What is Semantic Search?

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Definition: Semantic search refers to Google’s process of interpreting the context and intent of search queries rather than the verbatim text alone

The Future is Semantic Search

In the world of SEO, digital marketers spend so much of their time attempting to adapt to trends that they sometimes lose sight of what SEO itself is trending towards. Google has long since made it their mission to organize the world's information, and matching users with the most relevant and valuable content is their defined path to achievement. For this reason, traditional keywords are merely an early iteration of a more expansive idea. As Google and its algorithms have evolved, the usage of keywords and how we think about them has changed. Unfortunately for some, obsolete tactics have lingered and work against their company’s internet marketing strategy. There are still far too many websites across all industries that place keywords unnaturally throughout their content. It’s time for website content to adapt to Google’s ideals.

Back in 2013, Google’s Hummingbird algorithm update marked a renewed emphasis on user intent within search queries. The update came as a vehicle to enhance Google searchers’ overall experience. By deemphasizing verbatim keywords and placing a greater focus on contextual language, the search engine was able to produce more personalized search results to its users. Referring back to Google’s defined mission statement, it shouldn’t come as a surprise that each algorithm update moves the search engine closer to reaching its proposed objective. Staying cognizant of Google’s ultimate goal not only helps explain their logic for past updates, but it can also empower small businesses to anticipate forthcoming improvements.

Why Does Semantic Search Matter?

For Google, interpreting a user’s intent allows them to present more relevant results to said user and therefore create a more optimal searcher experience. Aside from matching search engine users with relevant content, semantics empower Google to weed out low quality content including spam, spun text, or any material that encourages search engine manipulation. In summary, semantic search contributes to each of the following:

• 1. Google advancement: Progresses Google towards a better search engine for its users.

• 2. Quality assurance: Prioritizes content that deserves higher rankings by its own merits.

• 3. User experience: Enhances the search engine user’s overall experience.

Latent Semantic Indexing (LSI)

The implementation of semantic search is most frequently referred to as latent search indexing or simply; LSI. The technique analyzes sets of data and how they relate to one another rather than interpreting each word, sentence, or title as exclusive from one another. This practice of language processing emerged prominently with Google’s 2013 Hummingbird update. The concept was framed as a way to distinguish Apple the fruit from Apple the tech company, a theory that can be applied universally, including on subjects far less prevailing than a globally renowned institution (Apple). Review each word within LSI to better understand its meaning:

• Latent: Concealed or dormant, which in this case refers to languages’ contextual meaning.

• Semantic: The relationship between words, phrases, and language within web content.

• Indexing: The listing or itemization of content, namely search results in this case.

A Macro Level Understanding of LSI

LSI and semantic search in general, align perfectly with Google’s broad scale objective, which is to provide personalized and relevant information to its users. The usage of synonyms as an accessory to keywords helps Google’s crawlers identify pages that provide diverse language to its readers, rather than redundancy. It’s not radical to presume internet users would rather consume content with varied language. In fact, the behavioral statistics confirm as much. The bounce rates of pages generally coincide with their inherent value and uniqueness, most simply; how much they appeal to a reader based on a corresponding search query. LSI targets content that is:

• Contextual: Relates to the intention of the user’s search query.

• Quality: Diverse in language and free from redundancy.

• Specific: Narrow in scope to the user’s search query.

The Ongoing Evolution of Semantic Search

With the emergence of Google Assistant and Amazon Echo, the necessity for semantic based content is even greater. Voice based assistants such as these represent the future of search engines. Google is moving towards search interactions that are conversational in nature. With this in mind, content produced for a company’s website or blog should incorporate conversational language. Some examples of conversational sentences include:

• NAP citations refer to digital business listings of a company’s name, address, and phone number.

• SEO is the process of influencing web content to satisfy search engines and their users.

• Website design helps small businesses grow their customer base through digital leads.

With the types of sentences above integrated into your website’s content, it will be simpler for user’s to find information on those subjects, either via voice query, or by traditional search. If a user were to search for what are NAP citations, the first example listed above would be a candidate for a voice response and a featured snippet. For those who are unaware of the term, a featured snippet is a block of text Google shows on the top of their organic results for certain queries (mostly question based). They are also regularly pulled by voice assistant software and presented as a response.

Refining Content for Semantic Search

As 2019 starts, it’s important for businesses with websites to adjust content to meet an evolving interpretation of digital information. With the number of search queries performed via voice assistant expected to increase gradually, the conversational component of web pages must mirror this ascendence. When investing resources into content refinement, it’s critical to align actions with Google’s overarching philosophy and never steer too far from its basis. As for actionable concepts that webmasters can implement directly, consider the following:

• Content Improvement: Rewriting web content with more conversational language.

• Featured Snippets: Optimizing on page content to earn featured snippets atop Google’s organic results.

• Schema Markup: Using structured data markup to tag elements of web pages and help Google more accurately interpret them.

Conclusion

Small businesses should align their content development processes with Google’s macro scale objective. Because the world’s top search engine aims to organize the world's information for its users, the content produced by websites should facilitate this directive. The practice of stuffing verbatim keywords on to a page for improved rankings has been rendered obsolete and the companies that take notice will prosper in the coming years. Producing high quality web pages with your users’ best interests in mind should be the objective of every webmaster in 2019 and beyond. Semantic search is the future, and the future is now.