Some search optimizers like to complain that “Google is always changing things.” In reality, that’s only a half-truth; Google is always coming out with new updates to improve its search results, but the fundamentals of SEO have remained the same for more than 15 years. Only some of those updates have truly “changed the game,” and for the most part, those updates are positive (even though they cause some major short-term headaches for optimizers).
Today, I’ll turn my attention to semantic search, a search engine improvement that came along in 2013 in the form of the Hummingbird update. At the time, it sent the SERPs into a somewhat chaotic frenzy of changes, but introduced semantic search, which transformed SEO for the better — both for users and for marketers.
What Is Semantic Search?
I’ll start with a briefer on what semantic search actually is, in case you aren’t familiar. The so-called Hummingbird update came out back in 2013, and introduced a new way for Google to consider user-submitted queries. Up until that point, the search engine was built heavily on keyword interpretation; Google would look at specific sequences of words in a user’s query, then find matches for those keyword sequences in pages on the internet.
Search optimizers built their strategies around this tendency by targeting specific keyword sequences, and using them, verbatim, on as many pages as possible (while trying to seem relevant in accordance with Panda’s content requirements).
Hummingbird changed this. Now, instead of finding exact matches for keywords, Google looks at the language used by a searcher and analyzes the searcher’s intent. It then uses that intent to find the most relevant search results for that user’s intent. It’s a subtle distinction, but one that demanded a new approach to SEO; rather than focusing on specific, exact-match keywords, you had to start creating content that addressed a user’s needs, using more semantic phrases and synonyms for your primary targets.
Voice Search and Ongoing Improvements
Of course, since then, there’s been an explosion in voice search — driven by Google’s improved ability to recognize spoken words, its improved search results, and the increased need for voice searches with mobile devices. That, in turn, has fueled even more advances in semantic search sophistication.
One of the biggest advancements, an update called RankBrain, utilizes an artificial intelligence (AI) algorithm to better understand the complex queries that everyday searchers use, and provide more helpful search results.
Why It’s Better for Searchers
So why is this approach better for searchers?
· Intuitiveness. Most of us have already taken for granted how intuitive searching is these days; if you ask a question, Google will have an answer for you — and probably an accurate one, even if your question doesn’t use the right terminology, isn’t spelled correctly, or dances around the main thing you’re trying to ask. A decade ago, effective search required you to carefully calculate which search terms to use, and even then, you might not find what you were looking for.
· High-quality results. SERPs are now loaded with high-quality content related to your original query — and oftentimes, a direct answer to your question. Rich answers are growing in frequency, in part to meet the rising utility of semantic search, and it’s giving users faster, more relevant answers (which encourages even more search use on a daily basis).
· Content encouragement. The nature of semantic search forces search optimizers and webmasters to spend more time researching topics to write about, and developing high-quality content that’s going to serve search users’ needs. That means there’s a bigger pool of content developers than ever before, and they’re working harder to churn out readable, practical, and in-demand content for public consumption.
Why It’s Better for Optimizers
The benefits aren’t just for searchers, though — I’d argue there are just as many benefits for those of us in the SEO community (even if it was an annoying update to adjust to at first):
· Less pressure on keywords. Keyword research has been one of the most important parts of the SEO process since search first became popular, and it’s still important to gauge the popularity of various search queries — but it isn’t as make-or-break as it used to be. You no longer have to ensure you have exact-match keywords at exactly the right ratio in exactly the right number of pages (an outdated concept known as keyword density); in many cases, merely writing about the general topic is incidentally enough to make your page relevant for your target.
· Value optimization. Search optimizers now get to spend more time optimizing their content for user value, rather than keyword targeting. Semantic search makes it harder to accurately predict and track how keywords are specifically searched for (and ranked for), so we can, instead, spend that effort on making things better for our core users.
· Wiggle room. Semantic search considers synonyms and alternative wordings just as much as it considers exact match text, which means we have far more flexibility in our content. We might even end up optimizing for long-tail phrases we hadn’t considered before.
The SEO community is better off focusing on semantic search optimization, rather than keyword-specific optimization. It’s forcing content producers to produce better, more user-serving content, and relieving some of the pressure of keyword research (which at times is downright annoying).
Take this time to revisit your keyword selection and content strategies, and see if you can’t capitalize on these contextual queries even further within your content marketing strategy.
For more content like this, be sure to check out my podcast, The Entrepreneur Cast!