When people communicate, they do so with far more than words. There are myriad non-verbal cues, from facial expressions to vocal variants to tonality. Because it comes so naturally to us, we don’t really appreciate how difficult communication is without these contextual indicators.
That’s where semantic search comes in. On a larger scale, semantic analysis is a process intended to make a topic or search result easier for artificial intelligence to process and understand certain concepts or ideas. In search, its applications are very similar.
Modern search engines are all about intent. They seek to understand not just the words a user has typed, but why they’ve typed them. But how exactly is this connected to semantics, and how can you apply that to your website.
Semantic search represents these efforts, generating results by understanding intent, context, and connections. It can be broken down into two primary concepts — semantic mapping and semantic coding. We’ll provide an overview of each.
Semantic mapping involves visualization of the connections between words, phrases, concepts, and entities. This is best exemplified by Schema, a semantic markup system created via a collaboration between Google. Microsoft, Yahoo, and Yandex. By analyzing the context of a search and how it may apply to different entities — something most of us largely do subconsciously — semantic mapping helps create richer, more relevant search results, especially where voice search is concerned.
Imagine, for instance, you’re searching for a mall. As a user, you’re likely looking for directions to the mall, or the hours/location of a particular mall within your city. A search engine will account for this, and deliver results based on your perceived intent.
The search engine understands a few things in this regard.
- A mall is a place.
- You as a user are probably looking for a mall within your location.
- How your recent search history plays into what you’re currently looking for.
- How certain qualifiers (near me, hours, size, etc.) influence intent.
These are all contextual elements that we take for granted because we don’t really need to stop and think about them. Search engines do. AI isn’t as formidable as the media might have you believe and requires constant guidance, learning, and information in order to grow and improve.
If semantic mapping is the foundation of semantic search, semantic coding is the application to a website. It explains to a search engine what entities, concepts, and information can be found on a particular page. This allows more efficient, effective indexing of the website, and helps a search engine better-determine if a website matches a user’s intent.
With semantic coding, a search engine understands not only what a particular web page says, but also the meaning behind those words.
Typically, semantic coding is applied via HTML. Don’t worry if you aren’t particularly experienced in that regard. Most content management systems like WordPress offer plugins that take care of the heavy lifting involved with Schema markup, and there are also professional solutions such as Schema App.
Google also provides a structured data markup helper that basically provides you with a step-by-step process for adding semantic coding to your site, and a structured data testing tool to make sure you’ve added everything properly.
The Power of Semantic Search
Can you still drive traffic to your website without using Schema? Certainly. But why would you? The easier you make your content for search engines to understand, the better that content will perform.
And at the time of writing, remarkably few brands are leveraging semantic coding. This means that using it will likely give you a considerable advantage over your competitors. And the value of such an advantage cannot be understated.