So What? SEO Competitive Analysis Basics

Well, hey there again, friends. Happy Thursday. Welcome to So What, the Marketing Analytics and Insights Live Show. I am joined by Chris and John. And today we're going to be talking about SEO competitive analysis basics.

So last week, if you uh missed that episode, we talked about SEO keyword research basics. And so what we wanted to do this week was then talk about uh the competitive analysis basic basics. And you know, competitive analysis in general is just one of those interesting things that I always find fascinating on how people approach it and why they do it. And so some people do it to, you know, see what their perceived peers are doing so that they can get ahead. Other people do it to see what their perceived peers are doing so that they can see if they're falling behind.

And then other people do it just to check a box and then never do anything with the information at all. So we could probably spend the full, you know, 40 minutes talking about why you should do a competitive analysis. But specifically today, we're going to talk about SEO competitive analysis and we're going to cover what it is. Uh, we're going to cover how to pull that information, how to get your competitors' uh keywords and topics, and then how to prioritize those things for your own content creation. So Chris, where do you want to start?

Well, let's start with this first. An important announcement. This is gonna be our last uh weekly show on Facebook. We are essentially, you know, trying to do less and less with uh Facebook as a channel. So if you are not already uh subscribed to our YouTube channel, go over to TrustInsights.ai/slash YouTube uh and follow us there.

That was uh that our LinkedIn channels will be the places where we'll this show will be um from now on. You know, just with everything going on with uh Facebook, uh it's it's time to uh to reduce everyone's dependence on it. So uh now that we've gotten the administrative stuff out of the way. What do I ask you this, uh Katie? Actually, I'll ask you this uh to John first.

Since you do the majority of our sales, who are our competitors? Oh yeah, that's a great, you know, we always fall back on the big consulting companies. You know, we just say that it's the um Andersons or whatever of the world where you'd normally pay half a million dollars, we do the same thing, cheaper, faster, better. Um, and then there are I mean we will take a half million dollars. Yeah, exactly.

400k special this week if you lock it in soon. But um, so that that's really our niche. We uh have really gone along that route of we don't tell our customers that there's anybody who can do what we do because what we have is unique, it's uh on its own in the market. Um so yeah, in some ways though, I regret that because in other spaces it's great if you have like five competitors that you know you're gonna get spreadsheeted against that you can just you know lay the landmines and let them get destroyed. So um it's it has both its um benefits and drawbacks when you go that route as far as targeting somebody way outside of your normal reach.

Katie, what about you? What who are our competitors to you? Well, you know, it depends. Um what I've found through my own research is it depends on what our angle is for competition. So if we're talking about services competitors, then uh some of the consulting firms that John just mentioned make the most sense.

But if we're talking about our organic search competitors, that's a little bit different because we the keywords that we have decided we want to rank for are not necessarily the keywords and topics that are that's why I kept saying perceived peers that our perceived peers are ranking for. And so when I took a look at this information, I found that our organic search and SEO competitors were different from who we thought we were competing against for services and audience. Um so we're looking at companies like Ventera and PCAN AI and Data Crunch Corp in terms of sharing the organic search space and trying to rank for the same keywords. That doesn't mean that they do the same things that we do, but they have decided that those are the keywords that they want. We've decided that those are the keywords that we want.

So we're gonna, you know, duke it out. So this is a really, really, really important part of competitive SEO. Um before you open up a single tool or spreadsheet, you've got to figure out what you're competing for. And John and Katie have illustrated the two different schools of thought on competitive SEO. One is who's got the traffic, right?

And that's going to be around specific terms and search engine rankings and stuff for those terms that you're duking it out for. So uh as Katie mentioned, something like uh other other AI technology firms. We write a lot about data science and AI. And so in a certain SEO tool, we would we would be going if we wanted the traffic for those terms specifically, we would be going after those terms. So and that's that's what most people do when they think competitive SEO.

They open a tool like spy Foo or SEMrush or whatever, say, here's my term, who am I competing with? And then you get your list and and it's off to the races. But the question that we should be asking is where are our customers? Right? Who are our customers?

Who's got our customers? Who could we take customers away from? And that more goes to the question I asked John, which is who do we lose sales to, right? Who do we uh who do we compete with? Who uh has a a competitive thing?

Because when we think about it, you go back to last week's um different categories of search, right? There's branded search, which is people searching for us by name, there's competitive branded search, which is people searching for our competitors by name, then there's unbranded, uh adjacent and novel. Last week we looked a lot at unbranded. Competitive branded search is when people are searching for a competitor by name. So to John's example, if we wanted to rank well for things around management consulting, neither us nor our our peer competitors are are really getting any traction for that.

You know, and our peer competitors, especially because they're all software, a lot of them are software companies, they're not showing up for change management. So a big part of that first step is okay, well, who are our who are our competitors that we need to be looking at, and who's got the audience, and then what are the terms that attract that audience? And that's there's a big difference in those two strategies. It is, and it's it's a lot more in-depth than just opening up uh uh spy foo and just plugging in your company name and seeing, you know, who do we compete with uh in the search space. Um, you know, and so it does take a lot more thoughtful planning.

And this is something that we've seen with a lot of our uh clients is they we we struggle to answer the question as well. So it's not just them, but who are your competitors? Nobody really knows. And I think that you know the digital marketing space has really changed what that means. You know, so you know, back, you know, before, believe it or not, there was a time before the internet.

So back before a time, you know, before there was internet, you know, you would compete with people who have similar products and similar services, and that was it. There was really no uh other way to slice it. But now when you bring it to the internet and you have all those different channels, you know, you have search and social and you know, email and all those things, it just changes the rules. And so you may have different competitors for each in every channel. Exactly.

So in search, um, to what Katie was saying, let's go ahead and look at um one of the tool, the more popular tools out there for competitors. Uh, this is a tool called Spy Foo. Again, if you have an SEO tool, you know, SEMrush, Hrefs, uh, Moz, all these tools essentially do more or less the same thing. The difference is going to be on data quality and and UI. But functionally, if we're using a tool that you don't see uh that you don't have, like don't worry about it, you're the one that you're paying for probably does something very similar.

So this is this is the the the search traffic perspective, what Katie had said uh initially, which is plug in your company's domain name and see who who's the tool thinks you're competing with based on the amount of overlap you have with keywords. So here we have uh us in blue and this data crunch corporation in in red. Now, the big question to ask is is this actually a competitor? So let's go to their website. They build software analytics AI that changes the world, join the family educational institutions, SMBs find massive gains with the predictive insights.

So the first thing that I would do is I would go to the services at the very top. I would look at education, I would look at website, I would look at custom because we do a fair amount of education. We just that's not one of the services that we lead with. Um so it then we need to make the decision of what are the things that we want to lead with. So they do analytics, uh, you know, data science-based technology, those are terms that we use.

So I would say this is a good overlap for search terms, right? I don't think it's who our audience is. I don't think that's the the audience. So one of the things that's interesting here is that we have a lot of overlap. Um, and what this this tool, like many of the competitive tools, does a really good job of saying, okay, you can look at just the words that are unique to you, just the words that are unique to a competitor, and then the things that you share, which is 45 out of you know, uh 10,000.

So even though that it looks like there's a large overlap, there really isn't. There's not a ton of overlap here, which indicates that this is probably not super competitive. Now, to what John was saying, let's put in BCG, which is uh a Boston Consulting Group. We can get them in here. And here we have uh now of almost what 20 times as much uh keyword volume, almost 400,000 keywords.

When we look at there's no one, there's nothing that all three of these have in common, right? So now we've got a uh we're starting to get a sense of okay. This large consulting firm may be may have the audience we want, you know, companies that that need help with things like change management, match consulting, but from uh a content perspective, there really is no overlap at all. Yeah, and so I'm not missing anything, right? Like their Venn diagram game needs some work there.

That's not how Venn diagrams work, as far as I know. Now, yeah, now this is interesting. Now, when I take away data crunch, uh, and now it's just us and the giant consulting firm. We actually have 128 terms uh that are shared, and we've still got our 2000 over here, and then they've got their 300,000 over here. Um, so at this point, this is now where we can start to say, okay, let's apply the same techniques that we were using last week in keyword basics to figure out um what's going on.

So let's start with um these these core. The core essentially means the overlap, the 128 terms that we share in common. I'm gonna go ahead and just export this as a CSV file. And then I also want to look at what we don't have, right? So the everything gonna take because we know we're we from last week we know we do have.

Uh let's take a look at this this is what they call the missing keywords. These are the ones that are exclusive to them. We're gonna export those as well. And as we did last week, I'm gonna go into Tableau, and again, you can use Microsoft Excel. You can use R if you want to get fancy, you can use Alterics, any any of the data processing tools that that we all know and love you can use to get this, get this data.

Let's go ahead and pull up our first that first the core keywords. This is the 120th at overlap. And let's use our keyword. And we're going to do our search volume. And we're going to look at our keyword difficulty.

And let's put this on a scatter plot. As we did last week, we're going to take the search volume and let's make it logarithmic so that it's a little easier to see. And let's fit this to the entire view. Let's put our keywords as little hover points. We can see what we've got here.

And we're going to reverse our ranking difficulty. Because again, the closer to zero a number is, the easier it is to rank for, you can there's more opportunity. So let's um put also our a couple of reference lines on here. So for our search, ah, you know, we need it, we don't need it for this point. So if you just imagine a two by two matrix here, stuff that has high volume and low difficulties in this quadrant is largely absent, right?

This it's it's pretty barren up here. There's there's not a whole lot. Stuff that is low difficulty and low volume, like consulting newsletter, um, you know, that's uh the voice of the customer consulting. These are things that you know, there's there's some opportunity there, but not a ton. Where the where things get challenging is um high difficulty and high volume, outside the box thinking, uh, change management framework, digital customer journey.

So, from a an opportunity perspective here, we have to figure out how to create other related content around these terms because there isn't an easy opportunity. There's not something here that that we could do really well protecting ourselves with. Okay. Let's see if the other still working on generating 400,000 keywords. Yeah, and I like I'm just I'm taking it all in because this is I feel like you can start to see like the wheels spinning the smoke coming out.

I'm like, oh man, I definitely have been looking at our competitors, the wrong competitors. Uh and so it's it's it's interesting. I feel like when I have this aha moment on our own show, I I would be interested to hear, you know, when people have that aha moment for themselves after they've watched the live stream. But like to me, I'm like, oh damn, okay, we've been doing it wrong. So how do we do better?

And so this is how we do better. Right. So now let's that other file finally finish downloading. This this might crash tableau because uh 400,000 keywords is a lot to deal with. Um we're gonna repeat the exact same process.

Now, this is just the keywords that um BCG does well for that we have no we're not ranking for at all. So there's there's no chance for us right now. Um if you look at the list really quick, and so you mentioned that it's you know 400,000 or something, some crazy number. Like, there's a lot on there that if you were just trying to clean up the list before you started doing this analysis, you could probably get rid of a lot of them. Like, we're not gonna try to rank for the and rocket, things that are Pepe is not on the list.

Yeah, Boston Tea Party. Um, those are things that we will never care about in terms of uh terms we want to rank for with the business. Right. Okay, let's do a little bit of filtering here to see if we can clean up um at least some of this stuff. Knock out uh the the things that have no search volume at all.

And let's go back to our plot. All right, ranking difficulty. Yep. So this needs to be an average because we got there's duplicates in the list. And we should do that here as well.

Okay, we're gonna rescale our search volume to logarithmic. And we're gonna res uh alter our ranking difficulty reverse it. So even in this gigantic huge 300,000 uh data point mess, you can still tell that upper right hand quadrant is still largely empty, right? There's not a lot in there, which indicates that you know this this is a this keyword list for this site is very mature, right? There's anything that you can rank for, you are ranking for.

There's not there's there's some not some hit, not a ton of hidden gems in here. Um there's still a few here and there, um, like seamless customer service, for example, the sharing economy, um uh, which is it, which is interesting. Um, commodities trading steps for buying a car, uh, management consultants. That one's interesting that that it has such low difficulty, even though um there's you know a several others, a thousand or so searches. Let's do a little bit of filtering to on the average search volume.

Let's increase this to 10. So at least it gotta have at least 10 searches. We can clean up the left-hand side of the script graph a bit more. Um so in something like this, um, this is everything that BCG ranks for. It would be impossible to try and build a content plan from uh 193,000 different keywords.

That's what we have left in here. So the next question that we would want to ask is is there a way? And there we the answer is yes. There is there a way to uh to filter this down to essentially terms that are at least relevant to what we do things around marketing and data, stuff like that. And for all of these um tools, there absolutely is uh are ways to do that.

Let's take a build ourselves a quick keyword filter here, and we're gonna wild card contains market, just that. And now we're we've got a lot uh more visibility into what you like. You have uh marketing in the digital age, bringing the supermarket to the apocalypse, that's interesting. That's why I feel like there's there's a decent amount of cleanup that can probably be done. Exactly.

Market share synonym, things like that. So there's there's definitely um you know, some cleaning that can be done here, as you said, but there are uh it's it's a little bit easier to see some of the things that you might want to work on. Let's take a look, let's do the same thing. Let's do beta. And now you see a lot of job stuff, job related things, but yeah, there's Snowflake, there's first party data.

So first party data has is relatively difficult, but there's some decent search volume for it. Um here, you've got data analysts uh salary surveys and things. Uh so one thing that would be very interesting to do is like if you want to create a piece of of competitive content would be to do a salary survey and publish it as pillar content on the blog, um, sort of rounding up what what the world out there seems to think uh would be appropriate surveys for data engineers for marketing analytics specialists and stuff. It's a it's a possibility. Um you do have other stuff in here too.

Um zero party data, which is something we were just talking about, uh gosh, I think it was about a month ago about difference between zero and first party data. So there's there are still some uh decent number of topics. If we go in, let's do one more on change and look at see if we can see what we've got on change management, uh change management consultant salaries, uh change management consultant salary, behavior change consulting, change versus transformation. That's actually sounds like a good uh a good topic. Why is change so hard?

What's interesting about this, and you know what's important about this is that again from the analysis we were doing, these are all the terms that we don't show up for at all. We're not in the game on any of these terms. So these would be opportunities for us to to go and dig in and say, okay, can we create content for these things? Knowing that BCG's audience is the right audience for us. We we know that, you know, uh the same would be true if we were to go back to here, uh let's put in McKinsey, right?

So what when I, you know, it's interesting. Uh as someone who would be creating some of this content, um, you know, and maybe this is where I just need to do some, you know, I guess for lack of a better term, I'll call it experimental writing. Uh, writing basically to see sort of like what comes out. Uh, because right now when I'm look when I'm thinking about some of these terms, I'm like, but how does that relate to the services that we do? Because isn't the whole point to create content to educate people around the types of things that we have capabilities for.

So I'm looking at some of these terms, and even though they are opportunities, are they still the right terms for us? I don't know. Um, you know, so you're talking about the salary surveys. Yeah, that would be an interesting thing that would drive people to our website, but does it have anything to do with the services that we offer? You could maybe draw like a dotted line to our data analysis and surveying skills, but are is that why people are looking into that piece of content?

So that's where I kind of get stuck when we do exercises like this. Think about it in terms of the marketing operations funnel, right? So when you're talking about content to attract people to us for our our products and services, that really is middle of the funnel content, right? We if you are looking for you know Google Analytics consulting help, you have unbranded intent that's saying, like, I I have a problem. I need I need help with this problem.

Who does this, right? You know, bottom of the funnel content would be the branded stuff. Like, I need trust insights to come help us with this thing. I need Katie Robert to come in and and and and shout at all the idiots I have working for me. Um that's happily where all this stuff comes into play is at the top of the funnel where we don't we know you don't have buying intent right otherwise you would have shown up in those middle of the funnel terms.

We know for sure that we we you don't have you have no buying intent but you're the right audience. And if we can attract your attention and enroll you in something like just like the newsletter and just as a way to hold on to your attention for just a little bit longer with each issue then like we talked about a few episodes ago when that that spotlight of purchasing briefly sweeps across your brand right for the two seconds here in the spotlight people will go oh I you know I get the Trust Insights newsletter every week and hey we've got a marketing analytics problem let me go give them a call right so there's the this is very much when we talked about sort of the three year marketing strategy you have brand building at the top you have publishing in the middle and you have community at the bottom and and we have publishing with the Trust Insights newsletter and this show and stuff like that. We have that nailed down right we're we're pretty good at that we have the bottom of the funnel community a Slack group analytics for markers um we we have that pretty well in hand you have 2,000 people uh in that group where we don't have as much is in the top of the funnel right in that in that do people even know who we are and we have talked in the past about things like well hey we have to go to a lot of conferences and events and be speaking just to get in front of crowds and we've discussed you know this conference is gives a better crowd than this conference but one of the interesting aspects about doing this kind of competitive SEO analysis is to say yeah there's a lot of stuff where somebody let's like take a look at this intersection here. There's 177,000 keywords that McKinsey and BCG share, right? Uh again, not all these are uh are going to be relevant.

Um, but some of them, you know, like artificial intelligence and things or quantum computing or even just you know basic digital marketing or shum haters creative destruction are things that this audience, which we know is a valuable audience, wants more of. Can we get any slice of that pie? As usual, Chris, you always give me a lot to think about. And now I'm just trying to figure out how to uh delegate this to John instead of me. And I just haven't quite figured that piece out yet.

Because it wouldn't be a live stream without giving John a big to-do list, but I guess I'm gonna have something on the list. Right, I'm the one who gets the to-do list this time. You know, to to that point, if you think about it, um if you were to to let's take a clear thing out here, let's put marketing over coffee in here. Here we go, John. John's podcast.

This will find we'll definitely find work that needs to be done here. Um so there's there's these other things that that currently have some overlap, but are these the the people that have an audience that we want as as podcasters, right? As people who have uh I would argue that probably not. Um probably if we want to attract people to our podcast, we want people who are interested in marketing in general, right? So we would probably want more people who would go like you know, our friends and clients, full disclosure, uh marketing profs.

You know, they have uh a really use uh good audience. We would look at people who go to places like Martech.org, um, because again, a really good uh group of folks. And so the question there is okay, well, what uh was that world look like? Where you know what are what topics are those talking about that we that marketing over coffee is not? Like brand building, for example, um, LinkedIn sales navigator, inbound marketing.

Uh these are all terms that those two other sites do well for that marketing over coffee does not. So as we're trying to come up with uh show topics or things like that, these are things we might want to talk about. Talk about brand loyalty on the show. Like we have I'm pretty sure we've not done a whole lot with with brand loyalty. Or if we have, we have not optimized those episodes for it.

Yeah, as it, you know, I've always stayed away from brand stuff. I kind of have this marketing ops bias of like, oh, the people that sit around and talk branding all day, like they don't really work. I don't want to have anything to do with those people. And obviously, this is telling me that, like, yeah, we're missing a huge opportunity. I need to give some glad handing to the brand term.

You know, it it's funny you say that because I used to think that way a lot about brand. You know, like it's it's just fluffy stuff. But ever since we started doing more and more with really advanced regression models uh and seeing more brand stuff cropping up, you know, going, you know what? There's a there there. It's it a lot of the folks who do brand stuff don't have access to those, you know, agre regression models.

But if they did, they would very clearly see, hey, this stuff is actually important. Uh and here the like the brand metrics that you need to pay attention to. You know, we talk about uh from time to time things like Google Search Console, like just looking at branded search, like how much does your branded search go up? Um, but there's a lot to unpack inside a brand. I mean, I feel better knowing, John, that you have stuff to do now too.

I know. Four episodes on branding. I'm actually psyched. That's a good one. I can definitely more show topics is a wonderful thing.

Uh but no, I mean, like, you know, it's funny being so close to everything, like being in the company every day. This is the stuff that we just gloss over. But then when we do these shows, I feel like I can sit almost in the seat of an audience member and get a lot out of it because you're using try you're always using trust insights as the example. And I feel like after every live stream, I'm like, man, like I feel like I've walked out of like a really good, you know, event session where people are like energized, like I need to do all the things, and you know, so I I always feel like that after these shows, and this one especially, because now I'm like, well, I have a lot more research that I have to do, and I have to, you know, get up to speed on all of these competitors that I didn't realize were competitors, and what's the language that they're using, and how can I apply all of our tech, all of our like, you know, processing techniques to learn more about what they're doing, and then how can I write the content that helps them compete? And so I just I find this exercise fascinating from that standpoint, where you would think that the person who owns the company wouldn't have their mind blown so much talking about what we do with the company, but without fail every week.

That's my little disclaimer. No, it's good because it's part of if you're doing data-driven marketing properly and well, you should have a lot of discovery sessions, a lot of, oh, I didn't know this was a thing, or wow, I've been thinking about this entirely wrong. Because we instinctively as people just don't do a great job of being able to think about data. It's just not not in the cards for us. You know, here now we're looking at McKinsey versus BCG.

So we're not in this fight. We have no horse in this race. 177,000 terms. Um, I I just looked at market and something like marketing in the digital age, zero difficulty, right? It gets a couple hundred searches a month.

Answering specific question. Who are Uber's relevant market and non-market stakeholders? So there's there's some interesting stuff in here. Let's look at uh data. See what these two giants are fighting over.

Uh data science salary, data science interview. So that was an interesting one. We don't necessarily need to know McKinsey's, but it would be interesting to see like if we were to put up a blog post about how to interview uh an agency for data science capabilities, how to interview data science candidates. Um again, these are things that not services we offer. Well, actually, we do.

Um see, but that's sort of where like you try to wrap your head around tying it back directly to trust insights. But Chris, I think to your point, you know, it's it doesn't need to be that direct line from here's the things we can talk about to here's the things that we can do, because right now our goal is to just attract more traffic to the website with content that is topically relevant uh to what the company trust insights is. And that's something that I'm still you know wrapping my head around in terms of like which of these things makes sense. You could make an argument that they all do. Exactly.

I I would say one of the things that you might want to do if you're looking at this kind of data is bucket it, you know, put a you know, top of the funnel, middle funnel, bottom of the funnel, you know, uh red, yellow, green, or or whatever schema, and then you can start looking at these different search terms and say, okay, where does this fit in? Data strategy consulting, that's sort of middle, right? You know, like if you were searching for data strategy consulting, you have some level of intent there, as opposed to say marketing in the digital age. That's very much a top of the funnel. Um, hey, I'm exploratory curious.

Uh there I there's not a need, right? There's there's there's not that implicit kind of need. So bucketing these things out would be a way to help classify and categorize like, yeah, this is these are the things that if we if you know your your funnel reasonably well, you can map these terms to. And then if you want to kick it up a notch, you look at your funnel, uh, because Katie, you do this every month with our marketing analytics. You look at the funnel and say, okay, here's where um you know top of the funnel numbers are, here's where the middle funnel numbers are, here's what the bottom of the funnel numbers are.

And we know the transition stages between them, you know, 2% conversion right here, 7% conversion right here. You figure out which is the which is the bucket that is leakiest, and then say, okay, how does that map to our search terms? Do we need more content in the middle of the funnel stage to bring people from one stage to another? Mm-hmm. Yeah, I mean, that makes sense because even just off the top of my head, I know for our funnel, there's a huge disconnect from people who, you know, uh visit our website uh to people who actually raise their hand and say, I want to work with you.

Once people raise their hand, you know, our close rates are really great because they know what they need and they know that we're the ones who can help, but it's getting people to that stage of okay, that was really interesting information, and I that I write, and then I go away to I know that I need your help. And that's the piece of the funnel. Um, I guess it's sort of like that like top to middle piece that definitely needs the most work. Yep. One other thing to think about is also when you look at the topics that have very high volume and have very high ranking difficulty, those are things you're not going to win on in SEO.

Ain't gonna happen, right? Um, you're you're not gonna beat McKinsey at being McKinsey. Uh, you're not gonna beat McKinsey at uh big data analytics. But where this data becomes becomes very helpful, then is to say, okay, if I did a predictive analysis on big data analytics, I know I'm not gonna win in search, but could I use that to inform the topics in my newsletter, right? To for the audience I have managed to retain, just serve them up something like, oh, you guys know this too.

Uh it's not just McKinsey that that knows, like, oh yeah, you know, a lot of people know big data analytics, it's not that special. Um, but if you can intercept the search volume and maybe publish a week or two or three weeks before the trend peaks, you're using essentially McKinsey's own competitive SEO data against them by anticipating the audience and beating them to the punch. Mm-hmm. So really I think the moral of the story is you can't just write whatever content you feel like and expect to get the audience from your competitors. You actually have to do a fair amount of planning and research and data analysis before you even get to the content writing phase, because you could, like me, admittedly, be thinking about the exact wrong competitors and going after the wrong kinds of keywords and then sort of scratching your head going, why aren't we getting the results?

Mm-hmm. And if you're if you one of the things that people forget about uh a lot of these terms, when you look at the super high volume terms like change management, 17,000 searches a month, 95% keyword difficulty, right? Again, you're not ranking for change management anytime soon. But if you create a post using, like we talked about last week, answer the public, where you have much longer tail terms like how do I implement change management in a small business? How do I implement change management in real estate?

How do I implement change management in a travel company? You will check the box to a degree on the core term, but you can pick up a lot of X extra traffic that is much lower in competition because it's not even on there, right? None of if you look here in what they're ranking for, none of these are long questions, right? It's simply not what they are ranking for right now. So you can use these big audacious terms, change organizational change management, 94% difficulty, organizational change, 95% difficulty, but splitting up to something that's your own spin on it, you can rank for those longer term questions.

And we know, thanks to you know these lovely devices that live on our desks and our smartphones that search queries are getting longer because people are asking in a in natural language. So, what can we do to anticipate getting those terms again with predictive calendaring so that we know when to have our content in market? The bigger the the the higher the keyword difficulty, the lower in the funnel that content should go because the lower in the funnel is we have more control over it should be in things that are podcasts and things that are emails that go directly to the audience that don't rely on Google as an intermediary. Um, and you can try and capture sort of that top and middle funnel on the on the super long tail stuff. I got a lot of work to do, Chris.

I mean, that's really that's really the I mean, but that's a good thing because it definitely speaks to, you know, at least at Trust Insights, we try not to be stuck in our ways, and like this is the way we've always done it. You know, it's daunting but also exciting to have to rethink about the way that you're approaching stuff because it means that you're paying attention to you know the latest and greatest tools and techniques. Yes, you have to maybe redo some things, but hopefully, you know, you can build upon what you've already done and not just completely start over. So I definitely have some ideas uh of what we can do with this information. And you know, when we get into our, you know, planning for the company sessions, then this is the information that we'll be using to do that.

But it's definitely, you know, it's exciting. Um, because it's I feel like it's just all it's green space in the sense of we haven't done it yet. It's obviously not new to our competitors, but to us, it's like, well, I mean, we just kind of get to do whatever we want and write about it however we feel like it. So like that's exciting to me. It is exciting, and I uh it one of the things that I think is so important for for us as a company is looking at those, you know, those big bottom-the-funnel terms like big data analytics, for example, and making sure it's it gets into publications because we have I have lost track of the number of people who said to us, oh, I didn't know you did that.

Right? Well that's that's our fault because like we didn't tell you we did that too. So uh but these topics give us a reminder to say, oh yeah, we do that too. Um and it can go in our publications, even if we never rank for it a day on Google. We don't have to.

We just we know it's of interest and we know that our audience has an interest in it. Um if our audience is you know, if we're getting the audience that we want. So from a prioritization file uh perspective, so as we as we talked about, the do that two by two grid, your top of the funnel stuff is gonna be your adjacent queries that a competitors are ranking for. Um your middle funnel is gonna be those intent terms that the competitors rank for, and then the bottom of the funnel is gonna be um either branded stuff or stuff that you're not gonna be able to compete with in SEO, but you know you can reach your audience in other ways. So that's how you prioritize.

So we've looked at what SEO competitive analysis is, and I think it's really important that we emphasize it's not you're using SEO data, but it's not just for SEO. It is for any kind of marketing where you want to know what's inside your customer's head. Um looked at how to extract the keywords and topics, and we just talked about how to prioritize them. So any any final parting words? John, you have a long to-do list now.

Get started. That's it. Yeah, it's get back to work. That's always the the punchline with this show. Um and just a friendly reminder for our viewers, this is our last show that we will be broadcasting live on Facebook.

So if you're looking for us, you can find us on YouTube at trustInsights.ai slash YouTube. That's our YouTube channel. And uh this show always goes out live over that channel, and you can always catch the replay there as well. Exactly. And always find on the blog over TrustInsights.ai.

Thanks for tuning in, folks, and we'll talk to you next week. 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. And our weekly email newsletter at TrustInsights.ai slash newsletter.

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