LSI keywords have long been a controversial subject among SEO experts. Some claim that they are the secret to boosting your search engine rankings and others outright deny it.
So what are LSI keywords and what is their impact on the search engine rankings of a website?
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LSI keywords
LSI keywords are Latent Semantic Indexed keywords. Semantic means words that somehow relate in meaning or logic. According to many SEO experts, LSI keywords are words and phrases that search engines like Google see as semantically related.

Starting with an example of “house”, semantic keywords can be “home”, ”mansion”, ”quarters”, and “residence”.
For the keyword ”dog”, semantic keywords will be “puppy”, “pup”, “canine”, “hound” etc.
But this statement by John Mueller makes things a little bit complicated.
“There is no such thing as LSI keywords—anyone who’s telling you otherwise is mistaken, sorry.”
John Mueller states the LSI keywords don’t exist.
If you are not familiar with the name let me introduce him to you.
John Mueller is a Senior Webmaster Trend Analyst at Google.
He has long been a voice of Google especially when it comes to SEO and SEO-related topics.
So what can be the reason behind this statement of John Mueller?
For answering this question first we’ll have to learn a little more about Latent Semantic Indexing.
Latent Semantic Indexing
Latent Semantic Indexing is also known as Latent Semantic Analysis. LSI or LSA was developed in the 1980s. It was developed as a natural language processing technique.
We’ll not dive into the concept of Latent Semantic Indexing because this model was developed with complex mathematical concepts. If you are interested in complex mathematics you might already be familiar with vectors, single value decomposition, and eigenvalues.
But we are not discussing the core concepts of this technology because they are very difficult to understand.
If you are interested in the working of LSI, there are many blogs and articles on the internet that you can easily find and read.
What we’ll discuss in this article is why this technology was invented and what problem was it supposed to solve?

The problem was that people use different words for different purposes and the computers were not very smart to realize the context of the search.
Search engines might index the information under one word and search engine users may use another word to search for it.
This concept may seem a little more complicated than it actually is.
Let’s take an example for clearing out any confusion regarding the above statement.
Let’s say that you are searching for information about a certain breed of dog. You have to write a report about this dog but you are having some technical issues with your electricity connection. No electricity means no WIFI so you are unable to use the internet for this purpose.
There is a very good library right across from your apartment, you decide to go there. You pick out an encyclopedia and start looking for a specific breed of dog, but you are unable to find it.
You don’t give up that easily and start looking for similar words to find the right breed of dog.
Under the word Canine, you finally find the information you were looking for.
Imagine this same problem for search engines. If they only display the content with the word dog in it when the keyword “dog” is searched. Users may not get the information they are looking for.
Polysemic Words and Synonyms
Synonyms
A synonym is word that has an identical or similar meaning to another word.
The words ‘Start’ and ‘begin’ are synonyms because they have similar meanings.
The word car is a synonym of the word” automobile.”
Phrases that have identical or similar meaning can also be defined as synonyms.
Many languages that we speak today, have different versions and people belonging to different geographical locations use them in various ways.
People belonging to different regions use different words to describe the same object. The meaning of a word also changes with the context it is used in.
For example, Americans use the word ”flat” and British people use the word “apartment” to describe the same object. Another example can be “starter” and “appetizer”.
Just like British English and American English are similar but different. Urdu and Hindi are also similar but different.
Now how does this similar concept translates for search engines?
Let’s say we are searching for the keyword” mobile phone” using Google. But Google is only returning the content with the words ”mobile phone” in it. It is ignoring all related keywords like ”smartphone” and “mobile device”.
The content written about a smartphone or mobile device might even be what you were looking for in the first place.
As a result, you may not find the content that you were initially looking for. For providing maximum benefit to its users, Google should return all the content that is related to your search.
We have come to the conclusion:
Unless Google understands the correlation between these words and phrases, it will be unable to provide the best results for its customers.
Polysemic words
Polysemic words are words that have more than one meaning. Polysemy can be described as the association of a single word with multiple meanings.
A polysemic word is called polyseme.
For example, “Fall” can mean falling down and it can also mean autumn season.
The word mouse is used to define an animal as well as a computer gadget.

These kinds of terms were also a problem for the search engines because unlike human beings computer were unable to recognize the context of a word or a phrase.
If a person is searching for a “bank”, a bank can either mean the bank that holds our money or it can also mean a riverbank.
If you search for Apple earphones, you don’t want the search engine to return with search results for buying apples and earphones separately. What you want the search engine to understand is that you are looking for earphones by tech-giant Apple.
If a search engine is unable to recognize polysemic words, it will provide irrelevant search results.
What is the role of LSI
Machines and computers are not smart like human beings.
They are unable to understand the relationship between different things on their own.
If a computer is not told that Luna and Moon are the same objects, it will never know this fact.
LSI is solving this very problem. Since we cannot tell the computer all this information manually because it will take too much time.
LSI Technology uses Mathematical formulas to derive a relation between words for different documents.
In simple words, if a document has both the “car” and “automobile” words in it. LSI will help the computer in understanding that cars and automobiles mean the same thing.
Is LSI used by Google?
Many people assume that Google uses LSI for creating a better user experience, but it is far from the truth.
LSI is a patented technology so Google or any other search engines are not allowed to use it.
Along with being licensed, this technology is also quite old for search engines like Google.
LSI cannot even handle half as much data as Google.
What we have concluded so far is that John Mueller is right and no such thing as LSI keywords is used by Google for website ranking.
Correlated Words
LSI keywords will not help you in boosting your search engine rankings but correlated keywords can.
If you use the words puppy, pup, dog and canine in a blog about a dog. Google might index your content for all these words thus increasing your chances of appearing in search results.
Bottom Line
There are many self-proclaimed SEO experts on the internet. Always look for information that is provided by trusted resources.
Always prefer the information provided by trusted sources to information present on random blogs or articles on the internet.
LSI keywords may not exist but correlated keywords do. These correlated words and phrases hold the power to boost your website’s search engine rankings.
Don’t try to stuff these semantically related keywords in your content, rather use them where they naturally fit.
Adding words like poodle or canine in a blog about your pet dog will help the search engine in indexing your blog.
Do you believe in the existence of LSI keywords?