Your Digital Marketing Coach with Neal Schaffer

Marketing Artificial Intelligence: AI, Marketing and the Future of Business [Paul Roetzer Interview]

• Neal Schaffer • Episode 271

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Artificial intelligence is forecasted to have trillions of dollars of impact on businesses and the economy.

Yet many marketers struggle to understand what it is and how to apply it in their marketing efforts.

The truth is,  AI possesses the power to change everything.

If you're in marketing, you need to invest in better understanding AI. Begin with this interview with Paul Roetzer, author of Marketing Artificial Intelligence: AI, Marketing, and the Future of Business.

Key Highlights

[02:17] Introduction of Podcast Guest, Paul Roetzer

[03:50] How Paul Start Getting Interested in AI and Marketing

[06:10] What is Quantum Computing

[08:05] Individual Use Case for AI

[11:53] What You Can Do to Leverage AI

[14:02] AI Tools in Marketing, Sales, and Influencer Marketing

[16:57] Leveraging Anonymous Data Across Clients

[19:57] 3 Areas That You Should Start Focusing

[23:47] The Pitfalls of Marketers With AI Technology

[28:36] Final Advice

[29:40] Connect with Paul

Notable Quotes

  • I mean, yeah, AI is language. It is vision technology, like dolly to was a big thing in April open release dolly to which could generate images, it's deepfake videos, it's like all these things you hear about. But at its core, machine learning is the primary subset of AI. And what machine learning does is it takes data in inputs, and it makes predictions generates outputs.
  • Everything we do is trying to predict behavior outcomes, and then you actually start to realize all the potential that AI has to transform what we do every day.
  • Data is an essential element of making AI work for you as a marketer. But it is not necessarily an obstacle.
  • You don't need AI, you need smarter tech that saves you time and money and makes you better at your job. It just so happens AI is what makes that possible.
  • We always says all AI is not created equal, just because you look at three platforms that do content intelligence, which is basically helping you figure out the right by using AI tools. They're not all created equal. And you're gonna have to be able to drill in and ask some different questions.
  • And I think if you go into AI thinking about it that way, that is an assistant, it is there to help you and recommend things to you and, and develop drafts of social shares and ads and copy like not write the thing for you, then you can have an amazing experience with AI.
  • You just gotta be curious, like, find the thread within AI that is interesting to you. 

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Neal Schaffer:

Artificial Intelligence, we know that AI is going to impact a lot of industries and the way we work. Do you know how it is already? And will in the future impact us marketers, entrepreneurs and business owners? If not, you really need to listen in to this next episode of The your digital marketing coach, podcast. Digital social media content influencer marketing, blogging, podcasting, blogging, tick talking LinkedIn, Twitter, Facebook, Instagram, YouTube, SEO, SEM, PPC, email marketing. Who knows, there's a lot to cover, whether you're a marketing professional entrepreneur, or business owner, you need someone you can rely on for expert advice. Good thing you've got, Neil, on your side, because Neal Schaffer is your digital digital marketing marketing coach, helping you grow your business with digital first marketing one episode at a time. This is your digital marketing coach. And this is Neal Schaffer. Hey, everybody, this is your digital marketing coach Neal Schaffer, welcome to my podcast. I know a lot of you are longtime subscribers. But if you are new or ever only listened to a few episodes, my mission is really to help educate and empower your digital content influencers, social media marketing, there is not one specific niche that I cover, because all of these are important pieces to the puzzle in leveraging digital and social media marketing as a strategic engine for growth. With that in mind, today, we're going to talk about artificial intelligence in a very broad way. But we're also going to get into the specifics of how it can impact your marketing. I think of AI as one of these emerging technologies similar to web three, that will impact the way we work the way we do business, obviously, the way we market in the future. But there are things that we should be doing now. And in fact, until today's interview with this special guest, I didn't realize how quickly this technology was evolving to the point where we can be using it in our everyday life as a marketer or marketing or business. So today's guest is Paul racer, he wrote the brand new book marketing, artificial intelligence, AI, marketing and the future of business. This book is literally coming out the week where this podcast has been published. So I was very fortunate to have an early copy of it, I highly recommend it. And I think after listening to this interview, you will want to go out and buy it as well. So today, it's less about specific, actionable and tactical advice. It's more about taking a step back looking at the bigger picture, and then figuring out how to best make use of this technology in our business. So without further ado, here's my interview with Paul rates or you're listening to your digital marketing coach, this is Neal Schaffer. Paul rates are welcome to the ER digital marketing coach podcast.

Paul Roetzer:

It's great to be with you. I appreciate you reaching out and having me on.

Neal Schaffer:

No can't wait to talk about something that's I have been involved with, although on a smaller scale. Those of you that read the the age of influence my own book, the final chapter was on how AI is going to impact influencer marketing. I wrote this back in 2020. So I've always had a personal interest. And I know behind the scenes, machine learning AI, whether we know it or not, is being utilized by more marketers and businesses. So let's take a step back. We're gonna talk all about that in a bit. But I guess I'm not gonna ask you where it all started, Paul, but how did you start getting involved? You've written a few books before, how did you start getting interested in this concept of AI and marketing?

Paul Roetzer:

Yeah, it actually did start right after the first book. So the marketing agency blueprint which I wrote in 2011, that was the your IBM Watson one on Jeopardy. And it actually started for me as a curiosity of what is that technology? And could it ever be applied to what I was working on in marketing, and specifically, at the time, I was trying to solve marketing strategy. And so I was when I came out of college in 2000, there was like five ways to spend your marketing dollars, there was advertising, trade shows, you know, print ads, direct mail, whatever, by 2011, there was like 5000 ways to spend your marketing dollars. And so I had become convinced that the human mind was incapable of optimal strategies and budget allocation. And so I actually just started with that hypothesis like, well, what if you could use whatever this Watson technology is, I did not understand it at the time. But if you could use it to do marketing strategy and budget allocation, and I then read a book called automate this by Christopher Steiner in fall of 2012. And he told the story of intelligent algorithms being used in Wall Street and logistics and transportation, and I was like, wow, like Wall Street in particular. 60% of all trades will be made by machines and no human interaction. I thought, well If there's way more variables in making a trade than there isn't, you know, spending $10,000 on ads, like that's a way more complex industry, maybe you could use it. And that just then started my multi year journey to understand what exactly was it? Could it be applied I wrote about in 2014. And my second book kind of like you like theorizing what happens when AI gets applied. But it wasn't until years later that we actually started really being able to explain it started the marketing AI Institute to share what we were learning and see if other people were as curious as we were.

Neal Schaffer:

That's very cool. And while you were very, very early on, I think even Christopher Penn wrote a book about AI and marketing. But even that was back in like, 2020 or 2019. Right? Yeah. So yeah, you were you were talking about this while we were in our virtual diapers. And it's very interesting, this is going to be a little bit different. But one of the clients I work with as a fractional CMO is in quantum computing. Every those industries that you talked about, there's almost this parallel I see with the industries that are using quantum computing. I know I'm probably jumping ahead a little bit. But do you see that impacting AI and marketing? Or is that still way in the future?

Paul Roetzer:

Way in the future is understatement? Yeah, I mean, so a quantum computing for people who don't know what that is, like basic premises, all computing is like zeros and ones it is or it is not, in quantum computing, the theory theory, in practice, I guess now is they're able to build these things as you can exist both as both a zero and a one. And so computationally, you can, in theory, do massive compute power, that could be used for everything from breaking encryptions to figure out marketing budgets, but it's still a very early development thing. And AI plays a role enabling, you know, quantum computing. But yeah, I follow that industry with a level of curiosity, not quite on par with AI. And there is a race. I mean, there are people I mean, Google, IBM, Honeywell, believe it or not, is actually one of the leaders in that space. But yeah, I don't I don't think marketers need to like really be building a quantum computing strategy.

Neal Schaffer:

Anytime. All right, yeah. Sorry. Sorry, for geeking out. No, I talked about this all day if you want it. So let's, let's take a step back yet. And this company is actually working on clinic computing in the cloud. So it's a really, really cool area of potential. Yeah, but let's take a step back. So Watson, and when I wrote this chapter on AI influence Mario Watson, correct me if I'm wrong is more about like, like, the language of natural language processing, and, and even like Jeopardy, like, you know, sounding like a human correct. So to me, I immediately think of marketing of AI generated content, which we're starting to see a heck of a lot of these days. On the other hand, we have the treating algorithms and then just figuring out well, I have $1,000 a budget, what keywords what's what, you know, strategy per keyword very applicable there? Were you like drawn to both worlds are or immediately you first saw it with budget optimization has been the first use case scenario?

Paul Roetzer:

Yeah, I was definitely very focused on an individual use case, which in this case, was, I want to get 500 leads next quarter for this client? How do I do it? And rather than me, the human thinking about the things I knew in my limited capacity and knowledge and education? So what if I had the world of data in front of me and knew what had worked for 1000s of other companies? What if I was HubSpot, and I had 50,000 customers at that time, and I could anonymize all their data. And I knew behaviors, could I predict what I should do to drive leads? At the end of the day? I mean, yeah, AI is language, you know, GPT, three people hear a lot about that. It is vision technology, like dolly to was a big thing in April open release dolly to which could generate images, it's deepfake videos, it's like all these things you hear about. But at its core, machine learning is the primary subset of AI. And what machine learning does is it takes data in inputs, and it makes predictions generates outputs. And those can be Netflix like recommending a show, it's predicting what show you want to watch based on behavior. Could be Google Maps, recommending or predicting what route to take. It could be Siri, or Alexa, actually using natural language understanding to ask what your what you understand what you're asking. But then its response is a prediction. It's predicting that this is what you wanted to know. And so when you think about prediction, it has 1000s of use cases across marketing and sales and service. It's literally what we what we do as marketers, when you step back and think about it is we make micro predictions all day long. What's gonna get them to open the email, what's gonna get them to click, what copy should I use to drive conversion, like, everything we do is trying to predict behavior outcomes, and then you actually start to realize all the potential that AI has to transform what we do every day.

Neal Schaffer:

So it sounds like just taking a step back and trying to not not do Comment down. But look at the practical application for listeners, it all begins with having a dataset is that correct assumption? So if you don't have a data set, you almost need to create a data set.

Paul Roetzer:

Yeah, potentially I, I try and teach you like, I wouldn't think of data. Data is an essential element of making AI work for you as a marketer. But it is not necessarily an obstacle. And what I mean by that is many of the solutions you would buy. So let's say, you go by an email subject, line writing tool, like let's say you're in a company that says 100,000 emails a month, and you're trying to write the most optimal subject lines to generate opens, you don't need 200,000 of your own emails as data necessarily, if you're a small business, you wouldn't need to have sent those 100,000 200,000. The company that has built the solution can learn from the millions of emails, its customers have sent and anonymize that data. So if you're MailChimp, for example, and you want to offer email subject line writing as a feature within your platform, you can learn from all of your customers data and look at open rates. And you can say, okay, should when I'm offering a promotion, should it be $1 offer or percentage off? Like that's, they have the data to answer that question, they can recommend that to you. So depending on the use case, you may not need your own data, you might just need to work with a vendor that has built software on anonymized data from enough people.

Neal Schaffer:

So just a lot of the advice on leveraging AI then come down to the tools that you use and seeing how that data can be added to that tool for you to use, or are we at the stage now where companies large enterprises, obviously like the IBM they have the resources to do it. But is there any way that that companies might be DIY in their efforts? Or is it always going to be with already established tools that are leveraging AI?

Paul Roetzer:

Yes, the way I teach people to get started and again, listen to this right now you can get started 20 minutes from now, like you do not need to be a machine learning engineer data scientist to do this stuff. The fastest way to do it is take out a spreadsheet on Google Sheets, whatever Excel, and make a list and column they have all the technical things you do in a day, a week or a month. So it could be writing email subject lines, figuring out what blog post titles to write, writing blog posts, sending emails, whatever it is, then have a column says how many hours a month you spend doing that, then a column on what tech you're using to do it, then a column on how much that tech costs, then a simple rating scale of one to five five is this would transform my life if AI could do this thing for me or help me with it. One is in wouldn't be a huge thing is only an hour a month, take all the things you would give a five and then go to Google and say AI for subject line writing API for blog post titles, go find someone who has built a tool to do that thing. The other thing you can do is to your point, you go to HubSpot, go to Oracle go to sales or whatever platform you're using, and say what what features do you have they're using that are smarter than the features I'm using now, that can save me time and money. Again, you don't need AI, you need smarter tech that saves you time and money and makes you better at your job. It just so happens AI is what makes that possible. So like but you may have features within your existing platform you're already paying for that you're not even using like lead scoring is a great example. And you may have lead scoring technology uses machine learning baked into your CRM and you might not even know it.

Neal Schaffer:

Yeah, you know, you bring up a topic that I'm really passionate about. Because I've been involved in marketing technology, I used to run a show called the social tool Summit, and talk a lot of technology vendors. And it's like you have the data, you can tell me, when are the most effective times to post on what day of the week based on all of your Why don't you make my life as a marketer easier by exposing that data? So I guess what you're seeing is more and more companies are starting to do that. And are we at the stage where it's like AI for influencer marketing AI for whatever marketing channel? Or are we at the stage now where no matter what marketing related keyword I put in? Is there a tool out there? Or is it still developing as we speak?

Paul Roetzer:

It's still very early. So the there are we track about 2000 Venture funded companies that are building AI tools in marketing and sales, about about eight to 900 of them have more than 50,000 funding. So it's a venture funding, it's probably more than that, just under 1000. But more more than 2000 that have funding of some degree. And they're building tools because to build AI, you build it to a very specific thing. You don't build AI that does all the things marketers do all email functions. So you may find a solution now influencer it's gonna be pretty limited. I know some interesting tools in that space. But like PR and communications, it's just tends to be a little behind. But if you're looking in the big players like advertising, ecommerce personalization, like if you're playing in the realm analytics, where it's a little more advanced, maybe more dollars tend to go into those areas of marketing than Absolutely there's going to be a collection of tools, then what you need to do is be able to figure out, we always says all AI is not created equal, just because you look at three platforms that do content intelligence, which is basically helping you figure out the right by using AI tools. They're not all created equal. And you're gonna have to be able to drill in and ask some different questions. But again, the way I tell people, it's just smarter tech. So if you don't understand any of this stuff, you can get ahead by just saying, I do this 12 hours a month, right? Now, here's the seven steps I take to do it. If I buy your software for $100, a month that you claim is using machine learning and natural language processing. What will my monthly task list look like? Is that 12 hours now? One hour? Is it six hours like? And is it better than what I was creating? Like? What does it look like when I use this? That's what you really need to answer for yourself.

Neal Schaffer:

So I guess, one, you know, and it's funny because not every technology vendor necessarily promoted as being this automated machine learning AI. Obviously, kind of example that I found that about recently, a tool called sell zone salesman comes from sem rush, which is a big seo software tool, sell zone is for Amazon, marketing, but they have an Amazon ad tool, where instead of you having to manually every day, looking at the Rec, it'll automatically set it for you. It's a set and forget, it's a perfect example. Because anyone that uses the Amazon app platform, probably every day or every week, whatever it is, they are going in there and adjusting those ads that you know, the budget and the bids, and this does it. So I guess that would be one example that you would recommend. I'm wondering, you know, in the ad world, I see a lot of these, you know, like Facebook ad automated tools. And it's more like if this, then it's not leveraging all the anonymous data, it's only specific to well, if you get five likes on this post will boost it or you know what I mean? So I'm wondering how far in terms of leveraging anonymous data across clients how far are they had these tools gone? Are we still at that sort of If This Then automation of your own data?

Paul Roetzer:

It definitely depends on the vendors, like, I mean, Facebook's algorithms don't exist without AI, like they can't. I mean, there's rules in there that it's not like it's all AI. But they can change weights and stuff. But generally speaking, like see that, that's the thing is like marketers, if you use Google, if you rely on Google in any way, you're using AI, like that platform doesn't exist without it either. So the big players, what they're doing isn't possible without it. Amazon's another example. So it's so infused into what they do into their culture. I actually the first chapter of our book that's coming out, it's dedicated to Microsoft, Google and Amazon and their two decade long adventure into AI like, this is not new. They've been working on it. The what's new is the leaps forward that were made starting in 2012, when deep learning really came onto the scene. And what that is, is there was for years, going back to the 1950s. Basically, there was this theory that we could teach machines to think like the human brain, you know, here's like neural networks, as you'll hear this called. And so in 2011 2012, this guy Geoff Hinton wins at this computer recognition, competition ImageNet, using deep learning, and coined it to be called deep learning. And that's when all the big players realize like, oh, my gosh, well, we've been talking about and academics for five decades might actually be real. We can commercialize this. And there was this massive land grab for AI talent, Yan Laocoon, goes and builds Facebook's AI research lab, Microsoft builds a research lab, Google goes and buys DeepMind, like just massive, hundreds of billions of dollars getting thrown around. That's when the race really started. So 2013 1314 When I was just starting to write about it. All of a sudden language AI started getting better virtual assistants started getting better. Google Search started getting more predictive language generation and understand all these things really happened last year. So to answer your question, a long form, the reason that most of these texts are still relatively new, and it is not seamlessly infused into everything that US marketers do, is because the current generation of AI and what it's capable of doing is generally about three to five years old. And so most of the best stuff lives in the big platform companies. And it's now being diffused down to these VC funded companies, because people are leaving the big platforms, and building specific solutions like a language generation tool.

Neal Schaffer:

That makes a lot of sense. I want to shift a little bit to your book marketing, artificial intelligence, AI marketing, and the future of business. So what is the official release date of your book? June 28. Okay, so I got an early copy that thank you very much. And I just want to just looking at the table of contents, for those that don't have the ability to to but well, you can buy it preorder you should that you talk about all these different areas and AI advertising analytics, AI and SEO and AI Social Media Marketing and AI. I guess from the you know, the small medium sized business owner or marketer that's listening to this podcast. Where are the three areas so that they should start focusing on saying, hey, now is the time for AI in these three areas? And it's really going to benefit you. I mean, above and beyond that exercise in terms of where are you spending your time? And and how do you automate? Are there? You know, are there a few areas that you think right today in June of 2022, that we should be laser focused on as marketers?

Paul Roetzer:

Yeah. So from a business outcome perspective, I always tell people, I just do things that accelerates revenue or reduce costs, you can do both. But like, if you're as a business, if you want to do either of those things, AI is of equal to do it. When you get into the specifics of marketing. Personalization is a lot of times the big one everyone looks at. So everybody talks about personalization. And then first name and company name in the email is not personalization, like those are tokens. Personalization is, I know the last 10 Things Neil read, he's opened 75 marketing emails from us over the last two years in visited 75 pages on our website, no human marketer is going to dig into that CRM data about Neil, and figure out how to customize the next email to him, it's just not going to happen. And if you have 100,000, or 200,000, contacts, you're never going to truly personalize the experience for them. The chat experience when they get to the site that already knows their customer, and knows the objection they ran into via email earlier that day, like true knowledge base about the individual. So you can personalize the experience, remove all friction, and drive the greatest possible outcomes for your business. And for them, that is like the thing that's really hard to do. But every business talks about personalization, the other for me is prediction. So again, predicting churn predicting conversions, predicting what action they're going to take next, those are critical, and those can be across a lot of and then the last one is creativity. AI is getting very good at language understanding and generation GPT. Three is a major player, Google just came out with their own thing. Microsoft is investing billions as like, language is going to a massive area. And then creation of images. I mentioned dolly to Google two weeks ago just released one called Imagine that does the same thing. You give it a text prompt, it creates an image in the style you want. I don't know the future of stock photography, I don't know the future of illustration, graphic design. Like I really don't know what those professions will be my wife is an artist. And the day I saw dolly to I went down, I was like, Thank God, you don't illustrate children's books for a living? Because I actually don't know that that's something people will do in the future. I think the machine does it. And I'm not bullish. Like I'm not saying I think this is good. I'm just stating facts. Like it's getting really good. And it's going to start taking things from us that we think are uniquely human.

Neal Schaffer:

Yeah, you know, it's funny, my 15 year old son was interviewing me for a history project at a school. And he's like, Daddy, tell me about some of the jobs you had when you were young. And I said, I was, I worked at a company, I was a paper filer, I took invoices, and I had to put them in files and put them in the folder cabinet. And that is something that is no longer necessary, right. And I think over time, it's not necessarily a bad thing. It's a good thing. But we invent, reinvent ourselves. And I see a lot of artists that are getting into the NFT space. And we find different ways of leveraging our capabilities. So so cool, personalization, predictability, and I lost my creativity. So very cool to look out for it. And I know like with me, when I use stock photo, yeah, I'm not I'm looking for like an emotion and a subject matter, it doesn't, you know, I could see AI generated imagery as fulfilling my need. Right, as a marketer. Obviously, for certain types of content, you might want that personal touch, you might want to take him by photographer that you know, or that's well respected. But I totally get that. So very, very cool. We've sort of talked over some of the areas to look into, what are some of the pitfalls, or the issues of how maybe marketers are misusing or maybe abusing this AI technology?

Paul Roetzer:

I mean, first comes to mind is that you assume it's magic. And it just works, that I'm just gonna go get some AI. And I mean, I no joke to 2018 I had somebody come to me and said, How much would it cost? And if money's not an issue, how much would it cost for us to put AI on everything? Like just AI all of it? And I was like, Do you know what that means? If he goes, No, but I know it does that stuff. Like what we got a couple million, like my whole marketing team, oh, marketing budget, I was like, Yeah, we're not there, man. Like that is not how this works. So I think we created this marketer to machine scale. And I did talk about this in the book. Ai doesn't go from zero to fully autonomous, like you're not buying technology that removes the human like, if anyone's been in a Tesla, and you use the autopilot where it drives itself. The humans still there, the human has to be able to take the wheel if things go wrong. The human controls everything every 30 seconds, you got to put your hands back on the wheel. The human is fully in the loop. It's Level Two out of level five in terms of autonomous driving, but it's amazing. Like it's phenomenal technology, and it changes the driving experience. That's where people have to set their expectations you don't need we ours goes from level zero to level four, level zero is all human all the time, level four is don't need the human level four doesn't exist, level three doesn't really even exist. But level one and level two are amazing. If you can get AI tech, that can be an assistant to you that can augment what you're capable of doing free you up from the repetitive data driven test, that can be empowering and fulfilling to you as a professional. And I think if you go into AI thinking about it that way, that is an assistant, it is there to help you and recommend things to you and, and develop drafts of social shares and ads and copy like not write the thing for you, then you can have an amazing experience with AI.

Neal Schaffer:

So Paul, it sounds like what you're saying, obviously, we had the big platforms invest the technologies old now we have new VC funded companies, people leaving the big companies started. So it sounds like we're at the stage where if you're a marketer, you need to sort of understand and keep an eye on this because it can really have an impact on your business. How much you can leverage right now, it depends a lot on the need, the scale of your your budget, obviously, and a lot of other things. But it's almost like web three, we don't know where it's gonna go. But we know what's important. And we need to sort of like keep an eye on it. Obviously, AI is probably a little bit more developed than that. And it just something that if we want to be smart with our marketing and invest in our future, we need to be on top of it now, which I assume is why you created the AI Marketing Institute, which I'd like you to sort of share what that's about.

Paul Roetzer:

Yeah, the the market answer is basically just a median event company and education company. So we just created a bunch of data, we run like 900 articles. And the whole idea was try and make this stuff approachable and accessible to everyone, if they're an intern to the CMO. And by demystifying it, get rid of all the jargon and just like this is what it is, is what it does, here's how you can use it, here's you can get started, here's a bunch of tech you can use. And so that's really, I mean, the middle section of the book you were talking about. It goes through each category of marketing and says, here's how it's being applied in advertising, here's sample use cases, here's seven technologies, you can go check out to, like really understand this stuff. And that's how we try and approach it is we just teach people how to look at it. Now. At a higher level, I just wrote something that was like two weeks ago, we did a podcast on it, I wrote a post called The Future of businesses AI or obsolete. And what I've come to truly believe is that there'll be three kinds of companies in the near future and it near future, I mean, like maybe five, maybe 10 years, like it's hard to say. One is AI native, someone's gonna look at every business model and second, build a smarter version of that they're gonna find inefficiencies in the business, take marketing agencies, I had a marketing agency for 16 years, if I were building an agency from scratch, today, I could obsolete most agencies I've ever known, because there's so much inefficiency in the Way agencies are run. And so you find smarter ways to build everything into it. So AI native is building from the ground up with ai, ai emergent is, I'm an existing company, I'm gonna find smarter ways to do everything, I'm gonna get better, more efficient than my competitors, and they're not gonna able to keep up with me and obsolete as everybody else. So people who don't think this is real, don't think you can actually apply it. That's cool, like, just wait five years, because then it will be infused into everything. And now it will be emergent with an all these different technologies. And you'll be five years behind the people who are already hit 60% profit margins and efficiencies through the roof. And like, that's what AI makes possible. And I think that that's what's going to happen in every single industry is you're just gonna have aI native and AI emerging companies, and they're gonna be the ones that dominate the industries.

Neal Schaffer:

That's really powerful advice. I think you've opened a lot of eyes through this short little interview. Paul, is there any other advice you'd give the listener that maybe we haven't covered up until now?

Paul Roetzer:

I just said, you just gotta be curious, like, find the thread within AI that is interesting to you. If it is, you're an advertiser, then find the thing in advertising, you can test and try if you're a CEO, or a CMO or an entrepreneur, like find the part of this that is intriguing to you and just go take a course go read a book, go listen to a pot, like just do the next thing this stuff doesn't make sense right away. This one podcast isn't going to solve this for you. We do an intro to AI for marketers live class every two weeks we've had like 4000 people registered we've done it 11 times. So that to me is like just we created it for that exact reason. Just like just spend 30 minutes on this stuff and I promise you will find something you can actually act on and then just start building on that don't flip a switch and I'm all AI all the time. Just do the next one thing that'll prove to you the value of it.

Neal Schaffer:

Awesome. Well obviously, you should all have your AI thinking caps on now. You should be going to Amazon or wherever you buy books looking for marketing artificial intelligence. by Paul Rudd, sir with Mike kaput and Paul thank you so much for sharing your your experience your expertise your advice with us outside of buying your book obviously where can people go and find you?

Paul Roetzer:

Yeah I'm I'm really active on LinkedIn and Twitter be the to for personally like I love people connect on LinkedIn. Let me know you heard the podcast I love to hear from people there and and tell me about your AI journey. Like I love the learning journey. So what we're trying to do is like how help people along that. So reach out on Twitter, LinkedIn, and then marketing ai institute.com is the main site for the organization.

Neal Schaffer:

Yeah. And I just want to remind the listener, I, you know, I had heard about AI and stuff. And that chapter I wrote that was with a company called Open influence. And they were showing me how they could really predict how influence or marketing campaigns would perform based on all that data. And it was extremely accurate. So yeah, just this is not something that's 10 years from now, as you said, and it's good to hear that there's a lot of technology and investment that's going into making this more successful because I believe that AI is going to make all of us smarter, more effective, it's going to help us do more value, add strategic things. So I'm embracing it. And I hope everyone listening to it. I know you are as well, my friends. I hope everybody listening does as well. All right. Well, thank you so much today. And yeah, I look forward to seeing everyone by and review your book on Amazon.

Paul Roetzer:

Thank you. All right, I

Neal Schaffer:

hope you enjoy the interview. And yes, I did geek out a little bit. For those of you that might have remembered I was the co founder of an event all about marketing technology called social tool Summit. So it's very exciting to see a new generation of AI infused tools that, as I mentioned in the interview, are going to make our lives easier and are going to give our businesses a competitive advantage. So your homework for this episode is to buy a copy of marketing, artificial intelligence, and go through the different tools that are mentioned in those different sections, find one or two that meet your needs, and see how that can simplify and make your business life more competitive as well. I'm gonna put the links to all these things in the show notes. Once again, if you're new to the show, I hope that you'll hit that subscribe button so you don't miss an episode. I do 50% You know, thought leader interviews 50% solo episodes. And if you are a frequent subscriber, I'd really appreciate if you could head on over to the podcast player of your choice. And write a little review mentioned what you got out of the show and maybe your favorite episode, maybe some feedback on what you'd like to hear more of I would really, really appreciate it because guess what, I am staring at a wall in my home office. While I record this podcast, it can be quite lonely. And just knowing that there is someone on the other end that is listening and actually engaging is really the fuel that well it's the fuel for my passion of continuing to do this and to educate and empower. So thank you again for listening. As always, make sure you keep your eyes on the goal. And until next time, this is your digital marketing coach Neal Schaffer signing off. You've been listening to your digital marketing coach, questions, comments, requests, links, go to podcast dot Neal schaffer.com. Get the show notes to this and 200 plus podcast episodes, and Neal schaffer.com to tap into the 400 Plus blog post that Neil has published to support your business. While you're there, check out Neil's Digital First group coaching membership community if you or your business needs a little helping hand. See you next time on your digital marketing coach.