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John Jantsch (00:47): Hello, and welcome to another episode of the duct tape marketing podcast. This is John Jan and my guest today's Paul Roetzer. He's the founder and CEO of marketing AI Institute, founder of PR 2020 HubSpot's first partner, agency HubSpots and sponsor of this show. As many of you know, he's also the author of the marketing performance blueprint, the marketing agency blueprint and creator of the marketing AI conference Macon. So guess what, we're gonna talk about AI, but he's also got a new book coming out co-author of marketing, artificial intelligence, AI marketing in the future of business. So Paul, welcome back.

Paul Roetzer (01:27): It's so good to be back together, John. It's good to see you.

John Jantsch (01:30): So, so we've been, we were laughing before we started the show. We've been talking about AI and now maybe for five or seven years, but I still think there's a lot of, like, what is that, you know, is that Hollywood? Is that, is that sci-fi, you know, how do you, when somebody just asks you, what is AI? Is there a simple answer?

Paul Roetzer (01:44): The definition I always give is the science of making machine smart and actually comes from de SaaS. Who's the co-founder and CEO of Google deep mind. And what I love about the simplicity of the definition is the software we use every day, as marketers, as consumers, the hardware we use the phones like your iPhone, they're incapable of doing things on their own, unless they're told how to do them. So machines being software and hardware with AI, those machines get human bilities to understand language, to generate language, to see, you know, with computer vision. And so that's really what they're doing, and they're able to learn from data and get smarter on their own. And so we'll talk, I'm sure we'll talk about some use case, some examples. Yeah, but that's the key is rather than just software, that's all human rules based AI enables vendors to build software that learns and evolves and makes predictions and recommendations to you to augment what you're capable of as a marketer.

John Jantsch (02:44): So let's start with the dystopian view, sure, uh, of, of, you know, which I'm sure you hear all the time, right. That, you know, it's taking over, there's no thinking there's no feeling, you know, like, you know, content marketers are, you know, like, yeah. I just put in a couple keywords and boom, I've got great content. You know, I don't have to hire anybody anymore. Uh, where does that view intersect with reality?

Paul Roetzer (03:08): AI's not that smart. So I think the key is there's definitely this nature one, you think it's abstract and it's, it is just the sci-fi thing. You're not actually using it. Two is it can seem overwhelming and highly technical. The reality is that AI isn't that advanced today. What, what happens is it's trying to do these very specific tasks at, at a very high level. And it's normally applied to things that are repetitive and data driven for us as marketers, things that we don't want to have to do a bunch of times anyway. Yeah. So you kind of look at these things in your daily life where it's repetitive, there's a defined process for it. That's a lot of times where AI being applied, it's augmenting what you do. It's intelligently automating pieces of it is not taking your job away. It's not replacing you as a writer. It's just there to be an it's easiest to think of it as an assistant. And so that's in the book we go into like these different levels of intelligent automation, and we're not going from zero to fully autonomous. We're just trying to get that little bit of support from the machine.

John Jantsch (04:05): Yeah. And I think some people can make a case for it actually frees you to do the creative work. And I think the argument probably 25 years ago when robots came around was, oh, it's taken, you know, these people's jobs, but like, do you really wanna put that bolt in 3 million times? , you know, over the next two weeks, is that a really satisfying job? Right. So that's a lot of what you're saying is it takes the repetitive stuff out. And, and so clearly if, if you're counting on having a job, that's based on repetition, I mean, you're probably, you probably are looking about at being replaced, aren't you?

Paul Roetzer (04:36): Yeah. I mean, the way I explain it is if your job is simply to AB test landing pages that is fundamentally all you do 40 hours a week, then yes, it will replace you like you. That is not gonna be something humans need to do. If you are looking at data and trying to figure out audience targeting for media buying AI is really good at that. It's really good at finding patterns and like being able to predict, you know, behaviors and outcomes. So it's just tasks. But if your entire being is doing those repetitive tasks, then yes, it would be a good time to start looking for other areas where there's uniquely human traits needed, like strategy, creativity, empathy, like those relationship building, those are machines not doing those things really. Yeah.

John Jantsch (05:17): So, so how, how are you talking to marketers specifically about the impact of this in their jobs? We, you kind of almost touched on it right there a little bit. Yeah. But how are, you know, how does it really, how will it, uh, impact the marketing

Paul Roetzer (05:31): Profession? So at a high level, we talk about this intelligent automation. We're under the working assumption that within three to five years, at least 80% of what marketers do will be intelligently automated to some degree, meaning tools, software you're using is going to have AI in them, but that's not unlike your consumer life. So you don't think about AI all the all day long, but every time you use Netflix and it's recommending shows and movies, Spotify learns, you know, your music and predict shows, Google maps routing you from a to B in the, in the fastest way. Anytime you talk to a, a virtual assistant like a Google or Siri, all of that is AI. And so your life is made more convenient, more personalized by AI. And that's, what's gonna happen in business, whether you're in advertising or email or communications or SEO, AI is going to be infused into the software and make it smarter. And in many cases, you're not even gonna notice it or even care. Yeah. But we're not there yet. And so what we tell marketers is you can get there now though, you can go find smarter tools to do what you do. It's not about buying AI. It's about buying smarter tech. You already buy this tech find tools that are getting better and making you better at your job.

John Jantsch (06:43): Yeah. And I think one of the, well, let me back up a little bit, cuz you, you alluded to a point I was gonna ask about is I think the AI's been with us a lot longer than people realize and it's in everyday stuff that we, you know, we don't realize. I, I wrote my last book exclusively in, uh, Google, uh, docs at somewhere along two, three years ago, you know, they started adding AI to Google docs to where it's actually, I could start writing a sentence and go, oh, I wasn't gonna say that. But that's pretty good. I mean, it would actually, you know, and I don't know if it's purely learning one to one with me or if it's just saying, oh, people commonly finish sentences with this word that start that way. So, so talk a little bit about some of the really everyday uses you started talking a little bit about 'em, but going to some examples of everyday uses that people are experiencing AI and, and maybe don't know it.

Paul Roetzer (07:35): Yeah. So the, we talk at a high level categorically and there's, I think it's chapter two of the book is, is broken into language, vision and prediction. And so it talks like these parent categories of different applications of AI. So language in particular is of interest to all marketers, right? And that is mainly around the understanding and generation of language. And so that's like what you're talking about Grammarly is a great example of AI embedded within a tool that many people use every day. Um, so zoom is another, like they use outer.ai to transcribe audio, right? So speech to text, text, text to speech is another one language generation with any, whether it's video or audio or written. So like all these Twitter out there, like copy.ai and Jasper and hyper write. And you know, you hear all these names, you probably see the ads for, and what they're doing is using a, the tool called G PT three or an underlining platform called G P T three, which is made by open AI.

Paul Roetzer (08:27): And that is a language generation it's using, what's called a large language model to generate language in all these different disciplines. And so you can go in and give it a sample website and say, okay, write me ad copy, or write me social media shares based on this. And it's doing it now. You're not gonna grab it and hit publish. But as a social media pro or an ad person or a blog post writer, you're going to take these almost as drafts and improve on them and then publish them. And so I think again, anywhere where you write, you're seeing it all over and that's gonna continue to become a part of your life. And then again, you just go disciplined by discipline, whether again, your communications, SEO, and just find ways where there's repetitive processes, predictions being made or language being read or generated.

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John Jantsch (09:57): So if somebody came to you and said, yeah, we we're an agency digital agency and we know about AI, but we haven't really been aggressively or intentionally trying to bring it to our clients. Where would you say, well, here's the starting point. Here are the five things that every digital agency should be diving into that it's gonna give them AI or it's at least gonna give 'em some advantages using AI.

Paul Roetzer (10:18): Yeah. So there's two ways we teach it. It's called the piloting. AI is that there's a chapter dedicated to this, too. What I tell people is take a spreadsheet, make a list of all the activities, the tasks that you do individually, or as a team each week, each month make a comment that says how many hours a month you spend doing it, uh, what software you use for it and how much that software costs per month. So you're basically getting a cost structure for each activity and then just apply of simple rating and says, well, how valuable would it be to intelligently automate this task? And so let's say you're a content strategist and you spend 10 hours a month on the editorial calendar, figuring out what to write, looking at past posts, trying to predict what work, what you should republish, what you should create new.

Paul Roetzer (10:58): Then that might be an area where you could say, wow, if AI could help me do this and cut it 80% of the time spent on it and be better at predicting, what's gonna work. That would be huge for me as a content strategist. There you go, AI for content strategy, go Google it, find three tools that do it, go demo those tools. So I always tell people is start where you're already spending time, where you can make a business case for the value it could create for you. And you're gonna know real quickly whether it's working or not. Cuz at the end of the day, AI is just designed to make you better at your job and make it cost less to do the job. And if it's not doing that in improving performance, then it's a waste of time.

John Jantsch (11:38): Yeah. I think that's a really great point too, because I think a lot of people look at this and say, oh, we can do new things and maybe start by by just getting efficiencies. Yes. I mean you could probably generate a tremendous amount of profit to the bottom line by just get, I mean, everybody that, by getting more efficient. So if you looked at these as efficiency tools alone, that would be a great start, wouldn't

Paul Roetzer (11:58): It? Yeah. And I know of companies that have, I have friends whose jobs and companies is to try and reduce the need for 15 new headcount down to five. Yeah. And they're basically just looking at not, they're not their job isn't to fire people, but it is to say, as we scale, how do we do it without having to hire more? And so they're looking at inefficiencies and work productivity and they're finding things that AI can do to at least some degree without the need for human involvement or minimal human involvement,

John Jantsch (12:25): Who are some companies that you think are doing this really well. I mean that are maybe kind of ahead of the curve and, and it might just be in their own operations or in their own marketing.

Paul Roetzer (12:33): Yeah. Most of as big enterprises, they don't talk about it much. But when you look at retail eCommerce or huge ones, just go to the top 10 eCommerce companies, top 10 retailers, um, CPG financial services. Those are healthcare. What you look for is companies and industries that have a lot of data and a, and a huge need for personalization. And there's a really good chance they've been doing this stuff for five to 10 years, not if not in marketing and sales and service across other areas of the company. But I mean, just like Mike, my co-author just put one on LinkedIn last week about like 15 retailers that are doing awesome things with AI. And it was the obvious ones. Walmart Starbucks McDonald's bought, bought AI com like they're buying AI companies, they bought one to customize the drive through screen for you based on the weather data and based on behavioral data of like what people are ordering that day. So it actually tailors what you're seeing. So I mean, it's just, retail was a huge one that, yeah, there's just tons on.

John Jantsch (13:29): So that's why that pumpkin spice shows up that day. Huh?

Paul Roetzer (13:32): Yeah. Well if it's in the middle of the summer. Yes. Because otherwise it just shows up in the winter, but yeah,

John Jantsch (13:38): That, yeah. So, so taking this back to non-enterprise yeah. Level companies, uh, which a great deal of our listeners are what's the, what's been the stumbling block. What's been the hard part, you know, of doing this.

Paul Roetzer (13:53): So we asked that question in our state of the industry survey we did with drift, like what are the obstacles to adoption? Number one far and away with 70% of people said, lack of education and training. They just didn't know where to go to get the information. And then in the 40 percentiles you had like lack of awareness, lack of team, right? Like talent, lack of strategy, lack of vision. My base assumption is the vast majority of marketers still have no idea what it is. So they can't explain it to you. They, if like, let's say you're at a, you know, a 30 person agency and you listen to this and you're like, this is kind of cool. And you're gonna walk into the CEO's office and say, I think we should start doing more AI. And the CEO says, why you're gonna say, I don't know, just, it sounds like we're just really cool. Like

John Jantsch (14:32): Everybody else is.

Paul Roetzer (14:33): Yeah. If they really say, well, what would be the business case for it? What exactly is it like most marketers can't give a basic definition and they don't know the main use cases for it. So I think it, it is just a lack of understanding across the industry. That's slowing adoption rates down,

John Jantsch (14:47): You know, I loved one of the filters. I think that you used for this, you know, when a lot of new social media platforms would come around and you know, clients would be saying, should we be doing that? You know, should we get on Twitter, this, you know, circa 2007 or something like that. Um, and, and I always did use the filter. Uh, would this help you serve your existing clients better? You know, if you make a case for that, then go all in and we'll get crazy with it. But, and I think that's probably a great starting place for looking at AI. Isn't it?

Paul Roetzer (15:15): Yeah, no doubt. I, I actually published something recently that wasn't in the book and it sort of came to me, uh, little later on, but the, what I think's gonna end up happening is, and again, keep in mind, I owned an agency for 16 years before I sold it. Right. So I, I live in the agency world and we work with lots of companies. So SMBs all the way up to, you know, fortune 500 companies. Um, I think in the not too distant future, there's three types of organizations. There's AI native. So they don't exist without AI, they're in an industry and they find a smarter way to do that industry, do the products and services in that industry. And they build from day one as an AI company, then there's AI emergent. Those are companies that exist today that look to the future and say, while there's smarter ways to do product and services, marketing sales, and then there's obsolete.

Paul Roetzer (15:58): And, and I don't think there's anything in between. So the way I look at it is AI is going to be so essential to the operations of every business. And so intertwined into the marketing sales and customer service, that if you don't find ways to adapt and evolve, someone else is going to build a smarter version of, of your business. That is way more efficient than you are without AI. And over time, I'm not saying like three years from now, we're all done. Like if you don't evolve saying, but over the next decade, like it's going, you're just gonna become less and less relevant if you don't find a way to become more efficient at what you do and deliver better results.

John Jantsch (16:34): Yeah. And I think some of that's very consumer driven too. You know, one of the things people always point to is Amazon changed the game because consumers got used to yeah. The way what they got to experience there and everybody else had to up their game or, you know, get left behind. And you know, what ways are you seeing consumer behavior change? Because whether they know it or not, they're being served this way.

Paul Roetzer (16:57): Yeah. I, I think the key for me is as consumers of consumer products, but also in our B2B world, you come to expect convenience and personalization. Like if I'm, let's say I'm shopping for new social media management software and I'm the entrepreneur of a five person company, or a 20 person agent, whatever it is, there's a good chance. I'm not doing that at 10:00 AM on a Thursday. There's a much better chance I'm doing it at 10:00 PM on a Friday after my kids go to bed. And I finally have a minute to look at that thing. That's not critical to my business, but is important to the future. So if I'm on a website for social media management software and it's like call us between Monday and Friday from nine to five, and there's no intelligent chat out there that actually helps me get what I'm looking for or understands that I've been on the site previously and kind of can predict my behavior and my intent, like I want personalization and convenience in my shopping experience, whether I'm on Amazon or I'm on some social media management software site. And so I think as consumers, we just come to expect convenience and personalization, and there is no way to do personalization at scale, without AI in the future. Like I've heard software CEOs talk about personalization as though AI, or as though it can happen without AI. It can't, like, we're not that good as humanist writing rules that apply to thousands of people.

John Jantsch (18:17): Right. Right, right, right. Right. So, so let's talk about the relationship between AI and your data, because I think that's what you're really in a lot of ways where, where people are starting to personalize without AI is because I know customer X has bought this product and I can cookie him or her. And so then I can serve a more relevant, personal experience perhaps, or relevant email newsletter perhaps. But where does, where do you see AI then? You know, must be applied. You know, if we can use these JavaScripts and we can use our own data, you know, where does AI come into play with that scenario?

Paul Roetzer (18:55): Yeah. So data is the foundation of AI. It's what it gives its predictive abilities, cuz that, that you almost every case AI is just making predictions about behaviors and outcomes. That's what machine learning is. So you hear machine learning thrown around is like synonymous with AI. Sometimes it's a subset of AI, but machine learning is all about the machine learning from data to improve its predictions and actions. And so that's what the data does is it gives you the ability to actually build these predictive models about customer retention, customer growth, churn rates, lead scoring, to predict who's likely to be a new customer. Who's gonna open emails. Who's gonna click on it's all predictions. And so data is at the foundation of that. Now you can be a small business. You don't have to have, you know, hundreds of thousands of records because what you can do is benefit from anonymized data. So if you're a HubSpot customer, they have 150,000 customers over money. They have, they can anonymize all that data targeted like, okay, this is a lump of cohorts. That's in this specific industry or this specific size company. And they can anonymize that data to improve your predictive ability. I'm not saying they're doing that, but that's what's happening. MailChimp is a good example. Hundreds of millions of records. They can use all that anonymized data to predict when you should send your emails, who you send 'em to subject lines, you should use things like that.

John Jantsch (20:07): Yeah. So let's, let's end by talking a little bit about future careers. If you were talking and you probably get asked to, to a group of college students that were in marketing, uh, what would you be? I know when I talk to 'em, I, I tell, 'em look, forget all the stuff you've been learning. This is what you actually should be focusing on. You know, what are you, what would you tell, uh, a group of folks that are just now getting into marketing, where they should be putting their attention?

Paul Roetzer (20:31): One, I think it's an incredible time to come into the profession because as you said so much of what got the rest of us, where we are, is going to evolve in the near future. yeah. And so the ideas to, to, to drive digital transformation, to evolve an organization, to, to do smarter marketing, that saves time and money and produces better outputs. It can come from the interns because a lot of executives don't understand this stuff and they're maybe even a bit intimidated by it because they don't understand and they think it's gonna be really hard to learn. So they just kind of avoid learning it, keep putting it off. Yeah. So I think that the people who take the initiative to go learn it and don't go and try and sell AI and machine learning like you, if you walk into the CMOs office as an intern and say, I think we're gonna, we do some machine learning.

Paul Roetzer (21:17): We could cut a hundred hours a month of productivity and like get outta my office. Like I . But if you go in and say, Hey, listen, I analyzed our email marketing activities and we spent a hundred hours last month doing these five things. I think there's a way to shave 50% of the time off and actually produce twice as much quality work now. Oh, talk to me about that. What is that? Okay. Well there's these two tools I've been testing and here's what they do. You don't ever even have to say AI. Yeah. Yeah. But you know, to go find smarter tools to do the thing and you identify opportunities to drive efficiency cuz you understand what it's capable of doing.

John Jantsch (21:51): All right. I lied. I'm not gonna end yet. Tell me where tell me, tell me where, what are you can need to say? Well, here are my favorite places to find AI tools or here are a handful of my favorite AI tools, either one, either way. You want to answer that.

Paul Roetzer (22:03): So in, in the book, there's 10 chapters in the middle that are piloting AI chapters and it's AI for advertising AI for communications. Each of those chapters just follow the same pattern. It explains the opportunity with that category of marketing. It goes into tech and then it goes into sample use cases or vice versa, use cases and tech. So there's about 70 different vendors featured in the book that are a good starting point on the marketing AI Institute blog. We regularly published lists of vendors across different categories and different things. Like we did 36 tools for AI co or for copywriting last week that, that sort of stuff. So yeah, we just follow along the newsletter or, you know, grab a copy of the book.

John Jantsch (22:39): And the, the fun thing is that like everybody's copy of the book will be different. Right.

Paul Roetzer (22:44): That would be awesome.

John Jantsch (22:46):

Paul Roetzer (22:47): There, there are a lot of things we tried to do with AI to do the book, but personalized copies for everybody. I don't think the publisher would've let me get away with

John Jantsch (22:56): That. No, no, that's a tough one. So speaking of an industry that, uh, maybe needs to come into the future, sorry. Uh, sorry. I'm not picking on your publisher,

Paul Roetzer (23:04): But my publisher's very open minded. I actually love what they're thinking of. We're doing some cool stuff with synthetic voice potentially. We may actually

John Jantsch (23:11): Do some stuff, so. Oh cool. Awesome. We'll tell people, you've mentioned a few things, but if you wanna invite people where they could connect with you and obviously the book will be available everywhere.

Paul Roetzer (23:20): Yeah. And so marketing, I institute.com. You can get to the book site from there. There's gonna be, uh, there's a couple of free downloads that actually the piling AI workbook that we talked about of how to figure out what to start with, that's gonna be a free download as part of the book. So you can go there and actually get that spreadsheet. And then there's a guide that has about 30 sample questions to ask AI vendors. So to help you assess them, it it's kind of a cool guide. So those will both be available there. So yeah, marketing institute.com is best and I'm really good on, uh, LinkedIn and Twitter. If you wanna reach out to me personally, I'm, I'm really responsive on both of those platforms. I am not a Instagram TikTok or Facebook guy. And if I'm missing anything else, I don't really do those either too much.

John Jantsch (23:56): gotta stay focused. Right. Awesome. Paul, it was a great catch up for you. I appreciate your stopping by the duct tape marketing podcast. Hopefully you will see you, uh, soon, one of these days out there

Paul Roetzer (24:05): On the road. Thanks so much, John.

John Jantsch (24:06): Hey, and one final thing before you go, you know how I talk about marketing strategy strategy before tactics? Well, sometimes it can be hard to understand where you stand in that what needs to be done with regard to creating a marketing strategy. So we create a free tool for you. It's called the marketing strategy assessment. You can find it @ marketingassessment.co not.com.co check out our free marketing assessment and learn where you are with your strategy today. That's just marketingassessment.co I'd love to chat with you about the results that you get.