{"id":16932,"date":"2026-05-06T11:48:29","date_gmt":"2026-05-06T09:48:29","guid":{"rendered":"https:\/\/incubeta.com\/?post_type=video-library&p=16932"},"modified":"2026-05-06T11:48:33","modified_gmt":"2026-05-06T09:48:33","slug":"the-digital-edge-s2-ep-7-how-to-move-from-ai-efficiency-to-strategic-growth-with-marketing-over-coffees-christopher-penn","status":"publish","type":"video-library","link":"https:\/\/incubeta.com\/ch\/video-library\/the-digital-edge-s2-ep-7-how-to-move-from-ai-efficiency-to-strategic-growth-with-marketing-over-coffees-christopher-penn\/","title":{"rendered":"The Digital Edge S2 Ep.7 | \u00a0How to Move from AI Efficiency to Strategic Growth with Marketing Over Coffee’s Christopher Penn"},"content":{"rendered":"\n

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In this episode of The Digital Edge, host Mark Reed-Edwards sits down with Christopher Penn, the Co-Host of the Marketing Over Coffee podcast, and the Co-founder and Chief Data Scientist at TrustInsights, to explore the seismic shifts happening in the AI and marketing landscapes. As organizations transition from the excitement of generative AI to the practical complexities of agentic workflows, Chris breaks down the evolution of the technology that impacts all marketers today. The conversation touches on one of the core ideas in Incubeta’s new research whitepaper «The Marketer’s Confidence Paradox.» Listen to their conversation, and download The Marketer’s Confidence for more insights into Research Insights into the Gap Between Marketing Performance and Real Growth with practical steps to bridge it.
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Read the Full Transcript Here<\/strong><\/h2>\n\n\n\n

Mark Reed-Edwards:<\/strong> This is The Digital Edge from Incubeta. I’m Mark Reed-Edwards. This podcast is about how you can balance technology and humanity. <\/sup><\/sup><\/sup><\/sup>How, as AI eats the world, you can integrate efficiency with empathy. <\/sup>We’ll talk with leaders from Incubeta and across the industry as we traverse the digital edge into tomorrow’s world. <\/sup><\/p>\n\n\n\n

On today’s episode, we’re joined by Christopher Penn, co-host of the Marketing Over Coffee Podcast, and the co-founder and chief data scientist at TrustInsights. <\/sup><\/sup><\/sup><\/sup>With the launch of Incubeta’s new white paper, titled «The Marketer’s Confidence Paradox,» Chris and I discuss the evolution of AI from longstanding techniques to generative AI. <\/sup><\/p>\n\n\n\n

If you’re a marketing leader or you’re interested in the seismic shifts we’re seeing, this is a must-listen. <\/sup><\/p>\n\n\n\n

Chris, welcome.<\/p>\n\n\n\n

Christopher Penn:<\/strong> Thank you for having me.<\/p>\n\n\n\n

Mark Reed-Edwards:<\/strong> It’s great having you here. Can you tell me a bit about your career path and your role at TrustInsights? <\/sup><\/p>\n\n\n\n

Christopher Penn:<\/strong> Sure. My career path vaguely resembles like a bad Dungeons Dragons quest. I’m doing stuff that I never set out to do. <\/sup> My undergraduate degree is in political science. My master’s degree is in Information Systems Management. And I don’t use either degree. <\/sup> I started in financial services early in my career. I started as an IT guy and spent about a decade doing that. <\/sup> IT became marketing technology, then moved full-time into marketing. And then marketing technology became machine learning, which became AI, which became generative AI. And here we are today. <\/sup><\/p>\n\n\n\n

So a very long and convoluted path. Today at TrustInsights. I’m a co-founder along with my CEO Katie Robert. We started the company in late 2017. <\/sup> So we’ve been at this, next year it’ll be a decade, which is pretty shocking. And we initially started out focusing on analytics and data science, and then as the technology moved, so did we. <\/sup><\/p>\n\n\n\n

Today, we spend our time and our days helping companies use artificial intelligence intelligently and get the most out of it. And it’s almost a profession unto itself keeping up with everything that’s happening in the AI space too. <\/sup><\/p>\n\n\n\n

Mark Reed-Edwards:<\/strong> So as someone deep into AI, what do you think of its impact on marketing? <\/sup><\/p>\n\n\n\n

Christopher Penn:<\/strong> Here’s the challenge with AI. AI is a broad umbrella term for a bunch of different fields that are overlapping. Things like regression analysis and classical regression techniques. Given a piece of data or given an outcome, can we predict more of the outcome or can we explain the outcome? <\/sup><\/sup><\/p>\n\n\n\n

And there’s classification: given a bunch of mixed up data, can we organize it? These two branches of AI have been around since the Eisenhower administration in the 1950s. So there’s what they call AI Summer and AI Winter — when it becomes trendy and not trendy. <\/sup><\/sup><\/p>\n\n\n\n

And then in 2017, Google DeepMind created a novel way for machines to do prediction that could take into account things that have happened in its data past that it was given called the Transformers Model. <\/sup>Eventually, five years later, OpenAI took it and ran with it and released in November ’22 ChatGPT, and the rest is history. <\/sup><\/p>\n\n\n\n

But it’s interesting seeing how people keep rediscovering the older branches in the same way that people keep rediscovering what’s called symbolic AI. There’s two competing philosophies in the AI field. There is neural networks, which is, «Hey, given enough data, we can teach a machine anything.» <\/sup><\/sup><\/sup><\/p>\n\n\n\n

And then there’s symbolic AI, which is, «Given enough rules we can construct rules that make machines be effective.» <\/sup><\/p>\n\n\n\n

Neither approach by itself is perfect. But there has been a sort of ongoing debate for 30 years now about how do we get to neuro symbolic in AI. We’re starting to actually see that now. <\/sup><\/p>\n\n\n\n

Mark Reed-Edwards:<\/strong> What do you think of its impact on marketing? How has it changed what people in marketing do every day? <\/sup><\/p>\n\n\n\n

Christopher Penn:<\/strong> Yeah, it is interesting. AI has uniformly been a thorn in marketer’s side for the last 20 years. And here’s what I mean. AI is an intermediary and marketers have been dealing with this really since the early 2000s. <\/sup><\/sup> Once companies like Google started adapting classical AI techniques to things like retrieve and rank. Like, «How do we decide what results to show somebody in the search engine result?» <\/sup><\/p>\n\n\n\n

Or how do you decide what’s gonna show up on your Facebook feed or your LinkedIn feed, or things like that. But AI has been the intermediary that marketers have been struggling against for quite some time. <\/sup>And we marketers will joke about things like: the algorithm, the LinkedIn algorithm, not realizing that actually is like 14 different interconnected systems going on behind the scenes. <\/sup><\/p>\n\n\n\n

But marketers have generally been in opposition to AI as an adversary because marketers want to get to the most people possible and have this perspective, which comes from classical marketing, of «How can I just talk to more people about my thing in the hopes that someone will buy something from me at some point?» <\/sup>And a lot of the machine learning algorithms have traditionally been, «How can we filter out the noise to give people exactly what they want?» <\/sup> And almost nobody wants marketing. And so these two forces oppose each other. <\/sup>With the additional conflict of interest, now, for a lot of the big technology companies to say, «You know what, marketers, we specifically do not want you talking to our people unless you pay us to let you talk to our people.» <\/sup><\/p>\n\n\n\n

So it’s this ongoing battle between marketers and machines. <\/sup><\/p>\n\n\n\n

Mark Reed-Edwards:<\/strong> Yeah, it changes things, doesn’t it? So you speak to a lot of marketing leaders yourself as part of your Marketing Over Coffee podcast. What do you hear from them about the state of marketing in the AI era? <\/sup><\/p>\n\n\n\n

Christopher Penn:<\/strong> Bewilderment, despair. <\/sup><\/p>\n\n\n\n

Mark Reed-Edwards:<\/strong> Of course. Yeah.<\/p>\n\n\n\n

Christopher Penn:<\/strong> A lot of folks, marketing leaders in particular, people whose hair color is the same as mine, are in a place where they don’t even understand the technologies and what’s going on. <\/sup>And you have this shattering of public spaces. <\/sup><\/p>\n\n\n\n

There was a period of time in digital marketing from about 2005 to 2015, which was the golden age of the digital marketer, when you actually had usable data, when you could see what people were doing, when you could understand your customer pretty well. <\/sup>And then, thanks to irresponsible use of data from companies like Facebook with the Cambridge Analytica scandal, thanks to marketing technology really becoming a sales vehicle for technology companies, marketers have seen the amount of data they have available to them retreating year after year to the point now where senior marketers are like, «We’re losing all of our traffic because no one’s clicking on anything.» <\/sup><\/p>\n\n\n\n

People are using AI overviews in Google search and getting the answers without ever having to leave Google. <\/sup><\/sup><\/sup><\/sup> So that’s a bust. Social networks have essentially banished unpaid marketing content to the far reaches of oblivion on most social networks. <\/sup> So that’s unavailable.<\/p>\n\n\n\n

Really, the only channels that digital marketers have that are reliable are things like email and texting and stuff like that. <\/sup> But consumer behavior itself has changed so radically. You have so many places now. You have Slack and Discord and Telegram and Signal and Mattermost. <\/sup>And it doesn’t help that, around the world — this is not just particular to one country — but around the world, authoritarian governments and points of view have been on the rise to the point where people don’t feel safe in public spaces. <\/sup> So they frequent them less and they spend more time in private spaces. Again, Discord and Telegram and Slack and group texts and things. <\/sup><\/p>\n\n\n\n

All of which are invisible to marketers, all of which are spaces marketers are explicitly not invited to be a part of. <\/sup> And so marketing leaders are like, «We don’t have any idea what our customers are up to.» And they’re also heavily pressured by stakeholders more and more to — it’s the perennial cliche — do more with less. <\/sup><\/p>\n\n\n\n

As the quip goes, «there’s a difference between lean and mean and skinny and pissed.» And that’s where marketing is now. So you have marketing managers and company leaders trying to ditch as much headcount as they possibly can in favor of machines. <\/sup><\/p>\n\n\n\n

And the results are not great, right? I think we can generally agree, particularly in digital spaces like social networks, the amount of pure AI slop that is invading every space is driving more people away from them. <\/sup><\/p>\n\n\n\n

Mark Reed-Edwards:<\/strong> You mentioned a couple of vehicles, email and text, which are based on a database that you build up over time. But the way you build that up traditionally has been through placing ads and adding people that come to your website or into your app. So as a result of that, how in this day and age can you build that list if you want to have a one-on-one relationship with your prospects and customers? <\/sup><\/p>\n\n\n\n

Christopher Penn:<\/strong> Ads still work as long as you have enough budget to reach people. The challenge as with everything in the hyperinflationary environment that we operate in globally right now is you need a lot of budget. <\/sup> Particularly for startups, there’s a very real cold start problem of how do you get your company off the ground? Because, a startup doesn’t have a hundred grand to drop on an ad campaign, particularly when you look at things like META’S ads or Google’s Performance Max ads, where you need a sizable budget and time to let the AI controlling the ad systems calibrate on your audience and figure out who’s going to respond to right? <\/sup><\/p>\n\n\n\n

Because they are supervised learning systems, effectively. <\/sup>If you don’t have that budget, if you’re like, I got 10 bucks a day those systems will never properly calibrate. <\/sup> And so you run into some really difficult challenges. The way around that, to the extent that there is one, you have to replace budget with a lot of legwork — looking at more niche places online, places like Product Hunt certain Subreddits, certain Discord servers, and try as best as you can to interact with people and see where there’s opportunities for you to start building that critical mass. <\/sup><\/sup><\/sup><\/sup><\/p>\n\n\n\n

But that cold start problem is very real. <\/sup><\/p>\n\n\n\n

And even for established brands, a lot of ways, marketing is like where it was in the 1980s, where you didn’t have search, where you didn’t have social networks, where you didn’t have these vehicles and only the richest folks could afford to place, a primetime television ad. <\/sup><\/p>\n\n\n\n

Everybody else is relegated to: «We gotta find little audiences where we can and try to market to them.» <\/sup><\/p>\n\n\n\n

Mark Reed-Edwards:<\/strong> Yeah. And that leads me to my next question. You know, there’s a lot of economic pressure surrounding the rise of AI. So when you think about that and the tendency to lean on AI for efficiency, where does that leave marketing? Will it make us or break us? <\/sup><\/sup><\/p>\n\n\n\n

Christopher Penn:<\/strong> How do I put this? In the short term, you will see substantial productivity gains and efficiency, but there’s two ways to use AI broadly, right? There’s optimization, which is bigger, better, faster, cheaper. <\/sup><\/sup> How do we do more with less? How do we do the same thing we’ve always done, but do it with less budget and less head count. <\/sup><\/p>\n\n\n\n

Ask any business coach: «you cannot cut your way to growth» is the axiom. <\/sup> So that’s an internal pressure that marketing is going to be facing. There’s a much bigger problem, and the much bigger problem is that when you use AI for efficiency, yes, you recoup all the wages that you’re paying to people that you have then laid off. <\/sup><\/p>\n\n\n\n

The downside is when that happens at scale, the number of people who can buy things goes down because they’re unemployed. <\/sup> And we are seeing this happening across many different knowledge workshops. I was talking to somebody not too long ago who works in the temporary staffing space, working with office temps and stuff like that.<\/p>\n\n\n\n

They have seen demand fall off a cliff. At one client they used to reliably place, 80 temps and they’re down to 15. <\/sup> So we’re talking massive reductions. If you think about it, an office temp is basically a human version of AI, right? <\/sup><\/p>\n\n\n\n

Because they have no institutional knowledge. Day to day, a different person may be sitting in that seat. It’s trivial now for a lot of those tasks that temp used to do, to just hand it off to a tool like Claude Cowork for 200 bucks a month instead of 200 bucks for the day and get better quality output, persistent memory if you use it right. <\/sup><\/p>\n\n\n\n

And so this creates massive economic pressures on the population at large. <\/sup> And the way this plays out is not going to be good. If you look back historically once you have structural employment jump like five or 10% in absolute numbers within a 10 year period, that’s when you get a lot of unrest, right? <\/sup><\/p>\n\n\n\n

So if you look at things like the 1930s, you look at a lot of periods of time when you have big jumps in structural unemployment, going back to the 1790s, when that happens, the pitchforks and torches come out. <\/sup> AI in the knowledge workspace, especially law, finance, etc., you could be talking 25 to 50% structural unemployment in half a decade. When that happens, because again, everyone’s chasing profitability, that’s when the pitchforks, torches and guillotines come out. <\/sup> So marketing will be facing those pressures. But marketing as a subset of society as a whole, has a lot of challenges ahead that the short term sort of profit chasing perspective that business has today and what people like to call late stage capitalism is very real and extremely dangerous, and no one in power, who has the ability to make economic policy stick is talking about how this is going to play out. <\/sup>They’re just burying their heads in the sand hoping that they can cash out before it all comes crashing down. <\/sup><\/sup><\/p>\n\n\n\n

Mark Reed-Edwards:<\/strong> So, thinking about marketers, our friends throughout the business, what do you think they get right and wrong about AI? <\/sup><\/p>\n\n\n\n

Christopher Penn:<\/strong> Here’s the thing about the way marketing is using AI. Marketing is using AI like taking a Harrier attack jet to the grocery store. Yes, you can do that. And it will do that, but that is dramatically underusing its power. <\/sup><\/sup><\/sup>And there’s a variety of reasons for that to maximize the capabilities of what you do with AI does require a lot of things like having good data, like having good governance, like having the ability to think differently, like being able to delegate well. <\/sup><\/sup><\/sup><\/sup>And a lot of people, myself included, are not always necessarily good at all of those things. <\/sup><\/sup><\/sup><\/sup>And so our limits as human beings are what constraints our ability to get the most out of marketing. <\/sup>If you look at where agentic AI is today, with tools like Claude Cowork, for example, my CEO Katie has, with a tool like Claude Cowork, which is a relatively non-technical tool, has literally 100 Xed the amount of stuff that she gets done on a week to week basis. <\/sup><\/sup><\/sup><\/sup> When you look at her progress log of the stuff that she’s been working on as a non coder, in marketing, website, revamps, content revamps, overall business strategy, it is mind bending just how productive she is to the point where, we are a four person company. And, we’re doing pretty decently in terms of revenue. <\/sup>We might not ever have an employee number five. <\/sup><\/p>\n\n\n\n

Because we’re able to do so much and get so much done. <\/sup>And again, when you look at the way marketers are using it, if you were still just chatting with ChatGPT to write blog posts, you are taking a rocket ship to the grocery store and there’s so much more you could be doing. <\/sup>In terms of what people get wrong, the number one thing is thinking that the machines can completely replace a human. <\/sup><\/sup><\/sup><\/p>\n\n\n\n

Unless you are so under utilizing your humans that a machine swap-in is easy. <\/sup> So the way that we see this play out a lot is. At a larger company, you have a hundred person content team. Today, you could take your top 10%, 10 of those people with AI and be as productive or more productive than the a hundred people total. <\/sup><\/sup><\/sup><\/sup><\/p>\n\n\n\n

So it’s not the job went away, it’s that the number of people you needed to do the job has dramatically decreased. <\/sup> Where marketers are running into trouble is they are doing what they’ve always done. «Let’s make more blog posts,» right? <\/sup> Supply is unconstrained now. A content marketer can create a million pieces of content a month now. <\/sup><\/sup><\/sup><\/sup> What’s gone in the other direction is demand is more constrained than ever, and I’m sure you see this. There are plenty of people who have AI summaries of everything. <\/sup> So I’m summarizing this, I’m summarizing that. I’ve got AI overviews. I don’t have to read anything. <\/sup><\/sup><\/sup><\/sup>I’ve got notebook LM making me podcasts and complex papers and books. <\/sup><\/sup>And so marketers are creating more content for a smaller and smaller audience. <\/sup> And they’re creating content that is easily summarized. They’re creating content that doesn’t really add a ton of value, and as a result, their metrics of success are getting worse. <\/sup><\/sup><\/sup><\/sup><\/p>\n\n\n\n

Mark Reed-Edwards:<\/strong> It’s a lot of busy work in some ways. <\/sup><\/p>\n\n\n\n

Christopher Penn:<\/strong> And this is something that is a real time of reckoning for knowledge work business. I used to work at AT&T when I was a very young man. AT&T had something like 16 levels of management — from the intern all the way through: it was four As, B, C, D, E, supervising manager, district manager and this is ridiculous. <\/sup><\/p>\n\n\n\n

Those 16 levels, probably 10 of them were completely unnecessary in terms of what that person’s output did that advanced the company forward. <\/sup>And when you look at what AI is capable of today, a lot of busy work happens inside companies that is not directly connected to usable outcomes. <\/sup><\/p>\n\n\n\n

And, we all know, we have all worked with that person whose sole remit seems to be to call meetings at a company, right? <\/sup> And you remember the management cartoons of years past, the boss saying we need to have a pre-meeting, meeting before the meeting. AI makes all that unnecessary. <\/sup><\/p>\n\n\n\n

I saw a great quote the other day. It was related to software development, that said that generative AI makes it cheaper to implement the feature than to have a meeting about implementing the feature. <\/sup><\/p>\n\n\n\n

In the five years preceeding generative AI, I had created something like around 20 pieces of internal software that we used, in analytics and data science and stuff like that, that were in production use. <\/sup> In just the last year, when I really started digging into Claude Code in particular. I’ve created over 200, right? <\/sup><\/p>\n\n\n\n

So I call it the «distance to done.» The distance to done gets shorter and shorter as AI gets more capable. <\/sup>Today we are at things with Open Claw, for example, or Claude Managed Agents or Open Code or Open work, Co work, etc., the distance to done is so short that if you have an idea, you can have it done before you have a meeting about it and do that proof of concept very quickly. <\/sup><\/sup><\/sup><\/sup><\/p>\n\n\n\n

And that is something that. Marketing leaders are not accustomed to. <\/sup>Software development has pivoted a little faster in terms of people recognizing what AI tools are capable of. <\/sup>Marketing leaders and business leaders and strategy leaders really haven’t gotten there yet. <\/sup><\/sup><\/sup><\/sup><\/p>\n\n\n\n

When you sit down with set of character cards from your ideal customer profiles and you have a virtual focus group where AI is running the entire focus group: the moderator, the participants, and stuff like that, and you just get the results of it, in 20 minutes, what would’ve taken two months to convene otherwise and the accuracy is still around 90% of what the humans would’ve done, the fact that you can prototype, put it before a synthetic focus group, get feedback, refine, and then deploy all within an afternoon for a small piece of software is absolutely mind blowing. <\/sup><\/sup><\/sup><\/sup>That’s a six month project, that becomes a six hour project. <\/sup><\/sup><\/p>\n\n\n\n

So a real simple example: in part of my stack, I have Google’s Notebook LM. <\/sup><\/sup> Notebook LM has a command line utility. There’s things like APIs for services like Reddit and your social media monitoring systems. <\/sup><\/sup><\/sup><\/sup><\/p>\n\n\n\n

An AI agent, I just did this the other day and in fact in another window, I have this running right now for an event I’m doing this week. <\/sup>The AI agent has gone out, used the Reddit developer’s API, so that we’re doing it ethically, to grab conversations that are relevant about this particular client, putting it into a notebook by itself, asking the notebook questions from what real people are saying to build the character cards, to run the focus group, to also build and deploy the software. <\/sup><\/sup><\/sup><\/sup><\/p>\n\n\n\n

And then I just show up at the end to look at it and go, «Okay, did you follow these steps? Let’s spot check the data.» <\/sup>But in general it just all happens by itself. <\/sup>Again, this is something that marketing leaders, and this is true of marketers in general, people’s brains are stuck in 2023. <\/sup><\/sup><\/sup><\/sup><\/p>\n\n\n\n

They’re stuck in, «I have to talk to ChatGPT about everything.» <\/sup>Instead of realizing that today you hand off a project plan to an agent team and you come back later and it’s done. <\/sup><\/sup><\/sup><\/sup><\/p>\n\n\n\n

Mark Reed-Edwards:<\/strong> Yeah, Notebook LM is fascinating. I’ve played with it a bit and it’s kind of scary capable. It can do so many things for you. <\/sup><\/sup><\/sup><\/sup><\/p>\n\n\n\n

Christopher Penn:<\/strong> It can, and what’s unique about it is you can ask it questions and if you did not provide the data, it will say, «I can’t answer that because you didn’t give me the data.» <\/sup>Which, if you’re dealing with sensitive information, if you’re dealing with stuff where you have to be factually correct, is incredibly valuable. <\/sup><\/sup><\/sup><\/sup><\/p>\n\n\n\n

It is one of the top tools I recommend that people learn how to use. <\/sup> And in particular in fields like finance or law or health, it is invaluable. I use it a ton in stuff that like health. I will go and find the peer reviewed papers that I care about on a topic, and I will load 60 or 70 of them into Notebook LM and then ask questions of those papers, specifically knowing that it’s not gonna be hallucinating random stuff that I didn’t include. <\/sup><\/sup><\/sup><\/sup><\/p>\n\n\n\n

Mark Reed-Edwards:<\/strong> So Chris, to close out our discussion, I want to expand on what we were just talking about. Give me some personal insights into the way you use AI, where you think it can really excel and what you love about it, and maybe some of the tools you use. <\/sup><\/sup><\/sup><\/sup><\/p>\n\n\n\n

Christopher Penn:<\/strong> So the tools that I use: Open Code and Claude Code. I practically live in Claude Code. At this point it’s almost a room in my house, I’m in it so often. <\/sup> And I use it for a ton of non-coding things. The name scares people off and so does using a terminal. <\/sup><\/p>\n\n\n\n

However, as a very simple example, I’m getting ready to deliver a workshop to a company this week. <\/sup>I took that company’s data that they gave me, I fed it through Claude Code, through a series of recipes that I’ve built with some skills and plugins that I built, that digest the data and says, «These are the things that this customer cares the most about,» and then helps me build the synthetic sample data so that we can work with it in the workshop without anyone worrying about dealing with confidential information. <\/sup><\/sup><\/sup><\/sup>And then I’ve used that to build the rest of the workshop. <\/sup> I have a startup routine every day. In Claude Code called My Daily Briefing, and it goes to Jira and Asana and Slack and my inbox, and my calendar, and pulls from all those different data sources to assemble a daily briefing saying, «Hey Chris, here’s what you’ve got going on today. Here’s what your next three days look like and here’s what you need to get done, prioritized.» <\/sup><\/p>\n\n\n\n

My tech stack is very heavy on the data side. What data do I have access to? What tools can I build to get me more high quality data? <\/sup><\/sup><\/sup><\/sup>The AI is almost secondary to retrieving and cleaning and preparing the data for use with AI. <\/sup><\/sup><\/sup><\/sup><\/p>\n\n\n\n

Mark Reed-Edwards:<\/strong> Chris, this was really a fascinating discussion. You shared so many great ideas for our audience. I really appreciate you joining me here on The Digital Edge. <\/sup><\/sup><\/sup><\/sup><\/p>\n\n\n\n

Christopher Penn:<\/strong> Well, thank you for having me. <\/sup><\/sup><\/sup><\/sup><\/sup><\/sup><\/sup><\/sup><\/sup><\/p>\n\n\n\n

Mark Reed-Edwards:<\/strong> So will you be trying the tools Chris mentioned? You’d be wise to. And, as AI continues to shape the world of the marketer, you can get an up close look from Incubeta’s new white paper, «The Marketer’s Confidence Paradox.» In it, Incubeta’s market research gives insights into the gap between marketing performance and real growth, touching on measurement, AI, reporting, and much more. <\/sup> Download the white paper linked in the description.<\/p>\n\n\n\n

Thanks for being here today. I’m Mark Reed-Edwards. Join me on The Digital Edge next time. <\/sup><\/p>\n\n\n\n

Speakers:<\/strong>\u00a0Host: Mark Reed-Edwards; Guest: Christopher Penn<\/p>\n\n\n\n

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