Now more than ever, search engines are placing far greater emphasis on conversational topics in order to give users the most relevant answers, especially as voice search becomes more mainstream.

A major component of this strategy has been huddled under the branch of semantic search and machine learning algorithms.

The role of semantics in search

As somebody who spent three years at university studying semantic theory, I could easily go off on some weird and wonderful tangents here. But, to save time (and your mind) a quick tap into Google pulls up the following definition;

search-semantics-definition

Semantics definition via Google search.

Looooong story short; semantics is all about the differences and/or similarities in perceived meanings of words, sentences, and/or phrases, in relation to context.

So what does semantics mean for search? Search engines know a significant amount about the semantics of natural language and the meanings and relationships between words, and use smart techniques (for example Google’s AI algorithm, RankBrain) in order to detect patterns in search queries, their contexts, and user behaviour and establish:

  • what a website is about
  • its relevance to various search queries
  • its relative value compared to other websites

In other words (well, visuals actually) individual keywords may appear to be unrelated to one another, but in a given context they can be strongly connected. Only those at Google HQ truly know how RankBrain et al works, but SEO guru, David Harry attempted to illustrate this concept nicely with a list of queries, using red lines to show strong connections, blue to show weaker connections.

David Harry -Moz - RankBrain Semantics

A visual representation of search semantics by David Harry.

The discipline of semantic search sets out to improve search accuracy through applying contextual meaning in order to better understand a searcher’s intent. Google’s Knowledge Graph is the epitome of this. Using processes like concept matching, synonyms, and natural language algorithms, search engines are able to produce highly interactive, relevant, and personalised SERPs.

Creating content with semantic search in mind

Semantically related words and phrases contribute additional weight and relevancy to a site, therefore including plenty of variety throughout can make for some considerable wins.

This is why crafting semantically-rich killer content is so integral to SEO strategy. For any given industry-specific website, we should expect to see a broad range of related words and phrases relating to its products and services.

If you’re not already thinking like this when writing your content, now is the time to start;

  • Carrying out detailed keyword research using a variety of tools
  • Conducting sufficient competitor research in order to distinguish yourself with current information that is relevant to your target audience
  • Keeping user intent and user experience in mind at all times. Write genuinely useful content in the language and tone of voice they will expect
  • Spending time browsing online communities and forums to see what questions your target audience is asking, and provide them with answers via content on your own site
  • Incorporating relevant internal and external links to build a bigger contextual picture
  • Distributing and repurposing your content to suit the various platforms your audience is using
  • Applying semantic markup and technical elements throughout your website
  • Regularly monitoring and analysing performance and adjust strategic approach where necessary

The landscape of search is without a doubt progressing towards meeting the demands of natural conversational language of its users in order to better provide them with the information they seek. Keywords still play an essential role in content strategy, but not in the same way they once did. Now more than ever, SEOs need to tackle their industry with a broad mind on their shoulders in order to incorporate semantics into their overall strategy.