Jeff Coyle: Creating New Content-Marketing Opportunities with AI – Episode 37

Jeff Coyle Generative AI tools and LLMs bring the need for a new kind of content awareness in organizations of all sizes. While some have focused on content creation, Jeff Coyle has grown and accelerated his content-marketing capabilities by leveraging the content discovery and operations improvements that AI can deliver. We talked about: his decade-long history in working with NLP, AI, and content his overview of the rapid progression of AI technology over the past two years the importance to businesses and enterprises of doing a data inventory to understand their unique strengths the exponential increases in both the capabilities of the AI services he uses and their affordability the importance of creating high-quality content in this new AI landscape how to capture your org's knowledge and use it to fuel your content plans how journalists are crucial for capturing that knowledge his take on the current state of content-industry employment the importance of aligning content and its performance to organizational KPIs the crucial differences between how you wish people would consume your content versus how they are consuming it and how they might be the ongoing difficulties of marketing attribution and how new predictive models that AI affords can help address them how a "process inventory" is even more important than a conventional content inventory Jeff's bio Jeff Coyle is the Co-founder and Chief Strategy Officer for MarketMuse. Jeff is a data-driven search engine marketing executive with 20+ years of experience in the search industry. He is focused on helping content marketers, search engine marketers, agencies, and e-commerce managers build topical authority, improve content quality and turn semantic research into actionable insights. His company is the recipient of multiple Red Herring North America awards, multiple US Search Awards Finalist, Global Search Awards Finalist, Interactive Marketing Awards shortlist, and several user-driven awards on G2, including High Performer, Momentum Leader and Best Meets Requirements. Prior to starting MarketMuse in 2015, Jeff was a marketing consultant in Atlanta and led the Traffic, Search and Engagement team for seven years at TechTarget, a leader in B2B technology publishing and lead generation. He earned a Bachelors in Computer Science from Georgia Institute of Technology. Jeff frequently speaks at content marketing conferences including: ContentTECH, Marketing AI Conference, Content Marketing World, LavaCon, Content Marketing Conference and more. He has been featured on Search Engine Journal, Marketing AI Institute, State of Digital Publishing, SimilarWeb, Chartbeat, Content Science, Forbes and more. Connect with Jeff online LinkedIn MarketMuse Twitter jeff at marketmuse dot com Video Here’s the video version of our conversation: https://youtu.be/Ij18O07YnYc Podcast intro transcript This is the Content and AI podcast, episode number 37. The label "generative AI" has led many to focus on using this new tech for content creation, while the real benefits may lie in different capabilities that LLMs and other AI tools afford. In his work, Jeff Coyle has enthusiastically adopted AI, using it to identify new content repurposing opportunities, to capture and leverage unique organizational knowledge, and to dramatically reduce the costs of content operations, discovering along the way new opportunities for content professionals. Interview transcript Larry: Hi, everyone. Welcome to episode number 37 of the Content and AI podcast. I'm really delighted today to welcome to the show Jeff Coyle. Jeff is the co-founder and Chief Strategy Officer at MarketMuse. We talked on my other podcast, Content Strategy Insights, a couple of years ago, and I'm really excited to have him back because one or two things have changed since then. Welcome, Jeff. Tell the folks a little bit more about what you're up to these days. Jeff: Oh, thanks, Larry. And I am glad to be back. I am the co-founder and Chief Strategy Officer for MarketMuse, as you mentioned. I'm working on building artificial intelligence and content strategy offerings so that teams can make better decisions about what content they create or what content they update and then execute a lot faster. And so I'm sure we'll get into the details, but my background, I've been in the search space, building products, building search engines, building lead management systems, or selling them for 25 years. And I've been in SEO for about that long as well. There's probably nothing in the SEO space that you could ask me about that I haven't tackled or got knocked over by and got back up and then tackled. But yeah, I'm looking forward to this discussion. Larry: There's so much going on in that world. I really want to stay focused on the AI stuff that we might have to slip into SEO a little bit because that's an old practice of mine way back in the day. Jeff: Sure. Larry: But the first thing I wanted to do, you mentioned the details and do want to get into the details, but what I would love to get, because you're somebody who's been in this world for 20 years and you were talking about LLMs and Prompt Engineering six months before ChatGPT hit the scene. You're clearly embedded in this world. I would love to get your top-level overview of the commercial landscape around just data and data sourcing and the services around LLMs and GPTs and that whole world. Can you give us just a quick high-level overview? Jeff: Yeah. Like you said, and I've been doing natural language processing and the artificial intelligence components for now, gosh, about a decade. Thinking about ways that I can do it. I mean, I was trying to figure out how to use language technology to automatically classify documents into categories and into taxonomies, literally in a project 10 years ago. And then before that, thinking about search engine indexing and search engine strategies and building vertical search engines, building intranet search engines, and then the implications of how to use that to be really great at building content and being really great at SEO. Right now we're in a very unique, and the world is moving so fast that I think everyone really, really needs to focus on the new features and components that come with some of these language model releases. Jeff: We just saw from, and this dating this in the late summer in 2024, we saw from recent releases with Llama some of these things that have been closed and not accessible. Now you can see the way that things are working, right? The way that they're open, the waiting, things that you can tweak. You're able to learn from what's being released a lot more than you were in the past. And that's amazing just by itself. The advancing models that come out, even if you don't modify them yourself, they're progressing so fast that if you have a process in place that's using natural language processing technology or large language models, every time a new model's releasing, you're talking about savings of factors of 10 minimum. I mean, I have processes that every time something new comes out, I'm able to knock down 90% of the costs, right? When you're talking about the data side of it, there is massive, massive diamonds built into anyone that has any proprietary data source right now. Jeff: Inside your business, if you're a mid-market to small enterprise to enterprise, you should be doing a data inventory. What do we have that's special? What do we have that could be used for someone else's benefit based on how fast this market is moving, whether the use case, if you don't understand the use case, come find somebody like me. Come find somebody like Andrew Amen from 923 Studios, find somebody who is all about knowing how to make use cases with data and turning those things into potential gold mines for your business. If you have a database of customer data, if you have a database of real estate data, if you have a massive search engine index, you can use those things to do magic and you can do it on the cheap now. And it keeps getting cheaper and cheaper. And that's where I don't think people are catching up right now. Jeff: They're not catching up to how truly fast and how truly cheap it is to do things that would've cost millions of dollars. And I'm not being hyperbolic there. Millions of dollars only three or four years ago. And I'm a kid in a candy store with these things, right? I mean, I did a proof of concept that would've cost me about a half a million dollars just two or three years ago. And I shocked myself because the total cost of the entire project was a dollar. I mean it was literally a dollar. And I was like, I'm paying more for the coffee that I'm drinking right now than that cost. And I'm like, well, could we scale this? I'm like, hey, let's spend $70. And we did and I'm like, the magnitude of the things that we're doing for the cheap, it's truly staggering. And so I think everybody's really got to think what makes them special, what data do they have or what data do they know about? Maybe it's a partner, maybe it's a peer, maybe it's a data provider, and you can turn it into a partnership and say, hey, you have this thing. We could really do something special with it. That's the new economy with artificial intelligence and with content that nobody's talking about. Larry: Yeah. And as you say that, I'm thinking it's probably a rich multi-sided environment too. I'm just picturing, like you just said, if you have the data and people with the data have more opportunities, but people with ideas about what to do with that data, there's also the world of data products, but also just data as a supply for other people's stuff. It just seems like there's so much going on there. And you mentioned the use case.