Semantic analysis, also referred to as LATENT SEMANTIC INDEXING (LSI), is a mathematic tool that scans the raw data of a document and identifies the relationship between the words and concepts found in it.
Semantic analysis has been extremely useful since the early days of computer-assisted language analysis. The early programs struggled with the multiple meanings of everyday language, which meant that they were close to useless in terms of identifying what a document was actually saying. When semantic analysis came along, it helped the programs discover the unstated (latent) relationships between the words (semantics) in order to better understand and compile them (indexing). Search engines also found latent semantic indexing extremely useful. Semantic analysis was great for scanning and understanding small pieces of static content like documents and images (which was all that was on the internet in the early days.)
But search engines have made huge strides since then. Google today uses a much more sophisticated set of algorithms to rank websites and content. These algorithms consider content quality, relevance, freshness, and hundreds of other factors. So the question is, does semantic analysis still deliver a punch?
The short answer is YES.
Google has moved more (not less) towards understanding natural language queries, thanks to algorithm updates like BERT, Hummingbird and RankBrain, which place great value on natural content, semantic relevance and optimization.
For a complete step-by-step guide on how to conduct semantic SEO and improve your content, check out this video:
This makes complete sense if you try and think about it. Look, our interactions with search engines have become more conversation-like and VOICE SEARCH is on the rise. This means that you should be producing content that “speaks” to your customers and engages them. Semantic analysis helps you do just that by identifying the different variations of your search query.
Once you have included the different LSI keywords that are relevant for a search query, you’d be better positioned to answer a user’s question (which is why they searched on Google in the first place). GOOGLE WANTS TO RANK CONTENT that matches the search intent of the user. As it moves towards better language understanding, particularly for conversational queries, you need to make sure that your content includes the different nuances and contexts of a word, too.
But you also need to appreciate the difference between having the RIGHT KEYWORD DENSITY and shameless keyword stuffing. Don’t create garbled content that uses only a few keywords over and over and over again: not only would readers hate your content, you will not rank on page 1 anyway (keyword stuffing died with the PENGUIN UPDATE.)
Apart from using semantic analysis to identify relevant LSI keywords for your main keywords, you can also focus on the following to maximize SEO benefits for your website: