ABOUT THIS EPISODE
The SEO landscape continues to evolve rapidly, with AI tools revolutionizing how professionals approach optimization strategies and workflow efficiency. Edd Dawson revisits his SEO tool stack from 18 months ago, highlighting the dramatic shift toward incorporating Large Language Models like ChatGPT and Claude into daily operations.
• Comparison between current tool usage and tools mentioned 18 months ago
• Large Language Models now essential for research, coding assistance, and strategy planning
• Google Search Console data increasingly vital for identifying content gaps
• Keywords People Use platform integrates with GSC to provide enhanced data insights
• N8n.com workflow automation tool creates efficiencies when combined with AI
• Explanation for why traditional SEO tools like Ahrefs and SEMrush aren't necessary for Edd's approach
• Focus on using tools that align with a philosophy that SEO fundamentals matter more than complex toolsets
SEO Is Not That Hard is hosted by Edd Dawson and brought to you by KeywordsPeopleUse.com
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"Werq" Kevin MacLeod (incompetech.com)
Licensed under Creative Commons: By Attribution 4.0 License
http://creativecommons.org/licenses/by/4.0/
SHOW NOTES 🔗
TRANSCRIPT 🔗
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Hello and welcome to.
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Seo is not that hard.
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I'm your host, ed Dawson, the founder of the SEO intelligence platform, keywordspeopleusercom, where we help you discover the questions people ask online and learn how to optimize your content to build traffic and authority.
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I've been in SEO and online marketing for over 20 years and I'm here to share the wealth of knowledge, hints and tips I've amassed over that time.
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Hello and welcome.
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Back to SEO is not that hard.
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It's me here, ed Dawson, hosting, as usual, and today I'm going to be talking about what my current tool stack is.
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So this is the kind of you know the tools that I'm using every day to get on with something that I do.
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You know all the work that we do, and I did a similar episode to this.
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Oh, let let's look at the date on this episode.
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It was episode 43, all the way back on December, the 18th, 2023.
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So possibly about 18 months ago, and in that podcast.
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I'll just briefly run through the list.
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What I discussed was MailChimp, which is an email management software for managing email lists.
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I mentioned Canvacom, which you know for creating graphics, that kind of thing.
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Clickycom, which is an analytics software that I use for our websites.
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I mentioned Descriptcom.
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Descript is the software that I use to record the podcasts.
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Buzzsprout, which is the tool that I use to actually host the podcasts.
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Claritymicrosoftcom so Microsoft Clarity, which is another kind of analytic software, but it helps with screen recordings, that kind of thing.
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I mentioned Dropbox, which I presume everyone's heard of, for sort of remote file storage.
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Trello, which is what we use for managing other projects we work on at Keywords People using our other websites.
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I mentioned keywords, people use itself, obviously and workspacegooglecom for things like, you know, spreadsheets, docs, all that kind of thing.
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Now I pretty much still use all of them.
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Um, they're all still reasonably important to me.
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I can't think of any that I've dropped.
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But what you'll probably notice from that, there is no mention of any AI tools in that.
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You know ChatGPT back then was around, had been launched.
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Yeah, I mean, at that point it had been launched over a year.
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I've not listened all the way through the podcast to see if I even mentioned ChatGPT, but it obviously was still quite a way off my radar in terms of it being an everyday tool that I use.
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So, yeah, that's the big difference I'm seeing in um the tool stack between now and then.
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So there's another, um, notable, notable one missing there, which is google search console.
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Now, I have used google search console for many, many years, but it's only more recently I think this has become more important to me, and that's for a couple of reasons which I will talk about shortly.
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So, yeah, first of all, let's think about what's in there now that was missing back then.
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And yet the clear, big, obvious one are large language models.
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Didn't mention any large language models then, and now I, you know, I don't think there's a day go okay, day goes by now without using chat, gpt, and regularly I also use claude as well from anthropic and you know, I think the difference is that they've come on significantly in their capabilities since 18 months ago.
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I don't use them for content creation.
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I think back in the early days of LLMs, the main use that people were using them for was content creation and putting content online, sort of for blog posts, all that kind of thing online creation, content creation and as I you know, it was impressive.
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It was nowhere near as impressive as it is now content creation, but it was still reasonably impressive.
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And but people were abusing it and google was just slapping it down all the time, and so I never wanted to use it for content creation in that way, so at that time I wasn't really using it.
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Where ChatGPT has really come into its own is with the models that have come out more recently and the fact that you can use it for everything that you might have used search for before.
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So, for example, if I'm trying to work out how to do some coding now, if I've got a coding problem, I will pretty much always go to ChatGPT to try and help solve this problem.
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If I'm trying to build something new, I'll go to ChatGPT and talk about the problem I'm trying to solve and what the solution might be for it.
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I will go to ChatGPT for sort of research into competitor research for products I'm thinking of building.
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Or if I'm looking for a new tool or a new product to solve a problem, I will talk to chat gpt about it first.
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I still might end up going to google, especially if it's that thing coming to a point to buy, but it's the kind of thing where I'll talk to chat gpt first.
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I'm trying to do something in aws.
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We use amazon web services for all our websites.
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It's perfect.
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Perfect to talk to ChatGPT about it.
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It knows it inside out, and the same with any other SaaS that I'm using.
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If I try to do something in Canva, I'll talk to ChatGPT.
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So this is where these large language models are really coming to their own.
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I'll even talk to ChatGPT about strategies worth thinking about implementing, ways in which we might develop products.
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It's really good to bounce ideas off.
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It's really good, now as well, that you can obviously share your own information.
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It can ingest information that you produce.
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I've done things since by giving it my entire transcripts of all our podcasts so it gets an idea of what I know about and what my views are on certain things.
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So when it's given me answers and it can sort of it, so when it's giving me answers, it can look at it from that perspective.
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So, yeah, massive, massive part of my day now is with Chet's GPT and yeah, I think I will be much less effective now without it.
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And that's not to say I haven't got its problems.
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That's not to say that it's not going to you know things.
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That's going to get even better in time.
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But yeah, definitely a big, big miss there.
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And claude is also good.
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Tend to use claude more for coding.
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And then what's come off the back of these large language models is now all the other tools that are now being built to really work with those large language models in really innovative ways.
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That's things like cursor, which is an integrated development environment for coding, where you can now actually do what I spoke about in just a podcast a week or so ago about vibe coding, where you can actually now use things like Cursor.
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And I have also used Replit, replitcom, which is another similar system where you can just talk to it about what you want to code.
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You can still code traditionally within them as well, but you can do a lot of it by just talking to them, and they're really interesting tools.
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I use them, as I said last week, just for prototyping things, not for production ready stuff.
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Yet um, that may change in time.
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Who knows um and?
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But there are definitely people out there who, especially in the, there's lots of games seem to be coming out that being created with those um tools and doing doing this kind of whole vibrating thing.
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But those are definitely two other things that are now part of my tool stack that I want to try something out.
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I will use systems like that to sort of accelerate prototyping um process and getting a lot of the sort of the legwork done.
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That's really quite boring to code, but you get it done for you to do that prototype, so it's really really cool for that.
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The other bigger mission from my podcast 18 months ago was, yeah, google search console, um, which I I really probably should have been in that list 18 months ago, but, um, maybe I was thinking of paid tools or something different.
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Mine, I couldn't have been because clarity is free.
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So, um, yeah, no, yeah.
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So google search console.
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Now I've been talking about that a lot recently in a lot of past.
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A lot of the past year I've done I've done episodes on google search console.
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Um, yeah, it is a really important tool because you're just getting that data out of google that you just can't get any other way.
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I think probably one thing that's changed obviously since then is using the API to get more than 1,000 rows out.
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That's the one big problem with Google Search Console out of the box, when you just use it at Google, is that you only get 1,000 rows of data.
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Now, if you've got a really small site, yeah, 1,000 rows of data isn't going to be a problem, but as soon as you quickly get past a certain size, you're going to be getting rows, you're going to be getting more than a thousand queries easily, um, or you've got more than a thousand pages ranking for certain things, then it's soon, you know, is soon missing data and you can get much more of that data by using the api.
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Now we've built into keywords.
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People use the search analytics tool, which uses the api API to get more data for you than you can get natively in Google Search Console.
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So, if anything, it's the data that's as important rather than the actual tool itself.
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That data is becoming more important and we're using that more and more ourselves and it's more and more embedded within keywords people use.
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Being able to proactively compare what people are searching for compared to the, the things you're actually ranking for, and it helps you work out where your content gaps are, helps you see where you're getting visibility, but you haven't got the content to sort of bring that visibility higher up the rankings, um, so, yeah, so that google search console piece and, yeah, and in keywords people use itself.
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Yeah, I sort of mentioned that there is the search analytics tool that is a it's, it's part of keywords people use.
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That is probably the part I use most now because you can use it, um, on a day-by-day basis because the the data is coming in all the time.
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You know, everyday fresh data is coming in and the content optimizer tool keywords people use where we, you know it's crawling our sites, comparing the content on our pages to the data that we're getting from google search console to find the opportunities for growth, um.
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And you know that's not just using other people too.
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So, yeah, I highly encourage you to look at those.
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Another tool that is new to my stack is n8ncom.
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I think I might have done said about it before, I'm not quite sure, but n8ncom it's a bit like zapier or makecom and essentially it's like a no code tool that allows you to build processes um that start off by being triggered by certain events and then they'll do some actions and produce some output for you um.
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But they can integrate um very well with lms themselves.
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So, for example, I've got um a process, um a flow they call them a flow in nan which will trigger every time a new one of my podcasts is released and it will take that podcast and it will transcribe it and then it will create drafts for blog posts, for linkedin posts, for email list posts from the content and there's a whole flow that it does that and it allows you to put sort of put building blocks together and it will send me these drafts or notifications of drafts and where to go and find them then if I can decide whether I'm going to use them, alter them, update them, etc.
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So it's really really good for automating parts of your business, automating parts of your flows, and the fact you can build it in with the lms now to sort of create content for you, make decisions for you or create agents with it.
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It's really really powerful and, yeah, I use nan over the others because it's open source.
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So there's a big, vibrant community who are constantly creating new nodes and for it, new functionality, for it that it's evolving faster than ones like zapier and such.
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So that's another one I'd recommend you look at.
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I suppose the only other thing to note is the absences in there um I.
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You may notice I haven't mentioned any other seo tools, and that's not because I'm down on them personally, but I have just never really found the need to use um things like ahrefs or hs or however you pronounce it, and semrush and those kind of things, because, um, they're just not tools that I need um.
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All the data I need I can get from google via the google search console.
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We can crawl, use things like people also ask, and google to complete the kind of stuff that we've put into keywords people use.
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So, um, I've not found any need for any other tool to do that yet.
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Clustering we've got that.
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We've built that.
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Um, you know, there's nothing I've found that meets my needs.
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It's one of the reasons why um, for building keywords people use in the first place was to to to build a tool that fit my philosophy, um, and share it with other people who are following a similar philosophy as me and trying to learn from the experiences we've had over the years to build up what works for us and hopefully it shares with others.
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And I'm not to say that you shouldn't use Ahrefs.
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It works for you, especially if you've got lots of clients.
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Ahrefs are so much more useful for you.
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But I've found that everything else on EDA can find for free or I've built a tool for it, so it's there for you and keeps people used, so, yeah.
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So I thought, yeah, that's it for today.
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Really, just to see how my tool stack has changed over 18 months, yeah, and that big change being how LLMs are now a big part of my day-to-day work, how I use them, um, and how, yeah, the fact it surprises me that they weren't in back then.
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I thought they might have come in sooner than then, and but maybe I just didn't rate them high enough to actually recommend them before now.
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Um, but yeah, so that's it for today.
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I hope you found this episode useful.
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Um, maybe giving you some tools to try out.
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It for today.
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I hope you found this episode useful.
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Um, maybe giving you some tools to try out.
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And you know, remember until next time.
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Stay curious, keep optimizing and remember.
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Seo is not that hard when you understand the basics.
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Thanks for listening.
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It means a lot to me.
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This is where I get to remind you where you can connect with me and my seo tools and services.
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You can find links to all the links I mentioned here in the show notes.
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Just remember, with all these places where I use my name, that ed is spelled with two d's.
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You can find me on linkedin and blue sky.
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Just search for ed dawson.
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On both you can record a voice question to get on the podcast.
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The link is in the show notes.
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You can try our seo intelligence platform keywords people use at keywords people usecom, where we can help you discover the questions and keywords people are asking online.
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Post those questions and keywords into related groups so you know what content you need to build topical authority.
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And finally, connect your google search console account for your sites so we can crawl and understand your actual content, find what keywords you rank for and then help you optimize, continually refine your content, targeted personalized advice, keep your traffic growing.
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If you're interested in learning more about me personally or looking for dedicated consulting advice, then visit wwweddawsoncom.
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Bye for now and see you in the next episode of SEO is Not that Hard.