Keep those two words in mind. By the time we are done here, you’ll have probably attached a deeper meaning and significance to them. However, – before we get to that – let’s talk a bit about how Google Search used to be.
About a decade ago, Search Engine Optimization ran an awfully different tune than it does nowadays. It used to be all about getting as many backlinks to a page as humanly possible, and cramming as many keywords as you felt you could get away with.
The game was almost exclusively about reverse-engineering the formulas by which Google’s algorithms chose what to rank, and using – sometimes abusing – that knowledge. Often to the detriment of the users.
Those days are long gone.
Not all backlinks are created equal, keywords alone can only get you so far, and most importantly: Content is king. Meaning that the quality and context in which you use those other SEO elements is more important than ever. And that’s what we are going to talk about today.
What Exactly Are Semantic Searches?
Long story short, “semantic search” is a handy shorthand we SEOs use to describe the way search engines go about generating the type of accurate results humans are after. However, you can already tell by your scroll bar’s length that things are a bit more nuanced than just that. Ready?
Semantic searches have, in essence, three primary components: Query context, word relationships, user intent. The idea behind these categories is for Google to come up with a system that actually understands language the way you and I would.
For example, if someone asked you, “What color is your car?” then follow that question with “and what is its make?” they were still referring to your vehicle. Well, it used to be that search engines were unable to understand the context behind the second question.
Instead, search engines would just look for websites matching those exact same keywords, “and what is its make?” and return those results.
That all changed around 2013 with Google’s Hummingbird update, which sought to match meaning over just words. Then a few years later, in 2015, with the advent of RankBrain – a machine learning system that is both ranking factor and an intelligent query analysis AI – semantic Google searches became even more accurate.
A wave of improvement that just keeps going, as RankBrain’s AI continues to learn by analyzing best-performing search results and finding similarities between pages users deem valuable – even if they don’t contain the exact matching words.
How Does Semantic Search Works?
We could spend a lot of time talking about this, but that’s not exactly why we are here. So, let me give you the cliff notes.
Your searches today don’t occur in a vacuum and, as I mentioned before, semantic search is all about understanding – and utilizing – context. Nowadays, Google seeks to draw contextual frameworks for your searches and anticipate user intent from elements like your search history, location, the global search history, spelling variations, etc.
It is why, when you type “restaurant” on your phone’s Google search bar, it returns a list of restaurants nearby. It is also why, if you search for Sabretooth and your last ten previous searches have been about paleontology, extinct creatures, and biology, Google will prioritize information about the Pleistocene cat, instead of the X-men character.
Using that initial setup, these algorithms improve and refine themselves by comparing the results they give against things like bounce rates, conversion rates, and other indicators that gauge their effectiveness.
In short, semantic search systems seek to emulate the type of contextual attributes we humans naturally use in our conversations, to glean what users actually want to find beyond just what they typed.
By adding this layer of understanding to queries, semantic search algorithms are able to produce more accurate and desirable search results. As a result, RankBrain may deem a page to be a “good response” to a query even if it doesn’t contain the exact words from the query.
Ok, But… Why Should I Care?
Self-betterment, of course!
Nah. I’m kidding. The point here is getting ahead of your competition, as always.
For one, semantic searches are putting the final nail in the outdated SEO practices’ coffin. Keep stuffing those keywords, sweetheart. It won’t make a difference when the AI overlords understand that you are just trying to game the game.
Transformative advances like these tell anyone listening exactly where the industry is going, and in which basket you’ll want to put your eggs going forward.
How long until a lack of semantic search optimization starts hurting your online presence and, in turn, your bottom line?
More importantly, do you want to sit and wait to find out?
But enough with the scary big-picture tales for now. Let’s talk about four major areas where semantic searches are poised to make – or have already made – an impact. And how the optimization game will shift accordingly.
The Philosophy Behind Semantic Google Search Optimization
In the light of the exponential growth semantic searches are experiencing, we can already see a noticeable shift in the way AI is poised to change the optimization landscape.
A Shift from Keyword-reliant to Topic-reliant Optimization
Creating content around keywords has been great and all, but it is a practice that will wither away as we move forward.
Don’t get me wrong, keywords will probably survive the future in some form or another, but they won’t be – and arguably haven’t been for a while – the end-all-be-all of optimization. Instead, the focus of optimization will turn into identifying and generating content around attractive, niche-specific topics you can cover in-depth.
The Rise of Voice Searches
However crude they might currently be, voice searches are lightyears away from what they were just a few years back. More importantly, it’s a growth pattern that’s only refining and accelerating.
The online world revolves around convenience, and you can bet your bottom dollar that the moment voice searches are as accessible and accurate as typed ones, the overwhelming majority of queries will come that way.
What does this have to do with anything? Well, the rise of voice search goes hand-in-hand with the tech behind semantic searches, and we are not too far away from making voice search optimization a priority.
UX Becomes a Priority
In a world where intelligent systems decide who finds what, ensuring that whoever finds your content walks away extremely happy becomes everything.
In the age of semantic search, user satisfaction will guide most SEO efforts. Google is in the business of providing its users exactly what they are looking for, and their satisfaction is key. As they continue to fine-tune their systems to better understand and satisfy searches, SEO efforts will start dancing to the same song.
User Intent Becomes THE Priority
And finally, we get to the crux of it all. Once Google contextualizes searches accurately and prioritizes what their users mean over what they type, keyword-targeting takes a backseat to intent-targeting.
The game changes to identifying the topics and types of queries that actually bring people to your site, and the focus shifts to creating content around them.
If there is one big mistake you want to avoid as you walk away from this piece, it is thinking that all these things are “a problem for later.”
As much as you’d like to think these techs are still some years away, the truth is that by the time you are reading this, machine learning algorithms have already been shaping Google searches for years. In fact, you probably stumbled into this article precisely because their AI assumed that you’d be interested in reading it.
These far-reaching transformations are taking – and have taken already taken – place in many aspects of optimization. And their impact and influence will do nothing but grow.
What can you do? Well, for one, you’ll want to partner with companies like OTT, who instead of following the herd, are herding the pack.
Otherwise, you run the risk of finding yourself worrying about “the perfect keywords” when everyone else has already moved to understand and capitalize on elements like user intent.