From The Vault - Natural Language Processing for SEO

MICHAEL:
Hi guys, Michael here. Do you want a second opinion on your SEO? Head to theseoshow.co and hit the link in the header. We'll take a look under the hood at your SEO, your competitors and your market and tell you how you can improve. All right, let's get into the show.

INTRO: It's time for the SEO Show, where a couple of nerds talk search engine optimization so you can learn to compete in Google and grow your business online. Now, here's your hosts, Michael and Arthur.

MICHAEL: Welcome to a very, very special episode of the SEO Show. Now I know I sort of say that every week, but this week it really is special because after 23 episodes, we've got Arthur in the house. Hello. We've got Michael in the house and we've got Rob in the house.

ROB: Yes, that's me.

MICHAEL: Rob is our first guest.

ROB: Hello.

MICHAEL: Yeah.

ROB: Oh yeah. I'm good. I'm good. I'm good. Um, yeah.

ARTHUR: I'm glad to hear you're good.

MICHAEL: Maybe I should explain a bit more about who Rob is and why he's here.

ARTHUR: Yeah, it's a good idea.

MICHAEL: Well, today we're going to talk about natural language processing and Rob is a guru when it comes to natural language processing. Right. So maybe tell us who you are and what you do.

ROB: Yeah. Um, I'm Rob. I am the SEO specialist at LocalDigital. Can I confirm?

ARTHUR: Yeah.

ROB: Can I confirm?

MICHAEL: The man of many nicknames?

ROB: Oh yeah, yeah, yeah, yeah. I go by many names, including Speed Demon. They call me Defense. Ridiculous. Ridiculous.

ARTHUR: A bit of context would be good maybe. Or maybe not, let's not, let's not go into it.

ROB: No, let's put a bit of mystery behind it. Exactly, exactly. And most recently they call me Annihilation Nation.

ARTHUR: There you go.

MICHAEL: We still don't know who they are, but one day we'll find out. I have a feeling they is Rob. But anyway. The reason we're bringing him on, when he's got that many nicknames, he must know a thing or two about language, right? And we're gonna be talking natural language processing because this is a little bit of a cool thing in the SEO world. And it's something that we've been having quite a bit of impact with when it comes to optimizing our client websites, so much so that we've built a whole tool based on natural language processing to make our jobs easier, which is where Rob comes in. He was the guru behind that. So if you wanna check that tool out, quick plug, go to natch.ai in your favorite web browser. But anyway, Rob, let's talk natural language processing. Cool name, sounds fancy, but what is it?

ROB: So what is natural language processing? Essentially it's like a sub-branch of artificial intelligence and computer science. The main use of it, I guess, for Google is to understand, I guess, human language. In regards to content, so traditionally Google would look more at the keywords, understand and rank. content, but now it's a lot smarter. And it looks at the, it uses NLP to understand the intent behind sentences, the tone behind it. So whether or not it's positive or negative, basically, and it can identify keywords and phrases in it and assign what's called entities. So like whether or not it's a person, it's an event. Placing, organization, all those.

MICHAEL: So I think that, I think the big thing with that is it's Google going beyond keywords. You mentioned keywords before.

ARTHUR: Google evolved basically. Yeah.

MICHAEL: Yeah. It's part of them becoming Skynet and soon they'll be just talking to us as an, you know, totally natural conversation with Google. It sounds like our dream as SEO. Yeah. But, but like basically if you think about like we've spoken in the past about Google's algorithm or it's crawlers reading content and looking at keywords to figure out what that content's about.

ARTHUR: Yeah.

MICHAEL: NLP is that on steroids.

ARTHUR: Yeah. So taking the next step away from just stuffing keywords on a page, actually making sure that it makes sense and trying to understand it. Yeah.

MICHAEL: Yeah. Um, so bit of history, this really became a factor in about 2019 when Google released BERT. So SEO, the SEO world does what the SEO world does when that happens. Panic. Have a mild panic, whinge about it on Twitter. And then a whole bunch of different SEOs around the world will reverse engineer what happened and share that knowledge. And it was pretty much widely agreed when that happened, that Bert was looking at content, like, you know, the depth of content, the quality of the content, the matching sentiment to the search intent, you know, of, you know, the content matching that search intent. And basically that's NLP at play. So when we're talking about it in a Google SEO sense, really NLP is in that whole Bert wheelhouse. Does that all make sense? Am I right in saying that?

ARTHUR: Yeah. Yeah. I mean, it makes sense to me. Hopefully it makes sense to the listeners. I think so.

MICHAEL: Yeah. That's what NLP represents basically. So you mentioned entities before, places, things, that sort of stuff. NLP's job is to select and evaluate these entities in your content. So like, let's say you put up an article about a movie, it's going to read all of that and then try and extract the entities related to that movie. So it might be horror or category directors, that sort of stuff, right?

ROB: Yep. I also just realized one thing, the Bert algorithm update, it's part of my name. It's part of my name.

ARTHUR: Wow.

ROB: Robert, there you go.

MICHAEL: That's a new nickname. It's meant to be. A new nickname has been born.

ARTHUR: They call me Bert.

MICHAEL: I call him Bob sometimes. Yeah, Bob's good. Well, there we go. That's the groundbreaking element of this episode. So let's come back to the concept of entities and salience, right? Tell us about like how that works. You know, what is salience? We know entities are the people, places, things like it's just categorizing the content, but what's the salience aspect to that?

ROB: Yeah, so there's a few scores that Google assigns to the entities. So the standard is essentially how important that entity is in the grand scale of things when compared to the rest of the text.

ARTHUR: How does it work on a scale of 0?

ROB: It goes from a scale of 0 to… 0.0 to 1.0. Yeah, yeah. That's it? 1.0, yeah. Obviously the higher the better. Yeah.

MICHAEL: The higher, the more salient it is.

ROB: Yes, that's it. There's also the sentiment score as well. And there's also like a score overall, which kind of represents the tone of the sentence and the keywords itself. Okay, so the entities itself. There's also the magnitude, which is how important overall that. that entity is. But yeah, so generally, Google is pretty smart at picking up like how positive or negative a tone as an entity is. So if I say or import something that says like, this Michael is very happy.

MICHAEL: Amazing.

ROB: Amazing.

ARTHUR: Michael's amazing. Yeah. Michael's amazing. Some sort of positive sentiment within that sentence, then it gives it a higher score.

ROB: Yeah. Then you will likely see like the overall sentence have quite a high sentiment. But on the contrary, if you do something that Google might not understand in terms of like context, maybe like Michael is, Not amazing. On top of the moon. Actually, Google probably understand what that is. But like, I guess the more- Something abstract. Something much more abstract. Google might not be able to pinpoint the sentiment assigned to that. And then we just give it like a more, like a either neutral, zero, zero, or like could potentially go negative, which depending on your content, you probably don't want that to happen. Right.

MICHAEL: All right, so basically with NLP, it's looking at these entities, it'll categorize the entities, it will give you salient scores, magnitude scores, sentiment scores, all that stuff. Which is all well and good, but I guess let's maybe take a step back, right? Because this happened a couple of years ago, this BERT update. The reason we're looking at Google's NLP is it's basically a tool or artificial intelligence that Google makes available to developers, right? Like you can pay Google to use this tool. So, you know, back in the day when we sort of learnt about this BERT algorithm update and then we were seeing all this chat about NLP, we did a bit of digging and investigation ourselves. You know, let's have a look at this tool. And we jumped on the NLP website and the website itself was saying things like in the marketing material on the site that like, natural language processing helps Google products like search.

ARTHUR: Didn't it say it plugs into the algorithm basically? In a way.

MICHAEL: In a way. It said NLP sort of helps search like products. So it was vague, but it was also saying NLP is involved in search. Yeah. So what did we do then? Like we started testing, right? This is where Speed Demon Bert came up with basically the way we use this NLP in optimizing content, right? So maybe if you can walk us through the early days of us testing and playing around with NLP, how'd we go about it?

ROB: Right, so the early days were having fun in Google's little demo. Tedious little demo. Very tedious little demo. It was very tiny. They had a small preview window. So the demo was like on the NLP website. Yeah, on the NLP's website. And basically you would just import your, well in our case, the client's content from the site. And it was just very, in terms of the process, it was very, very.

ARTHUR: Well, it would analyze the content and spit out all the recommendations, but you were dealing with a tiny little content box, probably 300 by 200 pixels. And it was extremely hard to edit within that box. So it was just a regular text editor. And then every time you wanted to rerun the content, you had to go back and it was just a very manual process. So you had to remember all the salient scores for each run. What else? I remember- It was a preview tool. It was a preview tool. It makes sense. But there was also, you only had a limited run, so you could do it maybe 10, 15, whatever, how many times before you got locked out. And then you just had to use a VPN if you wanted to continue doing it. It worked, but it was just limited in what you could do, basically.

MICHAEL: So let's say we might take 500 words of copy, put it in this box where you can only see one paragraph of that copy in the box, run it, see the scores, and then think, well, maybe we want to change like a couple of paragraphs here to try and improve our scores or influence the scores. And then you'd have to go back and redo it. I remember Rob's notebook that he had on his desk.

ARTHUR: Every time he'd do a run, he'd sit there and write down the changes that he made and how much it impacted what keyword. So it was super manual to the point where it was, you know, pen and paper basically at times.

ROB: I found like multiple ways of trying to doing it and trying to find which way it works. Sometimes I took screenshots and then I would print it out and then I would mark it out.

ARTHUR: But it got confusing. It got confusing, yeah.

ROB: And then sometimes I put it in the notebook, write down the Cs, which ones changed, I put a plus one here, a plus two there, this one shifted this way, I've made these changes. It's like analog SEO.

MICHAEL: Yeah, yeah, yeah. If we ever go into like a, no actually, I was going to say, if we ever sort of go into a dystopian future with no internet, you could still do SEO on pen and paper.

ARTHUR: Do you still have that notebook? I do. Maybe one day it will be worth something.

MICHAEL: It's already worth something. Maybe we can share a photo of the notebook on Instagram.

ROB: How far it has evolved. From paper to now, digital masterpiece.

MICHAEL: So the big thing I'm hearing there, the pain points was, The tool's cool. We're using it to understand sentiment and salient scores and entities, but it was an absolute pain in the ass to use in any meaningful way, in a scalable way. What we found when we were running copy through this tool is that if we tweak the copy and influenced the entity scores to be similar to like the top ranked sites in a space or, you know, if keywords were going after, we were getting results, the rankings would improve. So that's why we were going through this laborious process because, you know, we're able to get results for our clients, but it was a pain. So we wanted to be able to easily compare things and keep track of what's going on without having to resort to printing out worksheets and writing on them and all the likes. So we built Natch to address these pain points, right? Because no tool existed. Natch. Natch, yes. No tool existed that we could find that did that, right?

ROB: Yep. After extensive research, we were like, this tool, just doesn't exist.

MICHAEL: So, well, maybe, maybe we can give a little example of rankings improving or, you know, you know, I, I think you had an example of a, uh, I won't say the client's name, but there was that client maybe, maybe give a walkthrough of the process process. Yeah. And the results that we saw and why we felt that justified us investing as much time and effort and expenses we have in creating this tool. And then we'll talk about the tool maybe.

ROB: Yeah, so I guess it's a particular client. Can we say the niche?

MICHAEL: Doesn't matter. Yeah, they're a lead generation business in like a higher, they do higher products.

ARTHUR: That's all you need to know.

ROB: Yeah, essentially. So the website, I think in particular as well, the client didn't want to make too many visible changes in terms of the content that the user will see. So a lot of the SEO content is placed behind like a read more or a recording. And yeah, we spent a lot of time using the natural process to… the natural process to optimize this content because the client had previous experience in SEO or another agency and was pretty turned off by the fact of like keyword stuffing and stuff.

MICHAEL: So their copy in the past would have just been outsourced overseas and just read like absolute rubbish shoved on the site. Yeah. There you go. Your SEO is done.

ROB: Yeah, so I guess our way around it was saying, we're using Google's natural language, so we don't have to resort to any obvious keyword stuffing. And so what happened really was that I ran, I don't know, probably hundreds of tests on the coffee as a whole. The manual way? The manual way. And yeah, I was comparing it to the top competitors in terms of the Etsy's, because their previous copy in terms of Etsy's was all over the place. And a lot of it was irrelevant to what the content should be about. So if in this case, they're about higher, let's say they had something completely irrelevant, like mobile phones or something.

ARTHUR: So the competitors, I guess the entities were more related to the keyword that you wanted to rank for.

ROB: Yeah, so for example, let's say since the service is a product, then the consumer good entity type was what the competitor said. So we would have to, the reasoning behind it, the logic behind it was that if we could get the entities up there in that same category type, entity type, then they should rank well. And yeah, especially after we rolled it out, after various, many changes, we saw their rankings go up quite a bit. So two weeks after we rolled it out, they were on average on the sixth and seventh position. And two weeks after they were on the fourth position on average. And then two weeks after that, we rolled out another change. And they've been steadily going up ever since. And now they're in position two on average. So doing very, very well.

MICHAEL: And that's weird. maybe a little bit of link building and the like, but obviously we'd roll these changes out in the site, get Google to come back and recrawl it and rankings instantly improve.

ROB: Yeah. So the funny thing is, is that this client has been with us for a while, so like they've been continuing to doing link building and stuff. So to isolate, I guess. Yeah. Yeah. That was one of the main, the main changes we did. And it was after the January, core algorithm update as well. So I guess that kind of plays into the fact that, you know, Google is massive algorithm updates are likely going to affect how they read content. So the timing of it all just worked out as well.

MICHAEL: Yeah. And so with this, like, It's very hard to test this stuff in isolation because with SEO campaigns there's always other stuff going on, you know, technical optimization, your link building and the like. We just had a hypothesis, you know, you run this content through the tool, you get the entities and salient scores and stuff in the same ballpark as the top-ranked sites. And you should improve rankings. And we've just seen time and time again, that that works, it does work. So, um, that's generally the reason we created the tool we did and, and the, the, the process that we went through to get here. So maybe we should talk about Natch and, um, how it solved all of your woes when it comes to things like, you know, very small preview windows and not being able to track changes and not being able to compare and sort of easily review what's going on. So, um, Walk us through Natch. Give us a little brief history of Natch.

ROB: So Natch, yeah. So yeah, as mentioned, there's quite a few pain points. One of the main things that was addressed with Natch is that it now has a huge preview window. So you can actually see like 5, 10 paragraphs when you type something in. And it just makes things a lot easier when you need to go back and you want to change something. Another core thing that was added was the comparison function. So now you can actually run a test and then you can go, let's say run test B and then you can go and test it back to the original test and you can just keep doing that.

ARTHUR: I was gonna say, I guess how it all started was we were just brainstorming. Like imagine we had this tool that could do all these things that we can't do now. So basically, Rob started putting together a wish list of all the things that he would love Natch to be, or NLP testing to be. And that's where it all started.

MICHAEL: Yeah, so there's tools built on real-world SEO agency process being improved and optimized, I guess. Yeah. Maybe we should say the name Natch obviously is a slang term for natural, natural language processing. We just thought Natch was short and sweet. We can say, Oh, has that content been Natched yet? Yeah. Or this client's going to come on board. Let's Natch them. So, you know, it works pretty well. Yeah. I feel. It does.

ROB: Yeah.

ARTHUR: Anyway. It all started from a conversation really. Yeah.

ROB: Yeah, I think, yeah, we brainstormed as a team as well, like what we would want and how to make the process a lot easier. And yeah, it just came to fruition.

ARTHUR: Yeah. One day I think he just said, let's build it. Yeah. Yeah. Yeah.

MICHAEL: Pretty much. Pretty much. So let's, let's talk about what we've built. Like you put the content in, you run it through notch and then it will spit out all of the entities and the salient schools and all that good stuff. Then you can maybe tweak the copy based on what you saw there and run it again. And it will show you what all the new scores are, but then you can compare the two and it will show comparisons. So like next to each of them, what the scores are and how they've changed. Right. And you can segment it down by different entities and see where they are in the text and the like, and very visual and quick process to get a feel for what's going on with that content as you change things.

ARTHUR: That's a really cool feature of it. So being able to click on an entity and then highlighting it in the text so you can see where they are on the page and how they grouped. And that makes a massive difference because you can then try to group different, I guess, clusters of keywords together or different entities together, which you couldn't do before. It was just impossible to kind of. Maybe not impossible, but it would have been super hard to do that without it.

ROB: Yeah, because Google clusters a lot of the entities together and basically being able to click on it and highlighting the ones that are in that particular group makes it a lot easier to even optimise for that entity so you can go through and see what individual sentences are impacted. Yeah.

MICHAEL: I found that really helpful. Yeah. Even just the ability to leave like each run, you can put notes on it. So you can sort of keep track of what you were thinking at the time or, you know yeah, probably that's, that's sort of how I've used it. Just drop a note there. What I was thinking, what I was planning to test at the time. It's very visual. It's all stored there and you can go back and look at it in the future if things change. So.

ROB: Oh, you also can keep track of the changes made, so if you made a change to the copy of content and you compare it to the original, it will actually show and highlight the text changes.

MICHAEL: Right, yeah, little green highlight for new stuff, red for stuff that's been deleted. That's it. Very visual, very cool.

ROB: Exactly, because sometimes you're not going to be doing all the testing in one day, you'll be doing it across multiple days. It just makes things a lot easier to keep track of and then roll onto the client side once you're happy with it.

MICHAEL: Maybe we should talk about some of the interesting things we've seen when changing text, because it's, you know, it can be as little as a capital letter or a full stop that really changes the scores or the entities and has an impact on rankings. And that's why we, Like doing it the way you were doing before with notes and all that, that's why this new version with like a sort of visual tracking of what's been changed is so important because it can be such a minor thing that's changed, right? So maybe, what are some examples of that, you know, that goes on?

ROB: Yeah, like you mentioned, capitalization actually goes a long way when it comes to even Google understanding what type of Etsy it is. For example, let's say I do flowers, for example. I do like our flowers, lowercase, lowercase f. I've seen it show up as just the regular other entity. But then if you capitalize the F, it'll show as a consumer good entity. So even that, it changes quite a bit. Some other ones could be like putting an N- or an M- instead of a full stop, so you're kind of extending the sentence. So it's another, I guess, little That's it. You can sort of combine the two sentences together, and then that'll kind of change quite a bit of how Google reads. So there's a lot of really small things, like I think I've even seen like, what's that button called? It's like the semicolon, but it's got the little comma at the bottom.

ARTHUR: Oh, I don't know. The, the semi-colon with the little. Yeah.

ROB: It's basically underneath your P button. Yeah. Basically. Yeah. So there's a lot of these different little symbols that you can use and it would just change how Google reads it.

MICHAEL: So, which is funny, right? You wouldn't think that those things have the impact that they do, but they do. They do. They do. So what we should make clear, I guess, is, you know, there's tools out there in the SEO world where you can chuck in a URL and the tool crawls it and then says, Oh, go change all of this and it should get you in the ballpark. This tool is much more manual. Like it, it's part art, part science. You know, this tool makes it easy to see what NLP is saying, the entities and the salience and all that are. It's easy to track everything, but it relies on you as the SEO to use your thinking and logic. And I guess creativity to change the copy and change things up in a way that you think is going to impact things and test it and keep trying. And it's not just a, you know, one button and done process, right? Yeah.

ROB: For sure. I think like experience using NLP plays a big part of it, because the more you use it, the more nuances you pick up. And I think that will really differentiate between the people that use the tool, because obviously it doesn't spit out any recommendations. But yeah, I think the more you use it, the more you'll kind of have a little bit of an understanding of how Google is interpreting content. But you also find things that are going to be like, oh, what?

ARTHUR: Why? Well, you've got your little hints and tips cheat. Yeah, yeah. Which you're not going to give away. Yeah.

MICHAEL: So we've got all internal processes and docs that Rob's built based on his experience doing a lot of this stuff that is easy to use. But it's never going to be a tool where you just hit a button and it gives you recommendations. Like it's a tool for you to get in there and grind it out and find that really fine tuned piece of copy that is, you can Google all it needs to see to be the same as the top ranked sites basically.

ROB: I think it also like explains it clients.

ARTHUR: Yeah. I was going to say that. For me personally, being able to show little changes and how much they impact certain scores of different entities has been massive because a lot of the time without being able to share that to a client and you send them some copy with some minor changes and they'll look at it and be like, well, you've just, you've barely changed anything. And they might think you're crazy. If you can kind of demonstrate that the changes you have made to the copy have influence these scores and these keywords and the magnitudes and all that, then it starts to make a lot of sense. And every client that I've shown it to so far have been really impressed.

ROB: They just go, wow. Especially when they can see how many test runs that you've done, then the client will be like, It will help the client understand how much time goes into content optimization.

ARTHUR: I think that's a big thing as well, because they don't realize how much time actually goes into it. How did we actually get to this point?

MICHAEL: Yeah, you just read an article. Well, that should have taken 20 minutes.

ARTHUR: Yeah. But really, we spent two hours busting our brain trying to get these entities to push up. So for that alone, it's amazing.

MICHAEL: Yeah. So it is a, it's still a manual process, but this tool, it just makes it much more pleasant to do. Well, maybe that's a good segue into talking about the change monitoring aspect of the tool. Cause it's like what we've found with clients is they are prone to just adding things to sites or changing things or deleting things or all sorts of different modifications to a site. And that really hurts when we've been matching the copy for hours and getting it perfect to have things change. They might go in there and make wholesale changes to the copy. Yeah. So another feature we added to the tool is change monitoring where once we have fine tune copy and put it up on the client site, we enter the URL of that page into the change monitor and then natural go and crawl that page and keep a log of it in the database. And then it goes back daily. and crawls it again. And it's looking at things like meta title tags and description tags and page copy and heading tags and robots tags and XML sitemap and whether it has HTTPS, download speed, like all sort of key SEO factors. And it keeps it all in the database, and then if anything changes, it will alert us. So it alerts us via email. We've got integration with Slack, so we'll get pinged on Slack. We've also got a Zapier webhook, so you can build all sorts of automations on the back of it. But we sort of think of this as like insurance policy for your website, right? Because if you're investing all this time, particularly as a client, you might… you're obviously not always going to be aware that all this effort's gone into it. And so sort of finally tuned. So, um, you go change things and undo it and it could be weeks or months before it's picked up. And I can tell you some stories about that. Oh yeah. Oh yeah. So, and as an SEO, you, you want to be proactive, like you want to be on top of it. Definitely. Knowing and so you can reach out and say, hey, we've noticed you've changed this.

ARTHUR: Yeah. Well, it looks great. Yeah. And like in reality, I look at client sites every day, but I don't look at every single page on their site every day. So it could take me upwards of a week to or longer depending on the site. Yeah. To know that they've changed something. And by that point it could be too late.

MICHAEL: Yeah. And when we're talking like full stops and capital letters having impacts on these salient scores and entities and the like, if the client makes a change when you're not going to pick up on it and it could, it could be until their rankings go backwards and then you've got to try and reverse engineer what's happened.

ARTHUR: And by that point they're mad at you. What have you done? Yeah.

MICHAEL: I don't know. And then it turns out they've changed something. So now make sure that that doesn't happen. So, I guess that we were sort of trying to look at the whole life cycle of this process, right? We get the client on board, we're looking at the competition, we're trying to improve things, get it in the same ballpark, get it live and then make sure it stays that way and things don't change.

ARTHUR: Yeah. That's just taking care of all of that. Did you mention that it shows you what they've changed as well? Well, yeah.

MICHAEL: You kind of, yeah. It's sort of the same process as the NLP tool in that it has the original snapshot and it keeps a log of all the snapshots of changes and you can easily compare them and it will show you what's changed. It has little red and green indicators and it just makes it easy to jump in there. You can even just click view all the copy on the page and see what the copy is on the page and what it was and what's changed. So it makes it really good to quickly fix things, to be proactive, to reach out to clients. If you get pinged on Slack that something's changed, you go and see it and then quickly call the client and say, we've seen this has changed. They'll be like, wow, like you're really on top of things. So just from a client services point of view as well, it's a really cool feature.

ARTHUR: It is. It is. Sounds like you love it more than Natch or NLP.

MICHAEL: It's all Natch. It is. Natch is a multifaceted FCO suite. So, um, I guess what else is there to chat about really? Is there any, any takeaways you want to talk about when it comes to Natch or NLP?

ROB: Um, yeah, Google is very, very, uh, interesting in terms of like how it interprets concepts. Sometimes you'll see things like, Why is it happening like that?

MICHAEL: Sometimes you scratch your head thinking why they're not as smart as they might be made out to be.

ARTHUR: Well, it's a bit of both. You know, you look at it and you're like, wow, the algorithm's really evolved. And then you do things like add a random full stop to a sentence and you'd be like, okay, maybe not.

ROB: Yeah. So yeah, it's pretty, yeah. I mean, it's still evolving. So, I mean, it's pretty interesting to see that AI has gotten like so far that it can understand the tone behind it. It's because they're listening to us all the time.

ARTHUR: So they can, you know, capture all that data and analyze and get smarter. Yeah.

MICHAEL: Well, um, I think that's been a good intro to natural language processing and where things are at. Like it's a bit of a, as we said, part art, part science, like a lot of things in SEO, like we haven't done hardcore scientific testing to prove anything in this. It's more, we've, we've had a hypothesis, we've, done a bit of testing and we found results are positive, but you can't put your finger on exactly what's going on with it when you do it. But we have found the process is that if you can make your copy similar in terms of entities and salience and magnitude and all the rest to the top ranked sites, generally you'll see a ranking improvement. So it's worth the time and effort to do it, right?

ARTHUR: Correct.

MICHAEL: And it's where Google's headed. It's moving away from keywords. Keywords are still an important concept, but so too is NLP and understanding sentiment and all the rest of it. And it's only going to get more important. So if you are wanting to be on the cutting edge of SEO, then playing around with NLP, playing around with the preview tool or going to natch.ai and having a look at the tool we've got there is well worth it, right?

ROB: That's it. National day.

MICHAEL: I see you there. All right. Well, Rob, how was it? How was your first time on a podcast?

ROB: Yeah, pretty good. Um, yeah, I mean, uh, this is very, very fun. Um, I am the first guest. You might become, you might become a repeat guest all the time.

MICHAEL: Well, anyway, guys, thank you very much for listening as always. And if you liked that, like Rob's crew that are tuning in, give us a subscribe, give us a like, give us a review, all that good stuff. And until next time, Rob. Until next time.

ROB: I'll see you guys next time. I'll definitely see you guys next time. We'll see you back at the office. All right.

MICHAEL: Thanks for watching.