Latent Semantic Indexing (LSI) Is Powering Semantic SEO

Search engines are improving the way they interpret content via methods such as semantic indexing. Understanding how it works can help you target keywords better for your SEO.

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Search engines don't read information like humans do. They are trying hard and making important progress in natural language processing, but at the end of the day, they are still machines and software based on logical operations.

To efficiently interpret the implied meanings hidden in massive volumes of content, search engines use semantics and various undisclosed machine learning-based approaches. Before the internet even became mainstream, one such approach was patented. It carries the funky name of latent semantic indexing (LSI) and uses a semantic and statistical approach to detect topics in relation to words. What a cool technology.


Overview: What is latent semantic indexing (LSI)?

LSI is a classification approach used to find the topics a keyword is related to. It may be one of the approaches search engines use to index content they crawl on the World Wide Web, although it is probably not the only one. And there is some debate in the industry about whether Google really uses LSI. The term is generally used to describe the semantic interpretation of concepts.

To illustrate semantic indexing, let's say your webpage is about the topic brunch. I don't need to explain that the word is a combination of the words breakfast and lunch, and those two words are not necessarily the ones search engines will look for to qualify content for the keyword brunch.

It is much simpler than that. The latent semantic keywords the search engine will look for are things like scrambled eggs and bacon, pancakes, fresh fruits, French toast, butter, and jam. In other words, if you have the ingredients in your content, you qualify for the dish.

The entry for “brunch” in Wikipedia.

Sometimes you can find your semantic keywords in Wikipedia, like in this entry for brunch describing the traditional components. Source: wikipedia.org.


How is latent semantic indexing different?

When you do keyword research for SEO, you investigate different categories of keywords: on-topic keywords, synonyms, and semantic keywords. The on-topic keywords are the easiest to find as they are typically variations and combinations of the main keyword set.

Synonyms are another type of keyword, but they are different from semantic keywords. Synonyms can be substitutes for a keyword in a phrase, whereas semantic keywords are words that if taken together form the meaning of the keyword.


3 benefits latent semantic indexing (LSI) brings to SEO

Semantically associated keywords provide various benefits for SEO, whether they are based on LSI or another semantic methodology or approach. Let's have a look at them.

Better indexation of your contents

The most important benefit of using semantically related keywords is to increase your chances for a correct indexation of your content in relation to the keywords you target. If a search engine interprets your content wrong, your site will stand no chance of appearing in the SERP (search engine results pages) when users search for the targeted keyword.

Better content readability

Using semantically relevant words in your content, also helps the user understand the topic. The more sophisticated the topic is, the more important this is. Semantic keywords improve readability and comprehension for all levels of users.

Broader keyword coverage

By expanding the semantic field of your content, you also increase the chances of appearing on additional keywords or variations. This can further expand the SEO visibility of your content.


3 tips for optimizing for latent semantic indexing (LSI) keywords

Getting your head around latent semantic keywords is not easy, but once the concept is fully taken in, it can become a reflex.

1. Create mind maps

A great way to find semantic keywords is by exploring how you understand words yourself. After all, that is what search engines are using technology to try to understand. A great tool to do this is mind mapping.

Mind mapping allows you to establish connections between words visually. You can use a piece of paper or an online tool such as Coggle. And you can do the exercise yourself or as a group effort, which can provide an even richer experience.

2. Check autocomplete suggestions

Another place to look for inspiration is by playing with the autocomplete function in search engines. When you type in a keyword in a search engine, the autocomplete function suggests a number of additional words. These words can sometimes help you find semantically relevant keywords that users search with.

3. Use SEO tools

The fastest way to find semantic keywords is by using tools. There are two different aspects of SEO tools that can help you. The most obvious is the keyword research function most tools provide, although be aware that only a small portion of those keywords are what you would call semantic keywords.

Tools such as Ubersuggest find keywords from autocomplete and suggested search, and there are even tools such as LSI Graph presenting themselves specifically as LSI tools.

Other tools, including Searchmetrics and SEMrush, provide content enrichment features that suggest semantically relevant keywords for already-existing content.

The Searchmetrics content explorer tool.

In the Searchmetrics tool, comparative keyword analysis allows you to dig deeper into the keyword structures of your competitors to identify semantic keywords you may be missing. Source: searchmetrics.com.


Help the machine by being more human

With the strong focus on keywords and doing things for SEO, site owners sometimes forget that the actual target audience is not Google or Bing but real humans such as you and me.

Semantically enriching keyword sets is necessary for optimal results in SEO, but in the long run, search engines are likely to catch up. At that point, humans can return to more natural communication and simply focus on writing great content.

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Suzanne Frey, an executive at Alphabet, is a member of The Motley Fool’s board of directors. Teresa Kersten, an employee of LinkedIn, a Microsoft subsidiary, is a member of The Motley Fool’s board of directors. The Motley Fool owns shares of and recommends Alphabet (A shares) and Microsoft. The Motley Fool has a disclosure policy.