semantic search

If you spent any time in marketing circles this year, you probably heard the phrase “semantic search” tossed around in conversation quite a bit. But what in the world is semantic search, and how does it impact SEO? If this is a question you’ve asked, you’re in the right place. Semantic search was a big trend in 2016, but it isn’t new. It did, however, rise as a content marketing trend throughout this year. And guess what? Going forward, it’s going to continue to have a major impact on the way content marketers achieve success in the SERPs. Today, I’m here to take it apart, tell you how to best use it in content creation, and how it will impact content development now and in the future. [bctt tweet=”How do #semantic search trends impact content creation? Learn in @JuliaEMcCoy’s guide” username=”ExpWriters”] What is Semantic Search? In order to fully understand semantic search, let’s back up a bit to the basics of algorithms and how they work, and then explore semantics as it relates to Google searches. First, Understanding the Different Shades (Algorithms) of Google Since the inception of our search friend known as Google, the internet know-it-all has attempted to move search results into a more natural-sounding realm. Part of that strategy falls under the idea of semantic search and machine learning algorithms like RankBrain. In machine learning, a computer basically teaches itself how to do something, and RankBrain is just one component of Google’s search algorithm program. When we use Google to search for something, there are potentially millions of webpages that can provide a solution. Algorithms are the computer formulas that take our questions and turn them into the answers we are looking for. Past algorithms that Google has used include: Panda (Source): In 2011, Google updated search filters to stop sites with poor quality content from showing up in top search results. Penguin (Source): Penguin was launched in 2012 to catch sites that appeared to be spamming its search results in order to boost Google rankings. Hummingbird (Source): Launched in 2013, Hummingbird was designed to sort through information and deliver the best results–the name came from the speed of the algorithm. After the launch of Hummingbird, users may have noticed that Google was offering more precise answers to search queries. The update was one of the biggest overhauls to its search engine and it allowed Google to provide faster answers to questions and rank them according to the index. Semantics: Did You Really Say What You Meant to Say? Now, let’s move onto semantics. Merriam-Webster defines the word “semantics” as the study of meanings. In the field of linguistics, semantics is all about the logic behind the meaning of natural and artificial words, signs, and sentence structure, whether it’s a spoken language or that of computer programming. A famous author penned the following, and I feel that it quite adequately sums up semantics: “Do you wish me a good morning, or mean that it is a good morning whether I want it or not, or that you feel good this morning, or that it is a morning to be good on?” J.R.R. Tolkien, The Hobbit In other words, what are you really trying to say? Check out how this works when you type a question in Google. I love how Google is smart enough to correct bad spelling (Semantics FTW!): Semantics: Going Behind the Search For online content and its goals, semantic search involves the use of quality resources (and not just keywords) to perform a search and provide the best results. Here’s just how (creepily?) knowledgable Semantics is in its inner workings. It knows your history and uses it: semantic search takes the details of a user’s history and offers back the most relevant results. It knows logic and deciphers meanings: Semantic search looks for the logic, or intent, behind what a searcher is looking for in their quest for information. It is about going beyond the traditional definition and moving towards the motivation behind a searcher’s request. Rather than searching for what someone literally types in (as in, misspelled words), Google semantics uses a complex system of algorithms and prediction to make a guess as to what we actually mean, and then looks for the most relevant content. Ever feel like the search box is reading your mind? Thank semantics. Examples of Semantic Search Whether we know it or not, semantics plays a part in every search we perform. In his post over at Crazy Egg, Neil Patel gives us some good examples of common semantic search, something we can all relate to in our everyday lives. 1. Conversational queries We ask, Google answers. In this case, rather than provide us with every website that answers the question, “how do I bake?” or the words, “Christmas cookies,” semantic search works to first give us the directions, then relevant recipes. 2. Auto-corrected misspellings As we showed in the example above, it corrects misspellings. (I think that’s pretty cool.) Here’s another example. It’s safe to assume we all have enough Christmas “cookys”. After correcting for the misspelling, we have ideas for a Christmas cookie swap and the Best Christmas Cookie Recipes for 2016. 3. Information shown as graphics Relevant images are provided as part of the answer. Now, if only my Christmas cookies turned out like those.  3 Key Ways to Create Content With Semantic Search Standards in Mind The challenge in our field comes when we sit down to create the content our readers are looking for, and we forget the importance of staying relevant and natural. All in all, it’s simple (but in reality and the work/time/skill involved, not). 1. Stay away from subpar content that isn’t readable: invest in quality. Here’s the thing… Writing with Google Semantics in mind doesn’t really mean NEW advice for us content creators. It’s simple: write more for your reader. Why? Google Semantics will now (very quickly) identify, and then disqualify, keyword-stuffed content and spammy articles. Poor keyword usage won’t rank well. And, as we showed above, grammar is checked too … Read more