Mew ๐ Clarification regarding Keyword Density (KD)! A lot of people need to hear this Keyword density has never been defined by any authoritative source in Search Engine Optimization (SEO) as an exact phrase match. Keyword density is the words you use and their synonyms (MLID's) on a document, in contrast to the surrounding words. Or in other wordsโฆ If your keyword is [How to lose weight], any where "loosing", "weight", "lose", "pounds", "drop" appears on the page contributes to the total density of your keyword – it does not have to be "How to lose weight". Edit: The exact math is unknown so try not to look at it from this perspective. It's most likely based on custom vector space retrieval models that no one but Google can account forโฆor in other words, just write Good content. Happy Thursday! [filtered from 44 ๐ฌ๐จ]
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Abana Learned something new today. I thought it has to be the exact match. I go for 1 exact match in every 100 words. ๐๐ฝ3
Mew ๐โ๏ธ It absolutely does not. That is the out-dated SEO way that keeps your document from ranking for variant phrasing ๐ ๐๐ฝ๐6 Abana ยป Mew thank you. Horia ยป Abana , quite the opposite, actually. The more you repeat the same keyword over and over again, the likelier it is for Google to demote you. You have to write naturally, including exact-match keywords or key phrases, but also mixing it up with synonyms, related words, words from the same lexical family and so on. ๐๐ฝ3 Abana ยป Horia before I write, I try to find the synonyms for my Keywords. Then go for exact match once every hundred words. But with what Mew have said today, I will throw that technique out of the window from now on. Mew ๐โ๏ธ ยป Abana – You can do this still but it would be more like once every 500-700 words. ๐๐ฝ3 Abana ยป Mew thank you. ๐ ๐๐ฝ1 Horia Small caveat: I would be very wary of using mathematical "keyword densities". The reality is that keyword density never was a factor. At least not in the way most SEOs (SEO users) tend to use the term. Of course using key phrases and variations in a text is important, but there is no such thing as a metric calculating keyword-to-word ratio. ๐๐ฝ๐3 Abana ยป Horia thank you so much. Mew ๐โ๏ธ ยป Horia – Agreed, but people need a baseline in their head, unless they understand how vectors work – which most do not. ๐ Horia ยป Mew , I usually explain context vectors to my recruits and / or students by showing them a graphic similar to this one. If they can understand term weight and query matching, they will likely get a sense for vectors, at least in a hypothetical way, which will be useful for them to recall when working on copywriting assignments.
๐๐ฝ2 Mew ๐โ๏ธ ยป Horia – Love this! Thank you for the resource. It's great to have you in group! I look forward to more of your posts ๐ ๐๐ฝ1 Horia ยป Mew , thank you kindly! And thanks for having me! ๐ Looking forward to exchange ideas with you guys.
Horia ยป Maher , Term frequency-inverse document frequency (TF-IDF) is an SEO myth. While Google has been using it – probably for predicting word frequency – it is useless for SEOs. As Bill Slawski pointed out a few years back, since SEOs don't have access to the same corpus information Google has when estimating document relevance, they cannot efficiently use TF-IDF for any useful purpose. Moreover, I think it was also Bill who pointed out that Google (like many other search engines) have likely moved on to BM25 from TF-IDF. There are a lot of tools out there touting supposed "TF-IDF keyword research" or such bogus, but those are mostly capitalizing on hype. Just like all the hack writers who pen blog posts about how to crush your competition with TF-IDF keyword usage and such nonsense. TF-IDF is no more useful than Latent Semantic Indexing (LSI) or "keyword density". ๐๐ฝ3 Mew ๐โ๏ธ TF-IDF is pretty rudimentary. While there most likely is a way Google is measuring, it's probably based on VSRM (Vector Space Retrieval Models) and would take years to understand, to which it will have changed. Or in other words, just write good content and do the above to the best of ones ability. ๐๐ฝ1
Kevin I would emphasize 3 things: write good content for your audience (exactly as advised by Mew), tell a good story around a KW as a concept, not as a word AND write with "semantic search in mind". People search for a term in many different ways. So, exact, broad, and synonym match is critical to KD (which is my interpretation of what Mew is saying) ๐๐ฝ1
Mew ๐โ๏ธ ยป Kevin – Correct my friend! Exact maybe once or twice, broad multiple times and synonyms multiple times! The exact amount is unknown and does take time to figure out on certain queries over months (especially very competitive ones). Should be incredibly easy for local however. ๐๐ฝ1 Kevin ยป Mew It's interesting that you say Exact maybe once or twice. Lately, I have been writing articles around certain keyword clusters in an overcrowded and highly competitive space (food and recipes). I am noticing that most of the top 5 Search Engine Result Pages (SERPs) have their main keyword as exact match appearing a maximum of 4 times (and some even only once). One major player has an article of 17k words (including customer comments) with a relatively short article with the keyword appearing only twice on exact match. This for me blows KD expressed as an index or percentage out of the window. That said, I find it extremely useful to make sure I am not keyword stuffing. My only question is "how do we avoid keyword stuffing when we are dealing with words that don't have a synonym?". There are only two ways of saying ice-cream – ice cream or gelato (granita and sorbet are different). What is your advice on this last point? Mew ๐โ๏ธ ยป Kevin – Keep in mind Keyword Density has never been noted as an exact match and that the broad match and synonymous terms should be seen as a density relative to the total words of the document – but in any case it is not KD as most SEOs think of it. For ice cream I would recommend using Googles know MLIDโs. Let me check real quick. Gelato, Dessert, Soft Serve, Mochi and Tortoni/Spumone Some other words that pair with these are: cone, cold, frozen, scoop Kevin ยป Mew The way I see KD (and correct me if I am wrong because I am relatively new to on page SEO) is that: My article needs to tell a coherent story around a particular concept that is of value to my audience. My audience needs to pick me out and to do that I need to stand out. I use focus keywords (and synonyms) to do that and rank on search engines. I use KD to be able to tell these engines that my content is x words long is about a particular KW rather than another. In an article of about 1200 words, I use the exact keyword about 2 times and 2 or 3 additional synonyms or semantic relations. A particular dish like "baba ganoush" is going to be extremely hard to nail without exceeding the exact and broad match limits. Baba ganoush, spread, eggplant, aubergine, lebanese dish, middle eastern and north-african cuisine and so on can be used. Is this a good approach? Mew ๐โ๏ธ ยป Kevin – Youโre on the right track. To know what words you need to use, consult Googles image carousel at the top of there image page for your search. These are the words Google will look for in the vector array. https://www.Google.com/search?q=baba+ganoush&client=safari&hl=en-us&prmd=isvn&sxsrf=ALeKk02JGuPDYEVmcPrZ3PS8kHg1DCwYkw:1602254081269&source=lnms&tbm=isch&sa=X&ved=2ahUKEwjA-unK3afsAhUDsp4KHSpdC24Q_AUoAXoECB8QAQ&biw=375&bih=633&dpr=2 baba ganoush – Google Search Kevin ยป Mew thanks. Itโs very encouraging.
