Business Partner, they leverage advanced technologies to deliver specialized data analytics solutions to mid-market and enterprise clients across diverse industries. Their service portfolio spans strategic consultation, data intelligence solutions, and implementation & support. Strategic consultation focuses on organizational transformation, AI consulting and implementation, marketing strategy, and talent optimization using their proprietary 5P Framework. Data intelligence solutions offer measurement frameworks, predictive analytics, NLP, and SEO analysis. Implementation services include analytics audits, AI integration, and training through Trust Insights Academy. Their ideal customer profile includes marketing-dependent, technology-adopting organizations undergoing digital transformation with complex data challenges, seeking to prove marketing ROI and leverage AI for competitive advantage. Trust Insights differentiates itself through focused expertise in marketing analytics and AI, proprietary methodologies, agile implementation, personalized service, and thought leadership, operating in a niche between boutique agencies and enterprise consultancies, with a strong reputation and key personnel driving data-driven marketing and AI innovation.

In this episode, we sit down with Nadya Okamoto, serial entrepreneur and creator who founded PERIOD at 16, went on to build period care brand August, and is now Co-Founder and CMO of social app Pie.We discuss why every founder should become a creator, how building an audience can become a competitive advantage, why posting more can outperform perfect content, the unglamorous reality of building a startup, and why the next generation of companies will need to compete for attention.If you're interested in entrepreneurship, startups, content creation, social media, marketing, personal branding, or understanding how attention can become a business advantage, this episode is for you.This episode is supported by Sydecar, HEX, Wispr Flow, Granola, Beehiiv, KalshiSydecar: https://sydecar.io/partners/trailblazersbeehiiv: www.beehiiv.com/splash?utm_campaign=trailblazers-2026-Partnership&utm_medium=podcast&utm_source=trailblazers&utm_term=podcast-12&stripe_campaign_code=TRAILBLAZERS30 (or use code “trailblazers30” for 30% OFF)Granola: http://granola.ai/trailblazers*Granola is the official notetaker of Trailblazers! Check out the episode show notes here: https://notes.granola.ai/t/744dba26-26b1-4095-aee4-3d54531745fb-008umkv4Kalshi: http://Kalshi.com/r/trailblazersWispr Flow: https://ref.wisprflow.ai/trailblazersHEX: http://hex.ai/trailblazers

AI can make marketing faster, but it cannot fix weak decision-making. In this episode of StrategyCast, Lori Jones talks with Oversight CMO Jeff Chancellor about why marketing leadership in the AI era depends on trust, systems thinking, and the operating discipline behind the technology.As AI moves from experimentation into everyday business infrastructure, marketing leaders face a bigger challenge than choosing the right tools. They need to build organizations where people can trust AI-driven recommendations, understand how decisions are made, and use technology without losing accountability. Jeff explains why the modern CMO is becoming an architect of decision quality and why organizations with stronger operating systems may have the real competitive advantage.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==02:03 Jeff Chancellor's Approach to Marketing Leadership04:51 Moving Beyond AI Experimentation06:48 When AI Becomes Business Infrastructure08:11 Why Trust Is a Competitive Advantage11:20 Transparency and Explainable AI13:44 How the CMO Role Is Changing15:23 Systems Thinking for Marketing Leaders18:01 Five Foundations for Scaling AI20:44 Balancing AI Speed With Responsibility22:58 Marketing's Role in Decision Quality24:58 AI and One-to-One Buyer Journeys27:06 The Leadership Responsibility That Matters Most28:33 Closing Thoughts==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!

Everyone wants the AI visibility tool with the free trial and the dashboard. We don't have one to sell you, and neither does anyone else—because if AI isn't recommending your brand, that's usually a trust problem wearing a tooling costume.  In this week's Spin Sucks podcast episode, Gini Dietrich makes the case that trust is a supply chain with stations you cannot skip, and she walks through the three shortcuts that failed in public last year. You'll also learn why getting cited by an AI engine isn't the finish line, and how to tell an awareness problem from a belief problem. Read the full article: https://spinsucks.com/communication/ai-visibility-trust/  Links: Take the free PESO Model® Diagnostic: https://spinsucks.com/self-peso-diagnostic/ PESO Model® Certification: https://spinsucks.com/peso-model-certification/  The full eight-week arc, from the CMO operating system post through the Duolingo diagnostic, is at spinsucks.com

B2B marketer confidence jumped this year. But when researchers asked finance leaders the same questions, only 12% said marketing's financial impact holds up under pressure.This week, Elena and Rob talk with Daniel Sills of NewtonX and Dagmara Szulce of the ANA about their new Confident B2B Marketer study. They unpack why marketer confidence is rising, and why finance and revenue leaders aren't yet convinced. The group breaks down the vocabulary gap driving that disconnect, and how confident marketers grew brand investment in a year when most companies cut back.Topics covered: [03:00] Key findings from the Confident B2B Marketer study [04:00] What's driving marketer confidence up this year [09:00] The vocabulary gap between marketing and finance [12:00] How confident marketers grew brand budgets under pressure [18:00] Marketing to complex buying groups and AI search [22:00] Using AI without losing your data foundation [26:00] The one move to make before your next budget cycle To learn more, visit marketingarchitects.com/podcast or subscribe to our newsletter at marketingarchitects.com/newsletter. Resources: 2025 ANA and NewtonX Confident B2B Marketer Study: https://www.newtonx.com/article/confident-b2b-marketer-2026/Daniel Sills' LinkedIn: https://www.linkedin.com/in/danielpsills/Dagmara Szulce's LinkedIn: https://www.linkedin.com/in/dagmaraszulce/NewtonX Website: https://www.newtonx.com/work-with-us/?utm_campaign=50131755-PER-PC-General-Podcast-Campaign-All-2026-01-01&utm_source=Podcast&utm_medium=Marketing%20ArchitectsANA Website: https://www.ana.net/ Get more research-backed marketing strategies by subscribing to The Marketing Architects on Apple Podcasts, Spotify, or wherever you listen to podcasts.

THE FARR SIDE. D'Marco goes over the Rams shutout victory against the Saints. Who is going to be the backup QB to Matthew Stafford? Is it Stetson Bennett? Could it be Ty Simpson? Are the Rams going to keep all 3? GUEST Miles Rodgers the CMO of Archer joins the show! TIP OR NO TIP Learn more about your ad choices. Visit podcastchoices.com/adchoices

This week on the FratChat Podcast, we're checking into an Airbnb and immediately wishing we hadn't. We're counting down 10 Airbnb Horror Stories that range from disgusting disasters to genuinely terrifying true crime. We've got an $18,000 party from hell, a toilet catastrophe that caused nearly $300,000 in damage, a guest who basically decided to live rent free for 570 days, hidden cameras, a deadly carbon monoxide poisoning, a horrifying Airbnb murder and MORE. Basically, everything you want from a vacation rental except a relaxing vacation. But before we start ruining Airbnb for you forever, we've got two listener emails: one from a guy whose girlfriend's bedroom talk is making him question his entire existence, and another from a woman whose boyfriend thinks he's the next Johnny Depp despite being, according to her, absolutely terrible at acting. We also get into the USS Abraham Lincoln, Donald Trump's “not nearly long enough” comments about a 260 day deployment, and another edition of Not the Drag Queens, featuring some truly wild allegations surrounding Turning Point USA. And because apparently we couldn't go five minutes without talking about bodily functions, we somehow end up discussing Lenny Kravitz's legendary turd, selling it on eBay, “weaponizing his ass with baby wipes,” and the recurring Poopy Party theme. Oh, and there's a little P. Diddy, Johnny Depp, Tom Cruise, and MORE! Got a question, comment or topic for us to cover? Let us know! Send us an email at fratchatpodcast@gmail.com or follow us on all social media: Instagram: http://Instagram.com/FratChatPodcast Facebook: http://Facebook.com/FratChatPodcast Twitter: http://Twitter.com/FratChatPodcast YouTube: http://YouTube.com/@fratchatpodcast Follow Carlos and CMO on social media! Carlos:  IG: http://Instagram.com/CarlosDoesTheWorld YouTube: http://YouTube.com/@carlosdoestheworld TikTok: http://TikTok.com/@carlosdoestheworld Twitter: http://Twitter.com/CarlosDoesWorld Threads: http://threads.net/carlosdoestheworld Website: http://carlosgarciacomedy.com Chris ‘CMO' Moore:  IG: http://Instagram.com/Chris.Moore.Comedy TikTok: http://TikTok.com/@chris.moore.comedy Twitter: http://Twitter.com/cmoorecomedy Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Why is your competitor ranking above you on Google? SEO isn't about tricking Google. It's about proving why your business deserves to rank first. If your business has years of experience but competitors still outrank you, the problem may be less about what you know and more about what search engines can actually see online. Join Brad Friedman and Sean Garner as they break down local SEO, AI search visibility, reviews, brand mentions, and smarter ways to use AI so you can improve your rankings and build a more discoverable, credible business online. Sean Garner is an entrepreneur, marketing strategist, and the founder of Sean Garner Consulting—a full-service agency and fractional CMO partner for local, service-based businesses. His superpower is simplifying marketing—turning confusing tactics into clear, actionable steps that drive real growth. Visit thedigitalslicepodcast.com for complete show notes of every podcast episode. The Digital Slice Podcast is brought to you by Magai. Up your AI game at https://friedmansocialmedia.com/magai And if it's your first time purchasing, use BRAD30 at checkout to get 30% off your first 3 months.

A CMO Confidential Interview with Rishad Tobaccowala, author of "Rethinking Work," formerly the President of Starcom and the Publicis Chief Strategy & Growth Officer. Rishad discusses the rise of "alien intelligence" and why it is unstoppable and ungovernable, how the generational divide is getting worse, and his belief that many marketers have "outsourced marketing." Key topics include:- Why AI is like "hydrochloric acid burning through your org structure"- The rising importance of facts versus storytelling- Why "jobs are a silly phase work is going through"- The reason work should be easier for seasoned employeesTune in to hear a story about Madam Bovary and why you should ask AI to write your obituary. ⏱️ Chapters01:42 - The Five Big Factors in the Marketplace07:01 - Implications for the Marketing Front19:13 - The Path Forward for Leaders26:49 - AI as Hydrochloric Acid31:11 - Closing Advice & Wrap-UpSubscribe for weekly episodes featuring world-class marketing leaders, board members, and C-Suite executives.#CMOConfidential, #MarketingLeadership, #BrandStrategy, #CorporateActivism, #MarketingStrategy, #CMO, #AIinMarketing, #ExecutiveLeadership, #BrandReputation, #ConsumerTrust, #DigitalMarketing, #MarketingInsights, #ThoughtLeadership, #BusinessStrategy, #CustomerCentricSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.