LSI (Latent Semantic Indexing) keywords are a divisive topic within the SEO community. Many are confused about what they are and whether they actually help improve your website’s ranking in Google.
There is no denying that there are a lot of misconceptions about them.
We want to clear up this confusion and help you understand what LSI keywords are, and whether or not they are important. In this guide, we’ll take a closer look at LSI keywords.
What is an LSI keyword?
LSI (Latent Semantic Indexing) keywords are words that are related to a main keyword and are considered semantically relevant. If the main keyword of your page is “credit cards”, examples of LSI keywords would be “money”, “credit score”, “credit limit” or “interest rate”.
However, they are not synonyms (different words that mean the same thing). They are closely related words that help define the topic of a page.
At Semrush, we use “ semantically related words ,” and if you want your web pages to rank in the SERPs, you can’t ignore the importance of including them in your content.
Google has moved beyond indexing a
page based on specific keywords (which was the case before). Its algorithms use closely related keywords to contextualize content, especially in cases of ambiguity.
In the past, Google would look for occurrences of a keyword on a page to determine its relevance to the query. In our example above: if your page is about credit cards, that keyword was used to determine its relevance, and simplistically, the more mentions, the better.
But this wasn’t an accurate way to
determine the relevance of a page, and it malaysia telegram data led to keyword stuffing and an obsession with keyword density. So the search engine evolved. By using semantically related words. It can now define a topic. More precisely than by considering the number of times a keyword is mentioned.
In 2021, there’s no denying that optimization should focus on topics, not just specific keywords. This is especially evident when you analyze the search queries for which a high-performing page ranks.
To be convinced, just look at the page below, which is ranked for 5600 different keywords:
So why is there debate around LSI keywords?
This is because Google has confirmed multiple times that they don’t exist. However, we’ve written extensively on this topic , and we’ve concluded that it’s a myth.
But let’s not get sidetracked. Using related keywords in your content is important, it’s a critical part of launching a page that covers a topic scott saul executive vice president comprehensively. It’s the key to success.
Calling these LSI keywords isn’t necessarily correct, but it’s the underlying idea that matters.
And even though LSI keywords don’t exist in the literal sense, understanding Latent Semantic Indexing will definitely help you create better content that will rank well in SERPs.
What is Latent Semantic Indexing?
Also known as latent semantic analysis, LSI is a natural language processing (NLP) technique developed in the 1980s to identify the contextual relationship between words.
In a nutshell , latent semantic indexing “finds the hidden (latent) relationship between words (semantics) to improve the understanding of information (indexing).”
Understanding the content of a page can database d help determine the topic based on the language used.
In theory, it makes sense that Google
might use this technique to understand synonyms, among other things. In fact, using them throughout a piece of content helps the search engine better understand the topic.
The controversy surrounding the use of the term “LSI keywords” is not so much about the importance of addressing the points you would expect to see on a page about a particular topic, but rather about the fact that there is no evidence that Google uses latent semantic indexing to answer a query.
LSI is now an old technology. It was developed for smaller sets of documents. Not for the entire web.