Keyword formula

[Malkav1806]

There is no one size fits all, look at dominating sites and set their approach as your min standard

[Diligent_Force_4746]

it has changed a lot since LLM came into the picture. would suggest looking for AI tools like seozilla that can help you in content writing for LLMs, plus do the gap analysis and suggest accordingly.

[eashish93]

Things has been changed now, but core things remain same, find better keywords and write a blog. But focus should be on niche and topical authority building should be the main focus.

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[BoGrumpus]

The “O” part of SEO is for “optimization” – and going on a keyword/search term based strategy hasn’t been the “optimal” approach for over a decade now.

First… when someone types in a search term (anytime since around 2012) that’s NOT what the actual search algo sees. It goes through a prompt interpreter which rewrites it in various ways to help disambiguate or otherwise add more relevance to the context that’s in play. It might insert locational info (which is why “near me” isn’t usually needed anymore unless you’re searching locally for a distance barrier free product or service. It’s needed only when you’re going against the typical intent). It may include previous searches in its analysis to help determine if you’re on a new topic, or if you’re just trying to refine the last one.

Now… when we use GSC to see how people find us – we see the terms they type in, not the prompt that actually got sent out to the systems that generate your SERPs. You might see two very different keywords/search terms in your analysis that ultimately amount to the exact same search term that actually got sent to the search engine. And if you have a page for each of the typed in keywords – now, the ranking systems aren’t going to be sure which one to send it to because one has the actually words, but the other might describe the actual idea more accurately or clearly. And the choice it will tend to make is to just find another page on another site to link to.

Next, the way machine learning systems work is NOT by keywords (or tokens) but the vectors that connect or link any two keywords/tokens. The things don’t need to “match” – they just need a short vector between them. So this further confuscates the keyword (especially long tails) approach.

Instead, you need to first think about your brand and make sure ALL the things stay closely connected your well defined and disambiguated brand. And then you need to start thinking about the things, the ideas, the actual topics the people are asking when they put various keywords into search. And you don’t really need pages (or even the search terms) to appear on pages.

For example, in real estate like you’re doing, it’s one of the very few service area niches where individual town service area pages are still helpful for ranking. The reason for that is that towns are relevant and the answers to questions aren’t the same aside from location like plumbing would be. You get the same plumbing services in town 1 or town 2. The proximity of shopping can be very different from town to town in your area, and that’s one of the considerations people make when they buy a house.

So let’s say your keyword research suggests that a lot of people are asking about schools. These also change from town to town. If you have 20 towns in your area, you’d need to write 20 long form blog posts (or have AI generate some redundant copy that might rank for a minute while it’s “fresh” but die off in a few months). But really – what is it people want to know if they’re asking about schools? Primarily, it’s going to be about whether it’s a good school or not, or if there are private or parochial options, You don’t need any long form content to handle this – just add (and mark up) the data on your town page. Put a “schools” section on them and have it give the school’s ranking against all the other schools in the state with a citation link to the data source. Add a list of the schools (public and private) and across all levels. List any trade schools, etc.

One bonus here is that AI sucks at writing longform content that will rank for any extended period because it can’t write anything it doesn’t already know, so you have a hard time getting it to create content that’s unique enough to rank. And if it is unique enough now, by the time 50 other sites have had it write content for the same keywords, then it’s no longer unique, either.

But what AI is good at is extracting data. So you could easily get it to extract all the school names, addresses, web sites and contact info, some ranking data, and whatever else you find. And, in fact, most of your decent MLS listing tools will do this for your automatically (though they sometimes require an extra few bucks a month).

So anyway – if what people are searching for turns out to be best answered as a blog post or dedicated page on your site, then sure – that’s what you want to make. But in MANY MANY MANY cases, all you really need is to put “Ranked #128/4287” in your “Education” section of the relevant town pages and now you answered all the “How Good Are” or “What options for” schools in Town X? type questions. And along with all the other information you put on that page which relates to things people who are buying a home might ask about the area they’ll be moving too – that’s what makes it unique. You’re not just a real estate site, but you have all sorts of things to help people just moving to the area find out everything they might want to know about their potential new hometown.

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[BusyBusinessPromos]

Topical relevance and topical authority

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[ryanxwilson]

See, the basics of using keywords still matter, but SEO has changed a lot since then. Today, it’s not just about repeating a long-tail keyword. Focus on high-quality content, user intent, relevance, and natural usage. Local SEO, meta tags, backlinks, and user engagement play a bigger role now. A 300-word post with keyword stuffing won’t perform as well as a helpful, well-structured article that answers readers’ real questions.