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The Scripted Podcast: Semantic Search with guest Ahref's Michal Pecánek
The Scripted Podcast is a show created for content marketers and content writers featuring real Scripted writers. We'll talk about best practices in content and SEO, our favorite marketing tools, how to find and hire writers, and all the fun and misadventure that comes with being a professional freelance writer.
In this episode of The Scripted Podcast we sit down with Michal Pecánek, content marketer and fragrance enthusiast from Ahrefs.com. Michal has written extensively on digital marketing, including our topic today of Semantic Search. We talk about the history of search, how Google has evolved over time to get to semantic search and what it means for content writers and content marketers.
Quick Links:
Michal's Article on Semantic Search
Michal's Article on Google's Knowledge Graph
Episode Transcript:
Kevin O'Connor [00:00:00]: Welcome to the Scripted Podcast. I'm your host, Kevin O'Connor, marketing director here at Scripted.
John Parr [00:00:05]: And I am John Parr, the Writer Community Manager. It's, it''s been a little bit since our last episode, Kevin. I think Kevin actually has some good news to share as to why that is.
Kevin O'Connor [00:00:17]: Yeah, it's my fault. I apologize. I had a human baby.
John Parr [00:00:22]: Yep. Confirmed.
Kevin O'Connor [00:00:23]: (laughing) Was born on August 29th. So, this kind of set back things a bit but...
John Parr [00:00:32]: Yeah, yeah. What an inconvenience.
Kevin O'Connor [00:00:34]: Yeah.
John Parr [00:00:36]: A child is, right? For the podcast listeners.
Kevin O'Connor [00:00:38]: I'm mostly awake right now.
John Parr [00:00:43]: (laughing) I bet. And also exciting besides the newest addition to the Scripted family, is we also have a pretty exciting guest today. We have Michal Pecánek. And, Kevin, tell me a little bit about the guest we are going to have on.
Kevin O'Connor [00:01:03]: Ah, Michal Pecánek is a marketer for Ahrefs. One of our favorite tools and leaders in the industry and he's written some really great stuff on the subject of semantic search. So, we wanted to bring him in to tell us more about semantic search and why it is so important to understand for businesses and for content writers.
John Parr [00:01:25]; That's right. And with that, let's get into it. Alright.
Kevin O'Connor [00:01:55]: With us today is Michal Pecánek, a content writer and marketer at Ahrefs. Michal, welcome to the show.
Michal Pecánek [00:02:05]: Yeah, thanks for having me guys.
Kevin O'Connor [00:02:06]: Yeah, absolutely. So our topic today is semantic search. Something Michal has written about pretty extensively at Ahrefs. Let's start by asking you simply, what is semantic search? Why is it important? Why should we care?
Michal Pecánek [00:02:21]: Okay, so maybe before I say an explanation, a description of semantic search, I'm going to say an example of it. So, I guess you are familiar with Star Wars?
John Parr [00:02:25]: We are.
Kevin O'Connor [00:02:27]: Yes, of course, yes.
Michal Pecánek [00:02:28]: Okay, let's say that you are seeing one of the Star Wars movies for the first time. And you really like Chewbacca, but you don't realize who Chewbacca is. What is his name? So, let's say that you want to Google the name of the character, Chewbacca. What would you put into Google? What would you Google?
Kevin O'Connor [00:02:52]: Big. Big hairy guy. Star Wars.
John Parr [00:02:59]: Yeah, dog man Star Wars.
Michal Pecánek [00:03:05]: Yeah, I think this is a very good example of what a semantic search is and why it is really important. Because. I actually tried this yesterday. I was wondering and this was also my first thought. Yeah, like who is the hairy guy on Star Wars. Star Wars hairy guy with the cross bows. Star Wars the heavy built cross bow. Or if you're a little bit feminine or with the Star Wars universe, you can also ask Google who's Han Solo's co-pilot. Who's Han Solo's side kick. And they said that you're looking for the same answer, right? So, I used all of these search variances yesterday and Google picked like 7. It's Chewbacca. And I think that 5 out of 6 times they showed, gave me the knowledge graph. It's like 100% sure that it's Chewbacca. Chewbacca tried away with all, like giving me the flight millennium. And basically this is what semantic search is about and why it's so important. So, just to say the words, it's basically an information retrieval process that returns the most relevant results, based on the actual meaning of the search variance. So, you didn't mention Chewbacca in our search variance, but Google understood what it's about and returned the best search results for that.
Kevin O'Connor [00:04:33]: Right, and I don't think a lot of people think about what goes into that. And how difficult that was for Google to achieve. So, my question for you is when, how do they get there? What are the big things that they did and you mentioned a knowledge graph, right?
Michal Pecánek [00:04:56]: Yeah, we...I can start at the knowledge graph, but basically it's kind of the beginning of how Google gets started at some other search. Some other search angles start working, but I think it can be useful to actually mention things before that. Before what happens on the internet, on the web before even we had semantic search because that is what actually allows, we have to have some development of the world wide web to have the technologies available to enable some of the search graphs. If you are going really back to the history, basically we identify resources on the world wide web by the URLs. Those are uniform resource locators. As the word uniform is really important here because it's basically a standard of communication that the machines on the internet basically understand between each other. The problem with this was how we get to semantic search, we basically only get the URLs and the links between them, right? That's how Google actually was invented. It's how, it would have worked even before semantic search. But, the problem was that the only meaning that they were able to extract from those pages or how they are related was only through links. So, that was used as an indicator of kind of like related content. As we all know, Google or any search engine back in the days, it was really susceptible to kind of black SEO or as not really your SEO techniques, how it manipulates the rankings. But, it's really good now. So, this connection through links is how Google pay trade was born. Basically estimating the value of the page based on the quality and the quantity of pages that are linked to it. And then Google also had other stuff like meta keywords, which are really outdated these days. But, for example for Chinese search engine Baidu, they still use it. Then you have the standard stuff like vital facts, meta descriptions, and Google anchor text in links and exact keyword matches, which Google used before. And, that was like pretty simple stuff, website, compared to what we have now. But, as I already mentioned, and as we all know, that's, it was really easily manipulable. And Google wasn't really returning the best search results, before we had the semantic search. So, first we had to have something like a semantic web because there is no semantic search without a semantic web.
John Parr [00:07:46]: Right.
Michal Pecánek [00:07:46]: The funny thing is that the requisition of the idea of a semantic web was purposed by the same guys, Berners-Lee, that invented the world wide web. He actually purposed a system what where information is organized according to certain known rules, he called this linked data, will come back to the slider and it can be used for easier processing of information for people. And here is where we are getting to the semantic search. Because in 2011, that's when schematics four came to live and it's basically a project that promotes using structures that are on the web and it's a common project of the big corporate branches like Google, Microsoft and Baidu. And the most common language used for structured data these days is JSON-LD. Which has transcript modulation for blank data, so this is goes back to history of link data and here we semantic search and I think we can now talk good about the technologies.
John Parr [00:09:03]: Right.
Kevin O'Connor [00:09:05]: Yeah, like you said, the system used to be gamed, a lot, with keyword stuffing and black hat SEO, as you said. So, Google needed to evolve. And now that kind of brings us to semantic search - was the evolution, they put together. To put that gaming to rest, almost, right?
Michal Pecánek [00:09:25] : Yeah, yeah.
Kevin O'Connor [00:09:25]: So, the first big step in semantic search, to get there, was the knowledge graph, right?
Michal Pecánek [00:09:33]: Yeah, yeah, that's exactly it. And it was in 2012?
Kevin O'Connor [00:09:38]: Um-hum.
Michal Pecánek [00:09:41]: The year after schematics four was born. And basically knowledge graph is a knowledge base of interconnected entities. Which, may need some further clarification. So, entities are basically objects or concepts that can be distinctively identified. We can make them the most commonly asked – things, companies, places. Or it can be intangible stuff like, colors or feelings. And the knowledge graph basically extracts all these things from the base once they're indexed entities and creates relationships between them. How they are related to each other. And they already have a lot of these stuffs in their database. I think. They posted a few months ago and released a blog post and that figure was like 5 trillion entities, something like that.
Kevin O'Connor [00:10:44]: That's a lot of entities. That's a lot of people, places and things.
Michal Pecánek [00:10:45]: Yeah, yeah, that's a lot. The thing is, why this is so important for Google or for the negotiation of search or how the search works, how SEO works, is that the entities are actually language agnostic. So, once you have the entity in the knowledge graph, you know the relationship with other entities and you don't really need to care about the specifics of each language. So they can, let's say that they have the collections from English, but someone, let's use a language that's Portuguese, the Google algorithm might not be working that well as in English. And they can basically use the collections that they gathered from the English data to return the search results that are for Portuguese Google.
John Parr [00:11:49]: Yeah, okay. So, I'm currently studying Japanese, so I encounter this quite a bit when searching in Japanese. There are some similarities that I can see that some of the results, depending on what you are searching on. Is it different across all languages, or are some a little more centralized to the results that you are getting in English?
Michal Pecánek [00:11:59]: I'm not sure. I've never tested this. Not by where I can say by using Google and quite a lot of languages. Most of the time I use it in English. But, I'm Czech, so I use it in the Czech language. And I sometimes use Spanish and I have Chinese, so I do start searching in these languages as well. And yeah, sure, English probably works the best, but I think Google is really getting there. Where they don't really need to get, like polish their algorithms for each and every language. They can use that their unified entity system that too. Kind of like adjust the quality of the search results.
Kevin O'Connor [00:12:43]: Right. And always with Google, it's almost like where they want to be is what they promote. Rather than where they are.
Michal Pecánek [00:12:53]: Yeah, yeah.
Kevin O'Connor [00:12:53]: Right? So, when they talk about, like e, they have been trying to get to that with quality content for a long time and that's what they recommend as a guideline for content. But, are they 100% there yet? Are they serving up like, e quality content every time? Probably not, but they're working on it.
Michal Pecánek [00:13:19]: Yeah, we're seeing the progress basically all the time. I mean, after the knowledge graph, it was 2012, so it's 8 years ago. And since then we have much more technologies, important technologies regarding the semantic search. That Google came up with. So, the year later, in 2013, they came up with hummingbird birds. Which I think was probably one of the biggest algorithmic changes.
John Parr [00:13:42]: Right.
Michal Pecánek [00:13:42]: For Google...
Kevin O'Connor [00:13:43]: That was. That hit the SEO world pretty hard. Hummingbird was, is still very very talked about in algorithm updates and for people who might not know. Why don't you explain what kind of impact that had exactly.
Michal Pecánek [00:14:00]: So, basically hummingbird tried to solve the problem that from retrieving search results based on keyword matches to the actual meaning of the search results. So, it really went to semantic search direction. It's basically shift from keywords to complex and the actual meaning of the search query. So, if you, prior to hummingbird, if you were using like all of the weaknesses of Google and creating, let's say, 10 different pages all basically the same topic but targeting a bit different keywords, that step can be covered in the one topic. Then it was possible that you were writing for all of those 10 pages before hummingbird. But after hummingbird, Google figured out that it's just one topic and that none of those 10 pages really satisfies the search and they are kind of like duplicates of each other. So, instead what you had to do after that was to kind of put all of the content together and focus on topics instead of single keywords.
Kevin O'Connor [00:15:29]: Right, so John, do you? What used to happen before hummingbird is you would, on your website you would have a bunch of different pages of content that are basically around the same topic, but you would just substitute a similar word for it, right?
John Parr [00:15:46]: Right.
Kevin O'Connor [00:15:46]: Now, it would be...say you are trying to sell sneakers. Then you would have a page for black sneakers, but then you would have another page for black running shoes. Then another page for black Nike running shoes. And then that, like Michal said, you would end up ranking for all those terms on all those different pages. But, when hummingbird came along, that update helped Google understand that these were all the same and that one single page should really encompass all these terms.
Michal Pecánek [00:16:20]: Thanks for making it more clear than me.
Kevin O'Connor [00:16:32]: I had to give an example for John. John's not in the SEO world so much. He kind of represents the majority of our writing audience.
Michal Pecánek [00:16:33]: I see.
Kevin O'Connor [00:16:34]: So, being able to lay it out for them. For people who aren't in this every day for the last, however many years.
John Parr [00:16:45]: No, I remember that era as well. I remember the web pre-hummingbird in the sense where there was a lot of junk, like that.
Kevin O'Connor [00:16:54]: Yes, that was a great huge step in the, in the step toward more higher quality content and better search results, right?
Michal Pecánek [00: 17:03]: Definitely. But, that wasn't nearly the end of it. Google really progressed since hummingbird as well. So, what came after that was rank brain. Which, I think the best description of it would be, no one really knows what it does, exactly. But, it's one of the strongest ranking signals.
Kevin O'Connor [00:17:20]: It's like, sounds like an evil, like a villain in a Marvel comic. Rank Brain.
Michal Pecánek [00:17:27]: Yeah, yeah. It sounds really bad. So, my take on rank brain is that it's kind of, it's not standard algorithmic update. It's more of an update of hummingbird itself. It focuses more on searches true intents than inputs of ranking signals based on the search word. So, let's say that you're maybe looking for Chewbacca and this kind of sends maybe it's preferring pages that have the most links from Star Wars throughout their websites. That if you're searching for something regarding a disease that you may have, then it may put more importance on the author of the article than the domain where they are, where the information is. So, it's kind of like automatically adjusting ranking signals based on each and every query by their matching learning style. Which is super complex and I don't know anything about it, so I won't delve into that. But, yeah, that's my take on it.
Kevin O'Connor [00:18:40]: So, you mentioned structured data. What's that? And why is it important for business owners to understand structured data?
Michal Pecánek [00:18:50]: Okay, so, I think a lot of people actually associate structured data with the schema markup, but it's not the same thing. It's not a synonym. Schema markup is actually a part of structured data. It's the most permanent part in the SEO world. And in the world wide web. But, you have other kinds of structured data. So, you have data bases. Where you have stored information in a certain format that Google or other machines can really understand and read. So, I didn't say what structured data is in the first place. So, it's basically a bag of data that's easily readable for machines that they can understand what it basically is. So, you're making it easier for machines to understand your front and back provided with structured data. And, you have data bases like wiki data, which are basically just big tables of data, let's say, name, company, like Ahrefs, country, Singapore, founder, Dmitry Gerasimenko, and so on. So, Google can understand it from this. Then they have like company profiles on big prominent websites, let's say a front page or you have websites that are focusing on companies on the market, like Yahoo finances and Bloomberg, that these companies profiles, those are also kind of structured the same way so it's really easy to extract the entities from them to understand more about the entities or companies in this instance. Where the social media profiles, it's also kind of structured. So, these are data bases. Then you have HTML5, which is not as important as the other stuff, but it can also make it easier for machines to understand your content or how it is placed on your page, by using HTML5. So, the difference between using this and the previous versions is that, let's say for a bug open you would use a gif or spam image, you know, before HTML5. But, HTML5 instead of using gif or spam, this which doesn't say anything about, what the content is about or where it is on the page. You can actually use stats like article, or navigation or fooler. You are making it easier for machines to understand that. Where the content is. What actually is the roll of this on the bench, right?
Kevin O'Connor [00:21:30]: Right. So, is that we as SEOs recommend for content writers and website owners that their data, structured data is basically the same reason why we ask them to put sub titles and headings, like H1s and H2s, in their content? To make it easier for machines to understand?
Michal Pecánek [00:21:52]: Yeah, yeah. I think you can use this explanation as well. Definitely.
Kevin O'Connor [00:21:58]: Right.
Michal Pecánek [00:21:59]: As we talked about, you have the schema markup, which is really not a pretty big data base, of like, data drives and their properties that you can drive your content with. So, it's mostly used for rich snippets. So, let's say you have a product page, you have a customer store, you have products you can kind of like mark up the reviews, so that aggregates the overall review of the products, that you see right in the search that the product has 4 stars out of 5. You can mark up the price so that it can also appear in the search. A lot of types of these rich snippets.
Kevin O'Connor [00:22:32] Right.
Michal Pecánek [00:22:33]: But, you also have a lot of schema markups that can't be really used for the time you are shopping the search. But, you can use it for machines for Google to better understand your content and increase the chance of getting into the knowledge graph. Because as we already talked a bit about the evolution of the search, where it's going, I think Google is on the way that's shifting its focus from the main graph to the knowledge graph. So, it's kind of like, I don't know, maybe it's doing right now, maybe it's testing it. I don't know, progress of interest. It's like when we talk about the languages, of how it can be interesting. Other searches based on languages and what's going on with languages. These are from the entities, from the knowledge graph, right? So, I think it's gonna be very important to be part of the knowledge graph. It's even important now, but it's going to be more important in the future. To all the entity and the knowledge graph.
John Parr [00:24:00]: So, you know from a practical stand point, here. When you're reading this content on the web. How do you personally know when a writer has good on page SEO knowledge? What are the factors that make that up, within the content itself?
Michal Pecánek [00:24:15]: I'd probably take a bunch of the URLs of the content they have written and get it for organic traffic purposes, and find if it is ranking well. So, if it's not ranking well, it's a pretty good signal something's wrong. But, it not make the content order. It might not be caused by the writer themselves.
John Parr [0024:39]: Right. And so, sorry, what factors exactly, would fall onto the writer? For example, like in a instance where it is the writer's fault, that these aren't ranking.
Michal Pecánek [00:24:50]: So, once we know that it's really the writer's fault, so we kind of like, scratch off the technical factors of the website, the links pointing to that page and rule out the compound. Then, it's most likely about not satisfying the search engine. The easiest thing that the writer can do is taking the meta, the main keywords, plugging it into Google and click to show true results. And see if the angle of the compounds that they wrote about, if it's to the angle or similar, if it's to the top of the ranking results. If not, then they need to refresh their content.
Kevin O'Connor [00:25:42]: Right. I think we recommend that to our writers, as well.
John Parr [00:25:44]: We do.
Kevin O'Connor [00:25:46]: Always look at the top search results to see what's missing in the content. If there's ideas missing. But also, what is common in all those results. If there's topics that they cover in all of them, that should be included in yours as well if you want to rank in that topic, right?
Michal Pecánek [00:26:02]: Yeah. It's not like all the like. I think most people wouldn't get far if you just looked at the top ranking pages for a certain topic, it's still knowledge of the stuff that they just enter in a new article. Then we don't really bring any additional value, right? That's just like, writing an article based on 10 other articles. So, it's better just content based on what additional value you can provide. New angles, something like that.
John Parr [00:26:41]: So, I guess where I would go next is, you know, on this content, like let's say that we're trying to produce quality content here, would you say that these focus keywords and topics are in the title, the first paragraph, in title tags? Is it throughout the piece as a whole?
Michal Pecánek [00:26:59]: It's difficult questions you ask. To answer, it depends.
John Parr [00:27:00]: Right.
Michal Pecánek [00:27:00]: Because, first of all, you can make sure that the angle of the content, that you know the reader of the content. So, for example, based on experience of our SEO company, Ahrefs, I can basically write a really advanced link building article, like link building tips article. But, it will be like using automation staffs, APIs and all of this add-on stuff. So, it might be better. It might provide more value than your info link building stuff, but it's not for the reader, it's for the searcher of link building tips. The purpose of link building is mostly a beginner, and they are not looking for some advanced techniques. So, you need to know the writer, you need to know what they want to see.
Kevin O'Connor [00:27:59]: Yeah, so, it's not enough, like you said, to just re-create what's already out there. It's more about understanding. Your question should always be, what does the, what is the searchers intent. What is it they are trying to learn and how much can I answer in this one piece of content. Right? Rather than, this is where your keywords go. This is how many times you have to put your keywords in there. It's kind of antiquated at this point. Especially with semantic search. correct?
Michal Pecánek [00:28:30]: Yeah, yeah. I agree. I mean, I definitely would stick with the main keyword in order to pay gratitude and that. Because it basically summarizes the page. So, it kinda belongs there, so it's important. So, it belongs, also belongs to the meta descriptions that shows up in the search. As the headings, H1. H2, it should be structured so it makes sense for the reader, so it's probably, like, combined. Keywords that are most relevant to the topic, that should be talked about, right? So, it's kind of like, natural to include those. So, I wouldn't obsess over that, if you don't include certain keywords, but it's often comes natural.
Kevin O'Connor [00:29:14]: Yeah, I think I've got, our previous guest, John Tyreman, he does research in DC for a marketing agency. He mentioned basically, for content writers, all this means is following the rules of journalism. Of good writing. The who, what, wheres and whys. And just, basically trying to answer all those questions in your content. And taking those next steps, those deeper steps, the research and looking at the search results, help you with anything you may be missing in your content. Like, oh, I forgot to answer that question, or this question here that they answer and all these results is also inadequate. Maybe I can add to it.
Michal Pecánek [00:30:06]: Yeah. And it's not always about the words or the other content itself. Another example, from the Ahref story before I joined, we had a page about back link checkers. So the back link you were, was the topic. The back link checker people wanted to know, wanted to check your back links. And the problem was that it was just a product page about our back link checker, but it actually didn't have the back link checker on that site. And it didn't really rank that high, but once we added the actual back link checker tool to it, it's number 1 since then, I think.
Kevin O'Connor [00:30:39]: Right. So you gave them what they wanted. It wasn't exactly content, but you gave them what they were looking for, which is the actual checker, right? So, Google probably saw those certain signals. Like, the time they spent on the page, your bounce rate, stuff like that, and gave you a boost.
Michal Pecánek [00:30:57]: We don't know what exactly, like triggered that. It would be like, all these, like signals, the bounce rate, time on the page, dwell time. I wouldn't obsess over that. It's never been confirmed like a ranking signal. But, it's something that definitely satisfying the user. In fact, and contributing to a better user experience on the page.
Kevin O'Connor [00:31:26]: For sure.
Michal Pecánek [00:31:27]: Ah...
Kevin O'Connor [00:31:28]: And that's the goal, right?
Michal Pecánek [00:31:30]: Yeah, exactly.
John Parr [00:31:32]: And so, you know, out of curiosity, what is the most common SEO myth that you think is out there today?
Michal Pecánek [00:31:33]: Whoooo
John Parr [00:31:34]: I know that's probably a long list.
Michal Pecánek [00:31:34]: I think it's not like a myth, it's probably just like opposite to think that each and every piece that can contribute to how the results are arrived. So, I would talk right now about time on page, bounce page, right? Web time links, content, keywords, whatever, everything else on the page. If it's mobile optimized, how it's loaded and all these things collectively, whatever. People often think if it's out of the context, like it's never really depends on just one thing and you should channel. You should just strive to provide the best user experience and satisfy search and bandwidth. Which is kinda like goes above and beyond SEO. A lot of user experience, commenture, optimization. All of this stuff. It's all interconnected, intertwined.
John Parr [00:32:42]: Right, so, beyond even all of these different factors it kinda just drills back down to quality content then.
Michal Pecánek [00:32:51]: Quality content, links and basically other marketing activities that are getting you thee links and getting you the publicity. Getting the stuff, getting your content to people. I think it's not really an SEO thing, per se, but I think most of the drivers essentially spends too much time on writing the actual content, not much time on actually promoting the content.
Kevin O'Connor [00:33:19]: Right. Yeah, for sure. John, do you have anything else on the writer's end?
John Parr [00:33:25]: Yeah. So, what would you recommend for writers to better understand the concept of search intent? Like if a writer is just starting out here, you know. What would you recommend say like maybe as a resource, or what they could do today, to, you know, improve their own understanding, but also to improve the quality of their content in context of that?
Michal Pecánek [00:33:49]: Yeah, sure, so the easiest way, as I already mentioned is just plugging in a certain keyword, a certain topic, into Google and get true results. But, that way you don't really know what you're up against. I mean, you can write a piece of content, but not anything in the search results. But, because all of those are on the first pages of the surf. They have a lot of links. And they are established websites and factors. But, even though you might have the best content it might take ages or you may never get there. If the best. So, you have to look at other stuff too. That's why we have Ahrefs, right? So basically, that's what we do every time before we start writing any content. Before I or anyone else from the content team. Before we start outlining any content we always check how difficult it would be to write for a certain topic. And it's best alometric and prepare a metric of keyword difficulty, and that takes into account links pointing to the pages on the first circle, in the surf, basically. So, that tells you how difficult it would be to rank first with certain keywords. And, it's on a logical scale, so let's say keyword difficulty 0 – 30. It's pretty easy for most websites. And then it goes up. So, that's a huge difference. That's not much difference between the keyword if they go to 5 or if they go to 25. But, it's a huge difference between keyword difficulty 70 and 75. In terms of the matter and the links of the pages and the ranking keyword.
John Parr [00:35:47]: Sorry, go ahead Kevin.
Kevin O'Connor [00:35:48]: No no, I was just...We didn't really get into your background or what you're doing over there at Ahrefs. What I wanted to ask you really, how you ended up at Ahrefs, and what you got going on over there? We love your tools. I mean, you got...
Michal Pecánek [00:36:10]: I love to hear that. I actually was an avid Ahrefs user before I joined the team. Guess I should expect it from anyone on the marketing team. I don't think anyone using monser SEM much would just go to apply to Ahrefs. You gotta be kinda a family. Simply before I joined Ahrefs, I just, I was working as a head of marketing at another supply and service company. And, yeah, so, I just joined another supply and services company. And this time at a space I'm most interested about.
Kevin O'Connor [00:36:47]: Oh yeah, so you applied there and is there, like a...you worked out of a, like is there a headquarters that you're at?
Michal Pecánek [00:36:55]: We had our headquarters out of Singapore, but we have the team all over the world. I think it's like 50/50. Maybe 50% of the team is working in Singapore. And they are working from home these days, right? And, 50% is scattered around the world. I think we have people on every continent, pretty well.
Kevin O'Connor [00:37:23]: Global?
Michal Pecánek [00:37:23]: Yeah. We're global. For a small team, we have people everywhere.
Kevin O'Connor [00:37:27]: Can you tell us about any upcoming projects that you guys have going on outside of the box?
Michal Pecánek [00:37:33]: So, I think I can just disclose 2 things because by the time this episode is published. We already have those 2 new tools functioning to be released. The first one is really big one. It's a free version of Ahrefs. It's called Ahrefs webmaster tools. You'll be able to find it at Ahrefs.com/awt. And it's basically for any website owner and they will be able to see all the SEO issues they can have on their websites through our site audit. That's the first thing we add are the complete site functionality and the second thing they'll have access to HWT, is our site explorer, where they can see their back links and keyword and like that. Which is pretty cool considering that it's gonna be free. And the second functionality site audit tool. And it's for internal linking. Basically you'll be able to find internal linking opportunities really quickly and easily. It will basically tell you which page you might be missing internal links to other page, so you'll be able to better pass your internal page rank. So, these are 2 pretty cool things that we have going on right now, also.
John Parr [00:39:07]: Okay, so we're going to cycle into a different segment here in a moment. But, before we do, I noticed that you are a fan of fragrance. So, before we do, I want to ask you, your top fragrance recommendation in addition to your other expertise?
Michal Pecánek [00:39:25]: I'm a bit of a fragrance collector, these days. I have like 50 fragrances, like bottles and hundreds of samples. So, it's really hard to say my favorite fragrance of all of those. It really depends on the situation, but these days, in the summers, I'm a huge fan of agar. I'm living in agar. I like green tea. So, my favorite fragrance these days is green tea and it's from a company, like Chanel. It's called Willow Trap. So, it's like green tea based fragrance. I don't think a lot of people know about it because it's not in the Macy's or Forann or this kinds of shops, you know.
John Par [00:40:26]: Yeah, no no no, yeah. I know. I got into that myself a few years ago, and I keep it basic with mostly crème dip.
Michal Pecánek [00:40:33]: What's your favorite? Is it Aventus or is it something else?
John Parr [00:40:36]: Aventus, of course and maybe a little Green Irish Tweed from time to time.
Kevin O'Connor [00:40:44]: I got no idea what you guys are talking about.
John Parr [00:40:48]: The roles have reversed now. It's a...so for this next segment. We've got a segment called Solve My Problem. And basically the way it works is, we present an issue to you, and you tell us what you think the best solution for this particular problem would be.
Michal Pecánek [00:41:07]: Let's go. Let's do it.
Kevin O'Connor [00:41:08]: So, I own a boutique retail clothing store. And I have a nice e-commerce site up and I want to compete in organic search, but it don't know where to start. Is it possible for me to compete with these chain stores in organic? What should I be doing to gain visibility?
Michal Pecánek [00:41:27]: Is it starting? Like a brand new website?
Kevin O'Connor [00:41:31]: No, say we're established, 5 year old site.
Michal Pecánek [00:41:34]: Yeah, I get it. But, your not, your not really successful in organic yet, right?
Kevin O'Connor [00:41:41]: No, all I've done is Google ads and Facebook.
Michal Pecánek [00:41:44]: So, I would probably line up low hanging fruit opportunities for the content, so basically topics that don't have high keyword content that can generate a significant amount of traffic. So, we can target that because we can probably expect that such a website doesn't really have a strong back link portfolio. So, next you do is, in addition to kinda having a content plan based on the long hanging fruit opportunities. I would also say create a compound that can actually can acquire the links because, let's be honest, no one is going to link to your product pages, most of the time. Besides, I feel it's right that really doesn't count. So, you need some pages that will attract links. So, kinda like brainstorm ideas of, these pages don't really need to attract organic, they need to attract links. And from those pages you can kind of fast track to other pages that you care about. So, you can create some, you can come up with some info graphics, you can come up with some survey, data study, your own presentations from a new angle. Something that can get the needle moving.
Kevin O'Connor [00:43:16]: Yeah, so like something that will spark a debate.
Michal Pecánek [00:43:18]: Yeah, yeah, so, so, these would be 2 things that I would focus on content wise. But, besides content you have all the other technical stuff. If your website isn't really crawl-able or like you have indexing issues, then you have to take care of that first.
Kevin O'Connor [00:43:37]: Um hum. And sign-up for Google my business.
Michal Pecánek [00:43:41]: Yeah, yeah. For this, for this kind of business, that should actually help. And, I don't know how much impact it has on the knowledge graph, but once you're in Google my business, you can apply to the knowledge panel yourself. I don't know if I should call it the knowledge pane. Once you have the knowledge panel, it's a bit different. You look at like pizza, sushi, or barber shop, or something like that. You get these knowledge panels, Google my business, right? And you see it, you see it on the map, so you can get included in there. And it may increase the chance of getting you into the knowledge graph and getting the entities from your web pages extracted. Because Google my business is actually another database of structured data. You write your info in there.
Kevin O'Connor [00:44:34]: Right? Which brings us back to structured data.
Michal Pecánek [00:44:37]: Yeah, maybe, I'm not sure if I pointed this out, but structured data is pretty cool topic. But, I wouldn't advise that unless you have other SEO pass or like the important ones, so that the compound points or the technical aspect of the website. Even like the unix structures of school, but, it should never be the priority, most of the websites have more important things to do than structured data.
Kevin O'Connor [00:45:20]: Right, it's kinda the advanced.
Michal Pecánek [00:45:22]: Yeah, yeah.
Kevin O'Connor [00:45:24]: For sure.
John Parr [00:45:26]: Well thank you so much for joining us today. This is just amazing. You are, you know, a wealth of information.
Michal Pecánek[00:45:33]: I really enjoined the chat. Thanks for having me guys.
John Parr [00:45:36]: Of course.
Kevin O'Connor [00:45:37]: Do you have any shout outs? Any promotions you wanna plug for us?
Michal Pecánek [00:45:42]: Sure, I actually wrote quite a few articles on this and relevant topics that you can find on the Ahrefs blog. So, if you write Ahrefs, semantic search, knowledge graph, featured events, I wrote articles about it. And, basically we're publishing articles, most of the time, 2 times a week. And I'm really excited about it. I'm always make fun at our company. And I would also recommend people to subscribe to our youtube channel, Ahrefs youtube channel. Because Sam, our content creator on youtube, he has, I know I'm bad here, but he has, hands down. the best SEO videos on youtube. So, if you want to delve into SEO, that's the way to go. And, most of the time it's pretty big in our family. The topics are also for beginners.
Kevin O'Connor [00:46:29]: Yeah. I can't recommend the Ahrefs blog enough for beginners, or veterans to really take in complicated subjects and have them laid down in the simplest and easy to read format. You guys do a lot of great work over there.
Michal Pecánek [00:46:46]: I appreciate it. Thanks.
Kevin O'Connor [00:46:49]: Thanks Michal.
Michal Pecánek [00:46:47]: Thank you guys.
John Parr [00:47:20]: Alright, so that was quite in depth. There's a lot to kinda take from that there. I have a bunch of questions, Kevin. You know, pertaining to what we just discussed there. But, before I do, is there any kind of take-home points you'd like to discuss?
Kevin O'Connor [00:47:36]: Well, Michal is a very experienced and proficient marketer and he was able to break down some pretty complicated things for us. Basically, what Google does and how it's gotten to where it's gotten, is, is technical. And he, he explained that pretty great. And I understand that there are a lot of areas that may be a bit too technical. But, if you're a content writer or business owner, I think it's very valuable to understand how Google works and the steps it took to get there. And, what that means for your content. And how can you really write to these advanced algorithms.
John Parr [00:48:21]: Right, it's...you know my takeaway, despite the technicality of what we had there, is that it is possible to explain it, in a simpler way. I think part of the problem with these topics in particular is that they can seem kind of unapproachable. But, the things that pertain to say, you know, marketers, or that pertain to writers who are creating content, then it can be grasped. You know one question I have for you, too, on the marketing side here, is that something that you think is reflective to the industry as a whole? You know, that this, this monster has just kinda grown out of control in complexity?
Kevin O'Connor [00:48:52]: Yeah, I mean there's a lot of black box to it, I'm sure, that we just don't know that Google will just rank and not come out and tell you. That there is best practices that work. Then there's data behind those practices that show that it would work. And I think, too, a lot of what Michal said was that don't get obsessed with these rules. But, write to your user intent. And I think that's a good lesson. But, you wanna understand that there are rules. That there's technical rules behind why certain content ranks. But, at the end of the day, you should write for the searcher. What they're searching for and to do your best to answer those queries. And that's how you end up really giving yourself the best chance. There's obviously, there is link building and being an authority on your site that go into ranking and can quickly. But, as quickly as you can. But, really when you're a content writer, it's doing what you're taught and whatever school of writing that you went with. And it's the, you know, who, what, where and why, and answer to the fullest extent with, with good data behind it. And, I think that's a good lesson for any content writer to learn.
John Parr [00:50:28]: And so, are there any resources that may be available for any kind of writers who are trying to grasp a little of we just discussed with Michal?
Kevin O'Connor [00:50:29]: Yeah, Michal does a great job of writing about it on the Ahrefs blog and we'll include those links in the blog post for this episode, for sure. And, since we spoke to him, he couldn't really tell us about before. Ahrefs, actually launched a couple of free tools that are great for content marketers. There's the Ahrefs webmaster tools and the, their new internal linking tool, as well. We'll add links to those and let you guys see those, because we think what they're doing right now is great. And if it's free, then even better.
John Parr [00:51:10]: Yeah. We'll get those out to the writer community in the newsletter, as well. And get them into the hands of some of the writers at Scripted. That's about all I have on this topic. How about you Kevin?
Kevin O'Connor [00:51:25]: Yeah. I think we covered it. And, you know I really wanna thank Michal again for joining us today, and...
John Par [00:51:32]: Yeah.
Kevin O'Connor [00:51:32]: And, breaking down some pretty complicated stuff.
John Parr [00:51:36]: All right then. Well, until next episode, this was The Scripted Podcast.