So What? How to Use Generative AI to Audit Content Marketing

Well, hey there everyone. Welcome to So What, the Marketing Analytics and Insights Live Show. I am Katie joined by Chris and John. How's it going, guys? Hello.

Oh, you're gonna try to do a repeat of last week. Yeah, yes, I'm gonna get the virtual five. Yeah, nope, Chris left you hanging. That's the way normally the way high five works with us. It's always just like Um This Week we are talking about how to use generative AI uh to audit content marketing.

Um so this came up because last week in our Trust Insights newsletter, um if you're not subscribed, you can subscribe at TrustInsights.ai slash newsletter. Chris did an experiment where he was going through um, I think it was the content on your data diaries and sort of to audit it, see sort of what it came up with in terms of categories, where there were gaps. And I said to you, duh, of course, now I want this for everything on our website. And so we said, great, that's what we're gonna do for the live stream next week. And so what we're gonna do is show you how to use generative AI to audit your content marketing, how to build prompts to process and categorize that content, um, and how to build a plan with generative AI for the next phase of your content marketing.

So, Chris, since this was something that you came up with, um, where would you like to start? Um, I'm gonna st I'm gonna start by saying a good chunk of this you can't do with generative AI. Surprise. You know what? I actually I like that because and the reason I say I like that is because as nice and as expedient as generative AI is making a lot of things, it's not the right solution for everything.

There are things that you still have to do other things. And you know, I'm guessing that perhaps that might start with something like going through the five Ps to figure out what it is you're trying to do to see if generative AI is the right platform or if there's something else. Exactly right. So, Katie, I'm gonna push that right back to you. With purpose, what are we doing?

Why are we doing this? Why am I here? Well, um, if you would like the existential answer, then I think that we should do that on another show. But for the purpose for today is um what I wanna know is so let me back up a little bit. When we started Trust Insights about six years ago, surprisingly, we did not have a strategy or a plan for everything.

Um a lot of it was just kind of winging it, getting stuff set up. And I feel like a lot of teams and a lot of companies find themselves in that position is let's just start doing something and we'll figure it out as we go. And we were very much uh the same. Now, six years in, we have hundreds, if not thousands of pieces of content that are sort of categorized on our in our WordPress site using tags, but the nature of what we do and the nature of how we talk about things has evolved, but those tags, that categorization system hasn't. And so what I wanna be able to do is take a look at our content as a whole and figure out what pieces belong in what buckets.

And some pieces aren't tagged correctly either. And so I want to see what are the different categories of content that we have, recategorize them on the back end so it's cleaner user experience for the user, and then find out what the gaps are or where we need stronger content for different areas. So that's a very large user story. But as the CEO, I want to understand what content we have, what the gaps are, so that I can create or amend the existing content. Got it.

Okay, that's helpful. So to do that, we have to get the data, we have to get the content, we have to sort of understand what content is even worth looking at, and then use uh the various tools to extract that. So here's the challenge for the average person who's interested in doing this kind of content audit, you gotta get the content. Um for us, uh our our website is hosted by uh it's uh hosted on WordPress, right? So that theoretically should make things easy.

So, what you would want to do, the first step would be to get the actual content. So, to do this, you need to export your blog, your your website. You need to export the pages on your website uh by the page name, by uh the page URL, and any other you know, relevant information. So, in this case, I've gone into our WordPress hosting service because WordPress has a back end database. Um, this is gonna vary based on your CMS.

So if you use something like um ectron or Joomla or Drupal or uh Sitecore, this is this part of the process gonna be totally different for everybody. For if you're using WordPress, um there are plugins that will export your WordPress blog. You can also just go into straight into the back end database. I go into this back end database. That way I don't have to slow down the site by adding more software to it.

And what we're looking for is the posts table. Now one of the challenges for getting uh this stuff out of there is there's a WordPress is a surprisingly robust system. So we know for example we're gonna need when the post was written we're gonna need the content of our of what's on our site uh we'll need the title of it and we will need the status we won't want to get posts that are still in draft that's not helpful um and then we need to get the URL URL's not in here um surprise uh what is in here is what's called a slug uh which is the the the post name it's a tiny little it's basically the end of the URL fragment but not the whole URL so that's part one we got to get this stuff out of here and so if we were to do that we would say something like select we want the post date we want the post title we want the post content and we want the post name so those things from this where the post status is published and post type there's two different types of posts. Post type equals page or post type equals post. Because there's a bunch of other things in WordPress that are not that.

They're like, you know, sliders and carousels and all these other things. Sure. So now we've got our the content that we need. This has to get exported into a CSV file. So we're going to go ahead and do that.

And this is 1575 pieces of content. We have a very robust content marketing. Which is good. That gives us a lot to work with. That does.

Alone, it's not going to fit in any generative model, even the newest ones. I mean, that is a lot of content. In fact, let's just take a quick look here at just how large this file is. It is 25 megabytes. And it is wow, that is a big old file.

26 million characters. We have we have done a lot of foaming at the mouth in six years. So John, when Chris says things like 25 megabytes and 26 million characters does that mean something to you, or are you like me and just kind of nod along and be like, yeah, that sounds like a lot. What's it? There was uh an old um adage that I picked up somewhere along the way.

One megabyte is like a four foot or five foot stack of paper. So that like gives you a rough. So we're talking about like a 200 you know foot stack of paper. So that gives me at least a rough idea. Yeah, there's a lot of uh a lot of preaching there.

We've covered a lot of ground in that content. There is. There's also one other minor problem here, and you can probably see it on screen. The content of our posts is in HTML. It's not plain text, which means that uh part of this process would involve data cleansing to sort of trim that down.

Because if you don't do that, you're going to end up with a uh gender of AI is going to basically choke on this and not know what to do. But that's one part. The second part is we have 1500 pieces of content. Are all 1500 pieces of content equally valuable? Oh, I don't think so.

Okay. I would say honestly, if we need to break it up, then I would say let's, you know, if we've been around for six years, for example, let's take it in either two or three year chunks. So I would say the first we could deprioritize the first three years. Not that the data or the content is bad, but I'm guessing it's not going to be as strong or as relevant as it is in the past three years. Could we do it that way or should we do it with like page views and see what content's been the most popular?

You could, I mean, I think you could do it by page views. My concern there is that there's strong content that probably wasn't categorized correctly or uh promoted correctly, and that's part of what I want to be able to fix. Okay. So if we wanted to bring in page view data, that is also not stored in WordPress. That is stored in our friend Google Analytics.

And so part of our remit then would be to go into Google Analytics and get that data out. So that would necessitate going into the Google Analytics AP. Well, you can do it in the in the Explore Hub if if you like suffering. Um, or you can do it through the API and say, give me my page URL and the number of sessions and the page title for each of these pages. And so that gives you a data frame, uh, a spreadsheet that looks like this.

Let's go ahead and go up. So you see we have our page titles, we have the URL of the page, and we have the accounts. So there's a lot of things. So we see instant insights, how to write an effective chat GPT prompts, 7,000 views. We see uh blog posts in here, we see old newsletters, we see disclosures of copyright.

So there's a lot of of different chunks of uh uh content from our websites and we have the the views for that. And of course, this is very much a power law distribution, right? You have the the top 10% gets like 80% of the 90% of the page views, and then there's a whole bunch of nothing on the other end. So now to do what you're talking about, Katie, we need to blend these two things together. So let's go ahead and we're gonna get our posts and our GA data.

And like you mentioned, you want to trim down the amount of stuff. So you only want to focus on the last three years. So let's do a filter, yeah, where our post date is greater than or equal to today minus the under 65 times three. Because when I think about the type of content that I know we were writing, a lot of it was about universal analytics, uh, which is no longer something that we really need to spend our time on or optimize. Um you know, so like there's gonna be a lot of content that's irrelevant there, and then um we I don't remember the exact date that we launched or started talking about the five P's, but I know that it was in the past three years, and that's something that I want to get our better handle on because I know that content is not um clustered very well on the website.

So now we also have to so one of the other challenges we're gonna run into is Google Analytics gives you URLs. Our WordPress data does not. So we have to match up the last part of our WordPress URLs with our not at all formatted the same Google Analytics URLs. And to do that, um, I had to write some some extra code to basically monkey around with it. So after all is said and done, you also have to remove the HTML, which we did here, just saying we're strip anything out.

That's a that's a tag, and let's filter the page should have had at least at least two views in the last three years. If it doesn't have at least two views, then something's gone wrong. Um that leaves us with about 789 pages of stuff. Now we're in an area where we can probably start using generative AI, at least to some degree. So let's do this.

Let's put a get our our post content our content summary. We'll call it content summary. Uh we're gonna take our unified table. And we're gonna uh let's do select, let's start just with our post titles. I know you said you had to write a little bit of extra code, but is this theoretically something that if you were savvy enough you could do with lookup tables in Excel?

You could do the unification of the two tables. Yes, you can do that with Excel. Removing HTML tags from text, unless your name is Ozdu Sole, probably not. Um that's sort of a uh a LinkedIn joke. Oz is one of uh Microsoft's MVPs for Excel.

He is an Excel deity. Um short of that, I don't know any way of having Excel remove HTML from um from uh cell's contents. Uh and I'm guessing you'd have to bring it into a tool like uh BB editor text Wrangler and do some magic there, maybe, and then bring it back into Excel. You could probably do it visual basic. Visual basic code in Visual Basic to do that.

Okay. I'm not gonna write code in Visual Basic. No, no, no. I'm just I always like to try to give other options to people who are watching this who may not have these specific tools at hand. Um comment, uh, could AI remove the tags?

Yes, AI can. Here's the thing though, and this is really important. Generative AI can do stuff like that. It's a language-based task, but it is an incredibly expensive operation because generative AI itself is computationally very expensive compared to a classical way of doing it, which is uh regular expression. So this is the in this case what we're saying uh in this piece of code here is if it's between these two braces, the pointy braces, get rid of it.

Right. And that takes a nanosecond for for this to process hundreds of posts as opposed to trying to feed it to generative AI. Yes, it can, but it's not a good use of the tool. Oh, you know what you could totally do there is um do an AI prompt and say, give me a visual basic query to strip HTML. Exactly.

And then that you can still do that within Excel. I mean that I used to think I was great at Excel, and then I met a person who used Visual Basic in Excel, and I was like, oh, I actually don't know anything about Excel. All right. So now what we have done is after all that, we now have a list of over 700 different pages that have just the page titles in them as a starting point. We could do this uh format it to its page title and the content of the page.

Now that would be a little bit larger of a file, but that would give generative AI a lot to work with. This is about 5,600 words. So that's that's not too terribly bad. Let's do a version that has um that has the the full Monty, if you will Content full. Okay, so now that file is 10.9 megabytes large.

Let's see. Let's take a look at at how uh how heavy it is in terms of words. It is 1.9 million words. So that's still not gonna fit in a generative model because though they can hold about 700,000 words at a time. So even by filtering down to the last three years, um, it it's still a good amount of text.

So we have two forks in the road we could take right now. We can start working just the titles to see just broader what categories there are, or we can try and slim this down more. I would slim down and remove the newsletter and podcast because those come in as posts. Um, and I know that we've been repurposing the content from the newsletter as posts. So it'll be duplicative if we keep that in there.

So anything that's marked as a podcast or anything that's marked as the newsletter can get that is crazy though. You're still talking about like 18 or so books worth of stuff. I mean, have you ever heard Chris and I just rant for hours? Words pile up over years. That's we're really good at it.

I mean, John, how how many uh reams of paper do you think the marketing over coffee site is? Uh you know, the thing with the marketing of our coffee state, last time I did an export, I went through and it was like only about 20 or so percent, 25% was evergreen. You know, the majority of it was all topical news. You know, it's like nobody could give a single care about how to get your MySpace profile optimized right now. You know, those podcasts are are on the dead pile.

I'm surprised by that. I'm surprised actually I'm surprised it hasn't made like a resurgence with everything else going on in social media that the MySpace guy is like, ah, I'm here. You thought I was bad. Meet the other guys. Okay, so that now it down to 1.1 million words.

Now you want to know what the other large category is that creates an enormous amount of text? The weekly live stream. Yeah, we can take that out too. Okay. Yeah.

And the reason, you know, for those who are watching, the reason I'm okay taking those out is so the podcast and the live stream, the content there's really just the transcript, but everything exists on YouTube or on the podcast players. And then the newsletter, um, the content from the newsletter, the cold open that I do and the data diaries that Chris does are also repurposed as individual posts later on in the in our timeline in our editorial calendar. And so all of the content, like we're not going to be losing anything. We're actually, you know, just narrowing down to just the individual posts themselves without all of the other extra stuff in it. Exactly.

So now we're down to about 290,000 words, which is much more manageable. Uh and now we need to process it. Now we need to now we it's time to bring out the generative AI. Woo. So let's go ahead to uh AI Studio in Gemini.

And the reason we're gonna use AI Studio is because this is a lot of text. The the consumer version will simply not handle it. So what we want to do is we want to categorize this, right? So Katie, give me some thoughts about how you want to categorize this text. Um well, I mean, there's some basic basic categories that I think.

So it would be um, you know, we want five Ps. We want uh AI, we want uh marketing, and there's gonna be some overlap, but like I want to make sure we have like the basic what is I'm thinking about our services, and I want to be able to categorize our content and say, here's everything we've written about as it relates to gener our generative AI for marketers course, for example, or our AI consulting services, or you know, you want us to do a 5p audit. Here's everything we've written about it so that you can better understand what it actually is. Does that help? Okay.

So let's do so. We should get a list of our services. Okay. It's in there, yes. Okay, thank you.

Because I know, and that's so that's you know, one of the things that, you know, and I'm sure a lot of companies run into this same sort of uh challenge, is the approach to a service isn't necessarily the service itself. And so we don't have the five Ps as a service. We may at some point, um, but if you hire us to do some kind of consulting, the five P's is one of the tactics within the service itself. You know, so if you want us to do a Google Analytics audit, the five P's is part of that. If you want us to do a digital customer journey, the five piece is part of that, but it's not a standalone service.

And so if you're thinking about using your services as a way to categorize your content, if you also want to think about like what goes into those service offerings. Exactly. Uh now this is gonna take uh probably a couple of minutes, would be my guess, because we just fed it 400,000 tokens. Um, nope, it was faster than that. Let's see what we've got here.

Artificial intelligence consulting, disclosure copyright. Oh wow. So it's going to go through and try to align the different pieces of content with the categories. That's a useful, but B, wow, it's gonna be a while. Okay.

So uh so, John, what are you doing this weekend? So reading War and Peace and uh audiobook and um, you know, but I do think that it's a useful exercise to see um because one of the things that we talked about internally as our company is our goal for this year is to be more focused. There's a lot of things that we are subject matter experts in, but not all of the things that we're experts in translate into services, and so are we focusing our content enough to better support the services that we do sell? So I think that this, even though it wasn't our intention to do it this way, is a very useful exercise. It is.

I do see a few uh things from a data quality perspective here that we should do for the next run, one of which is remove thank you pages because we don't need those in here. Um to your point, it does also bring a lot of it does highlight the different types of content that fall in these different categories and stuff. We would have the way I would do this at scale in production is not to do it in a in a web interface like this, but actually to do it in Python code so that each post we fed in individually and say, here's the list of categories, you know, pick the category that fits best, uh, and then and then have the data spit out of the Python script into a database that you can then analyze. That makes sense. Um I'm thinking in terms of so once we have these categories and once we clean up things on the website, you know, I'm then thinking forward to someone like John who gets asked questions.

Well, what are your AI capabilities? You say you're experts, what does that mean? Well, wouldn't it be great if he could just point to you know one cornerstone content page that has all of our AI content listed and linked in one place? And so you don't have to search through the site, you know, and the search on our site, quite honestly, doesn't exist, so you can't search our site for all of your AI content, but from the AI services page, I could link to the cornerstone content that lists all of our AI related content or you know, whatever the topic is. And so when you're asking me at the start, like what's the purpose?

That's the purpose is a better user experience to help demonstrate our capabilities. Because we write about these things all the time, but there's no narrative that you know really connects everything. And so I want to be able to do that a little bit more cleanly so that it's you know better understood by someone who's coming to our site. Like, what do you do? How do you do it?

You say you've been doing AI for a decade. What does that look like? How deep is your knowledge actually go? Or are you just saying that I'm an AI expert because it's you know the trendy thing to do now? Exactly.

I I hit stop because I think otherwise it might keep going uh for quite some time. Um however, the next step, which what you said in the statement, I think is is useful, which is to say, well, what what content haven't we created that'll you know in our various services? So the way to do that, let's go ahead and bring in another file. I'm gonna go into Google Drive here and choose ICP and bring in our ICP, which we have done in previous episodes. Yeah, if you're looking to uh get a better understanding of how we built that um ideal customer profile, you can find that on the so what playlist at our YouTube channel, which is at trustinsites.ai/slash YouTube.

We did that a few weeks ago. I actually sent that video um to the director of the shelter that I volunteer at because she's really curious about generative AI, and she immediately put it to use and started building out things. It was actually really impressive, which I also give credit to us for doing such a good episode. Well, so what I just asked is review our ideal customer profile, which I brought in, it's in the it's in Google Docs, so it went straight in. And I said, based on our ICP and the content we have produced, what content have we not produced aligned with our services that our ICP would find most valuable?

So now this is this is a fairly complex reasoning task. Um effect of saying, here's what we have, here's who we made it for. What haven't we done that we should have done that this this person would would this type of person would take uh find value? And let's see content gaps for our profile based on the massive amount of industry content. Um we have industry specific content, of course, which we've talked about.

In fact, we had a whole issue of our newsletter devoted to uh identifying which which industries we should even be talking about, uh, hence last week's show on agencies. Role-based content. So that's an interesting one. We've not done a lot with roles like generative AI for the CFO, generative AI for the you know the CMO, etc. Pain point focused content, of course, staying ahead of new trends and problems and things, content formats and different channels, etc.

Um so this is a a decent good start. That's interesting. Multilingual. You know, it's funny. Um we could do that if that might be an interesting uh survey for another issue of our newsletter at one point, asking people what language they would prefer their content in.

And if there's if there's content, if there's a language that really stands out, it might be worth producing at least our our flagship content in that language, because we have um generative AI is an incredible translator. It is much, much better than existing translation tools. Uh, I did a thing a couple weeks ago in um in Italian in northern uh Northern Venetian Italian, which apparently every region of Italy has its own dialects, uh, and they're very, very protective of them. And the person I was working with said it is a little uncanny and dis and disturbing how natural it sounds, how it gets all the local idioms correct, knowing that you don't speak a word or so. I'm like, uh-huh.

So that multilingual content uh might be something uh super valuable, even to the point if you wanted to get really uncanny valley of then taking the translated content and using a service like the the avatars from HeyGen to have us reading out that content in that language. Yeah, we'll see. So now we've done our content audit. Well, we got the content data. Yep.

We we did some deed data cleaning on it, and we prepared it, we loaded it to generative AI. So the first three steps, no generative AI at all, to because and but they're mandatory, you can't skip them. Right. Uh, and and then use generative AI to read through the content, start categorizing it, and then use generative AI plus the ideal customer profile that we built previously to say here's what else we should be doing. Makes sense.

Um, you know, and obviously we'll do this offline, but I would love the rest of the analysis. Yes. Um, no, and I think that you know, in what 31 minutes, you've been able to show what's possible. Um, obviously, like you've done this before, and someone starting fresh is gonna take a little bit longer, but you can audit your entire, you know, database of content and figure out what's next and build that editorial calendar. Because I mean, how often do I say to you, Chris, what are you writing about?

What am I gonna write about? And you know, in all honesty, because I personally feel like I'm just sort of reiterating the same thing over and over again. And maybe that's fine if I can look at it from this lens and say, well, is it role-based or is it industry based? Then it's yes, I'm reiterating the same thing, but to a different audience that's tailored to them. Exactly.

How would you use the five Ps for a real estate agency? How would you use the five Ps for a healthcare firm? How would you use the five Ps for a CFO, right? If the CFO is like, hey, our finances are a hot mess. Well, great.

I mean, that framework fits literally any task. Like, how would you use the five Ps for an organic, all natural manure spreading business? Mm-hmm. Absolutely. So John, what do you think?

That's big business manure spreading. I'm just saying. No, it's great that you know, this is definitely the way to kind of comb through all this stuff and find out, you know, where the power curve is, you know. And I but the other side of it too, I do have to um give a plug for the long tail too. Because I think you had a great point of I think there's a lot of buried stuff that just doesn't get traffic because it wasn't promoted or it didn't catch or whatever.

But you know, there is stuff in there that when you go back and look, you see that, oh, this is you know, covers five of the topics that we should be covering and it didn't get any traffic the first time, so there's opportunity second time around. Yeah. The the dissemination and distribution is not something that generative AI can solve for you. That's a that's a you problem. That's a human problem.

It's not something that it can solve, but it is something that you can use to sort of gut check to validate, like um, for example, if you happen to keep a swipe file of LinkedIn posts that you've seen by other people, like that, like that oh yeah, that post did really well, and so on and so forth. You could say, here's a list of 10 or 15 posts seem to all do really well. A, figure out what they have in common, and B, here's my LinkedIn posts that I want to do. How could I edit it to be formatted more like or to tell a better story so that I get uh I get more of that attention. So, for example, one of the things that I've been doing a lot lately is I've been using um Thomas the Critic, uh, which is a uh a Gemini, a very, very large Gemini prompt.

Thomas the Critic has this long, long list of things that um he or it looks out for, like, hey, you you're you've got these biases, um, you've got survivorship bias and selection bias, framing effect, so all the basically all the the things that would make for terrible content because you're you're using stuff that is not well thought out argument. And so I say, here is a post I'm gonna write on LinkedIn. Three tell me up to three things that it does well, up to three things that it does poorly, and then three things that could do to strengthen it. So you could use a similar alignment with your ICP data. You could use, you know, show me three things that my ICP would like about this, three things my ICP would not like about this, and so on and so forth.

Or use the top 10 LinkedIn posts. You know, call this the LinkedIn guru or whatever. And uh, what would the LinkedIn guru think of my post? What three things that the LinkedIn guru love or hate and and so on and so forth. So any of these tools you can use generative AI in that kind of framework to make it better.

Oh, sure. And I think that that's all well and good. My original point by saying this was a human problem was if you write it, you still have to schedule it, disseminate it, distribute it. Like that's not sure. You can automate it with generative AI, but you still have to make the effort to get it from A to B to C to get it in front of people.

That's my point. Not that you have to write better, yes, you have to write better content, but you still have to schedule it. You still have to put it out there, and that's the piece that it's not necessarily going to fix for you. Yet. Um I said you don't need to argue with me on this.

I'm not arguing with you. I guess I am, aren't I? Yeah, well. Here's a sneak peek at the future. This is a framework called Crew, uh, is crew.ai, and it's available on GitHub.

It's totally free. What crew is is the essentially agent network software. And as you can see here, uh this is um a Python script that creates multiple AIs. And there's in this case, there's a researcher and a writer, and the researcher does one task, the writer does another task, and so on and so forth. So you might have down the road a social media uh poster.

You might have a reviewer, you might have uh an author, and you might wire together with in a code-based function the various tasks that a social media manager might do to create and post a highly effective LinkedIn post. And you might just hit go on this script. It might give you one thing and say, wait for human approval, and then using the APIs of your favorite social media management software might just go and do the thing for you. So that's not available today, but it's very, very soon. Sure.

I think that that's interesting. And my original point was still that just because you write the point, the post and put it on your website, that doesn't really count as dissemination. Because you still the human, you still need to set up that AI version of you know, posting to social, the you know, whatever it is. So it's still a human problem because it still needs to be set up, even if it's something right out of the box that WordPress is like, and just click this button and it'll immediately post it to social. Great, you still gotta click the button.

That's my point. My point is that's the human problem is that generative AI is all well and good, but someone still has to set it up. True, very true. And that someone, if it's not you, that someone can be us. That someone is John Wall.

Come to us, we'll solve all your AI AI problems. It's just that easy. All right. So I think we we covered the the basic content audit. I would encourage folks to use tools like Google Analytics.

Um get to know your CMS, because you're gonna need to in order to export your content out of it, uh, and then get comfortable with some of the data wrangling. Again, you can use data generative AI to write Python code to process your your data. So you absolutely can have it do that. Uh, and that will work pretty well for you. And then you can use generative AI to analyze it and to make suggestions for it.

But to where we started at the beginning of the show, this is not something that generative AI alone can do because it's not purely a language problem. It is a series of problems, you know, as one complex set of tasks. Yeah, I you know, and I I think that that's a good point to end on is that you know, generative AI is sometimes part of the solution, but not always the whole solution. So really go through your upfront requirements gathering, figured out what it is you want to do, use the five Ps, do some user stories, and then you can pick out which platform is best gonna solve your problem. You know, if, for example, you know, you're someone who's really good at visual basic, then use visual basic instead of trying to write Python code, for example.

Exactly. All right, that's gonna do it for this week. So we will catch you all on the next one. Thanks for watching today. Be sure to subscribe to our show wherever you're watching it for more resources and to learn more.

Check out the Trust Insights Podcast at TrustInsights.ai slash TI podcast at our weekly email newsletter at trustinsights.ai slash newsletter. Got questions about what you saw in today's episode? Join our free Analytics for Marketers Slack group at trustinsights.ai slash analytics for marketers. See you next time.