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You're listening to Built to Convert, the podcast where growth-minded marketers, founders, and creators come to level up.
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No hype, no guesswork, just bold insights that drive results.
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Let's go.
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Hey everyone, I'm Tyler Lane, founder of Session Interactive and the host of Built to Convert, where I talk with growth-minded leaders in healthcare, tech, e-commerce, and finance.
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We dig into how data, marketing, and strategy come together to help organizations make smarter decisions and scale with purpose in today's digital world.
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This episode is brought to you by Session Interactive, a digital marketing agency that helps businesses turn complex data into clear strategy from SEO and analytics to paid media and content.
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Session zeroes in on what truly drives growth, smarter decisions and better user experiences.
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Known for their collaborative approach and measurable results, they partner with forward-thinking companies across industries to solve digital challenges and turn them into opportunities.
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All right, a little bit different today, but I've got Chad here from Rise25.
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Chad's done thousands of interviews with successful entrepreneurs and CEOs, and we have flipped the script today, and he will be interviewing me.
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Chad, great to see you.
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Welcome to the show.
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Hey, great to talk to you again, Tyler.
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Um hey, I was thinking today we would focus kind of on the ways in which Session Interactive uses AI to do kind of some of the things you guys are known for.
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I know you guys are um you kind of describe yourselves as a data first agency.
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Uh, where is AI kind of most useful in that process, whether it's research, analysis, reporting, strategy, development, things like that?
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Yeah.
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What's AI chat?
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I've never heard of that before.
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I'm joking.
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It's this thing like going around.
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I've heard I've heard you know, people are talking about it outside.
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Gosh, yeah.
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Um yeah, let's start kind of out of the holistic view.
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I think um, you know, it's generative AI has been around for you know three and a half years at this point.
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Maybe it's and AI has been around for a long, much longer time and machine learning and those core components.
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I think um we'll get into specifics in terms of how we consider and how we configure certain things um around AI, but in terms of kind of the research flow and process, it's it's definitely helped expedite um a lot of kind of manual items, especially when going into sales calls and getting up to speed with competitor data and trends and perspective on certain things.
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So it's allowed us to um compile those insights a bit faster.
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I think it's not about just kind of basic prompting, it's about following a pragmatic structure around your um AI instance of choice, or if you remain agnostic as we do across a variety of large language models.
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So basically it's it's identifying, you know, and developing um either a skill file and a project structure around uh a particular need and then scaling it from there and making sure there's a prompt structure.
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I think the big thing that will probably come up a couple of times today, Chad, is just the need for the human review and QA process um before anything is sent over to a client or any particular perspective is generated.
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Yeah, yeah, I can imagine how that would be important.
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Um so when you're when you're breaking down kind of data or something, you know, doing an analytics audit, um, are there ways that AI can help you kind of identify various anomalies or or gaps or patterns that might be more difficult to catch, you know, just with the human eye?
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Yeah, I think to a certain extent.
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I mean, I think that there's a big the biggest thing with us is that we've got you know decades of experience.
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And I think the big thing um is the classic line is like, oh, use AI to summarize the the data and and get insights.
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It's like, yeah, but in order to really come to terms and have a strong position, those there's individuals that well before AI was a thing, they were pulling those reports manually.
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They were able to identify their own trends and patterns and insights and essentially review things and and understand nuance.
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So 100% AI can help compile things and put them in, but it's I think it a really important component for us.
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Again, the theme continues to come up in terms of the human integration, but is making sure you're having people that have been in the trenches that have pulled these reports and understand those details.
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Um, and now they can with AI can expedite certain things and they know where to call issues or where to call out this is this is totally inaccurate kind of thing.
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Um so yes, it does 100% help expedite certain things.
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I think it's it's probably more helpful in our pitch process than it is in an actual foundational deliverable for a client, like a full audit strategy and roadmap.
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We're gonna be using AI, but really it's gonna be all the nuance compiled and certain like mundane, remedial, recurring tasks.
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That's where AI takes takes a hold and does really well.
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Um I know I know you guys use analytics to kind of turn data into actionable insights.
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What role does AI play in that?
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Probably similar to how you've described it already.
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Yeah, you know, it does it does.
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I think um we're a marketing agency, right?
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But I think it's uh we're evolving to and creating workflows and um AI agents specifically that are not only benefiting our role in identifying data and matching data and concatenating data together to support other business units within companies.
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We're noticing improvement opportunities within operations and finance and product, you name it, um, outside of just the core marketing discipline.
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So that's a big thing of just the utilization of AI and how we're um being respectful with it and not incorporating any personal identifiable information and making sure that we're creating closed closed loop systems too, so it's not just opening it up to Claude or ChatGPT uh arbitrarily and exposing the data.
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So yeah, it's it's really um a combination of those strategies to get out uh the output that that we desire.
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I know credit unions are kind of a major client of yours.
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For for you know, clients like that and financial services clients, um, attribution can be complicated because uh a member may research online, but then convert later through a branch or a phone call or application flow or something like that.
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Um can AI help connect those dots, or is that still mainly a challenge that humans would face?
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Yeah, you know, a lot of the credit unions that we work with and have worked with in the past are dealing with, they have third-party application vendors, right?
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So if people are applying for a loan or whatever like that, they're utilizing a third party, and and nine out of 10 times those uh application flows are not tracked correctly.
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And that's not necessarily an AI use case right away.
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We need to use Google Tag Manager and Google Analytics to set those up and make sure it's tracked.
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So someone coming to the site um and then ultimately fills out a form, completes an application via third party, there's some level attribution.
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Now, is that going to be perfect um in terms of all the channels and all the steps that they took in terms of their uh conversion path?
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No.
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And I think the attribution has become a lot more difficult with large language models as people are empowering themselves more and more with research prior to ultimately converting.
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So may convert, they may do all their due diligence via ChatGPT or Claud and then ultimately convert via branded paid search ad or organic or a branded organic um listing.
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So it's making things more difficult for us.
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We are employing like referral traffic from from large language models.
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We are also um and that's usually you know utilizing UTM trackers and building custom reports within Google Analytics.
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I think the reporting evolution is is is interesting.
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We're we're gonna be seeing a lot of changes with people's prioritization around analytics, I think, too, is because we're seeing less and less traffic coming to websites.
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And you know, how is that going to change and evolve?
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And how do what does the modern analytics agency look like?
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Because data and metrics are still essential, but if people aren't going to websites, what else can we track?
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And so that's up to us.
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We're employing some new strategies and getting people thinking about kind of the new structure of AI integration and answer engine optimization and what that may or may not entail.
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Um regarding SEO, I know um session interactive helps content kind of become something that search engines and AI systems can understand and cite.
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Tell me a little bit about what that actually looks like in practice, maybe when you're working on a financial services website or something like that.
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Yeah, an essential component.
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You know, on-page and and uh on-page SEO and content strategy are your core component.
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Uh, you know, really maintaining uh the legacy principles of expert, authoritative, trustworthy contents, and which is a uh the the EAT acronym that um Google really fixated on.
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And you know, we don't we don't um we don't take we we take everything with Google uh that's Google's putting with a grain of salt, but we want to adhere to best practice, so to speak, so to speak, and always be above board and and a white hat SEO shop always.
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Um so I think you know that that is continues to be a practice that we fixate on, and um AI in particular, and how it relates to credit unions again just helps it helps, you know, the the theme too, is you've heard me say it already, is like mundane, remedial, recurring, repetitive tasks, right?
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And time-consuming tasks.
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Those are that's like usually the best use case within our pragmatic flow to get started with a particular skill file or a use case of AI.
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And by and that's a an opportunity right away for on-page and content.
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We're gonna be creating visualizations around okay, how your site is currently set up, and here's the content map to your research is your your prospects research stages, and here are the gaps that we need to fill based on the competition, based on what we know about your ICP, all those details.
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So before it was a ton of spreadsheets and it still is, but it's also now a lot of visualizations that people can see kind of before and after.
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Here's the gaps that we have, and now as we've grown your um we've evolved your content strategy, here are the gaps we're filling and the confidence level that we're filling those core gaps that people are actually going through through the research process, and your your brand is answering those questions.
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So that's a big win.
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So there's uh there's SEO, there's also GEO.
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Um, I think I used that over the weekend.
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I was using Chat GPT to help me find something close to me or something like that.
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How do you kind of measure whether a brand is actually becoming more visible in tools like ChatGPT or Google AI or Google AI or whatever?
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Yeah, I think the common um maybe misconception.
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I mean, we're all we're always succumbing to the shiny thing in the corner.
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We all are, right?
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It's like chat GPT, perplexity, claw.
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It's like, oh my God, there are so many amazing use cases, and we need to we need to be found, we need to be cited on those large language models.
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And yeah, that's an important component that you need to consider, but you also need to realize that Google is is you know 100x more um impactful around their AI engagement within AI overviews versus any type of uh ChatGPT perplexity claude, you name it, grok, you go down the list.
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That uh engagement in traffic is a tiny sliver of a percentage compared to what Google's able to do with AI overviews.
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Um Google recorded you know an increase in in traffic and engagement significantly based on AI overviews, and they they launched those a couple of years ago.
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So there's a different acronym being floated around GEO, AEO, components.
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Um, you know, a lot of those core items within GEO is ensuring that you have a quality foundation, uh foundational understanding and foundational practices around SEO first.
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Again, people are fixating on the shiny things.
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What do we need to do?
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It's like, okay, let's let's take a step back because you haven't established any of the foundational items with SEO.
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Then let's talk about some of those core items that may be more applicable.
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We do have some understanding of of what um those citation factors are, if you will, to get cited, but I'd say, you know, almost 90% of them are things that we've already been doing for clients.
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Uh adding FAQs and schema markup and um short snippets and answer-based content.
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That's that's stuff we've been doing for a long time now.
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So um we've seen instead of fixating specifically just on GEO practices to stick to um foundational components and evolve when the time is right and when the budget and um bandwidth constraints are lifted in certain cases as well.
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When you uh for content marketing, I know you guys um like to map content to each stage of the audience's research process.
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How are you using AI to uh uncover content gaps and identify user questions and things like that?
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Yeah, it's helpful to kind of expedite directional data, um, at least initially.
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I mean, think about within it within a pitch process.
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It's like we're we're utilizing it quite a bit to get the conversation going and making sure that um individuals are aware, like, hey, here, this is um, you know, we are we haven't conducted a complete process yet, but this is kind of a lot of ideas that we're compiling.
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And a lot of these um model context protocols, MCPs that are hooked up to third-party tools, can directly integrate with AI tools like a like Claude in particular, and can compile data a bit faster, um, which is super helpful and and allows us to get things honestly allows us to be a lot more thorough um within our pitches and our full audits and strategies than we were ever before because of the time saving and and certain things where we can compile data faster and we can use use the time uh for our team a lot why you know in more of a uh more wisely, if you will, because we're allowing them to spend less time compiling data and more time analyzing it and uh strategizing on fun ideas and cool concepts to get get clients excited and and certain things and to exhaust the possibilities.
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So um we'll talk about kind of the the foundational breakdowns, I'm sure, in terms of how we configure certain things, how we build process, especially within Cloud, uh, and take advantage of those.
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Um you kind of mentioned that AI can can produce content for you.
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Uh you know, you can write a 3,000-word blog or research paper in 10 minutes.
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How do you guys kind of keep that from becoming generic, um, especially for industries like credit unions, um, you know, where it's important to have trust between them and their clients?
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Yeah, Chad, great question.
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And actually, you know, shout out to the um the Digital Summit.
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It's a conference series, and I spoke at um this year and I spoke last year.
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And last year my talk was just around this.
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It's like with the advent of generation generative AI, everyone thinks they're a copywriter, a junior copywriter, a senior copywriter, they think they're God's gift to content.
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And it's it's really what it's producing is this spectrum, right?
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Where you have before generative AI, you had like terrible content, you had mediocre content, then you had superior content.
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And now with generative AI, it's the lion's shares around this mediocre or good content, if you will, was still a very small percentage of superior content.
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Now, the the terrible content should be not even a thing anymore because there's foundational practices and certain things like that.
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Now, am I advocating to use AI to generate content?
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No, I'm not.
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And um, we've tested it extensively, and people will argue with me on this 100%.
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You know, oh, we've created skill files and we're product requirement documents and persona files within Claude, and we're getting our voice and tone and everything dialed in.
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But the truth of the matter is that what individuals and people gravitate towards is statistical content, they human elements and nuance that um these LLMs are getting better at for sure, but the people want and in to engage with uh other humans for the most part.
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And I think there's gonna be this resurgence of authenticity, and we're not there's this always concept around AI slop, and that's people are like, oh, I'll just program do programmatic SEO and I'll generate a hundred pages of content in two days and I'll publish that.
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And it's like we couldn't recommend against that enough.
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Um, yes, there's templates and structure, but the human element and the voice and tone and the nuance that needs to be employed and and um maintain as much as possible.
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Um on your uh when it comes to paid searches, I know that um session interactive doesn't really simply rely on automated strategies.
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Uh you guys prefer more of a manual um review and campaign optimization in an AI kind of AI driven advertising environment, where do you draw the line between automation and human judgment?
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Yeah, it's a great, it's that's a great question.
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And I think um I always say this to our team.
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It's like quality is all we have, right?
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And and and then you could keep going down the list of of these other types of quotes like reputation is all we have and all this stuff.
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And it's um to me, it's we're not gonna be delivering a work product if we are not fully confident in it.
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Um, we're not going to be spinning something up very quickly, utilizing an AI platform and sending it out.
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We need to be, we need our reputation's at la uh at stake every time we send something over to a client.
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So um there are tasks and certain things that we are transparent with our clients around hey, this is definitely an automation task.
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This is something that's low level.
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Um, we're gonna we're gonna create a workflow around this within you know workflow tools integrated with AI, large language models, and other tools to get this insight.
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And we're very transparent with that.
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However, for more nuanced certain things, uh data gathering will use AI for, but ultimately disseminating that output and insights, we're gonna be really fixated on humans for the foreseeable future.
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What about using AI for like keyword expansion, competitor research, ad copy, um, ad copy testing, things like that?
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Yeah, for paid search, you know, those are pretty good use cases.
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I think ad copy for sure, um, and adding nuance and certain things.
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Again, taking, I think people are like, oh, just use AI for that.
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It's like open up Cloud and figure it out.
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It's like, yeah, you can figure it out, but you also need a pragmatic structure to that project folder to ensure that it follows rules and guidelines and adheres to those components.
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So um ad copy, um, you know, landing page reviews, CRO related initial CRO insights, 100%.
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What we found really be impactful, um, Jake, who who runs paid search in particular, um, who runs that department, is building out a ton of scripts, right?
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So things that um, especially for complicated, nuanced accounts, budget goes here or here.
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If keywords are decreasing, there's some a bit of automations that we can configure.
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Um, are we uh, you know, we're talking with other agencies, they're running a lot of their clients through Cloud and managing AdWords through Cloud.
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And all for that, you know, with respect for them, but you know, our again, our reputation's on the line, and we we're dealing with with large clients that have very uh lucrative budgets, and we want to make sure that um there's a human element and where there's no automations and um that that could essentially overspend or underspend or um just just blatantly uh go make things go awry, which is which is worrisome.
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When it comes to page social, that depends heavily on audience segmentation and creative messaging.
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Um, how has AI affected the way your team approaches you know things like audience research and message testing, creative variation, things like that?
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Yeah, a ton.
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We we're using a variety of third-party tools that help us aggregate audience insights.
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I mean, I think um and import directly into AdWords, import directly into Meta or LinkedIn specifically, and work with those platforms.
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Um we're also taking a look, of course, at clients' uh own persona data and evolving that data through ad content and data and uh analytics and data, web analytics specifically, and then piping those into various third-party tools that help aggregate and and um improve persona uh and just alignment across our uh paid and organic channels is a really core concept.
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That said, you know, Meta has really pushed AI a lot within Business Manager and pros and cons.
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And the same thing with Performance Max within AdWords, pros and cons there.
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We've we've dealt with we've audited numerous accounts over the years that are entirely almost run by the AI platform and the agent built within these platforms and notice uh wild inefficiencies and just overspend and just um blatant inaccuracies.
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So it's up to us.
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We we want to utilize those tools, but in certain cases sparingly because of just the um the wild assumptions and hallucinations that can still happen.
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Um when it comes to CRO, I know you got you guys do a lot of audits, A-B testing, heat mapping, uh, landing page optimization, user research, things like that.
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Um, how is how can AI help kind of prioritize which tests are most likely to improve conversions?
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Yeah, I mean, I think it's it's expedited things a lot.
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And I think uh in particular around we always had Google Analytics, and Google Analytics is helpful, but it's not nearly as helpful unless you lay around Google Tag Manager and start tracking things like buttons and clicks and hover tracking and scroll tracking, et cetera.
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Then you add in heat mapping data and crawl crawled um scroll tracking and other data via heat mapping tools like a Crazy Egg or Hotjar or Lucky Orange or Microsoft Clarity and that continues to tell like the piece of the pie.
00:22:06.400 --> 00:22:08.240
I was literally just talking with a client about this.
00:22:08.400 --> 00:22:20.960
And then if you have qualitative insights or survey data from your prospects or your internal team, that that continues to give us some um quality output.
00:22:21.119 --> 00:22:32.160
And what we do with that is we take it and pipe it into our project file system within Claude and have dedicated CRO experts as created markdown files, those CRO personas.
00:22:32.480 --> 00:22:38.559
And we have a whole process that has been trained up on our on our legacy and current CRO program.
00:22:38.720 --> 00:22:48.559
And then what it does is it allows us to expedite uh hypotheses and different testing um opportunities a bit faster for sure.
00:22:48.880 --> 00:23:01.279
And then wireframe creation within Cloud Design and Google's uh platform um stitch and others have been super helpful just to get some ideas out.
00:23:01.519 --> 00:23:18.880
And then what we're doing, we're still working uh a ton with Infigma to create those manual designs, but a lot of the ideation is coming through initial conversations, expanded data, and then utilization of um some of these um UXUI AI related tools.
00:23:19.279 --> 00:23:20.400
Final question for you.
00:23:20.559 --> 00:23:24.960
This one kind of has to do with um like customer behustomer behavior.
00:23:25.279 --> 00:23:35.839
Um, you know, over the weekend I I actually used AI to find a local restaurant in Columbus, Ohio that my nephew could use a gift card that I would buy him and he could take his fiancee to.
00:23:36.000 --> 00:23:38.240
Something like that, you know, like a non-chain joint type thing.
00:23:38.720 --> 00:23:43.519
Um so local listings are are important for uh branch-based organizations like credit unions.
00:23:43.680 --> 00:23:46.079
How do you see AI changing local search behavior?
00:23:46.160 --> 00:23:50.000
Um, you know, like how someone asks for like the best credit union near me or something like that.
00:23:50.319 --> 00:23:53.519
Yeah, you know, it's it's it's evolving things a lot.
00:23:53.599 --> 00:24:13.039
I mean, I think with uh local SEO, you you've got a lot of core tools like White Spark and uh Bright Local and Moz Local, and there's a there's a the X stuff's obviously this is still a big a big player with citation creation, distribution, and management.
00:24:13.359 --> 00:24:21.039
And um AI is is helpful to create templates and structures for content production.
00:24:21.279 --> 00:24:30.319
Now, of course, having um having content a copywriter reviewing and and prioritizing the voice and theme across those is really helpful.
00:24:30.400 --> 00:24:38.480
But you if you're dealing with some of our clients that have hundreds of locations, it's important you you need something, a solution at scale.
00:24:38.640 --> 00:24:41.599
Um, so that's that's helping to a certain extent.
00:24:41.839 --> 00:24:46.880
I think uh some of the insights and data gathering is is a bit more impactful.
00:24:47.119 --> 00:24:50.960
It's still very simplistic, if you will, local SEO.
00:24:51.119 --> 00:25:07.839
I'm not, I don't want to diminish it, but in terms of the uh local listing platforms and ensuring they're optimized, name, address, phone number, consistency, responding to reviews, encouraging reviews, of course, and then ensure you have a correct presence across the core citations, and there's a ton of them.
00:25:08.079 --> 00:25:19.440
And then, of course, what's represented on your website, a cat location category page, individual product or location pages, and how nuanced and how human are those pages is a really important concept.
00:25:19.599 --> 00:25:21.920
So those are influential factors.
00:25:22.079 --> 00:25:32.799
Um, just to name a few, not all of them by any means, but that will continue to be beneficial for local SEO, for credit unions, and any brick and mortar um business that has multiple locations.
00:25:33.119 --> 00:25:33.440
Okay.
00:25:33.759 --> 00:25:35.119
Hey, uh good stuff, Tyler.
00:25:35.279 --> 00:25:36.079
Always great to talk to you.
00:25:36.160 --> 00:25:37.119
Thanks so much for having me today.
00:25:37.279 --> 00:25:37.759
Thanks, Chad.
00:25:37.839 --> 00:25:38.319
I appreciate you.
00:25:38.559 --> 00:25:40.000
So long, everybody.
00:25:43.440 --> 00:25:45.759
Thanks for listening to Built to Convert.
00:25:46.160 --> 00:25:48.799
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00:25:48.960 --> 00:25:54.400
Subscribe, leave a review, and follow us for new episodes that drop straight into your feet.
00:25:54.559 --> 00:25:57.119
Until next time, keep building.
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You're listening to Built to Convert, the podcast where growth-minded marketers, founders, and creators come to level up.
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No hype, no guesswork, just bold insights that drive results.
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Let's go.
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Hey everyone, I'm Tyler Lane, founder of Session Interactive and the host of Built to Convert, where I talk with growth-minded leaders in healthcare, tech, e-commerce, and finance.
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We dig into how data, marketing, and strategy come together to help organizations make smarter decisions and scale with purpose in today's digital world.
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This episode is brought to you by Session Interactive, a digital marketing agency that helps businesses turn complex data into clear strategy from SEO and analytics to paid media and content.
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Session zeroes in on what truly drives growth, smarter decisions and better user experiences.
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Known for their collaborative approach and measurable results, they partner with forward-thinking companies across industries to solve digital challenges and turn them into opportunities.
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All right, a little bit different today, but I've got Chad here from Rise25.
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Chad's done thousands of interviews with successful entrepreneurs and CEOs, and we have flipped the script today, and he will be interviewing me.
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Chad, great to see you.
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Welcome to the show.
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Hey, great to talk to you again, Tyler.
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Um hey, I was thinking today we would focus kind of on the ways in which Session Interactive uses AI to do kind of some of the things you guys are known for.
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I know you guys are um you kind of describe yourselves as a data first agency.
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Uh, where is AI kind of most useful in that process, whether it's research, analysis, reporting, strategy, development, things like that?
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Yeah.
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What's AI chat?
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I've never heard of that before.
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I'm joking.
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It's this thing like going around.
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I've heard I've heard you know, people are talking about it outside.
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Gosh, yeah.
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Um yeah, let's start kind of out of the holistic view.
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I think um, you know, it's generative AI has been around for you know three and a half years at this point.
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Maybe it's and AI has been around for a long, much longer time and machine learning and those core components.
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I think um we'll get into specifics in terms of how we consider and how we configure certain things um around AI, but in terms of kind of the research flow and process, it's it's definitely helped expedite um a lot of kind of manual items, especially when going into sales calls and getting up to speed with competitor data and trends and perspective on certain things.
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So it's allowed us to um compile those insights a bit faster.
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I think it's not about just kind of basic prompting, it's about following a pragmatic structure around your um AI instance of choice, or if you remain agnostic as we do across a variety of large language models.
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So basically it's it's identifying, you know, and developing um either a skill file and a project structure around uh a particular need and then scaling it from there and making sure there's a prompt structure.
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I think the big thing that will probably come up a couple of times today, Chad, is just the need for the human review and QA process um before anything is sent over to a client or any particular perspective is generated.
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Yeah, yeah, I can imagine how that would be important.
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Um so when you're when you're breaking down kind of data or something, you know, doing an analytics audit, um, are there ways that AI can help you kind of identify various anomalies or or gaps or patterns that might be more difficult to catch, you know, just with the human eye?
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Yeah, I think to a certain extent.
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I mean, I think that there's a big the biggest thing with us is that we've got you know decades of experience.
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And I think the big thing um is the classic line is like, oh, use AI to summarize the the data and and get insights.
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It's like, yeah, but in order to really come to terms and have a strong position, those there's individuals that well before AI was a thing, they were pulling those reports manually.
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They were able to identify their own trends and patterns and insights and essentially review things and and understand nuance.
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So 100% AI can help compile things and put them in, but it's I think it a really important component for us.
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Again, the theme continues to come up in terms of the human integration, but is making sure you're having people that have been in the trenches that have pulled these reports and understand those details.
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Um, and now they can with AI can expedite certain things and they know where to call issues or where to call out this is this is totally inaccurate kind of thing.
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Um so yes, it does 100% help expedite certain things.
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I think it's it's probably more helpful in our pitch process than it is in an actual foundational deliverable for a client, like a full audit strategy and roadmap.
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We're gonna be using AI, but really it's gonna be all the nuance compiled and certain like mundane, remedial, recurring tasks.
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That's where AI takes takes a hold and does really well.
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Um I know I know you guys use analytics to kind of turn data into actionable insights.
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What role does AI play in that?
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Probably similar to how you've described it already.
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Yeah, you know, it does it does.
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I think um we're a marketing agency, right?
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But I think it's uh we're evolving to and creating workflows and um AI agents specifically that are not only benefiting our role in identifying data and matching data and concatenating data together to support other business units within companies.
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We're noticing improvement opportunities within operations and finance and product, you name it, um, outside of just the core marketing discipline.
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So that's a big thing of just the utilization of AI and how we're um being respectful with it and not incorporating any personal identifiable information and making sure that we're creating closed closed loop systems too, so it's not just opening it up to Claude or ChatGPT uh arbitrarily and exposing the data.
00:06:01.360 --> 00:06:08.480
So yeah, it's it's really um a combination of those strategies to get out uh the output that that we desire.
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I know credit unions are kind of a major client of yours.
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For for you know, clients like that and financial services clients, um, attribution can be complicated because uh a member may research online, but then convert later through a branch or a phone call or application flow or something like that.
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Um can AI help connect those dots, or is that still mainly a challenge that humans would face?
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Yeah, you know, a lot of the credit unions that we work with and have worked with in the past are dealing with, they have third-party application vendors, right?
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So if people are applying for a loan or whatever like that, they're utilizing a third party, and and nine out of 10 times those uh application flows are not tracked correctly.
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And that's not necessarily an AI use case right away.
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We need to use Google Tag Manager and Google Analytics to set those up and make sure it's tracked.
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So someone coming to the site um and then ultimately fills out a form, completes an application via third party, there's some level attribution.
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Now, is that going to be perfect um in terms of all the channels and all the steps that they took in terms of their uh conversion path?
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No.
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And I think the attribution has become a lot more difficult with large language models as people are empowering themselves more and more with research prior to ultimately converting.
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So may convert, they may do all their due diligence via ChatGPT or Claud and then ultimately convert via branded paid search ad or organic or a branded organic um listing.
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So it's making things more difficult for us.
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We are employing like referral traffic from from large language models.
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We are also um and that's usually you know utilizing UTM trackers and building custom reports within Google Analytics.
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I think the reporting evolution is is is interesting.
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We're we're gonna be seeing a lot of changes with people's prioritization around analytics, I think, too, is because we're seeing less and less traffic coming to websites.
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And you know, how is that going to change and evolve?
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And how do what does the modern analytics agency look like?
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Because data and metrics are still essential, but if people aren't going to websites, what else can we track?
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And so that's up to us.
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We're employing some new strategies and getting people thinking about kind of the new structure of AI integration and answer engine optimization and what that may or may not entail.
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Um regarding SEO, I know um session interactive helps content kind of become something that search engines and AI systems can understand and cite.
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Tell me a little bit about what that actually looks like in practice, maybe when you're working on a financial services website or something like that.
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Yeah, an essential component.
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You know, on-page and and uh on-page SEO and content strategy are your core component.
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Uh, you know, really maintaining uh the legacy principles of expert, authoritative, trustworthy contents, and which is a uh the the EAT acronym that um Google really fixated on.
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And you know, we don't we don't um we don't take we we take everything with Google uh that's Google's putting with a grain of salt, but we want to adhere to best practice, so to speak, so to speak, and always be above board and and a white hat SEO shop always.
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Um so I think you know that that is continues to be a practice that we fixate on, and um AI in particular, and how it relates to credit unions again just helps it helps, you know, the the theme too, is you've heard me say it already, is like mundane, remedial, recurring, repetitive tasks, right?
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And time-consuming tasks.
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Those are that's like usually the best use case within our pragmatic flow to get started with a particular skill file or a use case of AI.
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And by and that's a an opportunity right away for on-page and content.
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We're gonna be creating visualizations around okay, how your site is currently set up, and here's the content map to your research is your your prospects research stages, and here are the gaps that we need to fill based on the competition, based on what we know about your ICP, all those details.
00:10:01.600 --> 00:10:09.440
So before it was a ton of spreadsheets and it still is, but it's also now a lot of visualizations that people can see kind of before and after.
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Here's the gaps that we have, and now as we've grown your um we've evolved your content strategy, here are the gaps we're filling and the confidence level that we're filling those core gaps that people are actually going through through the research process, and your your brand is answering those questions.
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So that's a big win.
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So there's uh there's SEO, there's also GEO.
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Um, I think I used that over the weekend.
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I was using Chat GPT to help me find something close to me or something like that.
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How do you kind of measure whether a brand is actually becoming more visible in tools like ChatGPT or Google AI or Google AI or whatever?
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Yeah, I think the common um maybe misconception.
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I mean, we're all we're always succumbing to the shiny thing in the corner.
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We all are, right?
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It's like chat GPT, perplexity, claw.
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It's like, oh my God, there are so many amazing use cases, and we need to we need to be found, we need to be cited on those large language models.
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And yeah, that's an important component that you need to consider, but you also need to realize that Google is is you know 100x more um impactful around their AI engagement within AI overviews versus any type of uh ChatGPT perplexity claude, you name it, grok, you go down the list.
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That uh engagement in traffic is a tiny sliver of a percentage compared to what Google's able to do with AI overviews.
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Um Google recorded you know an increase in in traffic and engagement significantly based on AI overviews, and they they launched those a couple of years ago.
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So there's a different acronym being floated around GEO, AEO, components.
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Um, you know, a lot of those core items within GEO is ensuring that you have a quality foundation, uh foundational understanding and foundational practices around SEO first.
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Again, people are fixating on the shiny things.
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What do we need to do?
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It's like, okay, let's let's take a step back because you haven't established any of the foundational items with SEO.
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Then let's talk about some of those core items that may be more applicable.
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We do have some understanding of of what um those citation factors are, if you will, to get cited, but I'd say, you know, almost 90% of them are things that we've already been doing for clients.
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Uh adding FAQs and schema markup and um short snippets and answer-based content.
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That's that's stuff we've been doing for a long time now.
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So um we've seen instead of fixating specifically just on GEO practices to stick to um foundational components and evolve when the time is right and when the budget and um bandwidth constraints are lifted in certain cases as well.
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When you uh for content marketing, I know you guys um like to map content to each stage of the audience's research process.
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How are you using AI to uh uncover content gaps and identify user questions and things like that?
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Yeah, it's helpful to kind of expedite directional data, um, at least initially.
00:13:04.159 --> 00:13:06.559
I mean, think about within it within a pitch process.
00:13:06.639 --> 00:13:20.720
It's like we're we're utilizing it quite a bit to get the conversation going and making sure that um individuals are aware, like, hey, here, this is um, you know, we are we haven't conducted a complete process yet, but this is kind of a lot of ideas that we're compiling.
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And a lot of these um model context protocols, MCPs that are hooked up to third-party tools, can directly integrate with AI tools like a like Claude in particular, and can compile data a bit faster, um, which is super helpful and and allows us to get things honestly allows us to be a lot more thorough um within our pitches and our full audits and strategies than we were ever before because of the time saving and and certain things where we can compile data faster and we can use use the time uh for our team a lot why you know in more of a uh more wisely, if you will, because we're allowing them to spend less time compiling data and more time analyzing it and uh strategizing on fun ideas and cool concepts to get get clients excited and and certain things and to exhaust the possibilities.
00:14:13.519 --> 00:14:23.840
So um we'll talk about kind of the the foundational breakdowns, I'm sure, in terms of how we configure certain things, how we build process, especially within Cloud, uh, and take advantage of those.
00:14:24.399 --> 00:14:28.240
Um you kind of mentioned that AI can can produce content for you.
00:14:28.320 --> 00:14:33.279
Uh you know, you can write a 3,000-word blog or research paper in 10 minutes.
00:14:33.519 --> 00:14:43.360
How do you guys kind of keep that from becoming generic, um, especially for industries like credit unions, um, you know, where it's important to have trust between them and their clients?
00:14:43.600 --> 00:14:44.960
Yeah, Chad, great question.
00:14:45.120 --> 00:14:48.320
And actually, you know, shout out to the um the Digital Summit.
00:14:48.480 --> 00:14:52.159
It's a conference series, and I spoke at um this year and I spoke last year.
00:14:52.240 --> 00:14:54.320
And last year my talk was just around this.
00:14:54.480 --> 00:15:03.440
It's like with the advent of generation generative AI, everyone thinks they're a copywriter, a junior copywriter, a senior copywriter, they think they're God's gift to content.
00:15:03.679 --> 00:15:07.440
And it's it's really what it's producing is this spectrum, right?
00:15:07.519 --> 00:15:13.759
Where you have before generative AI, you had like terrible content, you had mediocre content, then you had superior content.
00:15:14.000 --> 00:15:24.159
And now with generative AI, it's the lion's shares around this mediocre or good content, if you will, was still a very small percentage of superior content.
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Now, the the terrible content should be not even a thing anymore because there's foundational practices and certain things like that.
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Now, am I advocating to use AI to generate content?
00:15:34.159 --> 00:15:35.279
No, I'm not.
00:15:35.519 --> 00:15:41.120
And um, we've tested it extensively, and people will argue with me on this 100%.
00:15:41.440 --> 00:15:50.159
You know, oh, we've created skill files and we're product requirement documents and persona files within Claude, and we're getting our voice and tone and everything dialed in.
00:15:50.320 --> 00:16:09.279
But the truth of the matter is that what individuals and people gravitate towards is statistical content, they human elements and nuance that um these LLMs are getting better at for sure, but the people want and in to engage with uh other humans for the most part.
00:16:09.360 --> 00:16:22.720
And I think there's gonna be this resurgence of authenticity, and we're not there's this always concept around AI slop, and that's people are like, oh, I'll just program do programmatic SEO and I'll generate a hundred pages of content in two days and I'll publish that.
00:16:22.879 --> 00:16:25.840
And it's like we couldn't recommend against that enough.
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Um, yes, there's templates and structure, but the human element and the voice and tone and the nuance that needs to be employed and and um maintain as much as possible.
00:16:38.320 --> 00:16:47.600
Um on your uh when it comes to paid searches, I know that um session interactive doesn't really simply rely on automated strategies.
00:16:47.679 --> 00:16:58.799
Uh you guys prefer more of a manual um review and campaign optimization in an AI kind of AI driven advertising environment, where do you draw the line between automation and human judgment?
00:16:59.200 --> 00:17:01.600
Yeah, it's a great, it's that's a great question.
00:17:01.759 --> 00:17:04.960
And I think um I always say this to our team.
00:17:05.119 --> 00:17:07.200
It's like quality is all we have, right?
00:17:07.359 --> 00:17:12.799
And and and then you could keep going down the list of of these other types of quotes like reputation is all we have and all this stuff.
00:17:12.960 --> 00:17:20.480
And it's um to me, it's we're not gonna be delivering a work product if we are not fully confident in it.
00:17:20.559 --> 00:17:26.480
Um, we're not going to be spinning something up very quickly, utilizing an AI platform and sending it out.
00:17:26.640 --> 00:17:31.839
We need to be, we need our reputation's at la uh at stake every time we send something over to a client.
00:17:32.079 --> 00:17:40.000
So um there are tasks and certain things that we are transparent with our clients around hey, this is definitely an automation task.
00:17:40.160 --> 00:17:41.759
This is something that's low level.
00:17:41.920 --> 00:17:51.119
Um, we're gonna we're gonna create a workflow around this within you know workflow tools integrated with AI, large language models, and other tools to get this insight.
00:17:51.200 --> 00:17:52.480
And we're very transparent with that.
00:17:52.640 --> 00:18:05.119
However, for more nuanced certain things, uh data gathering will use AI for, but ultimately disseminating that output and insights, we're gonna be really fixated on humans for the foreseeable future.
00:18:05.440 --> 00:18:12.319
What about using AI for like keyword expansion, competitor research, ad copy, um, ad copy testing, things like that?
00:18:12.559 --> 00:18:16.000
Yeah, for paid search, you know, those are pretty good use cases.
00:18:16.079 --> 00:18:20.960
I think ad copy for sure, um, and adding nuance and certain things.
00:18:21.119 --> 00:18:24.319
Again, taking, I think people are like, oh, just use AI for that.
00:18:24.400 --> 00:18:25.920
It's like open up Cloud and figure it out.
00:18:26.000 --> 00:18:37.039
It's like, yeah, you can figure it out, but you also need a pragmatic structure to that project folder to ensure that it follows rules and guidelines and adheres to those components.
00:18:37.200 --> 00:18:43.920
So um ad copy, um, you know, landing page reviews, CRO related initial CRO insights, 100%.
00:18:44.319 --> 00:18:53.519
What we found really be impactful, um, Jake, who who runs paid search in particular, um, who runs that department, is building out a ton of scripts, right?
00:18:53.680 --> 00:18:59.119
So things that um, especially for complicated, nuanced accounts, budget goes here or here.
00:18:59.200 --> 00:19:04.079
If keywords are decreasing, there's some a bit of automations that we can configure.
00:19:04.240 --> 00:19:11.759
Um, are we uh, you know, we're talking with other agencies, they're running a lot of their clients through Cloud and managing AdWords through Cloud.
00:19:11.920 --> 00:19:38.160
And all for that, you know, with respect for them, but you know, our again, our reputation's on the line, and we we're dealing with with large clients that have very uh lucrative budgets, and we want to make sure that um there's a human element and where there's no automations and um that that could essentially overspend or underspend or um just just blatantly uh go make things go awry, which is which is worrisome.
00:19:38.640 --> 00:19:43.839
When it comes to page social, that depends heavily on audience segmentation and creative messaging.
00:19:44.000 --> 00:19:52.079
Um, how has AI affected the way your team approaches you know things like audience research and message testing, creative variation, things like that?
00:19:52.319 --> 00:19:53.039
Yeah, a ton.
00:19:53.200 --> 00:19:58.079
We we're using a variety of third-party tools that help us aggregate audience insights.
00:19:58.160 --> 00:20:06.799
I mean, I think um and import directly into AdWords, import directly into Meta or LinkedIn specifically, and work with those platforms.
00:20:07.039 --> 00:20:36.160
Um we're also taking a look, of course, at clients' uh own persona data and evolving that data through ad content and data and uh analytics and data, web analytics specifically, and then piping those into various third-party tools that help aggregate and and um improve persona uh and just alignment across our uh paid and organic channels is a really core concept.
00:20:36.480 --> 00:20:45.599
That said, you know, Meta has really pushed AI a lot within Business Manager and pros and cons.
00:20:45.680 --> 00:20:50.559
And the same thing with Performance Max within AdWords, pros and cons there.
00:20:50.640 --> 00:21:07.759
We've we've dealt with we've audited numerous accounts over the years that are entirely almost run by the AI platform and the agent built within these platforms and notice uh wild inefficiencies and just overspend and just um blatant inaccuracies.
00:21:07.920 --> 00:21:09.119
So it's up to us.
00:21:09.200 --> 00:21:18.480
We we want to utilize those tools, but in certain cases sparingly because of just the um the wild assumptions and hallucinations that can still happen.
00:21:19.359 --> 00:21:28.480
Um when it comes to CRO, I know you got you guys do a lot of audits, A-B testing, heat mapping, uh, landing page optimization, user research, things like that.
00:21:28.640 --> 00:21:34.880
Um, how is how can AI help kind of prioritize which tests are most likely to improve conversions?
00:21:35.279 --> 00:21:38.000
Yeah, I mean, I think it's it's expedited things a lot.
00:21:38.079 --> 00:21:52.960
And I think uh in particular around we always had Google Analytics, and Google Analytics is helpful, but it's not nearly as helpful unless you lay around Google Tag Manager and start tracking things like buttons and clicks and hover tracking and scroll tracking, et cetera.
00:21:53.039 --> 00:22:06.240
Then you add in heat mapping data and crawl crawled um scroll tracking and other data via heat mapping tools like a Crazy Egg or Hotjar or Lucky Orange or Microsoft Clarity and that continues to tell like the piece of the pie.
00:22:06.400 --> 00:22:08.240
I was literally just talking with a client about this.
00:22:08.400 --> 00:22:20.960
And then if you have qualitative insights or survey data from your prospects or your internal team, that that continues to give us some um quality output.
00:22:21.119 --> 00:22:32.160
And what we do with that is we take it and pipe it into our project file system within Claude and have dedicated CRO experts as created markdown files, those CRO personas.
00:22:32.480 --> 00:22:38.559
And we have a whole process that has been trained up on our on our legacy and current CRO program.
00:22:38.720 --> 00:22:48.559
And then what it does is it allows us to expedite uh hypotheses and different testing um opportunities a bit faster for sure.
00:22:48.880 --> 00:23:01.279
And then wireframe creation within Cloud Design and Google's uh platform um stitch and others have been super helpful just to get some ideas out.
00:23:01.519 --> 00:23:18.880
And then what we're doing, we're still working uh a ton with Infigma to create those manual designs, but a lot of the ideation is coming through initial conversations, expanded data, and then utilization of um some of these um UXUI AI related tools.
00:23:19.279 --> 00:23:20.400
Final question for you.
00:23:20.559 --> 00:23:24.960
This one kind of has to do with um like customer behustomer behavior.
00:23:25.279 --> 00:23:35.839
Um, you know, over the weekend I I actually used AI to find a local restaurant in Columbus, Ohio that my nephew could use a gift card that I would buy him and he could take his fiancee to.
00:23:36.000 --> 00:23:38.240
Something like that, you know, like a non-chain joint type thing.
00:23:38.720 --> 00:23:43.519
Um so local listings are are important for uh branch-based organizations like credit unions.
00:23:43.680 --> 00:23:46.079
How do you see AI changing local search behavior?
00:23:46.160 --> 00:23:50.000
Um, you know, like how someone asks for like the best credit union near me or something like that.
00:23:50.319 --> 00:23:53.519
Yeah, you know, it's it's it's evolving things a lot.
00:23:53.599 --> 00:24:13.039
I mean, I think with uh local SEO, you you've got a lot of core tools like White Spark and uh Bright Local and Moz Local, and there's a there's a the X stuff's obviously this is still a big a big player with citation creation, distribution, and management.
00:24:13.359 --> 00:24:21.039
And um AI is is helpful to create templates and structures for content production.
00:24:21.279 --> 00:24:30.319
Now, of course, having um having content a copywriter reviewing and and prioritizing the voice and theme across those is really helpful.
00:24:30.400 --> 00:24:38.480
But you if you're dealing with some of our clients that have hundreds of locations, it's important you you need something, a solution at scale.
00:24:38.640 --> 00:24:41.599
Um, so that's that's helping to a certain extent.
00:24:41.839 --> 00:24:46.880
I think uh some of the insights and data gathering is is a bit more impactful.
00:24:47.119 --> 00:24:50.960
It's still very simplistic, if you will, local SEO.
00:24:51.119 --> 00:25:07.839
I'm not, I don't want to diminish it, but in terms of the uh local listing platforms and ensuring they're optimized, name, address, phone number, consistency, responding to reviews, encouraging reviews, of course, and then ensure you have a correct presence across the core citations, and there's a ton of them.
00:25:08.079 --> 00:25:19.440
And then, of course, what's represented on your website, a cat location category page, individual product or location pages, and how nuanced and how human are those pages is a really important concept.
00:25:19.599 --> 00:25:21.920
So those are influential factors.
00:25:22.079 --> 00:25:32.799
Um, just to name a few, not all of them by any means, but that will continue to be beneficial for local SEO, for credit unions, and any brick and mortar um business that has multiple locations.
00:25:33.119 --> 00:25:33.440
Okay.
00:25:33.759 --> 00:25:35.119
Hey, uh good stuff, Tyler.
00:25:35.279 --> 00:25:36.079
Always great to talk to you.
00:25:36.160 --> 00:25:37.119
Thanks so much for having me today.
00:25:37.279 --> 00:25:37.759
Thanks, Chad.
00:25:37.839 --> 00:25:38.319
I appreciate you.
00:25:38.559 --> 00:25:40.000
So long, everybody.
00:25:43.440 --> 00:25:45.759
Thanks for listening to Built to Convert.
00:25:46.160 --> 00:25:48.799
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