You may already be using AI for content generation. But how about for the steps before that? AI can be a powerful tool for content gap analyses, content strategies and more. Our Senior Digital Marketing Specialist, Sarah Thaler, spoke with our Chief Strategy Officer, David Fabbri, about the best ways to use AI across the content creation process.
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Quick note: This conversation was transcribed with the help of artificial intelligence and has been lightly edited for content.
David: Welcome to the latest episode of the LoSasso podcast. Today we want to talk about the state of AI and marketing, and specifically AI for content strategy and activation. I'm David Fabbri, Chief Strategy Officer and I'm here today with Sarah Thaler, who's our Senior Digital Marketing Specialist, really our SEO and content guru at the agency.
Sarah: I am just also very passionate about experimenting with the AI technologies that are coming to life over the last couple of years and really how we can leverage those tools to create amazing and engaging content.
David: Sure. And Sarah, you've been part of our AI committee here, just went to MAICON last month, which is the marketing AI conference. So, Definitely stuff that you're passionate about and dialed into, which is great.
Sarah: Yeah, that was a really fun event, very like like-minded people that were brought together from all different backgrounds and levels who dive into the tools, use it on a day to day to help projects and things, but also, leadership and C-suites and how they can get their companies rallied around using AI.
David: And it is funny how fast that stuff changes. I was at MAICON the year prior to you, and you know, just in terms of the way people are looking at it, using it, it changes so fast. So really great to stay up with it.
Sarah: Yeah, definitely.
David: So in terms of AI for content, when you say generative AI and you talk about content, I think the first thing that comes to mind for a lot of people is using it for chat GPT to write content, right? And obviously it can be very helpful there: First drafts, content outlines.
Obviously we do a lot of editing of those things, verifying with our subject matter experts. So a lot of human effort goes into that stuff, but it can really help in terms of scale. amount, complexity of content. So it is great for that. But today, focusing not on that, but more on how you use it for content strategy and activation.
Sarah: Yeah. Everything before the writing.
David: Right. And one of the things that I'm super excited about is it's such a fantastic research tool. So big picture understanding the industry that your client's in, trends and things that are happening, who the competitors are, what's going on with them, and audience insights.
For instance, we use it for new business If we want to get dialed in quickly to a new industry, what's happening, it lets us pull together a dossier and really get dialed in quickly. It's fantastic.
Sarah: It gives us that high level overview of the landscape so that we can get a baseline and be able to talk to prospective clients and be more well informed.
David: I think one of the things that's different now than it was a year or longer ago, for sure, was at first the LLMs were not connected to the internet, right? And so it was based on old information or you didn't have source information to know if something was hallucinating.
So at first we were using Perplexity, one of the AI tools, because it was connected and always provided source links, so you could validate the facts. But at this point, as of last month, Chat GPT is fully connected and providing all those source links as well.
Sarah: Yeah. And I think that's kind of just the bigger idea and picture with these AI tools is to make sure they are citing their sources. So building that trust with the information, people may have gotten that you know, in their traditional search results by seeing the company names, the websites, things like that. But if you're going straight to the AI tools, that's a super important factor that they're now building in, that you can verify and fact check. But also if you're wanting to learn more, you can just directly click.
David: Right. Because it often does dig up great resources to use for that stuff. And so in terms of this idea of front end research, there's a baseline you want to set in terms of understanding. it's also so much easier to quickly get updates, right? So what recent news might be affecting what's happening in the industry. You could do it before, but it was a much heavier load.
And this way it allows us to be so much more up to date in terms of timing of everything, coming up with new ideas because of it. I think it's pretty great. So maybe you can speak a little bit about that. I know you use it specifically now for helping to drive some of the content that we're doing and what it is. What are the sort of key areas that you use it in?
Sarah: I have really been experimenting with using it to make sure our clients' content strategies are in line with competitors. So in addition to some of the more traditional SEO tactics of keyword research and competitive landscape research, those similar best practices can be applied here, where we're looking at competitors top content, their top keywords that are driving traffic and identifying, okay, where are our clients, missing the mark or where are they not present in the search results, for a specific topic, as well as where our competitors are not appearing and where our clients may have that competitive advantage and opportunity for them to have the leg up on a specific topic.
It's really about combining the data that I traditionally find in the SEO tools, your SEM Rushes and all of your other keyword research tools, and then leveraging the AI to help cut through some of that data, gathering some of the insights much faster and at scale.
And oftentimes the content that I'm working with is quite technical. So it's also helping to simplify and parse down, really complex topics for us to help create amazing quality content.
David: That's a great example you talk about. Typically, we have subject matter experts at the client. We've also got the marketing team. And we're interviewing them, talking to them regularly, understanding what they think are the key topics and pain points for their target audiences.
But using some of the AI, we can really pull out more ideas to put in front of them.
So even going in and saying, who are the key decision makers in this industry and what are their pain points and challenges really can pull up a bunch of different ideas, some of which they, you know, we already may be tracking, with some we aren't. Certainly it lets us, iterate more quickly, get stuff in front of them to say, hey, we're thinking this, this, and this, you know, which of these resonate with you, here's why we picked this or where we found the info.
It really just makes things move faster. And again, you get more iterations of things more quickly.
Sarah: Yeah, I almost think of it in the process. Like you're just kind of like layering these things on top of each other, like during your chat with chat GPT, you know, you're starting with the target audience insights. You're gathering the competitive stuff and you're just like layering more data to get that really nice piece of content.
David: One of the other things you've talked about is content gap analysis. maybe in a little more sort of detail what you mean by that and how that works.
Sarah: Yeah, so really the content gap analysis is pinpointing topics—two ways of looking at it—that your competitors have a strong hold or are performing really well in organic search, or they're talking about a specific topic that you are not. Or you can think of it in vice versa, whereas you know that you have a competitive advantage in a specific topic area and your competitors may not.
And even though they're not talking about something, it's an opportunity for you as a brand to be able to talk about something and be that first mover into the market and have a presence. So then it's your competitors who are catching up to you.
David: Sure. And I suppose it's that Venn diagram too. So you've got, you know, what you understand to be the key pain points of the audience, what they're talking about, what you're talking about. And are there places where nobody's paying attention?
Sarah: And that's your good opportunity.
David: Yeah. I know one of the other areas that we're starting to look into more is more personalized content at scale. Right? I mean, we've always done segmented emails, so if we know we're going after target lists or whatever. But there is this idea that with AI and some of the generative stuff, we can leverage, whether it's CRM data or post-show survey information. For instance, we've got some trade show clients, and understand what people are looking for, and then marry that up with who they are and deliver different messages.
Sarah: So this whole idea of, you take, you know, like you said, trade show data. So, if you have registration data, we'll often, you know, fill out demographic information, industry, a bunch of questions, why you're attending all that good stuff. And you can marry that with your Google analytics data, which is giving you your site traffic, your registrations or other key conversion points.
And so one of the things that AI is really good at is categorization. And so when you're combining these two data sets together, it really marries that qualitative and quantitative opportunity so that you can take your specific audiences. What are the pages and the topic areas that are on your website? And again, identify some of those gap and opportunities and mismatches to create more content
David: So I think it's exciting times for this, you know, it really just is a different level of speed and detail that we always wanted to push toward, but really, even something like researching industries and competitors and things; if you're doing that on a Google search basis, you know, that's a long, slow, arduous process versus, something that can really compile everything that's out there and get you much further down the road more quickly.
Sarah: Yeah, I think that the time advantage is huge. The ability to just get there faster. And I even as a human, we have some sort of biases too that the AI might pick up, different trends, things like that. But I also wouldn't want to discount still doing more traditional Google search marrying that more traditional process that we're used to going straight to Google or Bing or whatever you use, researching and things like that.
I think there's still a need to marry the old fashioned and this newer to boost more of that research. If you have your own trusted go-to resources too.
David: Sure, And it's in terms of your own sort of intellect and curiosity, what are the things that are standing out and where do you want to drill in more? I think the AI is great because sometimes if you're doing Google search, you find somebody's thing and they've got a real agenda that you have to sort of suss out. And so the argument against some AI is that it is like the least common denominator, but at the same time, what it does do is it filters out some of that bias in a way that you get some good general input.
So I'd say, in general, things are going well. It's really exciting to be activating AI in a way that's really beneficial for us and our clients. And these are some use cases now where it's in action and really driving results and performance, which is great.
Sarah: Yeah, and I think, you know, as we're wrapping up, one of the things that we kind of have a philosophy is you don't want to be, this is kind of like the way of the future, you know? So it's good to get in and get dirty and experiment and try new things.
There's a lot of use cases that are established, but if there's a problem or something that just takes a lot of time and you're like, “hey, there's gotta be a better, faster, more efficient way,” think through how AI could help me get there.
David: Well, thank you, Sarah, for the time today. And I think we'll probably keep this marketing AI series going, maybe cover off on some other topics as well in the future.
Sarah: Sounds great, Thanks David.
David: Thank you!
